Advancing Indian monsoon rainfall predictions

Despite great strides made in seasonal climate forecasting using dynamical models, skill in predicting the Indian monsoon is woefully poor. Our analysis of the reasons for failure exposes a flaw in the popular design of dynamical prediction systems. The approach of driving atmospheric models with a projected ocean surface temperature presupposes Indian monsoon variability to be a consequence solely of the atmosphere reacting to the ocean. We demonstrate significant improvements in the skill of Indian monsoon predictions when atmospheric models are coupled to, and fully interactive with the ocean. The additional feedback of the atmosphere onto the ocean is thus deemed critical for harvesting skilful monsoon predictions

Tropical Origins for Recent North Atlantic Climate Change

Evidence is presented that North Atlantic climate change since 1950 is linked to a progressive warming of tropical sea surface temperatures, especially over the Indian and Pacific Oceans. The ocean changes alter the pattern and magnitude of tropical rainfall and atmospheric heating, the atmospheric response to which includes the spatial structure of the North Atlantic Oscillation (NAO). The slow, tropical ocean warming has thus forced a commensurate trend toward one extreme phase of the NAO during the past half-century

Atmosphere and ocean origins of North American droughts

The atmospheric and oceanic causes of North American droughts are examined using observations and ensemble climate simulations. The models indicate that oceanic forcing of annual mean precipitation variability accounts for up to 40% of total variance in northeastern Mexico, the southern Great Plains, and the Gulf Coast states but less than 10% in central and eastern Canada. Observations and models indicate robust tropical Pacific and tropical North Atlantic forcing of annual mean precipitation and soil moisture with the most heavily influenced areas being in southwestern North America and the southern Great Plains. In these regions, individual wet and dry years, droughts, and decadal variations are well reproduced in atmosphere models forced by observed SSTs. Oceanic forcing was important in causing multiyear droughts in the 1950s and at the turn of the twenty-first century, although a similar ocean configuration in the 1970s was not associated with drought owing to an overwhelming influence of internal atmospheric variability. Up to half of the soil moisture deficits during severe droughts in the southeast United States in 2000, Texas in 2011, and the central Great Plains in 2012 were related to SST forcing, although SST forcing was an insignificant factor for northern Great Plains drought in 1988. During the early twenty-first century, natural decadal swings in tropical Pacific and North Atlantic SSTs have contributed to a dry regime for the United States. Long-term changes caused by increasing trace gas concentrations are now contributing to a modest signal of soil moisture depletion, mainly over the U.S. Southwest, thereby prolonging the duration and severity of naturally occurring droughts

Diagnosis of Anomalous Winter Temperatures over the Eastern United States during the 2002/03 El Niño

The eastern United States experienced an unusually cold winter season during the 2002/03 El Niño event. The U.S. seasonal forecasts did not suggest an enhanced likelihood for below-normal temperatures over the eastern United States in that season. A postmortem analysis examining the observed temperatures and the associated forecast is motivated by two fundamental questions: what are these temperature anomalies attributable to, and to what extent were these temperature anomalies predictable? The results suggest that the extreme seasonal temperatures experienced in the eastern United States during December–February (DJF) 2002/03 can be attributed to a combination of several constructively interfering factors that include El Niño conditions in the tropical Pacific, a persistent positive Pacific–North American (PNA) mode, a persistent negative North Atlantic Oscillation (NAO) mode, and persistent snow cover over the northeastern United States. According to the simulations and predictions from several dynamical atmospheric models, which were not rigorously included in the U.S. forecast, much of the observed temperature pattern was potentially predictable

Improving Seasonal Prediction Practices Through Attribution of Climate Variability

The Seasonal Diagnostics Consortium of the Applied Research Centers is engaging in a real-time activity to detect and understand the role of sea surface temperature (SST) anomalies in observed climate anomalies. The activity is aimed to improve practices in seasonal climate forecasting by fully harvesting the accumulated research evidence of the climate's sensitivity to ocean forcing. The approach, in the first phase of the activity, involves performing ensembles of atmospheric general circulation models (AGCMs) at several institutions, using the most recently observed global SST anomalies as prescribed forcings. The runs are routinely updated each month as the latest SST observations become available, adding to the archive of historical simulations spanning the last half-century. The SST-forced signal in the seasonal mean climate is detected through the agreement among ensemble mean anomalies drawn from the simulations of the various AGCMs. The consortium activity also compares the dynamically forced signals with those estimated empirically, based on the observational archive. A comparison of the coordinated simulations with the observed climate anomalies is then made for two principal reasons: 1) to offer an attribution for the ocean's role in the origin of the observed seasonal climate anomalies, and 2) to determine the causes for success or failure of operational seasonal climate predictions, whose tools may be either mainly dynamically or empirically derived. It is expected that routine climate diagnostics and attribution efforts for climate anomalies will help further develop the knowledge base for improving the practice of seasonal climate predictions, and advance understanding of global climate on seasonal to decadal time scales

Northeast Colorado Extreme Rains Interpreted in a Climate Change Context

The probability for an extreme five-day September rainfall event over northeast Colorado, as was observed in early September 2013, has likely decreased due to climate change

Climatology and interannual variability of boreal spring wet season precipitation in the eastern Horn of Africa and implications for its recent decline

The 1981-2014 climatology and variability of the March-May eastern Horn of Africa boreal spring wet season are examined using precipitation, upper- and lower-level winds, low-level specific humidity, and convective available potential energy (CAPE), with the aim of better understanding the establishment of the wet season and the cause of the recent observed decline. At 850 mb, the development of the wet season is characterized by increasing specific humidity and winds that veer from northeasterly in February to southerly in June and advect moisture into the region, in agreement with an earlier study. Equally important, however, is a substantial weakening of the 200-mb climatological easterly winds in March. Likewise, the shutdown of the wet season coincides with the return of strong easterly winds in June. Similar changes are seen in the daily evolution of specific humidity and 200-mb wind when composited relative to the interannual wet season onset and end, with the easterlies decreasing (increasing) several days prior to the start (end) of the wet season. The 1981-2014 decrease in March-May precipitation has also coincided with an increase in 200-mb easterly winds, with no attendant change in specific humidity, leading to the conclusion that, while high values of specific humidity are an important ingredient of the wet season, the recent observed precipitation decline has resulted mostly from a strengthening of the 200-mb easterlies. This change in the easterly winds appears to be related to an increase in convection over the Indonesian region and in the associated outflow from that enhanced heat source

Changes in the Spread of the Variability of the Seasonal Mean Atmospheric States Associated with ENSO

For a fixed sea surface temperature (SST) forcing, the variability of the observed seasonal mean atmospheric states in the extratropical latitudes can be characterized in terms of probability distribution functions (PDFs). Predictability of the seasonal mean anomalies related to interannual variations in the SSTs, therefore, entails understanding the influence of SST forcing on various moments of the probability distribution that characterize the variability of the seasonal means. Such an understanding for changes in the first moment of the PDF for the seasonal means with SSTs is well documented. In this paper the analysis is extended to include also the impact of SST forcing on the second moment of the PDFs. The analysis is primarily based on ensemble atmospheric general circulation model (AGCM) simulations forced with observed SSTs for the period 1950–94. To establish the robustness of the results and to ensure that they are not unduly affected by biases in a particular AGCM, the analysis is based on simulations from four different AGCMs. The analysis of AGCM simulations indicates that over the Pacific–North American region, the impact of interannual variations in SSTs on the spread of the seasonal mean atmospheric states (i.e., the second moment of the PDFs) may be small. This is in contrast to their well-defined impact on the first moment of the PDF for the seasonal mean atmospheric state that is manifested as an anomalous wave train over this region. For seasonal predictions, the results imply that the dominant contribution to seasonal predictability comes from the impact of SSTs on the first moment of the PDF, with the impact of SSTs on the second moment of the PDFs playing a secondary role

Causes and Predictability of the 2012 Great Plains Drought

Central Great Plains precipitation deficits during May–August 2012 were the most severe since at least 1895, eclipsing the Dust Bowl summers of 1934 and 1936. Drought developed suddenly in May, following near-normal precipitation during winter and early spring. Its proximate causes were a reduction in atmospheric moisture transport into the Great Plains from the Gulf of Mexico. Processes that generally provide air mass lift and condensation were mostly absent, including a lack of frontal cyclones in late spring followed by suppressed deep convection in the summer owing to large-scale subsidence and atmospheric stabilization. Seasonal forecasts did not predict the summer 2012 central Great Plains drought development, which therefore arrived without early warning. Climate simulations and empirical analysis suggest that ocean surface temperatures together with changes in greenhouse gases did not induce a substantial reduction in sum mertime precipitation over the central Great Plains during 2012. Yet, diagnosis of the retrospective climate simulations also reveals a regime shift toward warmer and drier summertime Great Plains conditions during the recent decade, most probably due to natural decadal variability. As a consequence, the probability of the severe summer Great Plains drought occurring may have increased in the last decade compared to the 1980s and 1990s, and the so-called tail risk for severe drought may have been heightened in summer 2012. Such an extreme drought event was nonetheless still found to be a rare occurrence within the spread of 2012 climate model simulations. The implications of this study's findings for U.S. seasonal drought forecasting are discussed

Synthesis and Assessment Product

This Climate Change Science Program Synthesis and Assessment Product addresses current capabilities to integrate observations of the climate system into a consistent description of past and current conditions through the method of reanalysis. In addition, the Product assesses present capabilities to attribute causes for climate variations and trends over North America during the reanalysis period, which extends from the mid-twentieth century to the present. This Product reviews the strengths and limitations of current atmospheric reanalysis products. It finds that reanalysis data play a crucial role in helping to identify, describe, and understand atmospheric features associated with weather and climate variability, including high-impact events such as major droughts and floods. Reanalysis data play an important role in assessing the ability of climate models to simulate the average climate and its variations. The data also help in identifying deficiencies in representations of physical processes that produce climate model errors