Version 4 of the SMAP Level‐4 Soil Moisture Algorithm and Data Product.

2017a. De Lannoy, G. J. M., and R. H. Reichle. You will have access to both the presentation and article (if available).This content is available for download via your institution's subscription. The Level 1 products contain raw or calibrated and geolocated instrument measurements from the SMAP Radar and Radiometer; all Level 1 products have a temporal resolution of 49 minutes, the length of time required for the SMAP satellite to complete a half orbit of the Earth. One advantage of using very high-resolution resolution Sentinel-1A/Sentinel-1B data in the SMAP active-passive algorithm is the potential of obtaining the disaggregated brightness temperature and thus soil moisture at a much finer spatial resolution of 3 km and 1 km at global extent. The J2000 epoch starting point is January 1, 2000 at 12:00 ET, which translates to January 1, 2000 at 11:58:55.816 Universal Coordinated Time (UTC). the temporal evolution of soil moisture through data fusion. The relevant outputs are listed in the More information about error sources is provided in the ATBD under Section 4.1.2: Mathematical Description of the Algorithm.

Kyle R. Knipper, Terri S. Hogue, Kristie J. Franz, Russell L. Scott, "Downscaling SMAP and SMOS soil moisture with moderate-resolution imaging spectroradiometer visible and infrared products over southern Arizona," J. Appl. 2014, the ATBD for this product. Sens. The precipitation observations used to correct the GMAO precipitation estimates are obtained from the NOAA Climate Prediction Center (Reichle et al. Combin-ing high-resolution detailed atmospheric and snow models is Soil moisture analyses at higher spatial and temporal resolutions based on more modern LSMs are available. Data set: Selected SMAP L4, Version 4 HDF data (SPL4SMAU, SPL4SMGP, & SPL4SMLM) can be added to ArcGIS with a simple drag/drop or using the 'Add Data' function. The assimilation algorithm considers the respective uncertainties of each component and, if properly calibrated, yields a product that is superior to both satellite and land model data. Type is Float64.Time stamps for H-polarization and V-polarization observations are provided in the fields Flag indicating the orbit direction of V-pol brightness temperature composite fields (Time stamps for H-polarization and V-polarization observations are provided in the fields Flag indicating the effective resolution of V-pol brightness temperature composite fields (Time accrued since 2000-01-01 11:58:55.816. Type is Float64.Time stamps for H-polarization and V-polarization observations are provided in the fields Flag indicating the orbit direction of H-pol brightness temperature composite fields (tb_h_obs, tb_h_forecast, etc. (PDF, 1.4 MB; see Reichle, R., G. J. M. De Lannoy, Q. Liu, J. V. Ardizzone, F. Chen, A. Colliander, A. Conaty, W. Crow, T. Jackson, J. Kimball, R. D. Koster, and E. Brent Smith. 2019, and the Validated Assessment Report from Reichle et al. This study is based on the methodology developed in Fill values are also used, for example, in the SMAP data products employ a specific set of data values to connote that a field is fill. this kind of RCM have a temporal resolution of 6 h to 1 day (Cullather et al., 2016). Land model constants (lmc) are provided in a single file per Science Version. Gap values locate portions of a data stream that do not appear in the output data file. The median of the distributions is depicted in the dashed line and the mean in the solid line.Spatial comparison of soil moisture observations with downscaled products over the study period. L Band Microwave Remote Sensing and Land Data Assimilation Improve the Representation of Prestorm Soil Moisture Conditions for Hydrologic Forecasting. However, data users should note that for Validated Version 4 data, the algorithm ingests only the SPL1CTB radiometer brightness temperatures, contrary to the planned use of downscaled brightness temperatures from the SPL2SMAP product and of landscape freeze-thaw state retrievals from the SPL2SMA product. These spatial contrasts are a necessary condition for accurately downscaling low-resolution soil moisture products. Model simulations for each 1 km grid cell are conducted using the corresponding (nearest-neighbor) 9 km resolution SMAP Level-4 Soil Moisture and GEOS-5 inputs. SMAP Level-1, -2, -3, and -4 data sets from the NSIDC DAAC will be updated in summer 2020 as part of a scheduled annual reprocessing campaign. snow-covered land area)Uncertainty of analysis surface temperature (ensemble std-dev)Composite resolution Catchment model forecast 1.41 GHz H-pol brightness temperature Create a new folder below. ): 0=average over ascending and descending orbits, 1=ascending orbits only, 2=descending orbits only, Type is Unsigned32.Time stamps for H-polarization and V-polarization observations are provided in the fields Flag indicating the effective resolution of H-pol brightness temperature composite fields (tb_h_obs, tb_h_forecast, etc. WGEW covers only part of the surface of one SMOS and SMAP pixel. Yet because the SPL4SM data product is partially based on modeling, gaps are not expected to occur in the SPL4SM data stream. 2018.

SALINITY/DENSITY (2) Latency. These ancillary data requirements are described in detail in the ATBD, Section 4.1.3: Ancillary Data Requirements. By continuing you agree to the Copyright © 2020 Elsevier B.V. or its licensors or contributors. QA files contain spatial statistics across the SMAP Level-4 soil moisture products, such as the global minimum, mean, and maximum of each data field.Level-4 surface and root zone soil moisture estimates are validated to a Root Mean Square Error (RMSE) requirement of 0.04 mQuality control is also an integral part of the soil moisture assimilation system. NNX15AB28G. “LR” refers to the low-resolution (original) soil moisture product prior to downscaling. For a complete list and description of all data fields within these groups, refer to the Appendix of this document.The date/time corresponds to the center point of the 3-hourly time averaging interval.

Exploiting soil moisture, precipitation and streamflow observations to evaluate soil moisture/runoff coupling in land surface models. The MODIS (MOD/MYD15) fPAR product is produced at 500 m resolution and 8-day temporal fidelity from both NASA EOS Terra and Aqua sensor records.