Improved seasonal drought forecasts using reference evapotranspiration anomalies

Geophysical Research Letters

Volumn 43, Issue 1, 2016, Pages 377-385

  McEvoy, Daniel J ^a,b   Huntington, Justin L ^a,b   Mejia, John F ^a   Hobbins, Michael T ^c,d  

^a DESERT RESEARCH INSTITUTE   (United States)

^b Western Regional Climate Center Nevada   (United States)

^c Cooperative Institute for Research in Environmental Sciences ^*  (United States)

^d NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

Author keywords

complementary relationship; drought; evaporative demand; reference evapotranspiration; seasonal forecasting

Indexed keywords

ATMOSPHERIC PRESSURE; DROUGHT; WEATHER FORECASTING;

ACTUAL EVAPOTRANSPIRATION; CLIMATE FORECASTS; COMPLEMENTARY RELATIONSHIP; EVAPORATIVE DEMANDS; RECENT RESEARCHES; REFERENCE EVAPOTRANSPIRATION; SEASONAL FORECASTING; SOUTHERN OSCILLATION;

EVAPOTRANSPIRATION;

ACCURACY ASSESSMENT; CLIMATE PREDICTION; COMPLEMENTARITY; DROUGHT; EL NINO-SOUTHERN OSCILLATION; EVAPOTRANSPIRATION; FORECASTING METHOD; PRECIPITATION (CLIMATOLOGY); SEASONAL VARIATION; SPATIOTEMPORAL ANALYSIS; WEATHER FORECASTING;

UNITED STATES;

EID: 84957727753     PISSN: 00948276     EISSN: 19448007     Source Type: Journal    
DOI: 10.1002/2015GL067009     Document Type: Article

References (31)

1. Abatzoglou, J. T., (2011), Development of gridded surface meteorological data for ecological applications and modeling, Int. J. Climatol., 33, 121-131, doi: 10.1002/joc.3413. [Available at http://nimbus.cos.uidaho.edu/DATA/OBS/.]
2. Allen, R. G., I. A. Walter, R. Elliott, T. Howell, D. Itenfisu, and, M. Jensen, (2005), The ASCE standardized reference evapotranspiration equation, Rep. 0-7844-0805-X, 59 pp. [Available at http://www.kimberly.uidaho.edu/water/asceewri/ascestzdetmain2005.pdf.]
3. Anderson, M. C., C. R. Hain, B. Wardlow, J. R. Mecikalski, and, W. P. Kustas, (2011), Evaluation of a drought index based on thermal remote sensing of evapotranspiration over the continental United States, J. Clim., 24, 2025-2044, doi: 10.1175/2010JCLI3812.1.
4. Capotondi, A., et al., (2015), Understanding ENSO Diversity, Bull. Am. Meteorol. Soc., 96, 921-938, doi: 10.1175/BAMS-D-13-00117.1.
5. Daly, C., R. P. Neilson, and, D. L. Phillips, (1994), A statistical-topographic model for mapping climatological precipitation over mountainous terrain, J. Appl. Meteorol., 33, 140-158.
6. Dirmeyer, P. A., (2013), Characteristics of the water cycle and land-atmosphere interactions from a comprehensive reforecast and reanalysis, Clim. Dyn., 41, 1083-1097, doi: 10.1007/s00382-013-1866-x.
7. Hobbins, M. T., (2016), The variability of ASCE standardized reference evapotranspiration: A rigorous, CONUS-wide decomposition and attribution, Trans. ASABE, 59, doi: 10.13031/trans.5910975, in press.
8. Hobbins, M. T., and, J. L. Huntington, (2016), Chapter 42, in Handbook of Applied Hydrology, edited by, V. P. Singh, McGraw-Hill Education, New York.
9. Hobbins, M. T., A. Dai, M. L. Roderick, and, G. D. Farquhar, (2008), Revisiting the parameterization of potential evaporation as a driver of long-term water balance trends, Geophys. Res. Lett., 35, L12403, doi: 10.1029/2008GL033840.
10. Jia, L., et al., (2015), Improved seasonal prediction of temperature and precipitation over land in a high-resolution GFDL climate model, J. Clim., 28, 2044-2062, doi: 10.1175/JCLI-D-14-00112.1.
11. Karl, T. R., and, W. J. Koss, (1984), Regional and National Monthly, Seasonal, and Annual Temperature Weighted by Area, 1895-1983, Hist. Climatol. Ser., vol. 4-3, 38 pp., Natl. Clim. Data Cent., Asheville, N. C.
12. Kumar, S., P. A. Dirmeyer, and, J. L. Kinter III, (2014), Usefulness of ensemble forecasts from NCEP Climate Forecast System in sub-seasonal to intra-annual forecasting, Geophys. Res. Lett., 41, 3586-3593, doi: 10.1002/2014GL059586.
13. Lavers, D., L. Luo, and, E. F. Wood, (2009), A multiple model assessment of seasonal climate forecast skill for applications, Geophys. Res. Lett., 36, L23711, doi: 10.1029/2009GL041365.
14. McEvoy, D. J., (2015), Physically based evaporative demand as a drought metric: Historical analysis and seasonal prediction, PhD dissertation, Dep. of Atmospheric Science, Univ. of Nevada, Reno, Nevada. [Available online at http://www.dri.edu/images/stories/divisions/das/dasfaculty/mcevoy-dissertation-final.pdf.]
15. Mitchell, K. E., et al., (2004), The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system, J. Geophys. Res., 109, D07S90, doi: 10.1029/2003JD003823.
16. Miyakoda, K., G. D. Hembree, R. F. Strickler, and, I. Shulman, (1972), Cumulative results of extended forecast experiments: I. Model performance for winter cases, Mon. Weather Rev., 100, 836-855, doi: 10.1175/1520-0493(1972)100<0836:CROEFE>2.3.CO;2.
17. Mu, Q., M. Zhao, J. S. Kimball, N. G. McDowell, and, S. W. Running, (2013), A remotely sensed global terrestrial drought severity index, Bull. Am. Meteorol. Soc., 94, 93-98, doi: 10.1175/BAMS-D-11-00213.1.
18. O'lenic, E. A., D. A. Unger, M. S. Halpert, and, K. S. Pelman, (2008), Developments in operational long-range climate prediction at CPC, Weather Forecasting, 23, 496-515, doi: 10.1175/2007WAF2007042.1.
19. 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. Hydrometeorol., 14, 1057-1074, doi: 10.1175/JHM-D-12-0144.1.
20. Peng, P., A. G. Barnston, and, A. Kumar, (2013), A comparison of skill between two versions of the NCEP Climate Forecast System (CFS) and CPC's operational short-lead seasonal outlooks, Weather Forecasting, 28, 445-462, doi: 10.1175/WAF-D-12-00057.1.
21. Saha, S., et al., (2014), The NCEP Climate Forecast System Version 2, J. Clim., 27, 2185-2208, doi: 10.1175/JCLI-D-12-00823.1. [Available at http://nomads.ncdc.noaa.gov/data/cfsr-rfl-mmts/.]
22. Shukla, S., M. Safeeq, A. AghaKouchak, K. Guan, and, C. Funk, (2015), Temperature impacts on the water year 2014 drought in California, Geophys. Res. Lett., 42, doi: 10.1002/2015GL063666.
23. Tian, D., C. J. Martinez, and, W. D. Graham, (2014), Seasonal prediction of regional reference evapotranspiration based on Climate Forecast System Version 2, J. Hydrometeorol., 15, 1166-1188, doi: 10.1175/JHM-D-13-087.1.
24. Weiss, J. L., C. L. Castro, and, J. T. Overpeck, (2009), Distinguishing pronounced droughts in the southwestern United States: Seasonality and effects of warmer temperature, J. Clim., 22, 5918-5932, doi: 10.1175/2009JCLI2905.1.
25. Williams, A. P., R. Seager, J. T. Abatzoglou, B. I. Cook, J. E. Smerdon, and, E. R. Cook, (2015), Contribution of anthropogenic warming to California drought during 2012-2014, Geophys. Res. Lett., 42, 6819-6828, doi: 10.1002/2015GL064924.
26. Wood, A. W., A. Kumar, and, D. P. Lettenmaier, (2005), A retrospective assessment of National Centers for Environmental Prediction climate model-based ensemble hydrologic forecasting in the western United States, J. Geophys. Res., 110, D04105, doi: 10.1029/2004JD004508.
27. Wood, E., S. Schubert, A. Wood, C. Peters-Lidard, K. Mo, A. Mariotti, and, R. Pulwarty, (2015), Prospects for advancing drought understanding, monitoring and prediction, J. Hydrometeorol., 16, 1636-1657, doi: 10.1175/JHM-D-14-0164.1.
28. Yao, Y., S. Liang, Q. Qin, and, K. Wang, (2010), Monitoring drought over the conterminous United States using MODIS and NCEP reanalysis-2 data, J. Appl. Meteorol. Climatol., 49, 1665-1680, doi: 10.1175/2010JAMC2328.1.
29. Yoon, J., and, L. R. Leung, (2015), Assessing the relative influence of surface soil moisture and ENSO SST on precipitation predictability over the contiguous United States, Geophys. Res. Lett., 5005-5013, doi: 10.1002/2015GL064139.
30. Yuan, X., E. F. Wood, L. Luo, and, M. Pan, (2011), A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction, Geophys. Res. Lett., 38, L13402, doi: 10.1029/2011GL047792.
31. Yuan, X., E. F. Wood, J. K. Roundy, and, M. Pan, (2013), CFSv2-based seasonal hydroclimatic forecasts over the conterminous United States, J. Hydrometeorol., 26, 4828-4847, doi: 10.1175/JCLI-D-12-00683.1.