Lisa Cirbus Sloan

Regional Climate Modeling for the Developing World: The ICTP RegCM3 and RegCNET

Regional climate models are important research tools available to scientists around the world, including in economically developing nations (EDNs). The Earth Systems Physics (ESP) group of the Abdus Salam International Centre for Theoretical Physics (ICTP) maintains and distributes a state-of-the-science regional climate model called the ICTP Regional Climate Model version 3 (RegCM3), which is currently being used by a large research community for a diverse range of climate-related studies. The RegCM3 is the central, but not only, tool of the ICTP-maintained Regional Climate Research Network (RegCNET) aimed at creating south–south and north–south scientific interactions on the topic of climate and associated impacts research and modeling. In this paper, RegCNET, RegCM3, and illustrative results from RegCM3 benchmark simulations applied over south Asia, Africa, and South America are presented. It is shown that RegCM3 performs reasonably well over these regions and is therefore useful for climate studies in...

The North American Regional Climate Change Assessment Program: Overview of Phase I Results

The North American Regional Climate Change Assessment Program (NARCCAP) is an international effort designed to investigate the uncertainties in regional-scale projections of future climate and produce highresolution climate change scenarios using multiple regional climate models (RCMs) nested within atmosphere–ocean general circulation models (AOGCMs) forced with the Special Report on Emission Scenarios (SRES) A2 scenario, with a common domain covering the conterminous United States, northern Mexico, and most of Canada. The program also includes an evaluation component (phase I) wherein the participating RCMs, with a grid spacing of 50 km, are nested within 25 years of National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) Reanalysis II. This paper provides an overview of evaluations of the phase I domain-wide simulations focusing on monthly and seasonal temperature and precipitation, as well as more detailed investigation of four subregions. The overall quality of the simulations i...

Heat transport, deep waters, and thermal gradients: Coupled simulation of an Eocene greenhouse climate

For the first time, a coupled general circulation model with interactive and dynamical atmospheric, oceanic, and sea-ice components, is used to simulate an Eocene (∼50 Ma) “greenhouse” climate. We introduce efficient ocean spin-up methods for coupled paleoclimate modeling. Sea surface temperatures (SSTs) and salinities evolve unconstrained, producing the first proxy data-independent estimates for these Eocene climate parameters. Tropical and extratropical model-predicted SSTs are warmer than modern values, by 3 and 5°C, respectively. Salinity-driven deep water formation occurs in the North Atlantic and Tethys. The zonal average overturning circulation is weaker than modern. Eocene ocean heat transport is 0.6 PW less than modern in the Northern Hemisphere and 0.4 PW greater in the Southern Hemisphere. The model-predicted near-modern vertical and meridional Eocene temperature gradients imply that the dominant theory for maintaining low gradients—increased ocean heat transport—is incorrect or incomplete and other mechanisms should be explored.

Regional Changes in Extreme Climatic Events: A Future Climate Scenario

In this study a regional climate model is employed to expand on modeling experiments of future climate change to address issues of 1) the timing and length of the growing season and 2) the frequency and intensity of extreme temperatures and precipitation. The study focuses on California as a climatically complex region that is vulnerable to changes in water supply and delivery. Statistically significant increases in daily minimum and maximum temperatures occur with a doubling of atmospheric carbon dioxide concentration. Increases in daily temperatures lead to increases in prolonged heat waves and length of the growing season. Changes in total and extreme precipitation vary depending upon geographic location.

Climate model sensitivity to atmospheric CO2 levels in the Early–Middle Paleogene

This study examines the sensitivity of the slab ocean version of the National Center for Atmospheric Research Climate System Model with revised Eocene geography, orography, and vegetation to changing carbon dioxide (CO2) levels. We compare model results with temperature proxies from the geologic record for the Early–Middle Paleogene. We ran three modeling experiments with CO2 levels at 500, 1000, and 2000 ppm, and all with atmospheric methane levels of 3.5 ppm. Surface temperatures in the two higher CO2 scenarios are warmer than those of the 500 ppm scenario. The largest warming with increasing CO2 occurred in the high latitudes, particularly in the Northern Hemisphere, during the wintertime. Compared to the 500 ppm case, Arctic wintertime temperatures increased by ∼10°C for the 1000 ppm scenario, and ∼20°C for the 2000 ppm scenario. The 1000 and 2000 ppm scenarios produced mean annual and cold month mean temperatures in mid- and high latitudes that are much more compatible with the climate interpretations from Eocene flora, especially for data from the Southern Hemisphere. Tropical sea surface temperatures (SSTs) in the 2000 ppm scenario, however, are still ∼4°C higher than the warmest temperatures inferred from proxy data. The better match between temperatures in the high CO2 modeling scenario and high latitude climate interpretations is consistent with the idea that the CO2 levels during the Eocene were high, at least 3–4 times the pre-industrial value of 280 ppm, but the discrepancies in the tropics suggest that SST estimates from proxies are too low or that the models lack some tropical cooling mechanism that was important at this time.

Climate change projections of the North American Regional Climate Change Assessment Program (NARCCAP)

We investigate major results of the NARCCAP multiple regional climate model (RCM) experiments driven by multiple global climate models (GCMs) regarding climate change for seasonal temperature and precipitation over North America. We focus on two major questions: How do the RCM simulated climate changes differ from those of the parent GCMs and thus affect our perception of climate change over North America, and how important are the relative contributions of RCMs and GCMs to the uncertainty (variance explained) for different seasons and variables? The RCMs tend to produce stronger climate changes for precipitation: larger increases in the northern part of the domain in winter and greater decreases across a swath of the central part in summer, compared to the four GCMs driving the regional models as well as to the full set of CMIP3 GCM results. We pose some possible process-level mechanisms for the difference in intensity of change, particularly for summer. Detailed process-level studies will be necessary to establish mechanisms and credibility of these results. The GCMs explain more variance for winter temperature and the RCMs for summer temperature. The same is true for precipitation patterns. Thus, we recommend that future RCM-GCM experiments over this region include a balanced number of GCMs and RCMs.

Eocene hyperthermal event offers insight into greenhouse warming

What happens to the Earths climate, environment, and biota when thousands of gigatons of greenhouse gases are rapidly added to the atmosphere? Modern anthropogenic forcing of atmospheric chemistry promises to provide an experiment in such change that has not been matched since the early Paleogene, more than 50 million years ago (Ma),when catastrophic release of carbon to the atmosphere drove abrupt, transient, hyperthermal events. Research on the Paleocene-Eocene Thermal Maximum(PETM)—the best documented of these events, which occurred about 55 Ma—has advanced significantly since its discovery 15 years ago. During the PETM, carbon addition to the oceans and atmosphere was of a magnitude similar to that which is anticipated through the 21st century. This event initiated global warming, biotic extinction and migration, and fundamental changes in the carbon and hydrological cycles that transformed the early Paleogene world.

Climate sensitivity to changes in land surface characteristics

Abstract Using a recently developed global vegetation distribution, topography, and shorelines for the Early Eocene in conjunction with the Genesis version 2.0 climate model, we investigate the influences that these new boundary conditions have on global climate. Global mean climate changes little in response to the subtle changes we made; differences in mean annual and seasonal surface temperatures over northern and southern hemispheric land, respectively, are on the order of 0.5°C. In contrast, and perhaps more importantly, continental scale climate exhibits significant responses. Increased peak elevations and topographic detail result in larger amplitude planetary ∼4 mm/day and decreases by 7–9 mm/day in the proto Himalayan region. Surface temperatures change by up to 18°C as a direct result of elevation modifications. Increased leaf area index (LAI), as a result of altered vegetation distributions, reduces temperatures by up to 6°C. Decreasing the size of the Mississippi embayment decreases inland precipitation by 1–2 mm/day. These climate responses to increased accuracy in boundary conditions indicate that “improved” boundary conditions may play an important role in producing modeled paleoclimates that approach the proxy data more closely.

Probabilistic estimates of future changes in California temperature and precipitation using statistical and dynamical downscaling

Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly of similar magnitude to the projected T changes. In the monthly average, July temperatures shift enough that that the hottest July found in any simulation over the historical period becomes a modestly cool July in the future period. Januarys as cold as any found in the historical period are still found in the 2060s, but the median and maximum monthly average temperatures increase notably. Annual and seasonal P changes are small compared to interannual or intermodel variability. However, the annual change is composed of seasonally varying changes that are themselves much larger, but tend to cancel in the annual mean. Winters show modestly wetter conditions in the North of the state, while spring and autumn show less precipitation. The dynamical downscaling techniques project increasing precipitation in the Southeastern part of the state, which is influenced by the North American monsoon, a feature that is not captured by the statistical downscaling.

Regional climate model simulation of precipitation in central Asia: Mean and interannual variability

We examine how well the National Center for Atmospheric Research (NCAR) regional climate model (RegCM2) simulates the mean and interannual variability of precipitation in a semiarid region to more fully establish the strengths and weaknesses of the model as a tool for studying regional scale climate processes. We compare precipitation observations with RegCM2 output from a 5.5 year long simulation of the climate of central Asia, driven by the European Centre for Medium-Range Weather Forecasts analyses. RegCM2 simulates well the spatial patterns and annual cycles of precipitation observed in climatically different subregions. The magnitude of simulated precipitation is similar to observations except over the driest part of Central Asia where the simulated precipitation is too high. We calculate precipitation anomalies for each month as the difference between the monthly total and the 5 year average for that month, from both observations and RegCM2 output. The magnitude of simulated interannual variability is similar to observations, although there are differences. RegCM2 tends to underpredict (overpredict) the magnitude of variability in the same combinations of subregion and season for which it underpredicts (overpredicts) mean precipitation. RegCM2 closely reproduces precipitation anomalies observed in specific months, except during summer and during winter in the mountains. There is no correlation between model biases in mean precipitation and how well the model reproduces a series of precipitation anomalies. This suggests that the processes controlling the mean and the variability of precipitation differ. Therefore evaluating the ability of a regional climate model to simulate both quantities is a demanding test of model performance.