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Posters
Three prizes from the European Meteorological Society were awarded to
Valentina Sicardi (MPI of Biogeochemistry, Germany) Ana Prieto-Blanco
(University of Wales, UK), and Raul Lopez-Lozano (CITA, Spain) for the three
best posters.
Theme: Ocean
The LANS-Alpha Model of Sub-Grid Scale Turbulence in the POP
Ocean Model
Mark Petersen
Los Alamos National Lab.
(mpetersen@lanl.gov)
Abstract
POP, the Parallel Ocean Program developed and maintained
at Los Alamos National Lab., is widely used by the ocean and climate modeling
community. Like all numerical models, computational time limits the spatial
resolution at which POP can operate; standard simulations use grids of 0.5 to 1
degree in latitude and longitude. This resolution does not capture the motion of
eddies at the Rossby radius of deformation, and thus lacks the correct energy
cascade and heat transport at these scales. The Lagrangian-Averaged
Navier-Stokes alpha (LANLS-alpha) model, developed by Darryl Holm and colleagues
at LANL, improves these characteristics with a smoothed advecting velocity and
an additional nonlinear term.
Preliminary results show that the
POP-alpha model improves measures which depend on the resolution of meso-scale
eddies, such as vertical temperature profile, kinetic energy, and eddy kinetic
energy. In some cases these improvements are comparable to a doubling of
horizontal resolution, which increases computation by a factor of ten, while the
addition of the alpha model parameterization only adds a few percent in
computational time.
Influence of El Nino on the Biennial Rossby Waves in the Indian
Ocean with a Special Emphasis on Indian Ocean Dipole
Bakshi Hardeep Vaid
Research Fellow
(bhv@tropmet.res.in)
Abstract
The interannual variability of the tropical Indian Ocean
is examined using 44 years (1958 – 2001) of Simple Ocean Data Assimilation
(SODA) sea surface height anomalies (SSHA) and Hadley centre Ice sea surface
temperature anomalies. SODA SSHA over the Indian Ocean is filtered using
two-dimensional Finite Impulse Response filter and the filtered biennial Rossby
wave component is analyzed to understand its variability in the tropical Indian
Ocean. From the composite map of the biennial Rossby wave signals, a dipole
pattern is clearly observed in the equatorial Indian Ocean with the wave crest
occupying the western Indian Ocean and the wave trough occupying the
southeastern tropical Indian Ocean during the positive Indian Ocean Dipole (IOD)
events. Downwelling biennial Rossby waves along 1.5oS are seen propagating
westward from the eastern boundary, more than one year prior to the formation of
a positive IOD and reach in the western equatorial Indian Ocean during the peak
positive dipole time. Influence of El Nino on the propagation of biennial in the
Indian Ocean has been observed. In short, the present study supports the
intrinsic link between IOD and El Nino.
Advances in Coastal Altimetry over the Northwestern
Mediterranean
Jérôme Bouffard
LEGOS - CTOH/POC
(bouffard@notos.cst.cnes.fr)
Abstract
We describe the outcomes of research into applications
of altimetry in the Northwestern Mediterranean (hereafter NWM) Sea for the
following medium term purposes: to contribute to the oceanographic knowledge of
the area and to assess the applicability of altimeter techniques in coastal
systems.
The region is a perfect site for such investigations in virtue of
availability of various long-term in situ observations.
Altimetry is well
suited to the study of the general circulation in the open ocean. However using
altimetry is still a challenging issue for coastal studies such as in the NWM
partly because the dynamic is much more complex. Thus, an important aspect of
the research activity consisted in assessing the extent to which altimetry can
be employed in the area, and devising any possible improvement in the data
processing chain and in the retrieval of the geophysical parameters in order to
make altimetry more applicable. We describe the adopted processing strategy and
the comparison of the retrieved parameters with in situ data. The scales
accessible through the multi-sensor observing systems are then compared with the
3D coastal model Symphonie in order to show their capabilities to improve our
knowledge of the coastal area in the NWM Sea and especially concerning the
Catalan-Ligurian-Provençal current variability.
Effects of Absorbing Aerosols in the SST Using AI (TOMS) and
AOT (SeaWiFS)
Ana Belén Ruescas Orient
assistant researcher
(ruescas@his.uji.es)
Abstract
The presence of aerosols affects the measurement of sea
surface temperatures (SST), extracted by means of sensors situated on
satellites, because they are capable of absorbing and dispersing infrared
radiation. Dust particles, smoke, and volcanic ash make up what is called
atmospheric aerosols, and are key elements in cloud formation and in
precipitation. It is even believed that aerosols with high iron content are
crucial for the growth of phytoplankton in the sea (Bigg, 2003). In this study,
reference will be made to only one type of "naturally” occurring aerosol, that
is, one not originating from anthropogenic emissions, like dust from deserts. It
will specifically deal with the influx of dust from the Sahara desert and the
deserts of the Arabian Peninsula into the environment around the Mediterranean
Sea.
This influx leads to serious errors in the extraction of SST through
satellite imagery, which makes it necessary to carry out both a detailed study
of the effect they have on absorption for the channels in infrared wavelengths,
as well as a proposal of methods for correcting these errors.
The main
objective of this study is to evaluate the errors caused by these aerosol pulses
in the SST extracted by the AVHRR sensor through the use of two indicators of
aerosol presence: the TOMS Earth Probe aerosol index (AI) and the Aerosol
Optical Thickness (AOT) derived from SeaWiFS.
Earth Observation data assimilation in marine forecasting
Lars Boye Hansen
GRAS Ltd
(lbh@gras.ku.dk)
Abstract
Marine forecasting of physical and biological variables
is increasingly being used to assist decision making by authorities and
industry. For this purpose, data assimilation is an ideal framework for
constraining the models by measured marine variables. Earth observation sea
surface temperature (SST) and chlorophyll-a data provide a unique data set in
this respect. It has a high spatial resolution, but introduces the challenge of
handling information that is patchy in space and irregular in time.
In
this contribution examples of operational forecast models for the Sea of Chiloé
and the inner Danish waters are presented. Near real time SST and and
chlorophyll-a data are fed into the system via a simplified Kalman Filter
approach, in which the dynamical model is basically performing an intelligent
patch interpolation of the measured variables. Prior to the assimilation the EO
data are interpreted by use of the model variables themselves and an additional
surface layer turbulence description, thus transforming the measurements into
the model space. The performance of the EO assimilation approach is compared to
the existing operational services at both locations.
Modelling the shelf recruitment of c. finmarchicus on the west
coats of Norway
Annette Samuelsen
Mohn-Sverdrup Center /
NERSC
(annette.samuelsen@nersc.no) Abstract
The zooplankton
species c. finmarchicus is important in the Norwegian Sea because it is the main
food for planktivorious fish such as herring and capelin and for larvae of most
commercial fish stocks. c. finmarchicus has a one-year life-cycle, and the shelf
population is recruited each spring from individuals that has over-wintered at
depth either in a fjords or in the deep basins in the Norwegian Sea. The shelf
recruitment of c. finmarchicus is investigated using a numerical ocean model,
the HYbrid Coordinate Ocean Model (HYCOM), that forces an individual based model
(IBM) for c. finmarchicus. The model is set up on a 4 km grid along the west
coast of Norway and the focus is on shelf recruitment from the Norwegian Sea
population. Numerical experiment are performed investigate the effect of wind,
temperature, food availability on the size and fitness of the shelf population.
Here, the focus is on the years 1995 and 1996; 1995 is characterized by many
storms and strong southwesterly winds, whereas 1996 is characterized bye fewer
storms and weaker southwesterly winds. The shelf recruitment under these two
very different wind-regimes is investigated.
Issues about retrieving sea surface salinity in coastal areas
from SMOS data
Sonia Zine
Laboratoire d'Océanographie et du Climat - Expérimentation
et Approches Numériques (LOCEAN)/Université Pierre et Marie Curie-Paris
6/CNRS
(zine@lodyc.jussieu.fr) Abstract
Ocean salinity is a
key parameter in oceanic and climate studies. Together with the ocean
temperature, the salinity influences the density of the water masses and
actively participates in their formation and circulation. In situ sea surface
salinity (SSS) measurements, done by buoys and oceanographic or commercial
ships, remain sparse and irregular, with large parts of the global ocean never
sampled. In order to fill this gap, two missions carrying L-band (1.4 GHz)
radiometers have been recently proposed: the Soil Moisture and Ocean Salinity
(SMOS, ESA) and Aquarius (NASA) missions. Their objective is to estimate the SSS
on a global scale, in 200 km x 200 km boxes on a 10-day average with a precision
of 0.2 psu (practical salinity units, corresponding to parts per thousand). They
should allow a global monitoring of the SSS at a synoptic scale, and the
remotely sensed SSS should be suitable for assimilation into ocean circulation
models, according to GODAE requirements.
This study deals with SSS
retrieval from SMOS measurements in coastal zones. These zones are characterized
by strong and variable SSS gradients (several psu) on relatively small scales.
In particular, the extent of river plumes is highly variable, typically at
kilometric and daily scales. Monitoring this variability from L-band satellite
radiometric measurements is particularly challenging because of the resolution
of the satellite measurements (typically 30-100 km) and because SMOS
measurements over the coastal ocean are contaminated by the nearby land: land
brightness temperatures range from approximately 200 to 300 K, compared to
approximately 100 K for the ocean.
The objective of this study is to
assess to which extent SSS variability in coastal areas can be monitored with
SMOS. On the one hand, a set of academic tests are conducted with a linear
coastline and constant geophysical parameters. On the other hand, more realistic
tests are conducted over the Bay of Biscay, using SSS and SST fields simulated
by the MARS3D model developed by the IFREMER. SMOS brightness temperatures are
deduced from the measured visibilities using image reconstruction. The impact of
different apodization windows on the retrieved SSS as a function of the distance
to the coast is investigated. Under SMOS configuration, an ocean grid point is
seen by several cells with various view angles, various resolutions and various
ellipticities. The effects of the cells maximum resolution and elongation are
investigated by studying the bias and error on the retrieved SSS with respect to
the distance to the coast.
Observing Ocean Mass and Heat Storage Changes using GRACE and
Altimetry Data
Bert Wouters
TU Delft - DEOS
(bertw@deos.tudelft.nl)
Abstract
The Gravity Recovery And Climate Experiment (GRACE)
monthly solutions of the time-variable gravity field allows direct estimates of
changes in the ocean water mass budget. In combination with satellite altimetry
observations, this can be used to estimate heat content changes in the ocean as
well. Since the amplitudes of these signals are relatively small (compared to
the signal over land), it is important that both the GRACE and altimetry data
are corrected and combined in a consistent manner.
In this presentation we
focus on two corrections, i.e. the geocenter correction and de-aliasing of the
altimetry data for high-frequency signals. The former is due to the fact that
the GRACE satellites are insensitive to variations of the center of mass of the
Earth, whereas altimetry is not; the latter applies to oceanic signals with
periods shorter than the Nyquist period of the altrimetry observations.
Additionally, we discuss other corrections that should be applied to correctly
reconcile the two data sets and present the results.
SSALTO CALVAL Performance assessment Jason-1 GDR "B" / GDR
"A"
Sabine Philipps
CLS
(sabine.philipps@cls.fr)
Abstract
Altimeter Jason-1 data (GDR: geophysical data record)
were processed in version A until cycle 135 and in version B from cycle 136
until current cycle.
Recently, a reprocessing of the GDR was done by JPL
(cycles 1 to 21) and CNES (cycles 128 to 135). The main evolutions in the GDR
'B' are the implementation of a new retracking algorithm (order 2 MLE4), a new
precise orbit based on a GRACE gravity model and new geophysical corrections
(tidal models, MOG2D, Sea State Bias).
The objective of this study is to
compare the 'A' and 'B' versions of the GDRs. The impact of each change in GDR
'B' is analyzed as well as the global impact on Sea Surface Height (SSH)
performances.
Satellite chlorophyll as a tracer for upward velocities in the
surface ocean
Gabriel Navarro
ICMAN-CSIC
(gabriel.navarro@icman.csic.es)
Abstract
Upward velocities have been diagnosed through the
development of an approach based on the combination of remotely sensed daily
images of both chlorophyll and temperature at the ocean surface in subtropical
latitudes (Gulf of Cádiz and Alboran Sea). This novel approach allows to detect
areas of vigorous vertical velocities, through the generation of a calculation
algorithm built from the simple Lagrangian model of phytoplankton growth that
occurs during the rise of deep waters to surface.
Cold waters poor in
chlorophyll are quite unusual during spring-summer at the surface of the
subtropical latitudes. They result from very intense dynamic processes that lift
deep water of different properties to surface. Detection of these waters by
radiometers in orbit can be used as a satellite tracer for the areas where these
processes occur. The fast initial evolution of chlorophyll and temperature in
surface limits the implementation of the algorithm to high upward velocities.
Assuming this limitation, the values of vertical velocity diagnosed have been
found to be coherent with independent estimations based on diffusive and
advective inputs of nitrogen into the euphotic zone in the area.
The Mercator eddy permitting global ocean forecasting
system
Marie Drévillon
CERFACS
(mdrevillon@mercator-ocean.fr)
Abstract
The Mercator-Ocean eddy permitting global ocean
forecasting system has a 1/4° horizontal resolution and 46 levels on the
vertical (ORCA025), and is forced with daily surface fluxes from ECMWF
operational analyses. Satellite Sea Level Anomaly measurements (JASON, ENVISAT
and GFO) from january 2005 up to real-time are assimilated with a reduced order
optimal interpolation scheme (ROOI). Due to its relatively fine resolution, the
forecasting system provides an integrated description of the ocean with a
realistic description of the meso scale features.
Assimilation scores are
presented, and independant in situ data of the Atlantic, Pacific and Antarctic
ocean basins are compared with the simulation results in order to provide an
estimation of the performances of the system. The results are also compared with
the Levitus climatology, and with the ARMOR weekly products, which optimally
combine satellite (SST, SLA) and in-situ (T/S profiles) near real time
observations.
First results of the next generation of Mercator ocean
forecasting systems are presented, which use a multivariate and multidata
assimilation method, and which comprise a sea ice model (LIM). This system will
replace in 2007 the current operational system, and will allow us to perform a
global ocean reanalysis for the 1992-2005 period.
CryoSat Validation Experiment CryoVEx 2006 at Lincoln Sea
Eero Rinne
Finnish Intitute of Marine Research
(Eero.Rinne@iki.fi)
Abstract
CryoSat Validation Experiment CryoVEx 2006 was carried
out in April and May 2006. Part of the experiment was made on the sea ice of
Lincoln Sea. This experiment was a joint venture between European Space Agency
(ESA), Danish National Space Center (DNSC), Alfred Wegener Institut (AWI),
Scottish Association for Marine Science (SAMS) and Finnish Institute of Marine
Research (FIMR).
Due to very unfortunate launch failure of CryoSat
satellite, aircraft-borne radio altimeter ASIRAS was used in the experiment.
ASIRAS is similar to SIRAL instrument to be flown onboard CryoSat II. Ice
thickness measurements were also made with laser altimeter and a
helicopter-borne electromagnetic ice thickness sensor known as EM-bird.
During the airborne measurements ground teams collected in situ data
including ice thickness, density, salinity and snow properties. Overall
description of Lincoln Sea experiment including planning and realization is
presented. Preliminary comparisons between in situ and remote sensing data are
also presented.
The Rhine Region of Fresh Water Influence
Gerben De Boer
Delft University of Technology
(g.j.deboer@tudelft.nl)
Abstract
Co-authors: J.D. Pietrzak, J.C. Winterwerp
In
the Rhine ROFI (Region Of Freshwater Influence) stratification significantly
affects tidal currents. Cross shore velocities and stratification signals are
known to exhibit dominant semi-diurnal and fortnightly variations due to tidal
advection and mixing. We investigate the semi-diurnal variation known as tidal
straining. First, we used the 15-year 1-km NOAA-SST dataset at KNMI. We selected
time series that have over three images/day, do not coincide with strong wind
and show a marked temperature contrast between stratified water and the
surrounding sea caused by solar heating. The timing of the observed upwelling,
down welling and plume displacement vector are in accordance with tidal
straining theory. Second, an idealized 3D numerical model of the Rhine ROFI was
employed to explore the effect of stratification on the vertical structure of
tidal currents. In line with observations it shows anti-cyclonically rotating
surface currents and cyclonically rotating bottom currents. As a first
approximation, this can be understood with the dynamic Ekman equations (Prandle,
1982). In the special Kelvin wave case (zero depth averaged cross shore
currents) it already predicts a transition from almost rectilinear tidal
currents to an ellipticity veering of 50% as a function of bulk vertical eddy
viscosity only.
Envisat Ocean applications
Cristina Martin Puig
Starlab Barcelona
S.L.
(cristina.martin@starlab.es) Abstract
The uncontrolled
energy demand and the strong dependence on fossil fuels, have encourage various
energy sectors to work together in order to reduce the pollution emission, while
preserving the equilibrium of the ecosystems and the sustainable economic
development. Renewal energies are an efficient solution to this concern, as well
as the motivation of EOLISCAT; an internal Starlab Barcelona S.L. project which
aims to retrieve mesoscale wind fields from ASAR data. The results acquired will
help to the assessment of offshore wind farms deployment along the Catalan
coast, and widely contribute to the use of renewal energies in Spain. The poster
will describe the research work performed at Starlab, as well as preliminary
results.
ASAR is not the unique Envisat sensor that may help industry
development; multispectral satellite sensors such as Envisat's Medium Resolution
Imaging Spectrometer (MERIS) can observe the colour of surface water as a means
of deriving their environmental quality. Within this framework, the use of MERIS
data to support water bodies’ sustainability reports will be also presented in
this poster.
Introduction of inequality constraints into a Reduced Order
Kalman Filter for data assimilation into ocean circulation models
Claire Lauvernet
LEGI/CNRS
(claire.lauvernet@hmg.inpg.fr)
Abstract
In data assimilation into oceanographic models, one
of well-known classical problems is the estimation of variables physically
unrealistic. The aim in this work is to take into account inequality constraints
within a reduced order Kalman filter (the SEEK filter) to improve actual method
assimilating remote sensing data of temperature, salinity, pressure and
altimetry. These inequality constraints are specific to the hybrid ocean
circulation model used (HYCOM) which needs all layer thicknesses positive as
well as the density increasing with depth. To follow these constraints within
the assimilation scheme, a quadratic programming problem is inserted after each
analysis step. The model with an example of violated constraints after a SEEK
analysis are presented. Then, the purposed approach SEEK-3DVar is explained
theorically with discussion on several resolution methods. First results are
finally presented.
Estimates of Geostrophic Transport in the South Atlantic Bight
Using Satellite Altimetry
Dara Cadden
University of South Carolina
(Dara.Hooker@msci.sc.edu)
Abstract
Accurately quantifying long-term Gulf Stream transport
is critical to understanding the meridional heat transfer cycle and associated
global climate. In this study, in situ current measurements from cross-stream
transects of an Acoustic Doppler Current Profiler were used in conjunction with
satellite altimetry data to construct a model to predict Gulf Stream volume
transport. Additionally, CTD profiles were used to estimate the geostrophic
velocity via the thermal wind equation. The measured velocity profiles were
compared to the calculated velocity profiles using the thermal wind equation to
produce a statistical model of vertical variability in Gulf Stream flow.
Depth-independent estimates of the geostrophic current were computed from
cross-stream sea surface height anomaly data (SSHA) obtained from the
TOPEX/POSEIDON and Jason-1 satellite altimeters. These estimates provide the
boundary condition for the flow estimates obtained from the thermal wind
equation calculations. A data-calibrated model emerged that generated a decadal
time series of Gulf Stream transport for this area (31.5°N 79°W) of the South
Atlantic Bight (SAB) and could accurately compute the local depth-integrated
volume transport using historical SSHA data. Gulf Stream transport was observed
to increase gradually, not dramatically, in the SAB from the Straits of Florida
to just upstream of the Charleston Bump.
Applications of Satellite Oceanography
Adam Leonard-Williams
Fugro GEOS
(a.leonard-williams@geos.com)
Abstract
Satellite data are widely used within the field of
commercial oceanography in the assessment of winds, waves and currents. The
first example illustrates the use of data sources such as Topex/Poisedon, JASON
and ERS-1 and 2 in the calibration of a global wind and wave model and its
subsequent use in projects such as wave energy resource mapping and near-shore
wave modelling. The second example discussed is the number of recent of studies
into the tracking of large scale surface features such as the Gulf of Mexico
Loop Current, the North Brazil Current and the Aghulus Current. Combining
altimetry data and hindcast numerical model data have enabled these systems to
be effectively modelled and forecast enabling an assessment of their past and
potential impact on drilling locations.
Sea oil slicks remote sensing using MERIS spectral bands
Francesco Viti
Flyby srl
(francescoviti@yahoo.it)
Abstract
In this work are presented the results obtained by
simulating the total remote sensing reflectance at nadir for oil in sea water,
correlated with MERIS bands. The difference between water radiance (taking into
account also chlorophyll) and oil radiance has been implemented into a contrast
model that allows to verify the possibility to detect oil slicks in sea water by
means of MERIS images.
Water quality monitoring of the Eastern part of Gulf of
Finland.
Mikhail Itkin
Saint-Petersburg Center for Hydrometeorology and
Environmental Monitoring
(itkin.m@gmail.com) Abstract
Due to
many natural and antropogenic factors Eastern part of Gulf of Finland is
extremely sensitive to human impact. In order to manage local water resources
well with minimum risks for the nature having precise online data about
environmental state is vitally important.
The aim of the research is to
realize water quality monitoring in the area of Gulf of Finland based on use of
the data from the Moderate Resolution Imaging Spectroradiometer (MODIS/EOS
Terra) and radiometer AVHRR/NOAA. One of the main goals of the research is to
conduct an investigation wether the aforesaid type of sattelite data is usable
for researching such quantative and qualitative charachteristics of water in the
area of Gulf of Finland as sea surface temperature, concentration of chlorophyll
»a« and water turbidity which allow to trace thermal anomalies of the surface
waters, algal blooms and concentration of the suspended solids. Results of
satellite data processing are verified according to the ship observations and
data from the hydrometeorological ground-based observation stations network.
Theme: Atmosphere
The Urban energy balance: Parameterization of the
anthropogenic heat flux
Matthias Demuzere
Katholieke Universiteit
Leuven
(matthias.demuzere@geo.kuleuven.be) Abstract
Although
many studies show that heat released from human activities (anthropogenic heat
Qa) can be a significant contributor to the urban energy balance, QA is often
not well parameterized or even disregarded in atmospheric modeling. Often, the
ground surface flux and anthropogenic heat fluxes are combined and calculated as
residual of the energy balance, thereby incorporating all errors, both in
measurements and the model. Therefore, the goal of this study is to explicitly
parameterize the anthropogenic heat released from industry, traffic and domestic
households based on a spatial distribution of annual energy consumption (in
France), by means of land use and population density maps. A time dissagregation
is obtained using the concepts of ‘heating degree-days’ and ‘time
factors’ for building heating and traffic respectively. A 120x120 km² domain
centered above Marseille is selected to perform runs with the mesoscale
meteorological model ARPS during a 3-day IOP (20 – 22 June 2001). Effects of
QA on the urban energy balance are investigated using eddy covariance
observations in the center of Marseille provided by the ESCOMPTE campaign
(Expérience sur Sites pour COntaindre Modèles de Pollution et Transport
d’Emissions). Contrasts with rural sites are found using 2 rural stations
Meyrargues (maize) and Trets (grass).
Measuring Carbon Dioxide from Space
Alan Hewitt
University of Leicester
(ajh67@le.ac.uk)
Abstract
Until recently, Earth based measurements of CO2
concentrations have been sparsely distributed, and have poorly represented
continental land mass, where localised sources and sinks overwhelm measurements.
SCIAMACHY and later the Orbiting Carbon Observatory data will be used to give a
more accurate quantification and understanding of the carbon sources and sinks.
It is a requirement of the Kyoto protocol to accurately quantify and monitor CO2
sources and sinks.
The advanced FSI-WFM –DOAS method has been
developed to retrieve total columns of greenhouse gases (primarily CO2) with
increased precision, enabling the investigation of:
• The accuracy of
global CO2 measurements from NIR observations of SCIMACHY for the direct
determination of flux estimates.
• Co-retrieval methods as a way of
assessing emission fluxes.
• The application of cloud resonance as a
method of assessing the sensitivity to PBL CO2.
• Data assimilation of CO2
measurements as a means of providing a better error estimate for CO2 retrieval
errors and fluxes.
• Quantification of greenhouse and related biospheric
gas fluxes through inverse modelling constrained by assimilation of ENVISAT
measurements, with a focus on CO2.
Inverse modeling of emissions at a local scale: a study of
the Paris area
Isabelle Pison
McGill University / Meteorological Service of
Canada
(pison@lisa.univ-paris12.fr) Abstract
For
chemistry-transport models operated in atmospheric photo-oxidant pollution at a
local scale, surface emissions are an essential input data to which output
concentrations are very sensitive. Emissions are nevertheless poorly known and
remain a major source of uncertainty in current models. The possibility of
modifying existing inventories seems therefore promising for a better simulation
of concentration fields and a better understanding of pollution.
Emissions of the Paris area are optimized with a methodology for the
inversion of surface anthropogenic emissions at a local scale based on the
chemistry-transport model CHIMERE and its adjoint. It uses a kriging technique
to optimize the use of the information available in network measurements. A
dynamical spatial aggregation technique is elaborated for the Paris area to
reduce the size of the problem.
NOx emissions from the inventory
elaborated by AIRPARIF were inverted during the summers of 1998 and 1999: events
of the ESQUIF campaign are studied in detail. The optimization reduces large
differences between simulated and measured concentrations. Generally, the
confidence level of the results decreases with the density of the measurement
network. Therefore, the results with the higher confidence level correspond to
the most intense emission fluxes of the Paris area.
Satellite Characterization of Power Plant Aerosol
Emissions
Dina Santos
University of Évora
(dinas@uevora.pt)
Abstract
The aim of this work is the identification and
characterization of aerosols plumes emitted from the Portuguese Electrical
Company Power Plants using satellite measurements, with the purpose of
monitoring the emissions of pollutants and studying their atmospheric
dispersion. The methodology is based on radiative transfer calculations in the
atmosphere that, properly combined with satellite measurements, allow for the
detection and determination of the aerosols amount in the atmosphere and some of
their physical characteristics. The columnar amount of pollutants obtained in
this way (Aerosol Optical Thickness-AOT) is compared with the particles
emissions that are monitored on the top of the power plant towers, in order to
validate the values retrieved from the satellite-based method.
Satellite
measurements from the MODerate Resolution Imaging Spectroradiometer (MODIS) were
used, since they present the adequate spectral channels and spatial resolution
to observe and monitor disturbances in the Earth-atmosphere system.
The
analysis of the AOT values obtained with the satellite-based methodology,
confirmed that a higher value of AOT exists in the Power Plants areas and a good
agreement can be observed between the values of the optical thickness obtained
from the satellite data and the aerosol emissions measured at the top of the
power plant towers.
Impacts of Urbanization on the CaRBon Sequstration in
Europe
Kristina Trusilova
Max-Planck Institute for
Biogeochemistry
(ktrusil@bgc-jena.mpg.de) Abstract
Numerical
simulations with the mesoscale weather-predicting model MM5 suggested that
conversion of natural land cover to urban one caused reduction in temperature
diurnal range and in precipitation over the areas of perturbation. The
simulations showed an average reduction of the diurnal temperature range in
regions with urban land cover modification by 1.1°C and 0.9°C in summer and in
wintertime respectively. The total amount of precipitation averaged over the
whole domain over land was by -2.1 mm month-1 and -2.5 mm month-1 in summer and
wintertime respectively. Urban sites exhibited decreased rainfall in summer (-4
mm month-1) and increased rainfall in winter (+3 mm month-1).
This study
addresses the question: how do the changes in diurnal temperature range and
precipitation associated with urbanization influence the vegetation growth in
Europe? Series of numerical simulations with the Biome-BGC terrestrial ecosystem
model were performed to determine how productivity of vegetation responded to
urban-caused changes in climate of Europe. It was found that ecosystems situated
in dry warm environments were the least sensitive to the urban anomaly
temperatures and precipitation while the ecosystems in colder and moist climates
showed the greater response.
Aerosol Forecasts for Solar Energy Applications
Hanne Breitkreuz
DLR-DFD
(hanne-katarin.breitkreuz@dlr.de)
Abstract
In order to raise the effectiveness of renewable energy
production and to integrate the growing solar energy sector into existing power
supply systems, reliable near-real-time predictions of solar irradiance are
needed for 1-3-day forecasts of energy yields and consumer demands.
Accurate information about clouds, aerosols and water vapour is
necessary to calculate ground level irradiance. While water vapour forecasts are
already performed with classical weather models, prediction of aerosol
distribution is still a matter of research. Especially in mostly cloud-free
regions, which are of special interest for larger solar energy facilities,
aerosol forecasts are of great importance to obtain accurate irradiance
predictions. A first approach is given by the MM5-based EURAD model (European
Air Pollution Dispersion Model), developed by the University of Cologne for air
quality monitoring purposes. It predicts aerosol distributions distinguishing
between components such as soot, organic particles and inorganic acids.
In a case study forecasted AOD of the EURAD system was validated against
ground based aerosol measurements for five months in 2003. Results show a slight
underestimation of AOD, especially during the summer months. However, deviations
remain within currently accepted errors in satellite retrievals of aerosol
properties and within accuracy requirements for input parameters of irradiance
calculations.
Two-dimensional modelling of MIPAS trace species
information content
DeClercq Coralie
Belgian Institute for Space
Aeronomy
(coralie.declercq@aeronomie.be) Abstract
Operational
processors of Envisat Michelson Interferometer for Passive Atmospheric Sounding
(MIPAS) retrieve temperature and trace species profiles from limb radiance
measurements assuming one-dimensional atmosphere. Averaging kernels associated
with the retrieval enable one-dimensional characterisation of the retrieved
information as a function of altitude or pressure. Nevertheless, the MIPAS limb
scanning strategy, concurrent emission and absorption processes, and the orbital
progression of Envisat, combine to spread the actually probed information in
both the vertical and horizontal (angular) dimensions. Here, we describe a
simple radiative transfer model capable of calculating MIPAS limb radiance
emission spectra in a two-dimensional atmosphere. The model is applied to MIPAS
particulars (selected spectral microwindows, global fit retrieval approach) in
order to characterise the vertical and angular distribution of the information
available after a complete limb-scanning sequence.
Global Atmospheric CO2 Remote Sensing Data
Assimilation
Valentina Sicardi
Max Planck Institute for
Biogeochemistry
(vsicardi@bgc-jena.mpg.de) Abstract
The main
objective of this research, on global atmospheric CO2 remote sensing data
assimilation, is to develop and apply techniques for the assimilation of
remote-sensing and in situ based observations into a global atmosphere/ocean
carbon cycle model framework.
A case study with 1DVAR
Tien Du Duc
Hanoi University of Science
(duductien@yahoo.com)
Abstract
HRM (a High resolution Regional Model, developed by DWD)
has been running operationally in Vietnam since 2002. Observation should be
assimilated to improve the quality of initial fields for this model. Satellite
data is the main source for the poor-observation area, especially in sea region.
In this study, 1D-vartional assimilation system (developed in Met. Office of
U.K) will be applied for HRM with NOAA 15,16 data.
Estimating Regional CO2 Surface Fluxes In Complex
Landscapes
Stephan De Wekker
NCAR
(dewekker@ucar.edu)
Abstract
Mountain forests represent a large portion of gross
primary productivity within the United States and a significant potential net
CO2 sink. Therefore, there is a need to develop methods to estimate regional
fluxes of CO2 in mountainous terrain. We present results from a combined
modeling and observational study of regional CO2 fluxes in mountainous terrain
and discuss the major challenges. We use data from the Airborne Carbon in the
Mountains Experiment (ACME), conducted in May and July of 2004. Applying a
simple budget method to the aircraft data, we estimated CO2 drawdowns of several
ppm in the mountain boundary layer, representing significant CO2 uptake by the
forests. To understand the observations, we use a modeling framework consisting
of the Regional Atmospheric Modeling System (RAMS) and its adjoint. We prescribe
various scenarios of a CO2 flux at the surface and atmospheric conditions
resulting in a variety of spatial and temporal behaviors of CO2 concentration in
and above the mountain boundary layer. This enables the calculation of surface
CO2 fluxes using the same approach as in the observations. Ideas to use the
adjoint in a variational data assimilation approach to estimate regional CO2
fluxes will also be presented.
Spatial and Temporal Variation of Rain Fields in
Tuscany
Patrice Poinsotte
University of Pisa
(p.poinsotte@virgilio.it)
Abstract
The poster describe our current work in progress at
INFN-Pisa, regarding the spatial and temporal inhomogeneity of rain fields using
meso scale model (MM5) and fractal geometry.
The objective is to provide
valuable information on structures inside the rain fields, such as size
(diameter), shape and orientation of rain cells. This information is needed to
improve our knowledge on thunderstorms dynamics and to accurately model and
simulate the spatial variation of 2-D rain fields.
Spectral coupling method for limited area models
Raluca Radu
National Meteorological Administration
(raluca.radu@meteo.inmh.ro) Abstract
A one-way nesting method
for joining a large scale model with a high resolution limited area model (LAM)
has been developed and tested in terms of the spectral information transmission
through lateral boundaries. The spectral coupling method based on the bi-Fourier
representation of the fields was used as additional step to the presently used
flow-relaxation method (Davies, 1983). We investigated the proposed method's
capability to supply to the LAM's solution the possibly missing large scale
information. The performance of the LAM using spectral coupling versus
operational grid-points coupling was analyzed, the results showing a reduction
of errors in the forecast and an improved ability to simulate extreme events
produced through scales interaction.
Intercomparison of the primal and dual formulations of
variational data assimilation
Amal El Akkraoui
McGill University
(amal.elakkraoui@mcgill.ca)
Abstract
The variational formulation of the data assimilation
problem can be cast either in its primal or dual formulation.
The primal
formulation uses a control variable in model space: it corresponds to the
so-called 3D-Var algorithm, whereas the dual formulation proposes a different
angle by using a control variable defined in observation space: it corresponds
to the Physical-space Statistical Analysis System (PSAS). In the case where the
3D-Var cost function is purely quadratic, both methods have been shown to be
theoretically equivalent.
This work compares dual and primal formulations in
an operational framework. A PSAS scheme has been formulated using the
operational 3D-Var of the Meteorological Service of Canada. Our results show
that the two formulations give exactly the same results at convergence, and
confirm the analysis presented in Courtier (1997) : that is with their own
conditioning, 3D-Var and PSAS require a comparable number of iterations and a
similar overall cost to converge.
Finally, the converging properties of both
algorithms are looked at when approximate forms of the Hessian matrix by its
leading eigenvectors are used to precondition the problem. In PSAS, the Hessian
is relatively sparse which makes the preconditioning more efficient. This is
attractive particularly in view of the extension to 4D-Var and 4D-PSAS for which
a reduction in the number of iterations can make a huge difference in the time
required to produce an operational analysis.
Fast cloud properties retrieval scheme with SEVIRI
images
Alessandro Ipe
Royal Meteorological Institute
(Alessandro.Ipe@oma.be)
Abstract
In order to deliver near real-time estimates of the top
of the atmosphere (TOA) radiative fluxes from the Geostationary Earth Radiation
Budget (GERB) broadband radiometer on board of the Meteosat-8 satellite, a
radiance-to-flux conversion needs to be performed on the measured radiances. As
such a conversion is done by using the angular dependency models (ADMs)
developed from the Clouds and the Earth's Radiant Energy System (CERES)
experiment, the GERB ground segment has to rely on a scene identification based
on SEVIRI data.
In this poster, we present the method developed for the
GERB/SEVIRI scene identification within the RMIB GERB Processing (RGP) to
estimate the cloud properties needed to properly select the ADM according to the
observed scene. This cloud properties retrieval scheme based on reference
composite TOA clearsky reflectances allows to estimate robust a cloud flag,
cloud optical depth and cloud thermodynamic phase for each SEVIRI pixel. Even if
the method is based on lookup tables of radiative transfer computations, its
simple non-iterative behaviour allows to perform the retrievals faster than more
complex schemes found in the literature with a good confidence.
Impact of a Flow-Dependent Background Error Covariance
Model Based on Sensitivity Functions in a 3D-VAR
Cristina Lupu
UNIVERSITÉ DU QUÉBEC À MONTRÉAL
(UQÀM)
(lupu@sca.uqam.ca) Abstract
The a posteriori
sensitivity functions estimated as in Laroche et al. (2002) characterise the
change in the initial conditions that will lead to an important modification in
the short-term forecast. To take into account the specificities of the flow
characteristics, those sensitivity functions are introduced as structure
functions within the background error covariance matrix of a 3D-Var assimilation
system to allow the analysis to fit the observations while at the same time
imprint a structure that can trigger the development of a weather system. This
approach is referred to as the adapted 3D-Var was first proposed by Hello and
Bouttier (2001). A different formulation has been proposed and implemented
within the 3D-Var operational system of the Meteorological Service of Canada.
Experiments were carried out with different definitions of the sensitivity
functions to show their impact on the forecast. The analyses obtained with the
adapted 3D-Var were compared with respect to those of the operational 3D-Var and
to the sensitivity analysis in terms of their impact on forecasts. The adapted
3D-Var is shown to reduce the forecast error over the targeted area while at the
same time improving the fit to the observations over the sensitive areas.
A new kind of Static Fourier Transform Spectrometer for
atmospheric CO2 monitoring
Antoine Lacan
CNES
(antoine.lacan@cnes.fr) Abstract
CO2
is the major contributor to global warming. Yet, the current knowledge of the
carbon cycle cannot permit to predict correctly CO2 influence on the climate. To
increase this knowledge the spatial resolution of CO2 concentration measurements
must be better. The scientific community has expressed the need of measurements
at regional scale (the current on ground measurement network is a continental
network). Such a measurement cannot but be achieved thanks to a space remote
sensing monitoring. However, measurements must reach a precision better than 1 %
on the column mixing ratio in order to provide complementary information to the
on ground sparse but accurate measurement network.
CNES has developed a new
kind of Static Fourier Transform Spectrometer, which allows a spectral
resolution in acquaintance with the precision need, and, has smaller dimensions
than classical spectrometers compatible with micro satellite platform.
An on
ground breadboard is being built, its aim is to experiment the instrumental
concept and more precisely to test this concept for CO2 measurement. The
spectrometer is centred on a CO2 absorption band at 1573 nm (6357 cm-1). Spectra
are recorded on a spectral window 5.5 nm (22.5 cm-1) wide with a spectral
resolution of 0.04 nm (0.15 cm-1). A year long CO2 measurement campaign is
planned to examine the feasibility of the atmospheric column concentration
measurement.
Distributions of nitric acid in the troposphere and the
stratosphere derived from satellite measurements in the infrared
Catherine Wespes
Université Libre de Bruxelles
(cwespes@ulb.ac.be)
Abstract
Reactive nitrogen compounds play an essential role in
processes that control the ozone abundance in the low atmosphere. There remains,
however, significant lack of data regarding both the distributions of some
nitrogen oxides (NO, HNO3, PAN) in the troposphere and basically of all NOy
compounds at higher altitudes (upper troposphere and stratosphere).
In
this work, we analyze the distributions of HNO3 retrieved from the solar
occultation measurements collected by the Atmospheric Chemistry Experiment (ACE)
on the Canadian Scisat satellite in 2004 and from the nadir-looking
Interferometric Monitor of Greenhouse Gases (IMG), which operated onboard the
ADEOS platform between 1996 and 1997.
The HNO3 distributions obtained by ACE
in the upper troposphere and the stratosphere are presented and discussed by
comparison with the distributions of other nitrogen oxides, obtained by the same
instrument.
HNO3 abundances provided by the IMG measurements contain some
vertical information and permit us to derive, for the first time, global
distributions of HNO3 in the troposphere and the stratosphere. These results for
the troposphere are discussed by comparison with the distribution of NO2
obtained by the Global Ozone Monitoring Experiment (GOME) instrument for the
same period in April 1997.
Validation of NINFA aerosol optical thickness in the
Po-Valley with AERONET sunphotometer measurements
Suzanne Jongen
ARPA-SIM
(sjongen@smr.arpa.emr.it)
Abstract
In this poster, the ability of the air quality modelling
system NINFA to calculate aerosol optical thickness (AOT) in the Po-Valley is
evaluated. NINFA (North Italian Network to Forecast Aerosol pollution) forecasts
daily NO2, O3, SO2 and aerosol (PM10/PM25) concentrations (horizontal resolution
10 km) for the Northern part of Italy
(www.arpa.emr.it/smr/pagine/ambiente/nordItalia/).
It uses the three
dimensional chemical transport model Chimere
(http://euler.lmd.polytechnique.fr/chimere), driven by the meteorological model
LAMI (http://cosmomodel.
cscs.ch/public/various/operational/arpa/operationalAppsARPA.htm). Chimere
describes the most important phenomena affecting atmospheric pollutants:
emission, diffusion, transport, chemical reactions, depositions. Furthermore it
contains an aerosol module describing aerosol size distribution, -dynamic
processes and – chemistry.
AOT is calculated from the NINFA output
considering the aerosol extinction coefficient (Rayleigh and Mie theory) and the
vertical mass distribution. It is compared with AERONET sunphotometer
measurements at Modena and Venice. Results show good agreement.
As soon as
satellite data with a higher spatial- and temporal resolution are available,
NINFA AOT will be also validated with satellite data. If the validation is
succesfull, a lookup table, generated by NINFA, can be used to retrieve directly
NO2, SO2, O3 and aerosol concentrations /profiles from satellite AOT
measurements.
Search of solar induced effects on the ozone layer
Alessandro Damiani
Istituto di Scienze dell'Atmosfera e del Clima
(CNR)
(a.damiani@isac.cnr.it) Abstract
Present knowledge
related to solar induced effects on the ozone layer variability is discussed.
The following four main sources of variability are considered:
i. the
electromagnetic solar radiation;
ii. the solar wind, the electron
precipitations and auroral activity;
iii. the changing galactic cosmic ray
incoming;
iv. the transient effects induced by the arrival of energetic
solar particles.
In particular, examples of the mesospheric depletions
during energetic solar particle events are illustrated.
How good are simulated water vapour distributions in the
upper-troposphere/lower-stratosphere region?
David Livings
Department of Meteorology, University of
Reading
(D.M.Livings@rdg.ac.uk) Abstract
This project involves
comparison of UTLS water vapour predictions from the ECMWF forecasting system
with independent sources of data, especially satellite data. The aim is to
identify shortcomings in the model and to devise ways of correcting them. The
poster will present the results of preliminary comparisons.
The potential of SCIAMACHY hydroxyl airglow emissions to
derive atomic oxygen and hydrogen in the mesopause region
Catrin Lehmann
Forschungszentrum Juelich
(c.lehmann@fz-juelich.de)
Abstract
The energy budget of the upper mesosphere - lower
thermosphere (UMLT) region is significantly determined by atomic oxygen and
atomic hydrogen. Both species are very difficult to measure directly, and global
datasets are rare. One possibility to derive these species is via the
measurement of vibrationally excited OH.
Vibratationally excited OH is
produced in the O3 + H -> OH + O2 reaction, which is the most important loss
mechanism of ozone during nighttime. By applying a detailed non-LTE model of OH
considering the various production and loss mechanisms, the chemical heating can
be directly derived. If ozone abundance is measured simultaneously, one can also
derive atomic hydrogen denisities, and, in addition, atomic oxygen densities.
The ENVISAT satellite gives a unique possibility to derive all of these
quantities by the combination of SCIAMACHY and GOMOS data. Nighttime limb
measurements of SCIAMACHY extend from 75 to 100 km altitude. They cover the UV,
visible and near infrared region. In this study, data in the wavelength range
from 1 µm to 1,75 µm is used. GOMOS star occultation measurements provide
nighttime ozone abundance in the mesosphere and lower thermosphere.
Lagrangian Diagnostics of Tropical Cirrus
Akos Horvath
Rosenstiel School of Marine & Atmospheric
Science
(ahorvath@rsmas.miami.edu) Abstract
Cirrus clouds
associated with tropical deep convection play an important role in regulating
Earth's climate by influencing the radiative and moisture budgets of the upper
troposphere. In this study, we seek to better understand the evolution of such
clouds by creating a Lagrangian data base of convective systems. Specifically,
we are tracking 250km x 250km water vapor spatial patterns in hourly MTSAT
imagery using cross-correlations. The end product of our tracking algorithm is a
Lagrangian data base of cloud trajectories and associated cloud properties and
sea surface temperatures documenting the origin, evolution, and decay of cloud
systems. We are obtaining cloud properties (such as optical thickness, effective
radius, and ice water path) from the VISST/SIST algorithm developed by the NASA
Langley Cloud and Radiation Research Group (Minnis Group) and microwave sea
surface temperatures from Remote Sensing Systems. Our poster details the
methodology behind our automated cloud tracking algorithm, and presents a
preliminary statistical summary of the evolution of cirrus properties as a
function of sea surface temperature and their effects upon the downstream upper
tropospheric humidity.
Retrieval of Carbon Monoxide from MIPAS measurements
Claudio Belotti
IFAC CNR
(c.belotti@ifac.cnr.it)
Abstract
The Michelson Interferometer for Passive Atmospheric
Sounding (MIPAS), is operating on Envisat since March 2002, measuring
high-resolution atmospheric limb emission spectra in the interval from 685 to
2410 cm^-1 with a resolution of 0.025 cm^-1. For each orbit MIPAS performs 75
limb scans, each made of 17 spectra, 14 orbits per day.
In order to
manage this amount of data MIPAS/Envisat Payload Data Segment Level-2 analysis
is focused on the retrieval of profiles of pressure, temperature and volume
mixing ratio of six target species (H2O, O3, HNO3, CH4, N2O and NO2).
Nevertheless, spectra contain signatures of various other species. In particular
at IFAC the Optimised Retrieval Model code (ORM) has been used to perform the
retrieval of profiles of CFC-11, CFC-12, ClONO2 , N2O5 and CO.
In this
paper we present the results of CO profile retrieval and on tropospheric CO
monthly concentration mean maps.
Validation of OMI total ozone using ground-based brewer
observations
Vassilis Amiridis
Laboratory of Atmospheric Physics
(vamoir@auth.gr)
Abstract
Near-to-real time as well as “archive quality”
Brewer total ozone observations, which are performed with well
maintained
and calibrated instruments over the Northern Hemisphere have been used for the
validation of the total
ozone column product of the Ozone Monitoring
Instrument (OMI) aboard the NASA EOS-Aura satellite. During the
commissioning phase of OMI, the near-to-real time ground-based data, which
are submitted to the WMO Northern
Hemisphere Ozone Mapping Centre within few
hours after observation, have been employed to check the behaviour of
the
OMI instrument as a function of measuring geometry. In addition the near-to-real
time ground based data are also
used as an early warning tool for the
detection of possible problems during the operation of OMI. Archived groundbased
data have been used to validate more than one year of OMI-TOMS and OMI-DOAS
total ozone measurements.
The comparisons show an agreement of better than
1% for the OMI-TOMS measurements and better than 2% for OMIDOAS.
Retrieval of AOD from ground based Brewer
spectrophotometer measurements in Rome
Valerio Bonacquisti
University of Rome La
Sapienza
(valerio.bonacquisti@uniroma1.it) Abstract
Several
studies have pointed out the important role of aerosols in the Earth’s
atmosphere and their impact on global climate. Reliable long time series of
aerosol optical properties are still not available and there is no satisfactory
worldwide spatial coverage. Here a methodology to retrieve aerosol optical depth
(AOD) from Brewer direct sun measurements in the UV and visible regions is
presented, together with the preliminary results for its application to the
Brewer station of Rome (#067).
Homogeneity of the Vaisala radiosonde RH record
Tuomo Suortti
Finnish Meteorological Institute
(tuomo.suortti@fmi.fi)
Abstract
The results of this study suggest that it is inevitable
that the past changes in instrument performance will affect the homogeneity of
the radiosonde humidity (RH) record. The effects of developing measurement
technology are demonstrated best in the comparison of radiosonde data and ERA-40
time-series. In this comparison, climatologies for the whole record, and its
sub-periods, have been compared and the effects due to the changes in sonde
generations was estimated.
In addition, the differences between various
Humicap generations (RS80-A, RS90, RS92) and FN-sondes, were further assessed by
using the LAUTLOS-WAVVAP radiosonde hygrometer comparison results.
The
performance of the RS80-A in the upper troposphere has been debated for some
years, and several correction algorithms have been presented for correction of
these errors (Leiterer et al. , 2000, Miloshevich et al., 2001). The main
problems with Humicap measurement technology are related to the
temperature-dependent dry bias and time lag, and in addition, the effects of
chemical contamination (in the RS80-A). In this study, the impact of these
corrections were evaluated. The corected RH climatologies over Finland revealed
that the correction of the past two decades of radiosonde RH data will have a
drastic effect to the trend.
Theme: Land
Exploiting synergies of global land cover products for carbon
cycle modeling
Martin Jung
MPI-Biogeochemistry, Jena
(mjung@bgc-jena.mpg.de)
Abstract
This poster addresses the user community of global land
cover products. The overall objective is to present a straight forward method
that merges existing products into a desired classification legend. This process
follows the idea of convergence of evidence and generates a ‘best-estimate’
data set using fuzzy agreement. The method is applied to develop a new joint 1
km global land cover product (SYNMAP) with improved characteristics for land
cover parameterization of the carbon cycle models that reduces land cover
uncertainties in carbon budget calculations.
The overall advantage of the
SYNMAP legend is that all classes are properly defined in terms of plant
functional type mixtures, which can be remotely sensed and include the
definitions of leaf type and longevity for each class with a tree component.
Corroboration of SYNMAP against GLCC, GLC2000 and MODIS land cover products
reveals improved agreement of SYNMAP with all other land cover products and
therefore indicates the successful exploration of synergies between the
different products. SYNMAP is available on request from Martin Jung.
Spatial data-base of springs with the Dłubnia drainage basin as
an example.
Piotr Chelmicki
Department of Geoinformatics and Applied Computer
Science, Faculty of Geology, Geophysics and Environmental Protection, AGH
University of Science and Technology
(pchelmicki@geol.agh.edu.pl)
Abstract
For the past few years, creation a massive database of
springs was a frequent issue raised during several scientific conferences in
Poland. Up to now the database of that kind does not exist. The poster presented
shows an example of the spatial data-base used for storage and presentation of
geographical and hydrogeological characteristics of springs, with the springs of
the Dłubnia drainage basin (S. Poland) as an example. The data-base was created
using GeoMedia Professional and Microsoft Access packages. The information
stored covers the following characteristics of springs: geographical position,
aquifer description, water discharge, physical and chemical parameters of water.
The created database is to be used by Department of Hydrology, Jagiellonian
University, Cracow, for gathering, storing, updating and modifying data obtained
during field research. Application uses topographic maps along with
ortophotomaps to visualize the researched area and the springs themselves.
While created database covers only a fraction of springs in Poland, it may
serve as an example for further development and a model of using relational
database along with GIS technique in hydrological database applications.
Satellite estimation of biophysical parameters for ecological
models
Ana Prieto-Blanco
University of Wales Swansea
(304376@swan.ac.uk)
Abstract
The aim of this study is to establish a high-level
framework for the development of future satellite sensors linking ecological
models requirements and satellite capabilities.
The study focuses on
multi-spectral sensors with multiple viewing angles and the parameters
considered are: cover fraction, leaf area index (LAI), effective fraction of
absorbed photosynthetically active radiation (fAPAR), leaf chlorophyl content
and aerosol optical thickness. Two widely used ecological models - JULES and
BiomeBGC - are evaluated over three boreal coniferous forests.
The
soil–vegetation–atmosphere radiative transfer is simulated using a
combination of the PROSPECT, FLIGHT 5.5 and 6S models. These models are inverted
by means of a Look-Up-Table (LUT) approach. The advantage of the LUT technique
is that it allows inversion of any model with a minimum of simplifying
assumptions A second advantage is its low computer resources requirement at
run-time as the complex calculations are carried out once in advance.
Top-of-the-atmosphere (TOA) reflectances with different levels of noise
are used as “measured reflectances” in the retrieval of parameters from this
LUT. The retrieved parameters are then used to evaluate the sensitivity of
ecological models in terms of net primary production (NPP) estimated. Optimal
spectral and directional sampling configurations are analysed as well as the
effect of different levels of radiometric noise.
Statistical Learning Methods for Improving the Efficiency in
Landscape Image Clustering and Classification Problems
Selime Gurol
TUBITAK - BILTEN
(e141133@metu.edu.tr)
Abstract
Remote sensing techniques are vital for early detection
of several problems such as natural disasters, ecological problems and
collecting information necessary for finding optimum solutions to those
problems. Remotely sensed information has also important uses in predicting the
future risks, urban planning, communication.
Recent developments in remote
sensing instrumentation offered a challenge to the mathematical and statistical
methods to process the acquired information. Classification of satellite images
in the context of land cover classification is the main concern of this study.
Land cover classification can be performed by statistical learning methods like
additive models, decision trees, neural networks, k-means methods which are
already popular in unsupervised classification and clustering of image scene
inverse problems. Due to the degradation and corruption of satellite images, the
classification performance is limited both by the accuracy of clustering and by
the extent of the classification. In this study, we are concerned with
understanding the performance of the available unsupervised methods with
k-means, supervised methods with Gaussian maximum likelihood which are very
popular methods in land cover classification. A broader approach to the
classification problem based on finding the optimal discriminants from a larger
range of functions is considered also in this work. A novel method based on
threshold decomposition and Boolean discriminant functions is developed as an
implementable application of this approach. All methods are applied to BILSAT
and Landsat satellite images using MATLAB software.
Estimation of crop biophysical parameters as tool for precision
agriculture
Raul Lopez-Lozano
Centro de Investigacion y Tecnologia Agroalimentaria de
Aragon
(rlopezl@aragon.es) Abstract
Remote sensing constitutes
an important tool that could help to precision farming techniques that are being
applied in the last years. The purpose of this study is providing information
about the crop development that could be used as a source of information in
precision agriculture systems. Leaf Area Index (LAI) was estimated on two
different types of canopies, vineyard and corn, applying radiative transfer
models (RTM) on Quickbird imagery. Modelization of reflectance was carried out
using Markov Chain Canopy Reflectance Model (MCCRM) and a specific 3D model for
corn and rowMCCRM on vienyards. Iterative optimization and scaling up were
applied to retrieve LAI from reflectance showing acceptable accuraccy in
estimations (RMSE=0.50 for corn canopies and RMSE=0.38 for vineyards)
Soil parameters (electrical conductivity, presence of different
minerals...) and crop yield were also collected in situ and georeferenced. This
field information was plotted against LAI maps generated by means of RTM showing
that growing patterns described in satellite imagery are related with final crop
yield and soil charateristics that are present in the field. The integration of
generated spatial information (LAI, soil and yield maps) in a GIS could help in
taking decisions within precision farming systems.
An automatic method for operational calibration of AVHRR
reflective time series data
Michael Schmidt
CSIRO
(michael.schmidt@csiro.au)
Abstract
The Advanced Very High Resolution Radiometer (AVHRR)
data record acquired by instruments on the NOAA polar orbiting spacecraft series
comprises the longest existing daily remote sensing dataset (1979-2005). Inter-
and intra-satellite factors affect the usability of these data for the
generation of consistent time series. The temporal variation of the instrument
sensitivity in the short-wave reflective channels needs to be addressed to
ensure that derived trends are not sensor artifacts.
We describe a new
method using the Multivariate Alteration Detection (MAD) algorithm to
automatically select invariant features from multiple image pairs that are then
compared to assess change in instrument sensitivity. This method requires no
regional knowledge and is globally applicable. The derived calibration time
series is shown to remove long term trends from Pseudo Invariant Features (PIFs)
located in central Australia. The resulting MAD-based calibration has a root
mean squared error of ~5-6% for both channel 1 and 2 and is in alignment with
other approaches, and is preferable due to its operational nature.
Structural quantification of vegetative canopies based on
close-range remote sensing: from 2-D to 3-D.
Inge Jonckheere
Katholieke Universiteit
Leuven
(Inge.Jonckheere@biw.kuleuven.be) Abstract
Rapid,
reliable and objective estimations of leaf area index (LAI), defined as one half
the total intercepting area per unit ground surface area, are essential for
numerous studies of atmosphere-vegetation interaction, as LAI is very often a
critical structural parameter in process-based models of canopy response to
global
environmental change. The usefulness of indirect optical LAI
measurements by means of hemispherical canopy photography has already been
demonstrated in that context. LAI is then calculated by gap fraction inversion.
The interpretation of gap fraction in terms of LAI from optical in situ methods
is based on light extinction models, which link LAI and canopy structure to the
penetration of solar radiation through the canopy. This approach however is
limited to 2-D since the records used are 2-D projections of the vegetation
canopy,and consequently the canopy profile (z-dimension) is added based on model
assumptions. The advances in terrestrial laser-scanning of vegetation during the
last few years are quite promising and resulted in a variety of vegetation
structure reconstructions that are based on the evaluation
of 3-D point
clouds, which allow for adding the actual z-dimension for the LAI estimations in
vegetation canopies.
Multiangular Earth observation: validation of information for
improved terrestrial carbon cycle understanding
Martin Béland
CARTEL, University of
Sherbrooke
(martin.beland@usherbrooke.ca) Abstract
In the
context of growing concerns about global warming and its potential consequences
on humanity, reliable information about the sources and sinks of greenhouse
gases are increasingly needed. CO2 has the most significant contribution to the
greenhouse effect; its concentration in the atmosphere has increased
considerably since the industrial revolution, in part due to fossil fuel
burning. Part of these emissions has been absorbed by the Worlds oceans and
trees, which act has sinks, but in the case of forests can also act has sources
depending on management regime and natural events. Better understanding of this
terrestrial component of the carbon cycle is a crucial element of our future
ability to modify the global carbon cycle. This research aims at validating an
Earth observation method developed to characterize forest structure at large
scales. This information is of great importance for carbon cycle modeling, and
knowledge on its accuracy is essential. The main objective is the comparison of
the output of model inversion on MISR data with exhaustive field measurements
taken simultaneously with the satellite passage. It will be carried out in a
savanna environment of north-east Argentina; savannas being highly used and
often disturbed, and consequential for the global carbon exchange flux.
Remote sensing derived data for forest management modeling
Hannes Boettcher
Max Planck Institute for
Biogeochemistry
(hboett@bgc-jena.mpg.de) Abstract
While
globally pristine forests decline in area, managed forests expand. Science of
managed forests and the goods and services they deliver - such as timber,
bioenergy supply and carbon sequestration - will become more important in the
future.
The development of forest ecosystems under different management
scenarios can be projected into the future with the help of forest sector
models. Crucial information is data on forest area and biomass distribution
which is in general provided by forest inventories. However, this information is
not geographically explicit. At the current state remote sensing is capable to
deliver reliable estimates of forest area. From the comparison of satellite time
series regional management history can be observed which facilitates the
geographical allocation of forest age class structure. To detect the current
forest biomass distribution and other production related parameters, a
combination with ground based information from sample plots is needed. Large
scale information on forest distribution, biomass and productivity can provide
both, input and validation data for forest management models.
We want to use
remote sensing products to make inventory information more spatially explicit
and improve forestry model estimations of trends and potentials associated with
forest management and its services.
Preserving Switzerland's natural heritage: Remote Sensing for
the protection and conservation of Swiss dry meadows and pastures.
Achilleas Psomas
PhD Researcher
(Achilleas.Psomas@wsl.ch)
Abstract
Dry grasslands are amongst the most species rich
habitats of Switzerland. They are the result of centuries of sustainable land
use by man and their distinctive compositional and structural characteristics
depend greatly on climate, topography and the cultural history of each area. In
addition, dry grasslands are very important for nature conservation since 40% of
plant and in some cases over 50% of the animal species present on these dry
grasslands are included in the red lists and are classified as endangered or
threatened. However, these species-rich grasslands are endangered. It is
estimated that over the past 60 years their area has declined by about 90%
mainly due to intensification of agriculture.
In this poster we present a
remote sensing approach for improving the identification and assisting with the
monitoring of dry grasslands in Switzerland. We develop and apply a methodology
using information obtained from remote sensing sensors operating at different
spectral, spatial and temporal scales. We start at the plot-field scale using
ASD field-spectroradiometer recordings then move to a regional scale with Hymap
and Hyperion data and eventually come to the landscape scale with the use of
Landsat TM/ETM+ data.
The general outline and specific results of our
approach are presented.
Assimilation of meteorological and satellite data in snowmelt
runoff models
Petra Malcher
ENVEO IT GmbH
(petra.malcher@enveo.at)
Abstract
In mountainous terrain, topographically induced
variability of meteorological parameters governing snowmelt is complex, making
spatially distributed estimates an essential requirement in alpine hydrology.
Therefore preprocessing modules have been developed, accomplishing temporal and
spatial assimilation of either meteorological point- (measurements) or
raster-data (model forecasts). If the database comprises different time scales
temporal integration is applied, for spatial interpolation the IDW-method is
used. Besides meteorological data, snowmelt runoff modelling requires spatially
detailed information on snow cover, which is derived from satellite observations
using automated classification procedures. In order to minimize the gaps between
satellite acquisitions, snow cover information obtained from different sensors
(ASAR, MERIS, MODIS) are used in common. To correct for sensor specific
differences in the obtained snow cover, either caused by different imaging
geometry or target interaction mechanisms, a simple statistical approach is
used. Daily values of snow extent on days without satellite coverage are
obtained by applying a snow depletion model based on meteorological data. The
use of the assimilated datasets is demonstrated in a semi-distributed snowmelt
runoff model, which is operated on a daily basis in two high Alpine
catchments.
Modeling the relationship between directional and hemispherical
thermal emission
António José Rocha
DCEA FCT-UNL
(ajgr@fct.unl.pt)
Abstract
Upwelling long wave radiation (UPLW) over land is
required to close the surface energy budget and is an important input parameter
to many land surface process models. Over large areas, UPLW must be determined
indirectly since it is not possible to directly measure hemispherical parameters
at high temporal and spatial scales using remote sensing techniques. Land
Surface Temperature (LST), a common operational satellite product, is closely
related to UPLW, although it has limitations since it varies with sun-view
geometry. One way to estimate hemispherical UPLW from directional LST retrievals
is to use a physically-based model of radiation angular anisotropy, such as the
Modified Geometric Projection (MGP) model. MGP is based on a widely-used
Geometric Optics model, and it’s computationally fast such that it can be used
with global data sets.
In this study, the determination of the view angles
at which radiance is most closely correlated with hemispherical UPLW is
investigated. A sensitivity analysis of the MGP to the surface parameters that
most strongly affect this relationship is also performed.
Current results
were tested comparing the UPLW MGP estimates with tower-based pyrogeometer data
over a savannah site in southern Africa collected during SAFARI 2000
experiment.
Crop Drought Stress Monitoring by Remote Sensing
Georg Kaiser
Institute of Surveying, Remote Sensing and Land Information,
University of Natural Resources and Applied Life Sciences,
Vienna
(georg.kaiser@boku.ac.at) Abstract
The aim of this
project is to adapt and develop remote sensing based methods of detection and
monitoring of drought stress of agricultural crops (wheat and maize) exploiting
the potentials of optical remote sensing and the synergetic effects of various
sensor types offering different levels of spatial, spectral and temporal
resolution. To this end, physical vegetation canopy models describing the
relationship between drought stress level and reflectance characteristics of the
plants are being adapted and improved. The canopy reflectance models are usually
divided into two parts: modules to calculate the reflectance at leaf level (e.g.
PROSPECT) and routines to calculate the reflectance of the whole canopy (e.g.
SAIL). Drought stress may influence plant reflectance at leaf and at canopy
level. Biophysical crop parameters indicating drought stress such as chlorophyll
content and the leaf area index (LAI) can then be derived from reflectance
measurements by inversion of the reflectance models using artificial neural
networks or a look-up table approach. The applicability of data assimilation
techniques to the problem of crop drought stress monitoring by remote sensing is
discussed.
Ephemeral Water Resources Assessment in Arid Lands
Gaia Vaglio Laurin
ACS spa
(g.laurin@acsys.it)
Abstract
in progress
The influence of temperature and precipitation climate regimes
on vegetation dynamics: A satellite bioclimatology case study
Su-Yin Tan
Department of Geography, University of
Cambridge
(syt23@cam.ac.uk) Abstract
AVHRR-derived NDVI data
are widely used in global-change research, yet relationships between the NDVI
and ecoclimatological variables are not fully understood. This study attempts to
better define these relationships by modelling climate-driven vegetation
dynamics through a multivariate, spatio-temporal analysis of satellite-derived
NDVI data and ground-based meteorological data in the U.S. Great Plains. Monthly
maximum value composites of NDVI data (8-km resolution) and monthly temperature
and precipitation records from 305 stations were collected from 1982 to 2001.
Analyses involving deseasonalized datasets supported temperature as the dominant
climate regime, demonstrating a higher average NDVI/temperature correlation (r =
0.73) than the NDVI/precipitation relationship (r = 0.38). The PCA also
supported temperature as the dominant climate regime, accounting for 43.1% of
the variance in the spatial distribution of NDVI. Cluster analysis was used to
develop a climate regionalization scheme based primarily on temperature, and
NDVI characteristics of each sub-region were compared. The statistical modeling
methods applied were useful in capturing and characterizing the seasonal
response of NDVI to climate variability. In the context of global climate
change, findings from this satellite bioclimatology study emphasize the
influence of temperature and precipitation variability over vegetation cover in
the Great Plains region.
Remote Sensing Image Classification Method Based on
Geostatistics and ANN
Xiaotao Li
China Institute of Water Resources and Hydropower
(lxtsxn@hotmail.com) Abstract
Texture is the key character of
remote sensing image.In this paper, the image texture is extracted by means of
semivariogram. On the base of this, the study adopts the back propagation
artificial neural network method to classify Combining spectral feature with
many sort of textures. Then the classification results are compared with those
gained by maximum likelihood method and the results of the study proved that the
way that combining spectral features and textural measures based on the
geostatistics and NN theory to the classification of the remote sensing image
may improve the accuracy of image classification.
Fire severity mapping using Landsat 5 - TM, Envisat - MERIS and
Terra - MODIS post-fire images
Asuncion Roldan-Zamarron
Spanish Institute for Agricultural Research
(INIA) - Remote Sensing Laboratory
(roldan@inia.es)
Abstract
This analysis concerns an estimation of burned area and
fire severity levels in an area affected by a large wildfire that took place in
the South of Spain (Huelva-Sevilla) in July 2004. Fire severity is defined in
this work as the impact caused in vegetation by a fire. The objective was to
find an efficient method for quick fire severity mapping based on remote sensing
techniques that can be useful fos post-fire forest management. Several methods
for image analysis (Linear Spectral Unmixing, Matched Filtering, and Normalized
Burn Ratio Index) were applied to post-fire Landsat 5-TM, Envisat-MERIS and
Terra-MODIS images. Maps depicting fire severity of three levels of an
acceptable reliability were obtained using a small amount of field data and
following a simple method of processing. Linear Spectral Unmixing produced the
best classifications for MERIS and MODIS images, while the Matched Filtering
technique produced the most accurate classification for the TM image. These
preliminary results show that short-term severity maps can be obtained by means
of high to medium resolution post-fire remote sensing data, in order to evaluate
the situation after a forest fire and plan forest restoration works.
Assessment of time-dependent biases in the MODIS Land Surface
Temperature (MOD11_L2) product
Nuno Pacheco
New University of Lisbon
(nrap@fct.unl.pt)
Abstract
Land surface temperature (LST) is a key land parameter
to estimate the energy and hydrologic state of the Earth's surface. Over large
areas, this parameter is typically retrieved from moderate resolution sensors
(e.g., AVHRR, MODIS, AATSR) on polar-orbiting satellites (e.g., POES, EOS
Terra/Aqua, ENVISAT). However, these wide-field-of-view (~2000-3000 km wide
swath) sensors can observe land targets at very different local times (e.g.,
hours apart) within a single sub-second scan. Since instantaneous LST depends in
part on environmental and sampling variables that change predictably with time
(e.g., cumulative solar heating, atmospheric state, sun-view observation
geometry), systematic measurement biases may exist based solely on pixel
position within a swath. The goal of this study is to determine if statistically
significant temporal biases exist within swath LST data, and if so, to evaluate
their magnitude as a function of latitude, time of day and year, land cover
type, view geometry and other ground and observational parameters. We use data
from the MODerate-resolution Imaging Spectroradiometer (MODIS) LST product,
MOD11_L2 swath scenes, 1 km spatial resolution (at nadir), in our analysis. We
focus our study on the African continent and the year 2001. We will discuss
potential errors in our approach, and will conclude by proposing a method to
correct within-swath temporal biases.
Theme: Ice
Identification of Sea Ice Catchment and Snow Distribution from
Remote Sensing Data
John Iacozza
Centre for Earth Observation
Science
(iacozzaj@cc.umanitoba.ca) Abstract
The ocean-sea
ice-atmosphere (OSA) interface, is an important region for mass, gas and energy
transfer in the Arctic marine cryosphere. Snow regulates the growth and decay of
sea ice through its control on conductive and radiative fluxes across the OSA
interface. Through these processes snow moderates the global climate and is a
major controlling factor in the ecology of the Arctic system from algal
production in the ocean to habitat selection of apex predators such as polar
bears and whales. The pattern of snow distribution is primarily controlled by
the ice surface topography (Iacozza and Barber, 1999; Eicken et al., 1994;
Adolphs, 1999; Jeffries et al., 1995). These variations in the snow distribution
patterns for various ice types have significant influences on understanding the
physical-biological coupling. The primary objective of this research is to
investigate the relationship between sea ice surface roughness and snow
distribution for different classes of first-year sea ice at the satellite scale.
This will be accomplished by (i) characterizing ice roughness for fast and
mobile ice in Franklin Bay using EM induction data, (ii) relate the variability
at the local scale to that for satellite imagery using ASAR data, and (iii)
linking ice roughness to snow catchment at the satellite scale.
An Optimization Approach to Modelling Sea Ice Dynamics
Helga Schaffrin
University of Washington
(helga@amath.washington.edu)
Abstract
A new model for the dynamics of sea ice is explored. The
pressure field, instead of being derived from a local rheology, as in most
existing models, is computed from a global optimization problem. Here the
pressure is seen as emerging not from an equation of state but as a Lagrange
multiplier that enforces the ice's resistance to compression while allowing
divergence. The resulting variational problem is solved by minimizing the
pressure globally throughout the domain, constrained by the equations of motion
along with the natural limits on ice concentration. This formulation has an
attractive mathematical elegance while being physically motivated. Moreover, it
leads to an analytic formulation that is also easily implemented in a numerical
code, which exhibits marked stability and is suited to capturing
discontinuities.
The theory is initially tested in a one-dimensional model in Lagrangian
mass coordinates. The model results are compared to an exact analytic solution
for a simple test case, as well as to a particle-resolving model. After casting
the model in Eulerian coordinates, a finite ice strength is introduced,
permitting the important process of ice yielding to be captured.
Geometric changes of Austfonna Ice Cap, Svalbard
Geir Moholdt
University of Oslo
(geir.moholdt@geo.uio.no)
Abstract
Austfonna, 8200 km2, is one of the largest arctic ice
caps outside of Greenland. Apart from a few studies, little is known about its
response to recent climate change. As a part of the ESA collaborated campaign
for calibration and validation of the future CryoSat, the University of Oslo and
the Norwegian Polar Institute have set up an extensive program on Austfonna
which involves annual fieldwork of key glacier parameters. Ground truth data are
compared with simultaneous CryoSat simulation flights in order to correlate
physical properties of the snowpack with penetration depth and volume scattering
of the CryoSat radar signal.
Elevation changes on the ice cap are
estimated from annual GPS/GPR-profiles, airborne radar/laser overflights and
satellite altimeters such as ICESat, ERS/ENVISAT and future CryoSat. Some of
these measurements willl be combined with SAR interferometry from ERS/Envisat in
order to produce a more accurate DEM. In terms of geometric changes, the dynamic
regime of the ice cap also needs to be considered. Surface velocities are
measured on ground by repeated GPS measurements, and velocity fields can be
identified by differential InSAR.
Wind-blown snow interactions with a rift in the Ross Ice Shelf,
Antarctica
Katherine Leonard
Lamont-Doherty Earth Observatory / Columbia
University
(kleonard@ldeo.columbia.edu) Abstract
The Nascent
Rift in the Ross Ice Shelf, Antarctica has persisted for several years, with a
distinctive profile of ice mélange (a mixture of windblown snow, marine ice,
and pieces of ice talus broken from the ice shelf) filling it at a depth of
roughly 30m below the surrounding shelf surface. Modeling results obtained using
the Piektuk-Tuvaq blowing snow model (Dery & Tremblay, 2004) suggest that
the contribution of blowing snow to this mixture is significant. Windspeeds
sufficient to entrain snow into suspension occur during 20% of the year (73
days). Coincidentally, 73 days of 25m/s wind (at the 10m height) could fill the
100m wide by 30m deep rift with snow, while 16 years of 7.5 m/s winds are
required to deposit this same volume, due to the non-linearity of the suspended
snow mass transport Qt with windspeed. The saltating horizontal mass flux of
snow at low windspeeds is significant relative to the suspended blowing snow
mass flux. As the saltation threshold for snow is substantially lower than the
threshold for suspension, the annual mass flux of snow via this mechanism is
important, due to the greater amount of time when the region experiences such
low windspeeds.
Theme: Earth system
Monitoring Crop Evapotranspiration with Time Series of
MODIS Satellite Data in Northern Italy
Simone Rossi
CNR-IREA
(rossi.s@irea.cnr.it)
Abstract
Crop water need is defined as the water needed to meet
the loss through Evapotranspiration (ET). ET depends on meteorology and on the
crop type, health and phenological stage. The FAO methodology calculates crop ET
as the product of crop-specific coefficients (Kc) by the reference
evapotranspiration (ETo) and has been widely applied for irrigation planning,
using only three tabulated values of Kc referring to key phenological stages.
However, this approach cannot always match the Kc with the actual crop growth.
Previous research showed a linear relationship between Kc and Vegetation
Indexes (VI) from remote sensing. This relationship has recently been used with
high resolution images. This work aims at exploring the use of MODIS data to
operationally monitor Kc temporal and spatial variability and therefore crop
water needs.
MODIS time-series of VI have been processed with the
Savitzky-Golay filter. Kc tabulated values are then linearly related with the
corresponding VI values on the smoothed curve, obtaining a daily surface of Kc
values. Daily Kc maps are then multiplied by daily ETo surfaces (obtained with
geostatistical methods from meteorological stations data) to obtain daily maps
of potential crop ET, which is the crop water need to meet the atmospheric water
demand.
Time-variable Gravity Changes and Surface Deformation Due
to Atmospheric, Oceanic and Hydrologic Loading Processes
Jean-Paul Boy
EOST-IPG
(jpboy@eost.u-strasbg.fr)
Abstract
The global circulation of the surface geophysical fluids
(atmosphere, ocean, continental hydrology, etc.) induces mass redistribution at
the Earth’s surface and therefore gravity changes as well as global
deformation. These effects can be easily measured by many geodetic techniques
over a broadband spectrum (from a few hours to decades).
The precision
reached nowadays by geodetic observations (gravity changes measured by
superconducting gravimeters or by satellites, deformation measured by worldwide
GPS networks) allows detecting the effects induced by loading processes with
amplitudes of a few millimeters of equivalent water height, and spatial extends
of a few hundreds kilometers.
We focus especially on the GRACE (Gravity
Recovery And Climate Experiment) mission, showing its ability to detect long
wavelength continental hydrology changes at seasonal timescales. We also show
the crucial need for better ocean models at high frequencies (periods lower than
typically 10 days), describing the ocean response to atmospheric pressure and
winds, which are required for the processing and the de-aliasing of the GRACE
data.
Remote Sensing to Improve Water Quality Modelling in the
Land-Ocean Interface of a Coastal Catchment in Queensland, Australia
Birte Schoettker
Australian National University and
CSIRO
(birte.schoettker@anu.edu.au) Abstract
The changing
nature of coasts is the result of global and regional drivers, operating at
different spatial and temporal scales. Linking information on the land and ocean
interface is a current challenge facing environmental research.
In
Australia, the Burdekin River Catchment is with 130,000km2 the second largest
catchment draining into the unique ecosystem of the Great Barrier Reef – an
area of high iconic, ecological and economical value. The Burdekin River
catchment is highly variable and water quality is a key natural resource
management issue. The sediments and nutrients delivered to the marine
environment get mobilised predominantly during cyclonic and monsoonal events and
the sediment delivery is suggested to have increased fourfold since European
settlement and can exceed 10 Million tonnes per event.
The presented work
focuses on the improvement of the temporal and spatial resolution of existent
sediment erosion models through the integration and assimilation of
multisensoral, multitemporal remotely sensed information and ancillary data from
various sources. Information on certain catchment characteristics is used to
model event based sediment erosion. Furthermore, the objective is to combine the
results with ocean colour satellite sensor applications and modelling in the
adjacent coastal waters.
Satellite Gravimetry using the Energy Balance Approach
Christian Gerlach
Technische Universitaet Muenchen, Inst. Astronomical
and Physical Geodesy
(gerlach@bv.tum.de) Abstract
Since the
early days of satellite geodesy energy balance based methods for gravity field
determination have been considered. If non-conservative forces are known the
Hamiltonian along the orbit is a constant of the motion. Thus the gravity field
can be determined if position and velocity of the satellite are known and
accelerometer measurements are available to model the non-conservative part.
The German satellite CHAMP, launched in 2000, is the first satellite that
provides the user with those three kinds of data nearly continously. The
follow-up gravity satellite mission GRACE (US-German cooperation; launched in
2002) and ESA's upcoming GOCE mission (launch 2007) will extend the accuracy and
resolution of the derived satellite gravity models.
The methodology of the
methods as well as results with simulated and real data will be shown.
Quantifying Carbon Processes of the Terrestrial
Biosphere
Bakr Badawy
Max-Planck Institute for
biogeochemistry
(bbadawy@bgc-jena.mpg.de) Abstract
The
objective of this research proposal is directed at improving our understanding
of the terrestrial carbon cycle and how this can improve the global atmospheric
inversion simulations of the CO2 fluxes. This will carried out through
developing an integrated system of models that couples biospheric and
atmospheric processes across a comprehensive set of spatial and temporal scales.
Remotely-sensed data will play an important role in the development of these
models by providing information on the spatial and temporal variations of many
Earth system parameters including the extent of terrestrial vegetation and its
modification by anthropogenic influences and natural climatic variations.
This study will cover the following tasks:
A. Coupling of a
simple satellite-driven biosphere model to a global atmospheric inversion.
B. Coupling of a linearized terrestrial biosphere process model to a global
atmospheric inversion
C. Coupling of a regional higher-resolution
atmospheric model into a global atmospheric inversion (nesting)
Water Vapour, Energy and Carbon Dioxide Fluxes in a
Chronosequence of Afforested Temperate White Pine Forests in Southern Ontario,
Canada
Natalia Restrepo-Coupe
McMaster University
(restren@mcmaster.ca)
Abstract
The eddy covariance technique has been used to measure
changes in energy, water vapour, and carbon fluxes in a chronosequence of four,
afforested, white pine plantations, in Southern Ontario, Canada. The
chronosequence consisted of 65-year-old (WPP39), 30-year-old (WPP74),
15-year-old (WPP89), and 3-year-old (WPP02) stand.
Our results showed that
the youngest stand behaved as a carbon source during the first two years after
establishment, with NEP values of -18 gC m-2 and -41 gC m-2. By the third year,
the forest went from carbon source to sink (58 g C.m-2). This transition was due
to the increase in light use efficiency, attributed to higher soil moisture. The
three oldest stands were carbon sinks, with three-year (2002-2005) average
annual NEP values of 272, 438, and 719 gC m-2 for WPP39, WPP74, and WPP89,
respectively.
Evapotranspiration (ET) increased sharply from 302 mm, at the
recently planted stand, up to 676 mm, at a 15-year-old one. Afterwards, ET
decreased with stand age to ~412 mm, remaining approximately constant.
We
also observed variability in meteorological parameters, such as VPD, albedo, and
soil moisture across the chronosequence. We were able to show a feedback
relationship between meteorological parameters and energy fluxes as the forest
ages.
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