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national economy. Often not recognized, drought also has serious impacts on the mental health of farming families and people in agricultural communities with long-lasting effects [see U.S.-based review by Vins et al. (2015) ]. Improved understanding and forecasting of drought at least provides the possibility of improved anticipation of, and adaptation to, drought conditions with potential benefits for people and society. Understanding the physical causes of droughts in North America, and the relative
national economy. Often not recognized, drought also has serious impacts on the mental health of farming families and people in agricultural communities with long-lasting effects [see U.S.-based review by Vins et al. (2015) ]. Improved understanding and forecasting of drought at least provides the possibility of improved anticipation of, and adaptation to, drought conditions with potential benefits for people and society. Understanding the physical causes of droughts in North America, and the relative
2012 over much of the Great Plains. The delayed response of a regional climate to slowly varying oceanic forcing and land–atmosphere interaction provides the foundation for seasonal prediction over many regions around the world. State-of-the-art seasonal prediction models provide relatively skillful predictions of winter hydroclimate over the United States, but show virtually no skill in prediction of summer rainfall anomalies over much of the North American continent ( Quan et al. 2012 ). Seasonal
2012 over much of the Great Plains. The delayed response of a regional climate to slowly varying oceanic forcing and land–atmosphere interaction provides the foundation for seasonal prediction over many regions around the world. State-of-the-art seasonal prediction models provide relatively skillful predictions of winter hydroclimate over the United States, but show virtually no skill in prediction of summer rainfall anomalies over much of the North American continent ( Quan et al. 2012 ). Seasonal
MERRA-2, as described in section 2c , is shown in (a)–(c). The Z scores are computed as anomalies normalized by the standard deviation over 1999–2015. The box indicates the core drought region (105°–83°W, 33°–50°N), which is used for computing regional averages throughout the paper. The causes of the 2012 flash drought have been extensively studied yet remain an active area of research. While there is substantial evidence for a connection between North American drought and sea surface
MERRA-2, as described in section 2c , is shown in (a)–(c). The Z scores are computed as anomalies normalized by the standard deviation over 1999–2015. The box indicates the core drought region (105°–83°W, 33°–50°N), which is used for computing regional averages throughout the paper. The causes of the 2012 flash drought have been extensively studied yet remain an active area of research. While there is substantial evidence for a connection between North American drought and sea surface
observed spatial pattern of warm temperature anomalies over almost the entire North America at 2- and 3-month leads (i.e., November and December 1999), but the CFSR reforecasts predict a seesaw pattern with warm anomalies in the southern United States and cold anomalies in the northern United States and Canada ( Figs. 11b,c ). It is noted that the spatial pattern of 2-m air temperature in the CFSR reforecasts resembles more typical of the La Niña–induced response. Fig . 11. As in Fig. 8 , but for
observed spatial pattern of warm temperature anomalies over almost the entire North America at 2- and 3-month leads (i.e., November and December 1999), but the CFSR reforecasts predict a seesaw pattern with warm anomalies in the southern United States and cold anomalies in the northern United States and Canada ( Figs. 11b,c ). It is noted that the spatial pattern of 2-m air temperature in the CFSR reforecasts resembles more typical of the La Niña–induced response. Fig . 11. As in Fig. 8 , but for
reforecasts have higher skill over the northern United States and central Africa (left and center columns of Fig. 3c ). In boreal fall, the CFSR reforecasts still show a statistically significant correlation skill at week 4 over northeastern Europe, Mongolia, and northern China in contrast to the GLDAS reforecasts, whereas the latter displays a better skill over Alaska and Canada than the former (left and center columns of Fig. 4d ). It is noteworthy that over almost all of North America, the
reforecasts have higher skill over the northern United States and central Africa (left and center columns of Fig. 3c ). In boreal fall, the CFSR reforecasts still show a statistically significant correlation skill at week 4 over northeastern Europe, Mongolia, and northern China in contrast to the GLDAS reforecasts, whereas the latter displays a better skill over Alaska and Canada than the former (left and center columns of Fig. 4d ). It is noteworthy that over almost all of North America, the
datasets. This includes North American Land Data Assimilation System (NLDAS), Soil Moisture Operational Product System (SMOPS), and MODIS evapotranspiration (MOD16A2) as well as datasets used for downscaling SMOPS to 1-km resolution. Sections 4 and 5 briefly explain the land surface model used in this study and the procedure for parallel joint DA. Section 6 assesses the performance of the proposed methodology and section 7 discusses the results of the DA performance and drought monitoring over
datasets. This includes North American Land Data Assimilation System (NLDAS), Soil Moisture Operational Product System (SMOPS), and MODIS evapotranspiration (MOD16A2) as well as datasets used for downscaling SMOPS to 1-km resolution. Sections 4 and 5 briefly explain the land surface model used in this study and the procedure for parallel joint DA. Section 6 assesses the performance of the proposed methodology and section 7 discusses the results of the DA performance and drought monitoring over
Model-simulated soil moisture (in 0–10- and 0–100-cm soil layers) from 2003 to 2017 was also evaluated in this study because it represents an independent data source that can provide soil moisture estimates. Model-simulated soil moisture data are derived from phase 2 of the North American Land Data Assimilation System (NLDAS-2) ( Xia et al. 2012 ). NLDAS is a project developed by multiple organizations to construct land surface model datasets. Soil moisture is simulated at 1/8° spatial resolution by
Model-simulated soil moisture (in 0–10- and 0–100-cm soil layers) from 2003 to 2017 was also evaluated in this study because it represents an independent data source that can provide soil moisture estimates. Model-simulated soil moisture data are derived from phase 2 of the North American Land Data Assimilation System (NLDAS-2) ( Xia et al. 2012 ). NLDAS is a project developed by multiple organizations to construct land surface model datasets. Soil moisture is simulated at 1/8° spatial resolution by
North American land data assimilation system over the contiguous United States . J. Hydrometeor. , 13 , 996 – 1009 , https://doi.org/10.1175/JHM-D-11-0132.1 . 10.1175/JHM-D-11-0132.1 Novak , D. R. , C. Bailey , K. F. Brill , P. Burke , W. A. Hogsett , R. Rausch , and M. Schichtel , 2014 : Precipitation and temperature forecast performance at the weather prediction center . Wea. Forecasting , 29 , 489 – 504 , https://doi.org/10.1175/WAF-D-13-00066.1 . 10.1175/WAF-D-13
North American land data assimilation system over the contiguous United States . J. Hydrometeor. , 13 , 996 – 1009 , https://doi.org/10.1175/JHM-D-11-0132.1 . 10.1175/JHM-D-11-0132.1 Novak , D. R. , C. Bailey , K. F. Brill , P. Burke , W. A. Hogsett , R. Rausch , and M. Schichtel , 2014 : Precipitation and temperature forecast performance at the weather prediction center . Wea. Forecasting , 29 , 489 – 504 , https://doi.org/10.1175/WAF-D-13-00066.1 . 10.1175/WAF-D-13
