1. Michael B. Ek 1, Youlong Xia 1,2, and NLDAS team* 1 Environmental Modeling Center (EMC), NCEP, College Park, MD 2 IMSG at NOAA/NCEP/EMC, College Park, Maryland *NLDAS team: Collaboration scientists from EMC, CPC, NESDIS, NWS/OHD, NASA/GSFC, USDA, Princeton Univ., Univ. Washington Interagency Steering Committee on Multimedia Environmental Modeling (ISCMEM), 25- 26 February 2014, Washington, DC.

2. 1. NLDAS Configuration 2. NLDAS Drought/Flooding Analysis, Monitoring, and Application 3. Evaluation/Validation of NLDAS Products 4. Objective/Optimal Blends of NLDAS Drought Indices - An Initiative Indices - An Initiative 5. Summary and Future Work

3. 1. NLDAS Configuration Acknowledgments: NLDAS project was supported by NOAA/OGP GAPP Program, NASA Terrestrial Hydrology Program, NOAA/CPO CPPA Program (Climate Program of the Americas), and NOAA/CPO MAPP Program (Modeling, Analysis, Predictions and Projections).

4. NLDAS Collaboration Partners NLDAS Development NCEP/EMC: Michael Ek, Youlong Xia, Jiarui Dong, Jesse Meng, Helin Wei Princeton University: Eric Wood, Justin Sheffield, Ming Pan NASA/GSFC: Christa Peters-Lidard, David Mocko NWS/OHD: Victor Koren, Brian Cosgrove University of Washington: Dennis Lettenmaier, Ben Livneh NLDAS Products Application NCEP/CPC: Li-Chuan Chen, Kingtse Mo USDA: Eric Luebhusen, U.S. Drought Monitor Author Group NASA/GSFC: Hualan Rui, Guang-Di Lou NCEP/EMC: Youlong Xia, Jesse Meng NLDAS Input Data Support NCEP/CPC: Ming-Yue Chen, Wesley Ebisuzaki, NCEP/EMC: Ying Lin

5. NLDAS is a multi-model land modeling and data assimilation system… NLDAS is a multi-model land modeling and data assimilation system… …run in uncoupled mode driven by atmospheric forcing …run in uncoupled mode driven by atmospheric forcing (using surface meteorology data sets)… …with “long-term” retrospective and near real-time output of …with “long-term” retrospective and near real-time output of land-surface water and energy budgets.

6. NLDAS Data Sets and Setup

7. www.emc.ncep.noaa.gov/mmb/nldas NLDAS Drought Monitor NLDAS Drought Prediction Anomaly and percentile for six variables and three time scales: Soil moisture, snow water, runoff, streamflow, evaporation, precipitation Current, Weekly, Monthly NCEP/EMC NLDAS website

8. Distribution of NLDAS Products NCEP/EMC NLDAS Website EMC public sever ldas3 and nomad6 NASA NLDAS Website NASA GES DISC System The user can subset NLDAS datasets by region and/or by variable using the GES DISC's Mirador search tool (hourly, monthly) Mirador

9. 2. NLDAS Drought/Flooding Analysis, Monitoring, and Application Acknowledgments: NLDAS project was supported by NOAA/OGP GAPP Program, NASA Terrestrial Hydrology Program, NOAA/CPO CPPA Program (Climate Program of the Americas), and NOAA/CPO MAPP Program (Modeling, Analysis, Predictions and Projections).

10. Ek et al., GEWEX News, 2011 NLDAS Drought Monitor – Default Plots Soil Moisture Total Runoff RoutedStreamflow ET

11. 8 June 1988 – Drought year June 1988 – Drought year

13. Four-model ensemble mean total column soil moisture percentile (January 2010 – February 2014)

14. NLDAS Flood Monitoring Ensemble mean daily streamflow anomaly (m 3 /s) Hurricane Irene and Tropical Storm Lee 20 August – 17 September 2011

15. NLDAS Flood Monitoring Ensemble mean daily streamflow anomaly (m 3 /s) Superstorm Sandy 29 October – 04 November 2012

16. NLDAS Flood Monitoring Ensemble mean daily streamflow anomaly (m 3 /s) Colorado Front Range Flooding September 2013

17. Application NLDAS Products in USDM NLDAS GIS data (soil moisture and total runoff for daily, weekly, and monthly) are an integral part of the USDM process, both operationally and also as part of a weekly ppt sent to the USDM Listserv. Shading area is NLDAS product, contour line is US drought monitor boundary

18. Application of NLDAS Products in USDA Effect of dryness and wetness on cotton

19. NLDAS Support for NCEP/CPC Drought Monitoring and Assessment Activity NLDAS products directly fit in

20. 3. Evaluation/Validation of NLDAS Products Acknowledgments: NLDAS project was supported by NOAA/OGP GAPP Program, NASA Terrestrial Hydrology Program, NOAA/CPO CPPA Program (Climate Program of the Americas), and NOAA/CPO MAPP Program (Modeling, Analysis, Predictions and Projections).

21. NLDAS Evaluation and Validation Energy flux validation from tower: net radiation, sensible heat, latent heat, ground heat (Xia et al., 2012a, NLDAS book chapter, in press) Water flux: evaporation, total runoff/streamflow State variables: soil moisture, soil temperature (Xia et al., 2012b, JAMC, in press), skin temperature, snow water equivalent, snow cover Monthly streamflow anomaly correlation over continental United States (1979-2007 USGS measured streamflow) Ensemble Mean JGR, Xia et al., 2012a, 2012b Xia et al., 2014a: Evaluation of Multi-Model Simulated Soil Moisture in NLDAS-2, J. Hydrology, in press.

22. 4. Objective/Optimal Blends of NLDAS Drought Indices - An Initiative Ensemble-mean Monthly Percentile (NLDAS drought Indices) using: - Top 1m soil moisture (SM1) - Total column soil moisture (SMT) - Evapotranspiration (ET) - Total runoff (Q) To support CPC Experimental Objective Blends of Drought Indicators http://www.cpc.ncep.noaa.gov/products/predictions/tools/edb/droughtblends.php

23. US Drought Monitor and its Statistics Percentile Drought area percentage for each state Drought Classification Drought Classification (1) (2) (3) (4) Percentile

24. Evaluation of Optimal Blended NLDAS Drought Index in Texas 5 Drought Categories: D0-D4, D1-D4, D2-D4,D3-D4, D4-D4 JGR-Atmosphere, Xia et al, 2014b Texas Drought USDM NLDAS Blend

25. 2011-2012 Drought Variation: Monthly Animation Optimal Blended NLDAS Drought Index vs USDM 2011 USDM NLDAS - OBNDI generally captures USDM drought area percent, though sample size small for severe droughts. - Reconstructed drought index reproducible and can be used as a reference dataset.

26. GRACE-based ground water storage NLDAS simulation Land Data Information (LIS) developed by NASA ESI-Evaporative Stress Index VegDRI – Vegetation Drought Index SPI – Standard Precipitation index PDI – Palmer Drought Index PDSI – Palmer Drought Severity Index include snowpack (seasonal lag) 2012b

27. NLDAS Past, Present, and Future Past: Phase 1 (2000-2005) – to establish NLDAS configuration, model evaluation framework, and collaboration partners. Phase 2 (2006-2010) – to make long-term (30 years) retrospective NLDAS run using the improved forcing and upgraded models, to establish a quasi-operational NLDAS system to support NIDIS activities, and to assess NLDAS products using observations. Monitoring Mode Present: Phase 3 (2011-2014) – to maintain a quasi-operational NLDAS system, to transition all codes and scripts to NCEP central computer system, and to implement NLDAS system into NCEP operation.

28. NLDAS Past, Present, and Future Future: EMC Land group will maintain two NLDAS systems: operational version (current ) and research version. Any upgrades from both forcing and land models from research community will be quickly implemented to the research version to make an internal test on EMC local server and/or NCEP WCOSS computer. EMC Land group will collaborate NASA/GSFC to install their Land Information System (LIS) for NLDAS to construct a real data assimilation system to assimilate observed data from both in-situ and remote sensing. EMC Land group will collaborate with NWS/OHD to extend a fine scale (~4 km) NLDAS system to support U.S. operational flood and drought monitoring and prediction. Monitoring Mode

29. NLDAS Past, Present, and Future Prospective: EMC Land group will extend the NLDAS system from NLDAS domain to whole north America. The purpose is to support for North American Drought Monitor. EMC Land group will collaborate NCEP/CPC and the other NLDAS partners to further extend NLDAS system from whole north America to the globe to support Global Drought Monitor being initiated by multi-countries as EMC is generating its LIS- GLDAS product. EMC Land group will collaborate with its partners to improve land surface models (physics) and test the role of NLDAS initial conditions in coupled models for weather and climate predictions. Monitoring Mode An ongoing work from Jesse Meng of EMC Land-Hydrology Group

30. References Ek, M.B., Y. Xia, E.F. Wood, J. Sheffield, L. Luo, D. Lettemaier, and NLDAS team, 2011: North American Land Data Assimilation Phase 2 (NLDAS-2): Development and Applications, GEWEX news, 21, 6-7. Xia, Y., 2007: Calibration of LaD Model in the Northeast of the United States Using Observed Annual streamflow, J. Hydrometeo., 8, 1098-1110. Xia, Y., K.E. Mitchell, M.B. Ek, J. Sheffield, B. Cosgrove, and NLDAS team, 2012a: Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products, J. Geophys. Res., 117, D03109, doi:10.1029/2011JD016048. Xia, Y., K.E. Mitchell, M.B Ek, B. Cosgrove, J. Sheffield, and NLDAS team, 2012b: Continental-scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2 (NLDAS-2): 2. Validation of model-simulated streamflow, J. Geophys. Res., 117, D03110, doi:10.1029/2011JD016051. Xia, Y., M. EK, J. Sheffield, B. Livneh, M. Huang, H. Wei, S. Feng, L. Luo, J. Meng, and E. Wood, 2013a: Validation of Noah-simulated Soil temperature in the North American Land Data Assimilation System Phase 2. J. Appl. Meteor. Climatol. doi:10.1175/JAMC-D-12- 033.1. Xia, Y., B. Cosgrove, M. B. Ek, J. Sheffield, L. Luo, E. F. Wood, K. Mo, and NLDAS team, 2013b: Overview of North American Land Data Assimilation System, Chapter 11 in Land Data Observation, Modeling and Assimilation, edited by Liang et al., World Scientific, 335-376. Xia, Y., J. Sheffield, M. B. Ek, J. Dong, N. Chaney, H. Wei, J. Meng, and E. F. Wood, 2014a, Evaluation of Multi-Model Simulated Soil Moisture in NLDAS-2, J. Hydrology, in press. Xia, Y., M.B. Ek, C. Peters-Lidard, D. Mocko, M. Svboda, J. Sheffield, and E.F. Wood, 2014b: Application of USDM Statistics in NLDAS-2: Objectively Blended NLDAS drought Index over the Continental United States, J. Geophys. Res., 119, DOI: 10.1002/2013JD020994, in press. Xia, Y., M. Ek, D. Mocko, C. Peters-Lidard, J. Sheffield, J. Dong, and E. Wood, 2014c: Uncertainties, Correlations, and Optimal Blends of Drought Indices from the NLDAS Multiple Land Surface Model Ensemble. J. Hydrometeor., 15, doi:10.1175/JHM-D-13-058.1, in press.

31. Comments and Suggestions to the following scientists: Michael.Ek@noaa.gov Michael.Ek@noaa.gov LDAS (NLDAS, HRAP-NLDAS, GLDAS): Michael.Ek@noaa.govMichael.Ek@noaa.gov NLDAS EMC: Youlong.Xia@noaa.gov, NLDAS NASA: David.Mocko@nasa.gov, HRAP-NLDAS EMC: Jiarui.Dong@noaa.gov, GLDAS EMC: Jesse.Meng@noaa.gov Youlong.Xia@noaa.govDavid.Mocko@nasa.gov Jiarui.Dong@noaa.govJesse.Meng@noaa.govYoulong.Xia@noaa.govDavid.Mocko@nasa.gov Jiarui.Dong@noaa.govJesse.Meng@noaa.gov NOAA NLDAS Website http://www.emc.ncep.noaa.gov/mmb/nldas/ NASA NLDAS Website http://ldas.gsfc.nasa.gov/nldas /