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Abstract
The optimal anomalous sea surface temperature (SST) pattern for forcing North American drought is identified through atmospheric general circulation model integrations in which the response of the Palmer drought severity index (PDSI) is determined for each of 43 prescribed localized SST anomaly “patches” in a regular array over the tropical oceans. The robustness and relevance of the optimal pattern are established through the consistency of results obtained using two different models, and also by the good correspondence of the projection time series of historical tropical SST anomaly fields on the optimal pattern with the time series of the simulated PDSI in separate model integrations with prescribed time-varying observed global SST fields for 1920–2005. It is noteworthy that this optimal drought forcing pattern differs markedly in the Pacific Ocean from the dominant SST pattern associated with El Niño–Southern Oscillation (ENSO), and also shows a large sensitivity of North American drought to Indian and Atlantic Ocean SSTs.
Abstract
The optimal anomalous sea surface temperature (SST) pattern for forcing North American drought is identified through atmospheric general circulation model integrations in which the response of the Palmer drought severity index (PDSI) is determined for each of 43 prescribed localized SST anomaly “patches” in a regular array over the tropical oceans. The robustness and relevance of the optimal pattern are established through the consistency of results obtained using two different models, and also by the good correspondence of the projection time series of historical tropical SST anomaly fields on the optimal pattern with the time series of the simulated PDSI in separate model integrations with prescribed time-varying observed global SST fields for 1920–2005. It is noteworthy that this optimal drought forcing pattern differs markedly in the Pacific Ocean from the dominant SST pattern associated with El Niño–Southern Oscillation (ENSO), and also shows a large sensitivity of North American drought to Indian and Atlantic Ocean SSTs.
Abstract
Paleoclimatic evidence suggests that during the mid-Holocene epoch (about 6000 yr ago) North America and North Africa were significantly drier and wetter, respectively, than at present. Modeling efforts to attribute these differences to changes in orbital parameters and greenhouse gas (GHG) levels have had limited success, especially over North America. In this study, the importance of a possibly cooler tropical Pacific Ocean during the epoch (akin to a permanent La Niña–like perturbation to the present climate) in causing these differences is emphasized. Systematic sets of atmospheric general circulation model experiments, with prescribed sea surface temperatures (SSTs) in the tropical Pacific basin and an interactive mixed layer ocean elsewhere, are performed. Given the inadequacies of current fully coupled climate models in simulating the tropical Pacific climate, this intermediate coupling model configuration is argued to be more suitable for quantifying the contributions of the altered orbital forcing, GHG levels, and tropical Pacific SST conditions to the different mid-Holocene climates. The simulated responses in this configuration are in fact generally more consistent with the available evidence from paleovegetation and sedimentary records.
Coupling to the mixed layer ocean enhances the wind–evaporation–SST feedback over the tropical Atlantic Ocean. The net response to the orbital changes is to shift the North Atlantic intertropical convergence zone (ITCZ) northward, and make North Africa wetter. The response to the reduced GHG levels opposes, but does not eliminate, these changes. The northward-shifted ITCZ also blocks the moisture supply from the Gulf of Mexico into North America. This drying tendency is greatly amplified by the local response to La Niña–like conditions in the tropical Pacific. Consistent with the paleoclimatic evidence, the simulated North American drying is also most pronounced in the growing (spring) season.
Abstract
Paleoclimatic evidence suggests that during the mid-Holocene epoch (about 6000 yr ago) North America and North Africa were significantly drier and wetter, respectively, than at present. Modeling efforts to attribute these differences to changes in orbital parameters and greenhouse gas (GHG) levels have had limited success, especially over North America. In this study, the importance of a possibly cooler tropical Pacific Ocean during the epoch (akin to a permanent La Niña–like perturbation to the present climate) in causing these differences is emphasized. Systematic sets of atmospheric general circulation model experiments, with prescribed sea surface temperatures (SSTs) in the tropical Pacific basin and an interactive mixed layer ocean elsewhere, are performed. Given the inadequacies of current fully coupled climate models in simulating the tropical Pacific climate, this intermediate coupling model configuration is argued to be more suitable for quantifying the contributions of the altered orbital forcing, GHG levels, and tropical Pacific SST conditions to the different mid-Holocene climates. The simulated responses in this configuration are in fact generally more consistent with the available evidence from paleovegetation and sedimentary records.
Coupling to the mixed layer ocean enhances the wind–evaporation–SST feedback over the tropical Atlantic Ocean. The net response to the orbital changes is to shift the North Atlantic intertropical convergence zone (ITCZ) northward, and make North Africa wetter. The response to the reduced GHG levels opposes, but does not eliminate, these changes. The northward-shifted ITCZ also blocks the moisture supply from the Gulf of Mexico into North America. This drying tendency is greatly amplified by the local response to La Niña–like conditions in the tropical Pacific. Consistent with the paleoclimatic evidence, the simulated North American drying is also most pronounced in the growing (spring) season.
Abstract
How Great Plains climate will respond under global warming continues to be a key unresolved question. There has been, for instance, considerable speculation that the Great Plains is embarking upon a period of increasing drought frequency and intensity that will lead to a semipermanent Dust Bowl in the coming decades. This view draws on a single line of inference of how climate change may affect surface water balance based on sensitivity of the Palmer drought severity index (PDSI). A different view foresees a more modest climate change impact on Great Plains surface moisture balances. This draws on direct lines of analysis using land surface models to predict runoff and soil moisture, the results of which do not reveal an ominous fate for the Great Plains. The authors’ study presents a parallel diagnosis of projected changes in drought as inferred from PDSI and soil moisture indicators in order to understand causes for such a disparity and to shed light on the uncertainties. PDSI is shown to be an excellent proxy indicator for Great Plains soil moisture in the twentieth century; however, its suitability breaks down in the twenty-first century, with the PDSI severely overstating surface water imbalances and implied agricultural stresses. Several lines of evidence and physical considerations indicate that simplifying assumptions regarding temperature effects on water balances, especially concerning evapotranspiration in Palmer’s formulation, compromise its suitability as drought indicator in a warming climate. The authors conclude that projections of acute and chronic PDSI decline in the twenty-first century are likely an exaggerated indicator for future Great Plains drought severity.
Abstract
How Great Plains climate will respond under global warming continues to be a key unresolved question. There has been, for instance, considerable speculation that the Great Plains is embarking upon a period of increasing drought frequency and intensity that will lead to a semipermanent Dust Bowl in the coming decades. This view draws on a single line of inference of how climate change may affect surface water balance based on sensitivity of the Palmer drought severity index (PDSI). A different view foresees a more modest climate change impact on Great Plains surface moisture balances. This draws on direct lines of analysis using land surface models to predict runoff and soil moisture, the results of which do not reveal an ominous fate for the Great Plains. The authors’ study presents a parallel diagnosis of projected changes in drought as inferred from PDSI and soil moisture indicators in order to understand causes for such a disparity and to shed light on the uncertainties. PDSI is shown to be an excellent proxy indicator for Great Plains soil moisture in the twentieth century; however, its suitability breaks down in the twenty-first century, with the PDSI severely overstating surface water imbalances and implied agricultural stresses. Several lines of evidence and physical considerations indicate that simplifying assumptions regarding temperature effects on water balances, especially concerning evapotranspiration in Palmer’s formulation, compromise its suitability as drought indicator in a warming climate. The authors conclude that projections of acute and chronic PDSI decline in the twenty-first century are likely an exaggerated indicator for future Great Plains drought severity.
Abstract
Processes in the climate system that can either amplify or dampen the climate response to an external perturbation are referred to as climate feedbacks. Climate sensitivity estimates depend critically on radiative feedbacks associated with water vapor, lapse rate, clouds, snow, and sea ice, and global estimates of these feedbacks differ among general circulation models. By reviewing recent observational, numerical, and theoretical studies, this paper shows that there has been progress since the Third Assessment Report of the Intergovernmental Panel on Climate Change in (i) the understanding of the physical mechanisms involved in these feedbacks, (ii) the interpretation of intermodel differences in global estimates of these feedbacks, and (iii) the development of methodologies of evaluation of these feedbacks (or of some components) using observations. This suggests that continuing developments in climate feedback research will progressively help make it possible to constrain the GCMs’ range of climate feedbacks and climate sensitivity through an ensemble of diagnostics based on physical understanding and observations.
Abstract
Processes in the climate system that can either amplify or dampen the climate response to an external perturbation are referred to as climate feedbacks. Climate sensitivity estimates depend critically on radiative feedbacks associated with water vapor, lapse rate, clouds, snow, and sea ice, and global estimates of these feedbacks differ among general circulation models. By reviewing recent observational, numerical, and theoretical studies, this paper shows that there has been progress since the Third Assessment Report of the Intergovernmental Panel on Climate Change in (i) the understanding of the physical mechanisms involved in these feedbacks, (ii) the interpretation of intermodel differences in global estimates of these feedbacks, and (iii) the development of methodologies of evaluation of these feedbacks (or of some components) using observations. This suggests that continuing developments in climate feedback research will progressively help make it possible to constrain the GCMs’ range of climate feedbacks and climate sensitivity through an ensemble of diagnostics based on physical understanding and observations.
The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low 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 streamf lows 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.
The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low 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 streamf lows 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.
Abstract
The Facility for Weather and Climate Assessments (FACTS) developed at the NOAA Physical Sciences Laboratory is a freely available resource that provides the science community with analysis tools; multimodel, multiforcing climate model ensembles; and observational/reanalysis datasets for addressing a wide class of problems on weather and climate variability and its causes. In this paper, an overview of the datasets, the visualization capabilities, and data dissemination techniques of FACTS is presented. In addition, two examples are given that show the use of the interactive analysis and visualization feature of FACTS to explore questions related to climate variability and trends. Furthermore, we provide examples from published studies that have used data downloaded from FACTS to illustrate the types of research that can be pursued with its unique collection of datasets.
Abstract
The Facility for Weather and Climate Assessments (FACTS) developed at the NOAA Physical Sciences Laboratory is a freely available resource that provides the science community with analysis tools; multimodel, multiforcing climate model ensembles; and observational/reanalysis datasets for addressing a wide class of problems on weather and climate variability and its causes. In this paper, an overview of the datasets, the visualization capabilities, and data dissemination techniques of FACTS is presented. In addition, two examples are given that show the use of the interactive analysis and visualization feature of FACTS to explore questions related to climate variability and trends. Furthermore, we provide examples from published studies that have used data downloaded from FACTS to illustrate the types of research that can be pursued with its unique collection of datasets.
