1. 1 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 * 1 Environmental Modeling Center, NCEP/NOAA (*retired) 2 Department of Civil and Environmental Engineering, Princeton University 3 Department of Civil and Environmental Engineering, University of Washington 4 Hydrological Sciences Branch, NASA Goddard Space Flight Center 5 Office of Hydrologic Development, National Weather service/NOAA 6 Climate Prediction Center, NCEP/NOAA 7 Department of Geography, Michigan State University, East Lansing, Michigan NOAA Climate Test Bed Seminar, NASA GSFC, 14 April 2010 NCEP/EMC: NLDAS Support for Drought Monitoring and Seasonal Prediction

2. 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. 3 NLDAS Drought Monitoring Configuration N. American Land Data Assimilation System Uncoupled land model simulations –four land models: Noah, VIC, Mosaic, SACNoah, VIC, Mosaic, SAC CONUS domain –1/8 th degree resolution (daily gauge precipitation) Common land surface forcing –hourly and 1/8 th 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. 4 MosaicModel SAC Model Hydrology Community Soil-Vegetation-Atmosphere-Transfer Scheme Community VIC Model NCEP operational land model NWS operational hydrologic model

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

6. 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

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

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

9. 9 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). Direct application of NLDAS products to USDM

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

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

12. 12 Validation and assessment initiative of NLDAS products using in-situ observations and satellite retrieved data Validated Products: 1.Forcing – solar radiation, downward long-wave radiation, air temperature, precipitation, relative humidity 2.Streamflow and evaporation over the US 3.Soil moisture 4.Soil temperature 5.Snow water equivalent and snow cover 6.Skin temperature 7.Surface energy fluxes – sensible heat, latent heat, ground heat, net radiation Inter-comparison of model products 1.Similarities of different model products 2.Comparison of phase 1 and 2 for the same period 3.Comparative analysis of relationships between forcing (P, T) and water and energy fluxes

13. 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) strong correlation weak correlation

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

15. 15

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

17. 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. 18 Current Forecast System (Foundation Work) (Foundation Work)

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

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

21. 21 Ohio Basin Verification Performance of different approach Performance of different approach

22. 22 West and East US Drought 2007 JAN FEB MAR

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

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

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

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

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

29. 29 From Current System to Future Operational Version Much research needs to be done before operational transition! before operational transition! 1.To extend current system to Noah, SAC, and Mosaic (CLM) to achieve multiple models 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 2. Assessment of the system using 30-year (79- 08) CFS reforecast products

30. 30 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. To support NIDIS

31. 31 http://www.emc.ncep.noaa.gov/mmb/nldas/ http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings

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