Prospects for advancing drought understanding, monitoring, and prediction

Journal of Hydrometeorology

Volumn 16, Issue 4, 2015, Pages 1636-1657

  Wood, Eric F ^a   Schubert, Siegfried D ^b   Wood, Andrew W ^c   Peters Lidard, Christa D ^b   Mo, Kingtse C ^d   Mariotti, Annarita ^d   Pulwarty, Roger S ^d  

^a Princeton University   (United States)

^b NASA GODDARD SPACE FLIGHT CENTER   (United States)

^c NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

^d NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

Author keywords

ENSO; Hydrology; Land surface model; Nowcasting; Seasonal forecasting

Indexed keywords

CLIMATE PREDICTION; DROUGHT; EL NINO-SOUTHERN OSCILLATION; ENVIRONMENTAL MONITORING; HYDROLOGICAL MODELING; LA NINA; LAND SURFACE; NOWCASTING; WEATHER FORECASTING;

GREAT PLAINS;

EID: 84941281760     PISSN: 1525755X     EISSN: 15257541     Source Type: Journal    
DOI: 10.1175/JHM-D-14-0164.1     Document Type: Article

References (48)

1. AghaKouchak, A., and N. Nakhjiri, 2012: A near real-time satellite-based global drought climate data record. Environ. Res. Lett., 7, 044037, doi:10.1088/1748-9326/7/4/044037.
2. Anderson, M., C. Hain, J. Otkin, X. Zhan, K. Mo, M. Svoboda, B. Wardlow, and A. Pimstein, 2013: An intercomparison of drought indicators based on thermal remote sensing and NLDAS-2 simulations with U.S. Drought Monitor classifications. J. Hydrometeor., 14, 1035-1056, doi:10.1175/JHM-D-12-0140.1.
3. Below, R., E. Grover-Kopec, and M. Dilley, 2007: Documenting drought-related disasters: A global reassessment. J. Environ. Dev., 16, 328-344, doi:10.1177/1070496507306222.
4. Chaney, N. W., J. Sheffield, G. Villarini, and E. F. Wood, 2014: Development of a high-resolution gridded daily meteorological dataset over sub-Saharan Africa: Spatial analysis of trends in climate extremes. J. Climate, 27, 5815-5835, doi:10.1175/JCLI-D-13-00423.1.
5. Chirlin, G. R., and E. F. Wood, 1982: On the relationship between kriging and state estimation. Water Resour. Res., 18, 432-438, doi:10.1029/WR018i002p00432.
6. Dirmeyer, P. A., J. Wei, M. G. Bosilovich, and D. M. Mocko, 2014: Comparing evaporative sources of terrestrial precipitation and their extremes in MERRA using relative entropy. J. Hydrometeor., 15, 102-116, doi:10.1175/JHM-D-13-053.1.
7. Dong, J., M. Ek, D. Hall, C. Peters-Lidard, B. Cosgrove, J. Miller, G. Riggs, and Y. Xia, 2014: Using air temperature to quantitatively predict the MODIS fractional snow cover retrieval errors over the continental United States. J. Hydrometeor., 15, 551-562, doi:10.1175/JHM-D-13-060.1.
8. Hao, Z., and A. AghaKouchak, 2013: Multivariate Standardized Drought Index: A parametric multi-index model. Adv. Water Resour., 57, 12-18, doi:10.1016/j.advwatres.2013.03.009.
9. Hao, Z., and A. AghaKouchak, 2014: A nonparametric multivariate multi-index drought monitoring framework. J. Hydrometeor., 15, 89-101, doi:10.1175/JHM-D-12-0160.1.
10. Hao, Z., A. AghaKouchak, N. Nakhjiri, and A. Farahmand, 2014: Global integrated drought monitoring and prediction system. Sci. Data, 1, 140001, doi:10.1038/sdata.2014.1.
11. Heim, R. R., Jr., 2002: A review of twentieth-century drought indices used in the United States. Bull. Amer. Meteor. Soc., 83, 1149-1165, doi:10.1175/1520-0477(2002)083,1149: AROTDI.2.3.CO;2.
12. Hoerling, M., J. Eischeid, A. Kumar, R. Leung, A. Mariotti, K. Mo, S. Schubert, and R. Seager, 2014: Causes and predictability of the 2012 Great Plains drought. Bull. Amer. Meteor. Soc., 95, 269-282, doi:10.1175/BAMS-D-13-00055.1.
13. Huang, J., H. M. van den Dool, and K. G. Georgakakos, 1996: Analysis of model-calculated soil moisture over the United States (1931-1993) and applications to long-range temperature forecasts. J. Climate, 9, 1350-1362, doi:10.1175/1520-0442(1996)009,1350:AOMCSM.2.0.CO;2.
14. Infanti, J. M., and B. P. Kirtman, 2014: Southeastern U.S. rainfall prediction in the North American Multi-Model Ensemble. J. Hydrometeor., 15, 529-550, doi:10.1175/JHM-D-13-072.1.
15. Kirtman, B. P., and Coauthors, 2014: The North American Multimodel Ensemble: Phase-1 seasonal-to-interannual prediction; Phase-2 toward developing intraseasonal prediction. Bull. Amer. Meteor. Soc., 95, 585-601, doi:10.1175/BAMS-D-12-00050.1.
16. Koster, R. D., G. K. Walker, S. P. P. Mahanama, and R. H. Reichle, 2014: Soil moisture initialization error and subgrid variability of precipitation in seasonal streamflow forecasting. J. Hydrometeor., 15, 69-88, doi:10.1175/JHM-D-13-050.1.
17. Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994: A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophys. Res., 99, 14 415-14 428, doi:10.1029/94JD00483.
18. Luo, L., and E. F. Wood, 2007: Monitoring and predicting the 2007 U.S. drought. Geophys. Res. Lett., 34, L22702, doi:10.1029/2007GL031673.
19. Madadgar, S., and A. Moradkhani, 2013: A Bayesian framework for probabilistic seasonal drought forecasting. J. Hydrometeor., 14, 1685-1705, doi:10.1175/JHM-D-13-010.1.
20. McKee, T. B., N. J. Doeskin, and J. Kleist, 1993: The relationship of drought frequency and duration to timescales. Preprints, Eighth Conf. on Applied Climatology, Anaheim, CA, Amer. Meteor. Soc., 179-184.
21. Mitchell, K. E., and Coauthors, 2004: The multi-institution North American LandDataAssimilation System (NLDAS):Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J. Geophys. Res., 109, D07S90, doi:10.1029/2003JD003823.
22. Mo, K., 2008: Model-based drought indices over the United States. J. Hydrometeor., 9, 1212-1230, doi:10.1175/2008JHM1002.1.
23. Mo, K., and D. Lettenmaier, 2014: Objective drought classification using multiple land surface models. J. Hydrometeor., 15, 990-1010, doi:10.1175/JHM-D-13-071.1.
24. NCDC, 2012: Summer 2012 drought update. [Available online at www.ncdc.noaa.gov/news/summer-2012-drought-update.]
25. NIDIS, 2007: The National Integrated Drought Information System Implementation Plan. NIDIS Rep., 34 pp. [Available online at www.drought.gov/media/imageserver/NIDIS/content/whatisnidis/NIDIS-IPFinal-June07.pdf.]
26. NIDIS, 2012: National Drought Forum summary report and priority actions: Drought and U.S. preparedness in 2013 and beyond. NIDIS Rep., 53 pp. [Available online at www.drought.gov/media/pgfiles/2012-droughtForumFullReport.pdf.]
27. Nijssen, B., S. Shukla, C. Lin, H. Gao, T. Zhou, J. Sheffield, E. F. Wood, and D. P. Lettenmaier, 2014: A prototype global drought information system based on multiple land surface models. J. Hydrometeor., 15, 1661-1676, doi:10.1175/JHM-D-13-090.1.
28. Otkin, J. A., M. C. Anderson, C. Hain, I. E. Mladenova, J. B. Basara, and M. Svoboda, 2013: Examining rapid onset drought development using the thermal infrared based evaporative stress index. J. Hydrometeor., 14, 1057-1074, doi:10.1175/JHM-D-12-0144.1.
29. Palmer, W. C., 1965: Meteorological drought. Research Paper 45, U.S. Weather Bureau, 58 pp.
30. Pegion, K., and A. Kumar, 2013: Does an ENSO-conditional skill mask improve seasonal predictions? Mon. Wea. Rev., 141, 4515-4533, doi:10.1175/MWR-D-12-00317.1.
31. Pozzi, W., and Coauthors, 2013: Towards global drought early warning capability: Expanding international cooperation for the development of a framework for global drought monitoring and forecasting. Bull. Amer. Meteor. Soc., 94, 776-785, doi:10.1175/BAMS-D-11-00176.1.
32. Pulwarty, R., and J. Verdin, 2013: Crafting integrated early warning systems: The case of drought. Measuring Vulnerability to Natural Hazards: Towards Disaster Resilient Societies, 2nd ed. J. Birkmann, Ed., United Nations University Press, 720 pp.
33. Rienecker, M. M., and Coauthors, 2011: MERRA: NASA'sModern-Era Retrospective Analysis for Research and Applications. J. Climate, 24, 3624-3648, doi:10.1175/JCLI-D-11-00015.1.
34. Saha, S., and Coauthors, 2010: The NCEP Climate Forecast System Reanalysis. Bull. Amer. Meteor. Soc., 91, 1015-1057, doi:10.1175/2010BAMS3001.1.
35. Schubert, S., and Coauthors, 2009: A U.S. CLIVAR project to assess and compare the responses of global climate models to drought-related SST forcing patterns: Overview and results. J. Climate, 22, 5251-5272, doi:10.1175/2009JCLI3060.1.
36. Seager, R., L. Goddard, J. Nakamura, N. Henderson, and D. E. Lee, 2014: Dynamical causes of the 2010/11 Texas-northern Mexico drought. J. Hydrometeor., 15, 39-68, doi:10.1175/JHM-D-13-024.1.
37. Shafer, B. A., and L. E. Dezman, 1982: Development of a Surface Water Supply Index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. Proc. 50th Annual Western Snow Conf., Reno, NV, Western Snow Conference, 164-175. [Available online at www.westernsnowconference.org/node/932.]
38. Sheffield, J., and E. F. Wood, 2008: Global trends and variability in soil moisture and drought characteristics, 1950-2000, from observation-driven simulations of the terrestrial hydrologic cycle. J. Climate, 21, 432-458, doi:10.1175/2007JCLI1822.1.
39. Sheffield, J., and Coauthors, 2014: A drought monitoring and forecasting system for sub-Sahara African water resources and food security. Bull. Amer. Meteor. Soc., 95, 861-882, doi:10.1175/BAMS-D-12-00124.1.
40. Shukla, S., and A. W. Wood, 2008: Use of a standardized runoff index for characterizing hydrologic drought. Geophys. Res. Lett., 35, L02405, doi:10.1029/2007GL032487.
41. Smith, A., and R. Katz, 2013: U.S. billion-dollar weather and climate disasters: Data sources, trends, accuracy and biases. Nat. Hazards, 67, 387-410, doi:10.1007/s11069-013-0566-5.
42. Svoboda, M., and Coauthors, 2002: The Drought Monitor. Bull. Amer. Meteor. Soc., 83, 1181-1190, doi:10.1175/1520-0477(2002)083,1181:TDM.2.3.CO;2.
43. U.S. Government, 2014: National Integrated Drought Information System Reauthorization Act of 2014. H. R. 2431, 113th Congress.
44. Wang, H., S. Schubert, R. Koster, Y.-G. Ham, and M. Suarez, 2014: On the role of SST forcing in the 2011 and 2012 extreme U.S. heat and drought: A study in contrasts. J. Hydrometeor, 15, 1255-1273, doi:10.1175/JHM-D-13-069.1.
45. Wood, A. W., 2008: The University of Washington Surface Water Monitor: An experimental platform for national hydrologic assessment and prediction. 22nd Conf. on Hydrology, New Orleans, LA, Amer. Meteor. Soc., 5.2. [Available online at https://ams.confex.com/ams/88Annual/techprogram/paper_134844.htm.]
46. Xia, Y., and Coauthors, 2012: 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.
47. Xia, Y., M. B. Ek, D. Mocko, C. D. Peters-Lidard, J. Sheffield, J. Dong, and E. F. Wood, 2014: Uncertainties, correlations, and optimal blends of drought indices from the NLDAS multiple land surface model ensemble. J. Hydrometeor., 15, 1636-1650, doi:10.1175/JHM-D-13-058.1.
48. Yuan, X., E. F. Wood, J. K. Roundy, and M. Pan, 2013: CFSv2-based seasonal hydroclimatic forecasts over the conterminous United States. J. Climate, 26, 4828-4847, doi:10.1175/JCLI-D-12-00683.1.