Coupled land surface and radiative transfer models for the analysis of passive microwave satellite observations
Soil moisture is one of the key variables controlling the water and energy exchanges between\nEarth\u2019s surface and the atmosphere. Therefore, remote sensing based soil moisture\ninformation has potential applications in many disciplines. Besides numerical weather\nforecasting and climate research these include agriculture and hydrologic applications like\nflood and drought forecasting.\nThe first satellite specifically designed to deliver operational soil moisture products, SMOS\n(Soil Moisture and Ocean Salinity), was launched 2009 by the European Space Agency\n(ESA). SMOS is a passive microwave radiometer working in the L-band of the microwave\ndomain, corresponding to a frequency of roughly 1.4 GHz and relies on a new concept. The\nmicrowave radiation emitted by the Earth\u2019s surface is measured as brightness temperatures in\nseveral look angles. A radiative transfer model is used in an inversion algorithm to retrieve\nsoil moisture and vegetation optical depth, a measure for the vegetation attenuation of the\nsoil\u2019s microwave emission.\nFor the application of passive microwave remote sensing products a proper validation and\nuncertainty assessment is essential. As these sensors have typical spatial resolutions in the\norder of 40 \u2013 50 km, a validation that relies solely on ground measurements is costly and\nlabour intensive. Here, environmental modelling can make a valuable contribution.\nTherefore the present thesis concentrates on the question which contribution coupled land\nsurface and radiative transfer models can make to the validation and analysis of passive\nmicrowave remote sensing products. The objective is to study whether it is possible to explain\nknown problems in the SMOS soil moisture products and to identify potential approaches to\nimprove the data quality.\nThe land surface model PROMET (PRocesses Of Mass and Energy Transfer) and the\nradiative transfer model L-MEB (L-band microwave emission of the Biosphere) are coupled\nto simulate land surface states, e.g. temperatures and soil moisture, and the resulting\nmicrowave emission. L-MEB is also used in the SMOS soil moisture processor to retrieve soil\nmoisture and vegetation optical depth simultaneously from the measured microwave\nemission. The study area of this work is the Upper Danube Catchment, located mostly in\nSouthern Germany.\nSince model validation is essential if model data are to be used as reference, both models are\nvalidated on different spatial scales with measurements. The uncertainties of the models are\nquantified. The root mean squared error between modelled and measured soil moisture at\nseveral measuring stations on the point scale is 0.065 m3/m3. On the SMOS scale it is 0.039\nm3/m3. The correlation coefficient on the point scale is 0.84.\nAs it is essential for the soil moisture retrieval from passive microwave data that the radiative\ntransfer modelling works under local conditions, the coupled models are used to assess the\nradiative transfer modelling with L-MEB on the local and SMOS scales in the Upper Danube\nCatchment. In doing so, the emission characteristics of rape are described for the first time\nand the soil moisture retrieval abilities of L-MEB are assessed with a newly developed LMEB\nparameterization. The results show that the radiative transfer modelling works well\nunder most conditions in the study area. The root mean squared error between modelled and\nairborne measured brightness temperatures on the SMOS scale is less than 6 \u2013 9 K for the\ndifferent look angles.\nThe coupled models are used to analyse SMOS brightness temperatures and vegetation optical\ndepth data in the Upper Danube Catchment in Southern Germany. Since the SMOS soil\nmoisture products are degraded in Southern Germany and in different other parts of the world\nthese analyses are used to narrow down possible reasons for this.\nThe thorough analysis of SMOS brightness temperatures for the year 2011 reveals that the\nquality of the measurements is degraded like in the SMOS soil moisture product. This points\ntowards radio frequency interference problems (RFI), that are known, but have not yet been\nstudied thoroughly. This is consistent with the characteristics of the problems observed in the\nSMOS soil moisture products. In addition to that it is observed that the brightness\ntemperatures in the lower look angles are less reliable. This finding could be used to improve\nthe brightness temperature filtering before the soil moisture retrieval.\nAn analysis of SMOS optical depth data in 2011 reveals that this parameter does not contain\nvaluable information about vegetation. Instead, an unexpected correlation with SMOS soil\nmoisture is found. This points towards problems with the SMOS soil moisture retrieval,\npossibly under the influence of RFI.\nThe present thesis demonstrates that coupled land surface and radiative transfer models can\nmake a valuable contribution to the validation and analysis of passive microwave remote\nsensing products. The unique approach of this work incorporates modelling with a high\nspatial and temporal resolution on different scales. This makes detailed process studies on the\nlocal scale as well as analyses of satellite data on the SMOS scale possible. This could be\nexploited for the validation of future satellite missions, e.g. SMAP (Soil Moisture Active and\nPassive) which is currently being prepared by NASA (National Aeronautics and Space\nAdministration). Since RFI seems to have a considerable influence on the SMOS data due to\nthe gained insights and the quality of the SMOS products is very good in other parts of the\nworld, the RFI containment and mitigation efforts carried out since the launch of SMOS\nshould be continued.