smap temporal resolution
Standard statistical metrics include correlation (In order to determine the success of each downscaling technique, a statistical analysis on the Distribution of (a) spatial, (b) temporal standard deviations, and (c) soil moisture values for the Satellite-derived soil moisture distributions are much narrower for both original (not downscaled) low-resolution SMOS and SMAP products (top left and bottom left, respectively, Distribution of soil moisture values for original, DS1, DS2, and DS3 from SMOS (top, left to right) and SMAP (bottom, left to right) for WGEW over the time period. Combin-ing high-resolution detailed atmospheric and snow models is Soil Moisture Active Passive (SMAP) Project Assessment Report for Version 4 of the L4_SM Data Product. The Level 4 products provide model-derived root-zone soil moisture and carbon net ecosystem exchange.Twice-Daily rSIR-Enhanced EASE-Grid 2.0 Brightness Temperatures Typical output data from this kind of RCM have a temporal resolution of 6 h to 1 day (Cullather et al., 2016). L3 products are global in extent and gridded at 0.25degree x 0.25degree with an approximate spatial resolution of 60km. You have requested a machine translation of selected content from our databases. With regards to the last point, the SMAP and Sentinel overlap covers only ~250 km within the 1000 km swath width of the SMAP observations. Each pixel in this figure is patch of 4×4 SMAP pixels.
“DS1,” “DS2,” and “DS3” refer to downscaled soil moisture obtained through downscaling methods 1, 2, and 3, respectively. For more information on data product accuracy, refer to Reichle et al. For more detailed instructions, please see As a condition of using these data, you must cite the use of this data set using the following citation. Moreover, instantaneous forecast and analysis soil moisture and temperature estimates are provided along with the assimilated observations. This article outlines how to order NSIDC DAAC data using advanced searching and filtering. Data are then assimilated into a land surface model that is gridded using the 9 km global EASE-Grid 2.0 projection.These data are provided on the global cylindrical EASE-Grid 2.0 (Brodzik et al. In Version 4, both sss_smap and sss_smap_40km are provided in the same file.
2019. CONFERENCE PROCEEDINGS
Data from the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) can be accessed directly from our HTTPS file system or through our Application Programming Interface (API).
This analysis would typically assimilate all SMAP data observed between 01:30:00 UTC and 04:30:00 UTC.For the LMC product (time-invariant constants), which consists of only one file per Science Version, the date/time is 00000000T000000.Date/time in Universal Coordinated Time (UTC) of the data file, where:Time (delineates the date from the time, i.e.
Type is 64-bit floating-point and array is one dimensional.All SPL4SM HDF5 data fields have /cell_lat /cell_lon shape. For more information on data product accuracy, refer to Reichle et al.
For example, T030000 indicates an analysis for 03:00:00 UTC on a given day. The L3 product is a daily global composite of the Level 2 surface soil moisture data and is available at 40-km resolution output on a fixed 36-km updated equal-area scalable Earth-2 projection.Utilized MODIS products include the version 5 MODIS aqua 1-km resolution daily nighttime LST product (MYD11A1), version 5 MODIS terra/aqua 1-km resolution 16-day composite EVI product (MYD13A2/MOD13A2), and version 5 MODIS terra/aqua 1-km resolution 8-day composite Albedo product (MCD43B3). Two kinds of quality control (QC) measures are applied. Global Assimilation of Multiangle and Multipolarization SMOS Brightness Temperature Observations into the GEOS-5 Catchment Land Surface Model for Soil Moisture Estimation. By continuing you agree to the Copyright © 2020 Elsevier B.V. or its licensors or contributors.
2010. Hydrology and Earth System Sciences.
Temporal comparison of soil moisture observations with downscaled products over the study period. The precipitation observations used to correct the GMAO precipitation estimates are obtained from the NOAA Climate Prediction Center (Reichle et al. Note that for this version, the model background precipitation forcing is rescaled to match the climatology of the Global Precipitation Climatology Project (v2.2), which results in substantial changes in the precipitation and soil moisture climatology in Africa and the high latitudes, where the gauge-based Climate Prediction Center Unified precipitation is not used.For more information on each portion of the algorithm processing flow, refer to the ATBD.Note that for Version 4 SPL4SM products an improved version of the For in-depth details regarding the quality of these data, refer to the SMAP products provide multiple means to assess quality.
LMC data are provided in a single file per Science Version.Catchment model: Catchment deficit at which baseflow ceasesCatchment model: Maximum water holding capacity of land fieldCatchment model: Thickness of soil heat diffusion model layer 1Catchment model: Thickness of soil heat diffusion model layer 2Catchment model: Thickness of soil heat diffusion model layer 3Catchment model: Thickness of soil heat diffusion model layer 4Catchment model: Thickness of soil heat diffusion model layer 5Catchment model: Thickness of soil heat diffusion model layer 6Catchment model: Thickness of profile soil moisture layer (“depth-to-bedrock” in the Catchment model)Catchment model: Thickness of root zone soil moisture layerCatchment model: Thickness of surface soil moisture layerCatchment model: Thickness of soil layer associated with surface_tempDefines the parameters of the cylindrical 9 km Earth-fixed EASE-Grid 2.0 projection and the mapping from latitude/longitude to grid-native coordinatesDownward ground heat flux into layer 1 of soil heat diffusion modelFractional land area that is saturated and snow-freeFractional land area that is unsaturated (but non-wilting) and snow-freeMicrowave radiative transfer model: H-pol.
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