|From||ALBERGEL Clément <email@example.com>|
|Date||Mon, 10 Apr 2017 15:13:43 +0200 (CEST)|
**Assimilation of satellite data for water resources monitoring in the Euro-Mediterranean area
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 inter-annual 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.
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.
The PhD position is for 3 years, starting on October 1st, 2017.
Salary: around 1430 euros net/month Applicants should send (i) a statement of interest, (ii) a complete CV as well as (iii) copies of transcript of records of your MSc and (iv) contact information for two references via email to Dr Clement Albergel <firstname.lastname@example.org> and to Dr Jean-Christophe Calvet <email@example.com>.
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