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

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

Understanding uncertainties in future Colorado River streamflow

Artículo -- Universidad de Costa Rica. Centro de Investigaciones Geofísicas, 2014The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamflow changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamflows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the ~100 years of instrumental record.Universidad de Costa Rica. Centro de Investigaciones GeofísicasLamont-Doherty Earth Observatory of Columbia UniversityUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI

Influence of the ocean surface temperature and sea ice concentration on regional climate changes in Eurasia in recent decades

Numerical experiments with the ECHAM5 atmospheric general circulation model have been performed in order to simulate the influence of changes in the ocean surface temperature (OST) and sea ice concentration (SIC) on climate characteristics in regions of Eurasia. The sensitivity of winter and summer climates to OST and SIC variations in 1998-2006 has been investigated and compared to those in 1968-1976. These two intervals correspond to the maximum and minimum of the Atlantic Long-Period Oscillation (ALO) index. Apart from the experiments on changes in the OST and SIC global fields, the experiments on OST anomalies only in the North Atlantic and SIC anomalies in the Arctic for the specified periods have been analyzed. It is established that temperature variations in Western Europe are explained by OST and SIC variations fairly well, whereas the warmings in Eastern Europe and Western Siberia, according to model experiments, are substantially (by a factor of 2-3) smaller than according to observational data. Winter changes in the temperature regime in continental regions are controlled mainly by atmospheric circulation anomalies. The model, on the whole, reproduces the empirical structure of changes in the winter field of surface pressure, in particular, the pressure decrease in the Caspian region; however, it substantially (approximately by three times) underestimates the range of changes. Summer temperature variations in the model are characterized by a higher statistical significance than winter ones. The analysis of the sensitivity of the climate in Western Europe to SIC variations alone in the Arctic is an important result of the experiments performed. It is established that the SIC decrease and a strong warming over the Barents Sea in the winter period leads to a cooling over vast regions of the northern part of Eurasia and increases the probability of anomalously cold January months by two times and more (for regions in Western Siberia). This effect is caused by the formation of the increased-pressure region with a center over the southern boundary of the Barents Sea during the SIC decrease and an anomalous advection of cold air masses from the northeast. This result indicates that, to estimate the ALO actions (as well as other long-scale climatic variability modes) on the climate of Eurasia, it is basically important to take into account (or correctly reproduce) Arctic sea ice changes in experiments with climatic models

Different atmospheric moisture divergence responses to extreme and moderate El Niños

On seasonal and inter-annual time scales, vertically integrated moisture divergence provides a useful measure of the tropical atmospheric hydrological cycle. It reflects the combined dynamical and thermodynamical effects, and is not subject to the limitations that afflict observations of evaporation minus precipitation. An empirical orthogonal function (EOF) analysis of the tropical Pacific moisture divergence fields calculated from the ERA-Interim reanalysis reveals the dominant effects of the El Niño-Southern Oscillation (ENSO) on inter-annual time scales. Two EOFs are necessary to capture the ENSO signature, and regression relationships between their Principal Components and indices of equatorial Pacific sea surface temperature (SST) demonstrate that the transition from strong La Niña through to extreme El Niño events is not a linear one. The largest deviation from linearity is for the strongest El Niños, and we interpret that this arises at least partly because the EOF analysis cannot easily separate different patterns of responses that are not orthogonal to each other. To overcome the orthogonality constraints, a self-organizing map (SOM) analysis of the same moisture divergence fields was performed. The SOM analysis captures the range of responses to ENSO, including the distinction between the moderate and strong El Niños identified by the EOF analysis. The work demonstrates the potential for the application of SOM to large scale climatic analysis, by virtue of its easier interpretation, relaxation of orthogonality constraints and its versatility for serving as an alternative classification method. Both the EOF and SOM analyses suggest a classification of “moderate” and “extreme” El Niños by their differences in the magnitudes of the hydrological cycle responses, spatial patterns and evolutionary paths. Classification from the moisture divergence point of view shows consistency with results based on other physical variables such as SST

Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability

Systematic climate shifts have been linked to multidecadal variability in observed sea surface temperatures in the North Atlantic Ocean1. These links are extensive, influencing a range of climate processes such as hurricane activity2 and African Sahel3, 4, 5 and Amazonian5 droughts. The variability is distinct from historical global-mean temperature changes and is commonly attributed to natural ocean oscillations6, 7, 8, 9, 10. A number of studies have provided evidence that aerosols can influence long-term changes in sea surface temperatures11, 12, but climate models have so far failed to reproduce these interactions6, 9 and the role of aerosols in decadal variability remains unclear. Here we use a state-of-the-art Earth system climate model to show that aerosol emissions and periods of volcanic activity explain 76 per cent of the simulated multidecadal variance in detrended 1860–2005 North Atlantic sea surface temperatures. After 1950, simulated variability is within observational estimates; our estimates for 1910–1940 capture twice the warming of previous generation models but do not explain the entire observed trend. Other processes, such as ocean circulation, may also have contributed to variability in the early twentieth century. Mechanistically, we find that inclusion of aerosol–cloud microphysical effects, which were included in few previous multimodel ensembles, dominates the magnitude (80 per cent) and the spatial pattern of the total surface aerosol forcing in the North Atlantic. Our findings suggest that anthropogenic aerosol emissions influenced a range of societally important historical climate events such as peaks in hurricane activity and Sahel drought. Decadal-scale model predictions of regional Atlantic climate will probably be improved by incorporating aerosol–cloud microphysical interactions and estimates of future concentrations of aerosols, emissions of which are directly addressable by policy actions

Origin of Variability in Northern Hemisphere Winter Blocking on Interannual to Decadal Time Scales

Variability of mid-latitude blocking in the boreal winter northern hemisphere is investigated for the period 1960/61 to 2001/02 by means of relaxation experiments with the model of the European Center for Medium-Range Weather Forecasts. It is shown that there is pronounced interannual and decadal variability in blocking, especially over the Eurasian continent, consistent with previous studies. The relaxation experiments show that realistic variability in the tropics can account for a significant part of observed interannual blocking variability, but also that about half of the observed variability can only be explained by extratropical tropospheric variability. On the quasi-decadal time scale, extratropical sea surface temperature and sea-ice, in addition to tropical variability, play a more important role. The stratosphere, which has been shown to influence interannual variability of the North Atlantic Oscillation in previous studies, has no significant influence on blocking according to our analysis

Model uncertainties in climate change impacts on Sahel precipitation in ensembles of CMIP5 and CMIP6 simulations

The impact of climate change on Sahel precipitation suffers from large uncertainties and is strongly model-dependent. In this study, we analyse sources of inter-model spread in Sahel precipitation change by decomposing precipitation into its dynamic and thermodynamic terms, using a large set of climate model simulations. Results highlight that model uncertainty is mostly related to the response of the atmospheric circulation to climate change (dynamic changes), while thermodynamic changes are less uncertain among climate models. Uncertainties arise mainly because the models simulate different shifts in atmospheric circulation over West Africa in a warmer climate. We linked the changes in atmospheric circulation to the changes in Sea Surface Temperature, emphasising that the Northern hemispheric temperature gradient is primary to explain uncertainties in Sahel precipitation change. Sources of Sahel precipitation uncertainties are shown to be the same in the new generation of climate models (CMIP6) as in the previous generation of models (CMIP5)