PhD-position MeteoFrance; Assimilation of satellite data for water ressources monitoring
Hosting research unit:
CNRM - UMR 3589 (Meteo-France, CNRS)
Proposal title :Assimilation of satellite data for water ressources monitoring in the Euro-Mediterranean
area
PhD supervisors :
Dr Clément Albergel (CR CNRS),
clement.albergel@meteo.fr, +33 561079015
Dr Jean-Christophe Calvet (IGPEF, Meteo-France, Habilitation),
jean-christophe.calvet@meteo.fr, +33 561079341
The increase in the occurrence of extreme weather events (droughts, floods, heat waves) in
connection with global warming is a proven fact. The latest IPCC (Intergovernmental Panel on
Climate Change) simulations indicate that occurrence of droughts and warm spells in the Euro-
Mediterranean region will increase. Observing and simulating the response of land biophysical
variables to extreme events is a major scientific challenge in relation to the adaptation to climate
change. Among them, soil moisture is one of the most difficult to apprehend because of its high
spatial heterogeneity and its strong temporal variability. The modelling of terrestrial variables can
be improved through the dynamical integration of observations. Remote sensing observations are
particularly useful in this context because they are now unrestrictedly available at a global scale.
Many satellite-derived products relevant to the hydrological and vegetation cycles are already
available. Assimilating these data into land surface models permits their integration in the process
representation in a consistent way.
The National Center of Meteorological Research (CNRM) has developed a Land Surface Data
Assimilation Systems (LDAS) able to constrain the ISBA (Interaction-Sol-Biosphere-Atmosphere)
land surface model using satellite derived observations. The LDAS was implemented in a
monitoring chain of terrestrial water and carbon fluxes. It is now the only system able to
sequentially assimilate vegetation products such as LAI together with surface soil moisture (SSM)
observations. SSM can be estimated from radar backscattering coefficient (sigma0) observations
from satellite scatterometers (radar sensors) such as ERS1 and 2, and ASCAT. Current radar-derived
SSM products are based on change-detection approach (e.g. Wagner et al. 2013). This approach is
efficient in eliminating soil roughness effects. Seasonal vegetation phenology effects are accounted
for to some extent, but interannual variability in vegetation effects is not represented. As a result, a
complex seasonal bias correction has to be performed before assimilating SSM in ISBA and the
assimilation is not completely efficient during extreme events affecting vegetation such as droughts.
Since sigma0 contains information on both SSM and vegetation, the LDAS has potential to fully
use this information and to better analyze soil moisture together with vegetation biomass.
The main objective of this thesis is to improve the representation of land surface variables linked to
the terrestrial water and carbon cycles in ISBA through the assimilation of sigma0 ASCAT
observations. The proposed methodology includes (i.) the design of an observation operator capable
of representing sigma0 from the ISBA simulated variables on a global scale, (ii.) a comparison of
the simulated values with those observed from space, and the quantification of the influence of
various factors on the signal (soil moisture, vegetation, open water surfaces, freeze / thaw, snow),
(iii.) assimilation of sigma0 in ISBA and analysis impact on vegetation and on the various variables
of the terrestrial water cycle, (iv) a comparative study of the assimilation of SSM and sigma0 in
ISBA.
The PhD student will use the SURFEX modelling platform, the TRIP river discharge model, and the
data assimilation tools developed by the research team. Since the collaboration with a foreign
research lab (TUWien) is needed for one of the tasks, working language will occasionally be
English.
Reference
Wagner W., S. Hahn, R. Kidd, T. Melzer, Z. Bartalis, S. Hasenauer, J. Figa, P. de Rosnay, A. Jann, S.
Schneider, J. Komma, G. Kubu, K. Brugger, C. Aubrecht, J. Zuger, U. Gangkofner, S. Kienberger,
Y. Wang, G. Bloeschl, J. Eitzinger, K. Steinnocher, P. Zeil, F. Rubel: The ASCAT Soil Moisture
Product: A review of its specifications, Validation Results, and Emerging Applications,
Meteorologische Zeitschrift, 22(1), 2012.doi: 10.1127/0941-2948/2013/0399.