UMAC data callpage 1 of 11NLDAS EMC Operational Models North American Land Data Assimilation System (NLDAS) Michael Ek Land-Hydrology Team Leader Environmental.

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Presentation transcript:

UMAC data callpage 1 of 11NLDAS EMC Operational Models North American Land Data Assimilation System (NLDAS) Michael Ek Land-Hydrology Team Leader Environmental Modeling Center NOAA / NWS / NCEP

UMAC data callpage 2 of 11NLDAS NLDAS four-model ensemble monthly soil moisture anomaly July 30-yr climateJuly 1988 (drought)July 1993 (flood)July 2011 (TX drought) Overview of North American Land Data Assimilation System (NLDAS) Land models: Noah, SAC, VIC, Mosaic run in “uncoupled” mode. Forcing: NCEP Climate Prediction Center obs precip (gauge-based, radar/satellite disaggregated), and atmospheric forcing from NCEP North American Regional Climate Data Assimilation System. Output: 1/8-deg. land & soil states, surface fluxes, runoff/streamflow. Climatology from land model assimilation runs for 30+ years provide anomalies used for drought monitoring; supports USDM, NIDIS etc. Operational at NCEP 05 Aug Research supported by NOAA Climate Prog. Office for NLDAS partners: NASA/GSFC, NWS OfficeHydro. Develop., Princeton U.., U. Washington.

UMAC data callpage 3 of 11NLDAS NLDAS components: Land Models Research Models Operational Models

UMAC data callpage 4 of 11NLDAS NLDAS components: Land Data Sets Max.-Snow Albedo (1-deg, Robinson) Snow-Free Albedo (seasonal, 1-deg, Matthews) Green Vegetation Fraction (GVF) (monthly, 1/8- deg, NESDIS/AVHRR) JulyJansummerwinter Soil Type (1-deg, Zobler) Vegetation Type (1-deg, UMD) Fixed climatologies, or near real-time observations (e.g. GVF); some quantities to be assimilated (e.g. snow, soil moisture).

UMAC data callpage 5 of 11NLDAS NLDAS components: Atmospheric Forcing Common atmospheric forcing from Regional Climate Data Assimilation System (real time extension of the North American Regional Reanalysis, NARR) – forcing “backbone”. CPC gauge-based observed precipitation, temporally disaggregated using radar data (stage IV), satellite data (CMORPH), bias-corrected with PRISM monthly values. Bias-corrected NARR solar radiation from GOES retrievals.

UMAC data callpage 6 of 11NLDAS NLDAS components: Evaluation and Validation Monthly streamflow anomaly correlation ( USGS measured streamflow) Ensemble Mean Comprehensive evaluation against in situ observations and/or remotely sensed data sets. Energy flux validation from tower: net radiation, sensible, latent & ground heat fluxes. Water budget: evaporation, total runoff/streamflow. State variables: soil moist., soil/skin temp., snow depth/cover. Daily top 1m soil moisture anomaly corr. ( US SCAN Network) Xia et al., JGR-atmosphere (2012)Xia et al., J. Hydrol. (2014) RMSE<0.06 m 3 /m 3

UMAC data callpage 7 of 11NLDAS NCEP/EMC NLDAS Website NLDAS Products: Web Sites NASA/GSFC NLDAS website NLDAS User Statistics for calendar year 2014: Number of distinct users: 5,437 Number of files downloaded: 44,119,161 (over 44 million) Total volume downloaded: 93,459 Gb (over 93Tb) ftp://ftp.ncep.noaa.gov/pub/data/nccf/com/nldas/prod ftp://ldas.ncep.noaa.gov/nldas2/nco_nldas/

UMAC data callpage 8 of 11NLDAS NLDAS Products: Users NCAR/UCAR Princeton University Michigan State Universi ty Centers for Disease Control and Prevention

UMAC data callpage 9 of 11NLDAS US Drought California Drought NLDAS Products: Total Soil Column Soil Moisture Anomaly: March 2012 – December 2013

UMAC data callpage 10 of 11NLDAS NLDAS Products: Streamflow for Hurricane Irene & Tropical Storm Lee 20 Aug – 17 Sep 2011 Ensemble mean daily streamflow anomaly (m 3 /s)

UMAC data callpage 11 of 11NLDAS NLDAS Future:  Extend the current NLDAS to run under NASA Land Information System (LIS) parallel environment, latest land model versions, assimilation & validation tools.  Improve/include: –Forcing, e.g. precipitation. –Land data sets, e.g. vegetation greenness. –Land data assimilation, i.e. snow, soil moisture. –Land model physics, e.g. vegetation dynamics, carbon, irrigation, etc., via latest Noah or Noah-MP land model. –Higher resolution/downscaling (forcing, model output). –Enhance land model spin-up procedures. –Products, e.g. “Objective Blended NLDAS Drought Index”.  Extend NLDAS domain/resolution: first North America, then “merge” with CFS/Global LDAS.  Provide initial land conditions for NAM, GFS, CFS.  Earth System modeling: Include hydrological prediction.