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regression method using several frequencies are employed. The seasonal pattern of microwave emission and relative accuracy of the soil temperature retrievals are influenced strongly by landscape properties, including the presence of open water, vegetation type and seasonal phenology, snow cover, and freeze–thaw transitions. The retrieval of soil temperature(More)
−2 · day −1 for GPP, ecosystem respiration (R tot) and NEE, while mean residual differences were 43% of the rmse. Similar accuracies were observed for both TCF and BIOME-BGC model simulations relative to tower results. TCF-model-derived SOC was in general agreement with soil inventory data and indicates that the dominant SOC source for R h has a mean(More)
The development and continuity of consistent long-term data records from similar overlapping satellite observations is critical for global monitoring and environmental change assessments. We developed an empirical approach for inter-calibration of satellite microwave brightness temperature (T b) records over land from the Advanced Microwave Scanning(More)
The authors evaluated several land surface variables from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) product that are important for global ecological and hydrological studies, including daily maximum (Lnax) and minimum (Lnin) surface air temperatures, atmosphere vapor pressure deficit (VPD), incident solar radiation (SWrad),(More)
were then applied within an AMSR2 multifrequency brightness temperature algorithm for deriving atmosphere-corrected surface air temperatures. The estimated temperatures agree favorably (R 2 > 0.80 and rmse < 3.5 K) with independent weather station daily air temperature measurements spanning global climate and land cover variability. The resulting PWV(More)
The rate of vegetation recovery from boreal wildfire influences terrestrial carbon cycle processes and climate feedbacks by affecting the surface energy budget and land-atmosphere carbon exchange. Previous forest recovery assessments using satellite optical-infrared normalized difference vegetation index (NDVI) and tower CO(2) eddy covariance techniques(More)
We developed an algorithm to estimate surface soil moisture, vegetation optical depth and fractional open water cover using satellite microwave radiometry. Soil moisture results compare favorably with a simple antecedent site precipitation index, and respond rapidly to precipitation events indicated by TRMM. High optical depth reduces soil moisture(More)
Ecosystem productivity models rely on regional climatic information to estimate temperature and moisture constraints influencing plant growth. However, the productivity response to these environmental factors is uncertain at the global scale and has largely been defined using limited observations from sparse monitoring sites, including carbon flux towers.(More)
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