ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Earth Resources and Remote Sensing  (1)
Collection
Keywords
  • Earth Resources and Remote Sensing  (1)
Years
  • 1
    Publication Date: 2019-07-13
    Description: The Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real-time) and provides 3-hourly, global, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root-zone) soil moisture measurements for 43 (17) reference pixels at 9-km and 36-km grid-cell scales located in 17 (7) distinct watersheds. Sparse networks provide point-scale measurements of surface (root-zone) soil moisture at 401 (297) locations. Core validation site results indicate that the L4_SM product meets its soil moisture accuracy requirement, specified as an unbiased RMSE (ubRMSE, or standard deviation of the error) of 0.04 cu m/cu m or better. The ubRMSE for L4_SM surface (root-zone) soil moisture is 0.038 cu m/cu m (0.028 cu m/cu m) at the 9-km scale and 0.034 cu m/cu m (0.024 cu m/cu m) at the 36-km scale. The L4_SM estimates improve (significantly at the 5 level for surface soil moisture) over model-only estimates, which have a 9-km surface (root-zone) ubRMSE of 0.043 cu m/cu m (0.031 cu m/cu m) and do not benefit from the assimilation of SMAP brightness temperature observations. Time series correlations exhibit similar relative performance. The sparse network results corroborate these findings over a greater variety of climate and land cover conditions.
    Keywords: Earth Resources and Remote Sensing
    Type: GSFC-E-DAA-TN45148 , Journal of Hydrometeorology (ISSN 1525-755X) (e-ISSN 1525-7541); 18; 10; 2621-2645
    Format: application/pdf
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...