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College Park, MD, United States

Mo K.C.,Climate Prediction Center
Journal of Geophysical Research: Atmospheres | Year: 2011

This study employs precipitation (P) and ensemble soil moisture data sets from 1916 to 2007 to study the drought onset and demise over the United States. Both meteorological drought, classified using the standardized precipitation indices (SPIs), and agricultural drought, classified using the soil moisture percentiles, are studied. Drought onset is more predictable than drought demise. It takes 5-8 months for a region to accumulate enough P deficits to begin a drought, whereas a drought demise can come within one month to one season. A few strong rainfall episodes can end drought. The preferred season for the meteorological drought onset is at the beginning of the rainy season. Even though drought has a preferred season to begin, the ratio between the onset occurring in that season and the total drought events is less than 45%. For agricultural drought, the ratio is 60% or higher for the northwestern interior states and the Southwest. Over the Southern Plains, a cold El Niño-Southern Oscillation (ENSO) event occurs one season before the onset of drought. No drought events occur during the warm ENSO years. Therefore, the occurrence of a cold ENSO event can serve as an early warning for drought. For other areas influenced by ENSO, such as the lower Mississippi basin, the Ohio Valley, the Pacific Northwest, the upper Missouri basin, and the Southeast, most drought events occur during ENSO. The one-to-one correspondence between ENSO and drought is not good. For these areas, ENSO can only serve as a signal for intensive drought watch. Copyright 2011 by the American Geophysical Union.

Butler A.H.,Climate Prediction Center | Polvani L.M.,University of Applied and Environmental Sciences | Polvani L.M.,Lamont Doherty Earth Observatory
Geophysical Research Letters | Year: 2011

Recent studies have suggested that El Nio-Southern Oscillation (ENSO) may have a considerable impact on Northern Hemisphere wintertime stratospheric conditions. Notably, during El Nio the stratosphere is warmer than during ENSO-neutral winters, and the polar vortex is weaker. Opposite-signed anomalies have been reported during La Nia, but are considerably smaller in amplitude than during El Nio. This has led to the perception that El Nio is able to substantially affect stratospheric conditions, but La Nia is of secondary importance. Here we revisit this issue, but focus on the extreme events that couple the troposphere to the stratosphere: major, mid-winter stratospheric sudden warmings (SSWs). We examine 53 years of reanalysis data and find, as expected, that SSWs are nearly twice as frequent during ENSO winters as during non-ENSO winters. Surprisingly, however, we also find that SSWs occur with equal probability during El Nio and La Nia winters. These findings corroborate the impact of ENSO on stratospheric variability, and highlight that both phases of ENSO are important in enhancing stratosphere-troposphere dynamical coupling via an increased frequency of SSWs. Copyright 2011 by the American Geophysical Union.

Kumar A.,Climate Prediction Center
Climate Dynamics | Year: 2010

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction's (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS's hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50°E-110°E and 10°S-35°N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon Rainfall (AISMR; only the land stations of India during JJAS), the predicted mean AISMR with March, April and May initial conditions is found to be well correlated with actual AISMR and is found to provide skillful prediction. Thus, the calibrated CFS forecast could be used as a better tool for the real time prediction of AISMR. © 2009 Springer-Verlag.

Arias P.A.,University of Texas at Austin | Arias P.A.,University of Antioquia | Fu R.,University of Texas at Austin | Mo K.C.,Climate Prediction Center
Journal of Climate | Year: 2012

This study shows that the North American monsoon system's (NAMS) strength, onset, and retreat over northwestern Mexico exhibit multidecadal variations during the period 1948-2009. Two dry regimes, associated with late onsets, early retreats, and weaker rainfall rates, occurred in 1948-70 and 1991-2005, whereas a strong regime, associated with early onsets, late retreats, and stronger rainfall rates, occurred in 1971-90. A recovery of the monsoon strength was observed after 2005. This multidecadal variation is linked to the sea surface temperature anomalies' (SSTAs) variability, which is a combination of the Atlantic multidecadal oscillation (AMO) and the warming SST trends. These SST modes appear to cause an anomalous cyclonic circulation and enhanced rainfall over the southeastern United States and the Gulf of Mexico, which in turn increases the atmospheric stability over the monsoon region. However, these SST modes cannot fully explain the circulation and rainfall anomalies observed during the early-retreat monsoons. An expansion of the North Atlantic surface high (NASH) in recent decades also contributes to the anomalous circulation associated with the early retreats of the NAMS. A northwestward expansion of the NASH further enhances the anomalous cyclonic circulation and rainfall over the southeastern United States and the Gulf of Mexico. Its associated northwestward shift of the subtropical jets over the western United States enhances subsidence over the NAMS region. The combined effects of the AMO, the warming trends, and the NASH expansion on atmospheric circulation contribute to a stronger and more persistent earlier retreat during the recent dry regime (1991-2005), while the earlier dry regime (1948-70) appears to be only influenced by the positive phase of the AMO. © 2012 American Meteorological Society.

Chen M.,Climate Prediction Center | Wang W.,Climate Prediction Center | Kumar A.,Climate Prediction Center
Journal of Climate | Year: 2010

Using the retrospective forecasts from the National Centers for Environmental Prediction (NCEP) coupled atmosphere-ocean Climate Forecast System (CFS) and the Atmospheric Model Intercomparison Project (AMIP) simulations from its uncoupled atmospheric component, the NCEP Global Forecast System (GFS), the relative roles of atmospheric and land initial conditions and the lower boundary condition of sea surface temperatures (SSTs) for the prediction of monthly-mean temperature are investigated. The analysis focuses on the lead-time dependence of monthly-mean prediction skill and its asymptotic value for longer lead times, which could be attributed the atmospheric response to the slowly varying SST. The results show that the observed atmospheric and land initial conditions improve the skill of monthly-mean prediction in the extratropics but have little influence in the tropics. However, the influence of initial atmospheric and land conditions in the extratropics decays rapidly. For 30-day-lead predictions, the global-mean forecast skill of monthly means is found to reach an asymptotic value that is primarily determined by the SST anomalies. The lead time at which initial conditions lose their influence varies spatially. In addition, the initial atmospheric and land conditions are found to have longer impacts in northern winter and spring than in summer and fall. The relevance of the results for constructing lagged ensemble forecasts is discussed.

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