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Youlong Xia 1 , Mike Ek 1 , Eric Wood 2 , Justin Sheffield 2 ,

Youlong Xia 1 , Mike Ek 1 , Eric Wood 2 , Justin Sheffield 2 ,. Lifeng Luo 2,7 , Dennis Lettenmaier 3 , Ben Livneh 3 , David Mocko 4 , Brian Cosgrove 5 , Jesse Meng 1 , Helin Wei 1 , Victor Koren 5 , John Schaake 5 , Kingtse Mo 6 , and Kenneth Mitchell 1 *.

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Youlong Xia 1 , Mike Ek 1 , Eric Wood 2 , Justin Sheffield 2 ,

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  1. Youlong Xia1, Mike Ek1, Eric Wood2, Justin Sheffield2, Lifeng Luo2,7, Dennis Lettenmaier3, Ben Livneh3, David Mocko4, Brian Cosgrove5, Jesse Meng1, Helin Wei1, Victor Koren5, John Schaake5, Kingtse Mo6, and Kenneth Mitchell1* NCEP/EMC: NLDAS Support for Drought Monitoring and Seasonal Prediction 1Environmental Modeling Center, NCEP/NOAA (*retired) 2Department of Civil and Environmental Engineering, Princeton University 3Department of Civil and Environmental Engineering, University of Washington 4Hydrological Sciences Branch, NASA Goddard Space Flight Center 5Office of Hydrologic Development, National Weather service/NOAA 6Climate Prediction Center, NCEP/NOAA 7Department of Geography, Michigan State University, East Lansing, Michigan NOAA Climate Test Bed Seminar, NASA GSFC, 14 April 2010

  2. Collaboration Partners for Drought Monitoring • NCEP/EMC – Noah Model (EMC colleagues developed and executed the NARR) • Mike Ek, Y. Xia, Ken Mitchell* (*retired) • Transition of CPPA PI NLDAS research to operational prototype at NCEP • Noah model development and realtime run for NARR-based forcing and four models • Maintain and upgrade NCEP/NLDAS drought monitoring and prediction website • Evaluate, validate and analyze NLDAS products • Princeton U. – VIC Model • E. Wood, J. Sheffield, L. Luo* ( *now at Michigan State University) • VIC model development and seasonal prediction system with three methods • NASA/GSFC HSB – Mosaic Model • B. Cosgrove*, D. Mocko, C. Alonge** (*now at NWS/OHD, **now in private sector) • Mosaic model and retrospective land surface forcing from NARR, drought monitor web site design • U. Washington • D. Lettenmaier, Ben Livneh • Multi-decadal retrospective NLDAS • NWS Office of Hydrologic Development (OHD) – SAC model • P. Restrepo, J. Schaake, V. Koren • SAC model and precipitation analysis • NCEP/CPC • K. Mo, H. Van den Dool, Y. Fan* (* now at NWS Office of Science and Technology) • User applications (especially in CPC), realtime NARR extension, US gauge precip analysis • NIDIS Drought Monitor Group (drought.gov) – Eric Lubehusen, USDA and application to US Drought Monitor

  3. NLDAS Drought Monitoring ConfigurationN. American Land Data Assimilation System • Uncoupled land model simulations • four land models: Noah, VIC, Mosaic, SAC • CONUS domain • 1/8th degree resolution (daily gauge precipitation) • Common land surface forcing • hourly and 1/8th degree • Jan 1979 to present realtime • Retrospective mode • 30-year: 1979-2008 • 15-year spin-up • 30-year climatology for each land model (1979-2008)

  4. Soil-Vegetation-Atmosphere-Transfer Scheme Community Mosaic Model NCEP operational land model Hydrology Community NWS operational hydrologic model VIC Model SAC Model

  5. NCEP/NLDAS Drought Monitoring and Prediction Website http://www.emc.ncep.noaa.gov/mmb/nldas NLDAS Drought Prediction NLDAS Drought Monitor Anomaly and percentile for six variables and three time scales

  6. The web shows not only four-model ensemble mean anomaly and percentile but also separate model anomaly and percentile. GSWP2 results demonstrated that multi-model ensemble mean gives more robust simulations when compared to the separate model simulations. Therefore, ensemble mean results will be shown in NLDAS drought monitoring An Example

  7. June 1998 – drought year Monthly total column soil moisture anomalies and model spread (mm/month) Large similarity and small spread

  8. July 1993 – flood year Monthly total column soil moisture anomalies and model spread (mm/month) Similar characteristics and large spread

  9. Direct application of NLDAS products to USDM NLDAS soil moisture and total runoff products are provided to Eric Lubehusen at USDA who is one of the authors of the US drought Monitor. He created top 1m and total column soil moisture images and sent them to the entire Drought Monitor group (contour – US Drought Monitor boundary, and shaded plot is NCEP NLDAS ensemble mean percentile).

  10. NLDAS Forcing and Model Products to directly Support NCEP/CPC Monthly Drought Briefing

  11. Extension from 1/8o (14 km) to 4 km (HRAP grid) resolution (Hydrologic Rainfall Analysis Project) NWS/OHD SAC Total Soil Moisture Anomaly Current NLDAS High Resolution NLDAS July Climate July 1988 July 1993

  12. Validation and assessment initiative of NLDAS products using in-situ observations and satellite retrieved data Validated Products: • Forcing – solar radiation, downward long-wave radiation, air temperature, precipitation, relative humidity • Streamflow and evaporation over the US • Soil moisture • Soil temperature • Snow water equivalent and snow cover • Skin temperature • Surface energy fluxes – sensible heat, latent heat, ground heat , net radiation Inter-comparison of model products • Similarities of different model products • Comparison of phase 1 and 2 for the same period • Comparative analysis of relationships between forcing (P, T) and water and energy fluxes

  13. Simulation skills: Correlation between observed and simulated monthly soil moisture anomalies averaged over 16 sites of Illinois for four land surface models (1985-2004, white color shows the correlation is not significant at 95% confidence level) weak correlation strong correlation A validation example

  14. Distribution of NLDAS Products http://www.emc.ncep.noaa.gov/mmb/nldas http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings 31 years (1979-2009), hourly temporal resolution, 1/8th degree spatial resolution, NLDAS region. Forcing data and outputs from four land models

  15. Future Work - Transition NLDAS to NCEP operation - Evaluation and validation of NLDAS products - Extend current NLDAS system to Land Information System (LIS) and to use ensemble Kalman filter to assimilate obsrvations - Improvement of land surface models through collaboration with NLDAS partners

  16. Drought Prediction over the Continental US Using the Seasonal Forecast System Developed by Princeton University and University of Washington

  17. Collaboration Partners for NLDAS Seasonal Drought Prediction NCEP Environmental Modeling Center (EMC) Mike Ek, Youlong Xia, and Ken Mitchell (retired) Transition seasonal hydrological forecast system to EMC as a test system Depending on initial conditions of VIC water mode being run by Lifeng Luo Princeton University Eric Wood, Lifeng Luo, Justin Sheffield, and Haibin Li Developing seasonal hydrological forecast system using NCEP Climate Forecast System (CFS) forecast products and Ensemble Streamflow Prediction (ESP) approach Assessment of seasonal forecast system using CFS reforecast products (not funded yet) Michigan State University Lifeng Luo (moved from Princeton University) Extension of seasonal hydrological forecast system to SAC and Noah (not funded yet) Run nowcasting of VIC water mode University of Washington Dennis Lettenmaier, Andy Wood, Ben Levnieh Developing seasonal hydrological forecast system using NCEP Climate Prediction Center (CPC) seasonal outlook products NCEP Climate Prediction Center (CPC) Kingtse Mo and Jin-Ho Yoon Test various bias correction schemes to improve seasonal hydrological forecast system skills at Southeast and Colorado basins

  18. Current Forecast System (Foundation Work)

  19. OBS Bayesian Merging of Information Posterior Likelihood function (relates local scale to GCM scale and above) Prior (local climatology) 1/8th degree scale variable Variable at GCM scale and above Bayes Theorem

  20. Flowchart of Seasonal Hydrologic Ensemble Prediction System GCM Seasonal Forecast (ensemble forecasts) GCM resolution monthly time step Bayesian Merging Downscaling (Ta, P) Meteorology climatology 1/8 degree daily time step “Weather” Generator (ensembles) Hydrology climatology Hydrologic ensembles Land surface (hydrology) models Drought product generation Web

  21. Ohio Basin Verification Performance of different approach

  22. West and East US Drought 2007 JAN FEB MAR

  23. UW: CPC Approach precipitation temperature From outlook forecast products to get model forcing

  24. NLDAS Forecast Products http://www.emc.ncep.noaa.gov/mmb/nldas 6 month forecast using three approaches [CFS, CPC, and Ensemble Streamflow Prediction (ESP)] Monthly mean total soil moisture anomaly and percentile, evaporation anomaly and percentile, streamflow anomaly and percentile, precipitation anomaly, drought probability forecast

  25. CFS Forecast Products – an example 2-month forecast precipitation anomaly Forecast total column soil moisture anomaly Forecast total column soil moisture percentile Forecast evaporation anomaly Forecast evaporation percentile Forecast baseflow anomaly Forecast baseflow percentile Forecast soil moisture drought probability

  26. Streamflow Forecast Similar variation tendency There are differences for different approaches Need to be evaluated using USGS gauge staremflow measurement 25%-75%

  27. Support NCEP/CPC Seasonal Drought Outlook CFS 1-month forecast Drought will continue for a while CFS 2-month Forecast CFS 3-month Forecast 27

  28. Future Operational Version Multi-models and multi-methods forecast system

  29. From Current System to Future Operational Version Much research needs to be done before operational transition! • To extend current system to Noah, SAC, and Mosaic (CLM) to achieve multiple models 2. Assessment of the system using 30-year (79-08) CFS reforecast products 3. To use multiple coupled GCM models forecast products (through climate testbed) to improve model forcing reliability 4. To add short-middle term forecast products to enhance forecast skills

  30. To support NIDIS To support NCEP/CPC seasonal drought outlook and drought prediction of National Integrated drought Information System (NIDIS), a stable and reliable operational multi-models and multi-methods seasonal hydrological ensemble forecast system is required. However, this system heavily depends on more research from our NLDAS collaborators and US research community to make this system mature so that it can be transitioned to NCEP operations.

  31. North American Land Data Assimilation System (NLDAS) Phase 2 Thank You Welcome to use our products! http://www.emc.ncep.noaa.gov/mmb/nldas/ http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings

  32. Thank you! Suggestions and comments to: Youlong.Xia@noaa.gov Michael.Ek@noaa.gov Eric Wood:efwood@princeton.edu Lifeng Luo:lluo@msu.edu

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