A parameterization of SEVIRI and MODIS daily surface albedo with soil moisture: Calibration and validation over southwestern France

Abstract In climate models, it is important to simulate the partitioning of the surface albedo into soil and vegetation albedo components because these latter address different processes that are time-scale dependent. Vegetation albedo primarily varies along with the growing season while soil albedo shows day-to-day variations caused by rainfall events. In this study, the objective is to disentangle soil albedo from surface albedo within the visible (VIS) and near infrared (NIR) spectral bands of MODIS and SEVIRI sensors in order to yield a calibration with surface soil moisture (SSM). In a first step, we derive global static maps of soil and vegetation albedos from MODIS products at the resolution of 0.05° over a 4-year period. In a second step, we estimate a daily MODIS white-sky albedo (WSA) by combining 8-day BRDF and TERRA/AQUA reflectance values for each orbit pass. These MODIS products are then projected on the SEVIRI grid of 4 km for further comparison. Then, a physical method is presented to get a daily soil albedo from both MODIS and SEVIRI data. Good correlations are obtained between satellite time series for 2007 and 2008 of retrieved soil albedo and in situ SSM measurements at the 12 SMOSMANIA stations located in southwestern France. A function of an exponential type between albedo and SSM, as supported by the theory, could be verified. As in the VIS domain, the goodness of fit r2 is about 0.42 and 0.54 for Lahas and Condom, respectively. The Chi-Square test indicates that the relationship is significant with p-value

[1]  M. Roxy,et al.  Variability of soil moisture and its relationship with surface albedo and soil thermal diffusivity at Astronomical Observatory, Thiruvananthapuram, south Kerala , 2010 .

[2]  Jean-Louis Roujean,et al.  ECOCLIMAP-II: An ecosystem classification and land surface parameters database of Western Africa at 1 km resolution for the African Monsoon Multidisciplinary Analysis (AMMA) project , 2010 .

[3]  C. Woodcock,et al.  Consistency of MODIS surface bidirectional reflectance distribution function and albedo retrievals: 2. Validation , 2003 .

[4]  Ranga B. Myneni,et al.  Analysis and optimization of the MODIS leaf area index algorithm retrievals over broadleaf forests , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[5]  O. Hautecoeur,et al.  Daily estimates of aerosol optical thickness over land surface based on a directional and temporal analysis of SEVIRI MSG visible observations , 2010 .

[6]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[7]  Ni Guo,et al.  Variability of soil moisture and its relationship with surface albedo and soil thermal parameters over the Loess Plateau , 2009 .

[8]  F. Baret,et al.  Relating soil surface moisture to reflectance , 2002 .

[9]  Ann Henderson-Sellers,et al.  Biosphere-atmosphere Transfer Scheme (BATS) for the NCAR Community Climate Model , 1986 .

[10]  D. Lobell,et al.  Moisture effects on soil reflectance , 2002 .

[11]  R. Lacaze,et al.  Global mapping of vegetation parameters from POLDER multiangular measurements for studies of surface-atmosphere interactions: A pragmatic method and its validation , 2002 .

[12]  Alexander P. Trishchenko,et al.  Surface bidirectional reflectance and albedo properties derived using a land cover-based approach with Moderate Resolution Imaging Spectroradiometer observations , 2005 .

[13]  Feng Gao,et al.  Use of Moderate-Resolution Imaging Spectroradiometer bidirectional reflectance distribution function products to enhance simulated surface albedos , 2004 .

[14]  Alan H. Strahler,et al.  Consistency of MODIS surface bidirectional reflectance distribution function and albedo retrievals: 1. Algorithm performance , 2003 .

[15]  Jean-Louis Roujean,et al.  Development of an operational procedure to estimate surface albedo from the SEVIRI/MSG observing system by using polder BRDF measurements. II. Comparison of several inversion techniques and uncertainty in albedo estimates , 2003 .

[16]  Michael T. Coe,et al.  Deforestation and climate feedbacks threaten the ecological integrity of south–southeastern Amazonia , 2013, Philosophical Transactions of the Royal Society B: Biological Sciences.

[17]  D. Fahey,et al.  Black carbon aerosol size in snow , 2013, Scientific Reports.

[18]  M. Guérif,et al.  Crop reflectance estimate errors from the SAIL model due to spatial and temporal variability of canopy and soil characteristics , 1998 .

[19]  A. Henderson‐sellers,et al.  A global archive of land cover and soils data for use in general circulation climate models , 1985 .

[20]  F. S. Nakayama,et al.  The Dependence of Bare Soil Albedo on Soil Water Content. , 1975 .

[21]  W. Oechel,et al.  FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities , 2001 .

[22]  Yanmin Shuai,et al.  Validation of Moderate Resolution Imaging Spectroradiometer (MODIS) albedo retrieval algorithm: Dependence of albedo on solar zenith angle , 2009 .

[23]  R. Betts,et al.  The impact of new land surface physics on the GCM simulation of climate and climate sensitivity , 1999 .

[24]  A. Dalcher,et al.  A Simple Biosphere Model (SIB) for Use within General Circulation Models , 1986 .

[25]  C. Albergel,et al.  An evaluation of ASCAT surface soil moisture products with in-situ observations in Southwestern France , 2008 .

[26]  Bernhard Geiger,et al.  Land Surface Albedo Derived on a Daily Basis From Meteosat Second Generation Observations , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[27]  J. Roujean,et al.  A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data , 1992 .

[28]  Jean-Louis Roujean,et al.  Impact Assessment of Daily Satellite-Derived Surface Albedo in a Limited-Area NWP Model , 2012 .

[29]  Jean-Christophe Calvet,et al.  In situ soil moisture observations for the CAL/VAL of SMOS: the SMOSMANIA network , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[30]  C. Bohren,et al.  Reflectance and albedo differences between wet and dry surfaces. , 1986, Applied optics.

[31]  J. Mahfouf,et al.  The ISBA land surface parameterisation scheme , 1996 .

[32]  Jean-Louis Roujean,et al.  ECOCLIMAP-II/Europe: a twofold database of ecosystems and surface parameters at 1 km resolution based on satellite information for use in land surface, meteorological and climate models , 2012 .

[33]  F. J. García-Haro,et al.  INTER-COMPARISON OF SEVIRI/MSG AND MERIS/ENVISAT BIOPHYSICAL PRODUCTS OVER EUROPE AND AFRICA , 2008 .

[34]  N. C. Strugnell,et al.  First operational BRDF, albedo nadir reflectance products from MODIS , 2002 .

[35]  Sandra C. Freitas,et al.  The Satellite Application Facility for Land Surface Analysis , 2011 .

[36]  Peter R. J. North,et al.  New Vegetation Albedo Parameters and Global Fields of Soil Background Albedo Derived from MODIS for Use in a Climate Model , 2009 .

[37]  K. Oleson,et al.  Assessment of global climate model land surface albedo using MODIS data , 2003 .

[38]  K. Oleson,et al.  Technical Description of an Urban Parameterization for the Community Land Model (CLMU) , 2010 .

[39]  A. Ångström The Albedo of Various Surfaces of Ground , 1925 .

[40]  Alina Barbu,et al.  Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France , 2013 .

[41]  Jean-Louis Roujean,et al.  Comparing Operational MSG/SEVIRI Land Surface Albedo Products From Land SAF With Ground Measurements and MODIS , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[42]  R. Dickinson,et al.  The Common Land Model , 2003 .