Open AccessRemote sensing field experiments evaluate retrieval algorithms and land‐atmosphere modeling
Author(s) -
Kustas W. P.,
Jackson T. J.,
Prueger J. H.,
Hatfield J. L.,
Anderson M. C.
Publication year - 2003
Publication title -
eos, transactions american geophysical union
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.316
H-Index - 86
eISSN - 2324-9250
pISSN - 0096-3941
DOI - 10.1029/2003eo450002
Subject(s) - environmental science , remote sensing , data assimilation , radiometer , meteorology , vegetation (pathology) , atmosphere (unit) , scale (ratio) , microwave , radiometry , water content , computer science , geology , geography , medicine , telecommunications , cartography , geotechnical engineering , pathology
The 2002 Soil Moisture Experiment (SMEX02) and the Soil Moisture Atmosphere Coupling Experiment (SMACEX) were both conducted during June and July 2002 near Ames, Iowa. The primary objectives of SMEX02 are to validate microwave soil moisture retrieval algorithms for existing and new, prototype microwave sensor systems under rapidly changing crop biomass conditions; and to explore the effects of rapid vegetation growth on the brightness temperatures and soil moisture retrievals from the Advanced Microwave Scanning Radiometers (AMSR) on NASA Aqua and ADEOS‐II. SMACEX is a combined measurement and modeling program that will address one of NASAs core missions: rigorously building a bridge between remotely sensed data and operational forecast models, including advances in operational assimilation schemes. The field observations will support the analysis of heterogeneities, ranging from within field‐ or patch‐scale (∼100 m) to regional scales that are commensurate with prediction models for weather and climate (10–100 km). The unique in‐situ and aircraft measurements of atmospheric and soil variables and fluxes provided by this data set will be used to validate both surface states and fluxes diagnosed using remote sensing methods at various scales. The experimental approach is thus also a “scaling” endeavor, in that it investigates how remotely sensed data at different horizontal and temporal scales can be utilized for both diagnosis and prediction of surface states and energy exchanges from patch to regional scales.