Search Results

You are looking at 1 - 10 of 14 items for :

  • Journal of Hydrometeorology x
  • Advancing Drought Monitoring and Prediction x
  • All content x
Clear All
Hailan Wang, Siegfried Schubert, Randal Koster, Yoo-Geun Ham, and Max Suarez

where the amplitude of the anomalies exceeds two standard deviations. The substantial differences in the record heat and drought that developed over the United States during 2011 and 2012 offer an important opportunity to assess further the differing roles of SST forcing in the development of such extreme events. The 2011 and 2012 U.S. droughts were accompanied by SST anomalies that had important similarities as well as some differences. Figure 2 shows that La Niña conditions existed in the

Full access
Bart Nijssen, Shraddhanand Shukla, Chiyu Lin, Huilin Gao, Tian Zhou, Ishottama, Justin Sheffield, Eric F. Wood, and Dennis P. Lettenmaier

impact is much larger in the developing world, where agriculture typically occupies a larger percentage of the labor force and food insecurity is a major concern ( Brown and Funk 2008 ). Given the magnitude of projected changes in drought from climate models ( Dai 2011 ), the potential increase in susceptibility to droughts is alarming. Even though Sheffield et al. (2012) found little evidence indicating a change in the occurrence of drought events globally over the past 60 years, the

Full access
Eric F. Wood, Siegfried D. Schubert, Andrew W. Wood, Christa D. Peters-Lidard, Kingtse C. Mo, Annarita Mariotti, and Roger S. Pulwarty

NOAA’s Climate Program Office, which set up a Drought Task Force (DTF) with the overarching goal of advancing drought understanding, monitoring, and prediction through coordinated research activities that address a number of NIDIS-relevant scientific objectives. These include (i) the scientific understanding of the weather and climatic mechanisms that lead to the onset, maintenance, and recovery of drought; (ii) improving drought prediction skill by identifying and exploiting sources of drought

Full access
Richard Seager, Lisa Goddard, Jennifer Nakamura, Naomi Henderson, and Dong Eun Lee

subtropics and a poleward expansion of subtropical dry zones ( Solomon et al. (2007) ; Seager et al. 2010b ; Cayan et al. 2010 ) and also a shift to more extreme precipitation events. Was the TexMex drought a case of such anthropogenically induced climate change? It would certainly be rash to draw such a conclusion given that past droughts in the U.S. Southwest and Plains have been reliably attributed to forcing of atmospheric circulation anomalies by naturally occurring cool tropical Pacific and, to a

Full access
Kingtse C. Mo and Dennis P. Lettenmaier

part because of variations among multiple drought indicators, different land surface models, and forcings. Mo et al. (2012) compared the NCEP and UW products, which use different land surface models and forcing data. They found that the SM and runoff differences between systems are larger over the western than the eastern United States, and in general, the differences were too large to support drought classification. The differences between the two sets of products were mostly attributable to

Full access
Xing Yuan, Eric F. Wood, Nathaniel W. Chaney, Justin Sheffield, Jonghun Kam, Miaoling Liang, and Kaiyu Guan

evaluated drought forecast skill using a set of hindcast experiments ( Mo et al. 2012 ; Yoon et al. 2012 ; Yuan et al. 2013 ). The CGCM-based drought forecasting approach can be divided in two steps. First, meteorological forcings from the CGCM forecasts are bias corrected and downscaled to the resolution that is suitable for regional applications, with the resulting precipitation used to calculate a meteorological drought index, such as the Standardized Precipitation Index (SPI; McKee et al. 1993

Restricted access
Jiarui Dong, Mike Ek, Dorothy Hall, Christa Peters-Lidard, Brian Cosgrove, Jeff Miller, George Riggs, and Youlong Xia

records extend through 2005. The USHCN stations are located in relatively flat regions scattered across the CONUS and feature a mean elevation of about 520 m ( Fig. 1 ). c. NLDAS forcing The NLDAS project has produced over 30 years of retrospective and real-time forcing from 1979 to the present to support its land surface modeling activities ( Cosgrove et al. 2003 ; Xia et al. 2012 ). NLDAS forcing features a ⅛° spatial resolution and an hourly temporal resolution and is based on spatially and

Full access
Youlong Xia, Michael B. Ek, David Mocko, Christa D. Peters-Lidard, Justin Sheffield, Jiarui Dong, and Eric F. Wood

monthly anomalies and percentiles of hydrologic fields (soil moisture, snow water equivalent, total runoff, streamflow, evaporation, and precipitation) output from the four land surface models [Noah, Mosaic, Sacramento (SAC), and Variable Infiltration Capacity (VIC)] on a common ⅛° grid using common hourly meteorological forcing (see the drought tab on the NLDAS website, ). The climatology of each hydrologic field was calculated as the average of 28 yr (1980–2007) of

Full access
Sujay V. Kumar, Christa D. Peters-Lidard, David Mocko, Rolf Reichle, Yuqiong Liu, Kristi R. Arsenault, Youlong Xia, Michael Ek, George Riggs, Ben Livneh, and Michael Cosh

; Zaitchik et al. 2010 ; Xia et al. 2012c ). These studies note that the model-based estimates suffer from uncertainties in the forcing inputs, model parameters, and model structural errors. Data assimilation (DA) techniques have been employed as an effective strategy to combine the strengths of both modeling and observations to generate superior estimates by appropriately weighting their respective sources of errors ( Reichle 2008 ). There have been several studies that have examined the assimilation

Full access
Johnna M. Infanti and Ben P. Kirtman

( Ropelewski and Halpert 1986 , 1987 ; Mo and Schemm 2008a , b ; Seager et al. 2009 ). In contrast to Mo and Schemm (2008a) , Seager et al. (2009) concluded that rainfall is more closely related to internal atmospheric variability, particularly in summer. Noise or internal atmospheric variability, for the purposes of this paper, is unpredictable, that is, we cannot relate it to specific forcing or feedback (ocean–atmosphere or atmosphere–land). This unpredictable variability is due to internal

Full access