Climate Change and...
- Climate Variability
- Climate Models
Effects of Climate Change
Ito, A. (2005). Climate-related uncertainties in projections of the twenty-first century terrestrial carbon budget: off-line model experiments using IPCC greenhouse-gas scenarios and AOGCM climate projections. Climate Dynamics 24 (5): 435-448
ABSTRACT: A terrestrial ecosystem model (Sim-CYCLE) was driven by multiple climate projections to investigate uncertainties in predicting the interactions between global environmental change and the terrestrial carbon cycle. Sim-CYCLE has a spatial resolution of 0.5°, and mechanistically evaluates photosynthetic and respiratory CO2 exchange. Six scenarios for atmospheric-CO2 concentrations in the twenty-first century, proposed by the Intergovernmental Panel on Climate Change, were considered. For each scenario, climate projections by a coupled atmosphere–ocean general circulation model (AOGCM) were used to assess the uncertainty due to socio-economic predictions. Under a single CO2 scenario, climate projections with seven AOGCMs were used to investigate the uncertainty stemming from uncertainty in the climate simulations. Increases in global photosynthesis and carbon storage differed considerably among scenarios, ranging from 23 to 37% and from 24 to 81 Pg C, respectively. Among the AOGCM projections, increases ranged from 26 to 33% and from 48 to 289 Pg C, respectively. There were regional heterogeneities in both climatic change and carbon budget response, and different carbon-cycle components often responded differently to a given environmental change. Photosynthetic CO2 fixation was more sensitive to atmospheric CO2 , whereas soil carbon storage was more sensitive to temperature. Consequently, uncertainties in the CO2 scenarios and climatic projections may create additional uncertainties in projecting atmospheric-CO2 concentrations and climates through the interactive feedbacks between the atmosphere and the terrestrial ecosystem.
Morales, P., Hickler, T., Rowell, D. P., Smith, B., Sykes, M. T. (2007). Changes in European ecosystem productivity and carbon balance driven by regional climate model output. Global Change Biology 13 (1): 108-122
ABSTRACT: Climate change resulting from the enhanced greenhouse effect together with the direct effect of increased atmospheric CO2 concentrations on vegetation growth are expected to produce changes in the cycling of carbon in terrestrial ecosystems. Impacts will vary across Europe, and regional-scale studies are needed to resolve this variability. In this study, we used the LPJ-GUESS ecosystem model driven by a suite of regional climate model (RCM) scenarios from the European Union (EU) project PRUDENCE to estimate climate impacts on carbon cycling across Europe. We identified similarities and discrepancies in simulated climate impacts across scenarios, particularly analyzing the uncertainties arising from the range of climate models and emissions scenarios considered. Our results suggest that net primary production (NPP) and heterotrophic respiration (Rh) will generally increase throughout Europe, but with considerable variation between European subregions. The smallest NPP increases, and in some cases decreases, occurred in the Mediterranean, where many ecosystems switched from sinks to sources of carbon by 2100, mainly as a result of deteriorating water balance. Over the period 1991-2100, modeled climate change impacts on the European carbon balance ranged from a sink of 11.6 Gt C to a source of 3.3 Gt C, the average annual sink corresponding with 1.85% of the current EU anthropogenic emissions. Projected changes in carbon balance were more dependent on the choice of the general circulation model (GCM) providing boundary conditions to the RCM than the choice of RCM or the level of anthropogenic greenhouse gases emissions.
Potter, C., Klooster, S., Tan, P., Steinbach, M., Kumar, V., Genovese, V. (2005). Variability in terrestrial carbon sinks over two decades. Part III: South America, Africa, and Asia. Earth Interactions 9: 29
ABSTRACT: Seventeen years (1982 - 98) of net carbon flux predictions for Southern Hemisphere continents have been analyzed, based on a simulation model using satellite observations of monthly vegetation cover. The NASA Carnegie Ames Stanford Approach (CASA) model was driven by vegetation-cover properties derived from the Advanced Very High Resolution Radiometer and radiative transfer algorithms that were developed for the Moderate Resolution Imaging Spectroradiometer ( MODIS). The terrestrial ecosystem flux for atmospheric CO2 for the Amazon region of South America has been predicted between a biosphere source of - 0.17 Pg C per year ( in 1983) and a biosphere sink of + 0.64 Pg C per year (in 1989). The areas of highest variability in net ecosystem production (NEP) fluxes across all of South America were detected in the south-central rain forest areas of the Amazon basin and in southeastern Brazil. Similar levels of variability were recorded across central forested portions of Africa and in the southern horn of East Africa, throughout Indonesia, and in eastern Australia. It is hypothesized that periodic droughts and wildfires associated with four major El Niño events during the 1980s and 1990s have held the net ecosystem carbon sink for atmospheric CO2 in an oscillating pattern of a 4-6-yr cycle, despite observations of increasing net plant carbon fixation over the entire 17-yr time period.
ABSTRACT: Results from an ensemble of climate change experiments with increasing greenhouse gas and aerosols using the Canadian Centre for Climate Modelling and Analysis Coupled Climate Model are presented with a focus on surface quantities over the Rocky Mountains. There is a marked elevation dependency of the simulated surface screen temperature increase over the Rocky Mountains in the winter and spring seasons, with more pronounced changes at higher elevations. The elevation signal is linked to a rise in the snow line in the winter and spring seasons, which amplifies the surface warming via the snow-albedo feedback. Analysis of the winter surface energy budget shows that large changes in the solar component of the radiative input are the direct consequence of surface albedo changes caused by decreasing snow cover.
Although the warming signal is enhanced at higher elevations, a two-way analysis of variance reveals that the elevation effect has no potential for early climate change detection. In the early stages of surface warming the elevation effect is masked by relatively large noise, so that the signal-to-noise ratio over the Rocky Mountains is no larger than elsewhere. Only after significant continental-scale warming does the local Rocky Mountain signal begin to dominate the pattern of climate change over western North America (and presumably also the surrounding ecosystems and hydrological networks).
ABSTRACT: Results are presented from a present-day and a doubled CO2 experiment over the Alpine region with a nested regional climate model. The simulated temperature change signal shows a substantial elevation dependency, mostly during the winter and spring seasons, resulting in more pronounced warming at high elevations than low elevations. This is caused by a depletion of snowpack in doubled CO2 conditions and further enhanced by the snow–albedo feedback. This result is consistent with some observed temperature trends for anomalously warm years over the Alpine region and suggests that high elevation temperature changes could be used as an early detection tool for global warming. Changes in precipitation, as well as other components of the surface energy and water budgets, also show an elevation signal, which may have important implications for impact assessments in high elevation regions.
ABSTRACT: Regional climate models (RCMs) have improved our understanding of the effects of global climate change on specific regions. The need for realistic forcing has led to the use of fully coupled global climate models (GCMs) to produce boundary conditions for RCMs. The advantages of using fully coupled GCM output is that the global-scale interactions of all components of the climate system (ocean, sea ice, land surface, and atmosphere) are considered. This study uses an RCM, driven by a fully coupled GCM, to examine the climate of a region centered over California for the time periods 1980–99 and 2080–99. Statistically significant increases in mean monthly temperatures by up to 7°C are found for the entire state. Large changes in precipitation occur in northern California in February (increase of up to 4 mm day−1 or 30%) and March (decrease of up to 3 mm day−1 or 25%). However, in most months, precipitation changes between the cases were not statistically significant. Statistically significant decreases in snow accumulation of over 100 mm (50%) occur in some months. Temperature increases lead to decreases in snow accumulation that impact the hydrologic budget by shifting spring and summer runoff into the winter months, reinforcing results of other studies that used different models and driving conditions.
ABSTRACT: General Circulation Models (GCMs) suggest that rising concentrations of greenhouse gases will have significant implications for climate at global and regional scales. Less certain is the extent to which meteorological processes at individual sites will be affected. So-called ‘downscaling’ techniques are used to bridge the spatial and temporal resolution gaps between what climate modellers are currently able to provide and what impact assessors require. This paper describes a decision support tool for assessing local climate change impacts using a robust statistical downscaling technique. Statistical DownScaling Model (SDSM) facilitates the rapid development of multiple, low-cost, single-site scenarios of daily surface weather variables under current and future regional climate forcing. Additionally, the software performs ancillary tasks of predictor variable pre-screening, model calibration, basic diagnostic testing, statistical analyses and graphing of climate data. The application of SDSM is demonstrated with respect to the generation of daily temperature and precipitation scenarios for Toronto, Canada by 2040–2069.
E. Sánchez, C. Gallardo, M.A. Gaertner, A. Arribas, M. Castro (2004). Future climate extreme events in the Mediterranean simulated by a regional climate model: a first approach. Global and Planetary Change 44 (1-4): 163-180
ABSTRACT: Within the frame of PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects, EVK2-CT2001-00132), 5th Framework European programme project (2002–2005) European research project, two 30-year time-slice simulations with a regional climate model (PROMES-RCM) nested in the Hadley Centre global model have been performed: present-day climate (1961–1990) and one of the IPCC greenhouse gases emission future scenario (A2 IPCC-SRES) for 2071–2100. Model domain is centered in the Mediterranean basin, considered one of the most sensitive areas regarding to global warming and future climate extreme conditions. This study is based on objective indices to describe extreme climate events of maximum and minimum temperature and precipitation. The statistical frequency and persistence of cold spells, heat waves and intense rain days simulated in the current climate run are compared against the ones resulting from future scenario numerical experiment. Description of extreme processes in both intensity and frequency give a different and complementary overview of extreme events changes in future climate conditions for any of the magnitudes analyzed. In fact, a common feature obtained from the results is the absence of correlation between both magnitudes, as much as for temperatures as for precipitation. Results also point to the usefulness of very high-resolution models (RCM) to study extreme events, due to the great spatial variability obtained in any of the variables studied.
ABSTRACT: We present a review of climate change projections over the Mediterranean region based on the most recent and comprehensive ensembles of global and regional climate change simulations completed as part of international collaborative projects. A robust and consistent picture of climate change over the Mediterranean emerges, consisting of a pronounced decrease in precipitation, especially in the warm season, except for the northern Mediterranean areas (e.g. the Alps) in winter. This drying is due to increased anticyclonic circulation that yields increasingly stable conditions and is associated with a northward shift of the Atlantic storm track. A pronounced warming is also projected, maximum in the summer season. Inter-annual variability is projected to mostly increase especially in summer, which, along with the mean warming, would lead to a greater occurrence of extremely high temperature events. The projections by the global and regional model simulations are generally consistent with each other at the broad scale. However, the precipitation change signal produced by the regional models shows substantial orographically-induced fine scale structure absent in the global models. Overall, these change signals are robust across forcing scenarios and future time periods, with the magnitude of the signal increasing with the intensity of the forcing. The intensity and robustness of the climate change signals produced by a range of global and regional climate models suggest that the Mediterranean might be an especially vulnerable region to global change.
ABSTRACT: This paper describes an approach to computing probabilistic assessments of future climate, using a climate model. It clarifies the nature of probability in this context, and illustrates the kinds of judgements that must be made in order for such a prediction to be consistent with the probability calculus. The climate model is seen as a tool for making probabilistic statements about climate itself, necessarily involving an assessment of the model’s imperfections. A climate event, such as a 2°C increase in global mean temperature, is identified with a region of ‘climate-space’, and the ensemble of model evaluations is used within a numerical integration designed to estimate the probability assigned to that region
Y. Zhang, Y. Xu, W. Dong, L. Cao, M. Sparrow (2006). A future climate scenario of regional changes in extreme climate events over China using the PRECIS climate model. Geophysical Research Letters 33 (L24702): doi:10.1029/2006GL027229
ABSTRACT: Based on the PRECIS climate model system, we simulate the distribution of the present (1961~1990) and future (2071~2100) extreme climate events in China under the IPCC SRES B2 scenario. The results show that for the present case PRECIS simulates well the spatial distribution of extreme climate events when compared with observations. In the future the occurrence of hot events is projected to be more frequent and the growing season will lengthen, while the occurrence of cold events is likely to be much rarer. A warming environment will also give rise to changes in extreme precipitation events. There would be an overall increasing trend in extreme precipitation events over most of China. The southeast coastal zone, the middle and lower reaches of the Yangtze River and North China are projected to experience more extreme precipitation than the present.
M. Flannigan, I. Campbell, M. Wotton, C. Carcaillet, P. Richard, Y. Bergeron (2001). Future fire in Canada's boreal forest: paleoecology results and general circulation model - regional climate model simulations. Canadian Journal of Forest Research 31 (5): 854-864
ABSTRACT: General circulation model simulations suggest the Earth's climate will be 1–3.5°C warmer by AD 2100. This will influence disturbances such as forest fires, which are important to circumpolar boreal forest dynamics and, hence, the global carbon cycle. Many suggest climate warming will cause increased fire activity and area burned. Here, we use the Canadian Forest Fire Weather Index to simulate future forest fire danger, showing the expected increase in most of Canada but with significant regional variability including a decrease in much of eastern Canada. These results are in general agreement with paleoecological data and general circulation model results from the 6000 calendar years BP interval, which was a time of a warmer climate that may be an analogue for a future climate.
P. B. Duffy, R. W. Arritt, J. Coquard, W. Gutowski, J. Han, J. Iorio, J. Kim, L.R. Leung, J. Roads, E. Zeledon (2006). Simulations of present and future climates in the western United States with four nested regional climate models. Journal of Climate 19 (6): 873-895
ABSTRACT: In this paper, the authors analyze simulations of present and future climates in the western United States performed with four regional climate models (RCMs) nested within two global ocean–atmosphere climate models. The primary goal here is to assess the range of regional climate responses to increased greenhouse gases in available RCM simulations. The four RCMs used different geographical domains, different increased greenhouse gas scenarios for future-climate simulations, and (in some cases) different lateral boundary conditions. For simulations of the present climate, RCM results are compared to observations and to results of the GCM that provided lateral boundary conditions to the RCM. For future-climate (increased greenhouse gas) simulations, RCM results are compared to each other and to results of the driving GCMs. When results are spatially averaged over the western United States, it is found that the results of each RCM closely follow those of the driving GCM in the same region in both present and future climates. This is true even though the study area is in some cases a small fraction of the RCM domain. Precipitation responses predicted by the RCMs in many regions are not statistically significant compared to interannual variability. Where the predicted precipitation responses are statistically significant, they are positive. The models agree that near-surface temperatures will increase, but do not agree on the spatial pattern of this increase. The four RCMs produce very different estimates of water content of snow in the present climate, and of the change in this water content in response to increased greenhouse gases.
ABSTRACT: To study the impacts of climate change on water resources in the western U.S., global climate simulations were produced using the National Center for Atmospheric Research/Department of Energy (NCAR/DOE) Parallel Climate Model (PCM). The Penn State/NCAR Mesoscale Model (MM5) was used to downscale the PCM control (20 years) and three future (2040–2060) climate simulations to yield ensemble regional climate simulations at 40 km spatial resolution for the western U.S. This paper describes the regional simulations and focuses on the hydroclimate conditions in the Columbia River Basin (CRB) and Sacramento-San Joaquin River (SSJ) Basin. Results based on global and regional simulations show that by mid-century, the average regional warming of 1 to 2.5 °C strongly affects snowpack in the western U.S. Along coastal mountains, reduction in annual snowpack was about 70% as indicated by the regional simulations. Besides changes in mean temperature, precipitation, and snowpack, cold season extreme daily precipitation increased by 5 to 15 mm/day (15–20%) along the Cascades and the Sierra. The warming resulted in increased rainfall at the expense of reduced snowfall, and reduced snow accumulation (or earlier snowmelt) during the cold season. In the CRB, these changes were accompanied by more frequent rain-on-snow events. Overall, they induced higher likelihood of wintertime flooding and reduced runoff and soil moisture in the summer. Changes in surface water and energy budgets in the CRB and SSJ basin were affected mainly by changes in surface temperature, which were statistically significant at the 0.95 confidence level. Changes in precipitation, while spatially incoherent, were not statistically significant except for the drying trend during summer. Because snow and runoff are highly sensitive to spatial distributions of temperature and precipitation, this study shows that (1) downscaling provides more realistic estimates of hydrologic impacts in mountainous regions such as the western U.S., and (2) despite relatively small changes in temperature and precipitation, changes in snowpack and runoff can be much larger on monthly to seasonal time scales because the effects of temperature and precipitation are integrated over time and space through various surface hydrological and land-atmosphere feedback processes. Although the results reported in this study were derived from an ensemble of regional climate simulations driven by a global climate model that displays low climate sensitivity compared with most other models, climate change was found to significantly affect water resources in the western U.S. by the mid twenty-first century.
N. L. Miller, J. Kim, R. K. Hartman, J. Farrara (1999). Downscaled climate and streamflow study of the southwestern United States. Journal of the American Water Resources Association 35 (6): 1525-1537
ABSTRACT: Downscaling coarse resolution climate data to scales that are useful for impact assessment studies is receiving increased attention. Basin-scale hydrologic processes and other local climate impacts related to water resources such as reservoir management, crop and forest productivity, and ecosystem response require climate information at scales that are much finer than current and future GCM resolutions. The Regional Climate System Model (RCSM) is a dynamic downscaling system that has been used since 1994 for short-term precipitation and streamflow predictions and seasonal hindcast analysis with good skill. During the 1997–1998 winter, experimental seasonal forecasts were made in collaboration with the NOAA Climate Prediction Center and UCLA with promising results. Preliminary studies of a control and 2°CO2 perturbation for the southwestern U.S. have been performed.
ABSTRACT: A distributed data and simulation system for forested watersheds was used to investigate the potential changes in watershed hydrological and ecological processes under hypothesized climate change scenarios. RHESSys (Regional HydroEcological Simulation System) incorporates a spatial representation of nested catchment and lake systems in a GIS, along with a set of process submodels to compute local flux and storage of energy, water, carbon, and nutrients. A hierarchy of potential climate change shifts in weather, forest canopy physiological processes, and forest cover were used to operate RHESSys for comparison with control simulations for present-day conditions. Use of projected temperature and precipitation changes alone led to qualitatively different forecasts of watershed climate change impact when compared to simulations that also incorporated adjustment of canopy physiology to elevated concentrations of atmospheric CO2 . In addition, ecosystem processes may be more resilient to climate change due to the existence of a series of offsetting effects. Annual net effects on specific processes such as watershed outflow and forest productivity may qualitatively vary from year to year rather than showing consistent increases or decreases relative to current conditions. The model results illustrate the significance of incorporating a reasonable description of terrestrial ecosystem processes within the contributing watershed when assessing the impact of climate change.
C. A. Gibson, J. L. Meyer, N. L. Poff, L. E. Hay, A. Georgakakos (2005). Flow regime alterations under changing climate in two river basins: implications for freshwater ecosystems. River Research and Applications 21 (8): 849-864
ABSTRACT: We examined impacts of future climate scenarios on flow regimes and how predicted changes might affect river ecosystems. We examined two case studies: Cle Elum River, Washington, and Chattahoochee-Apalachicola River Basin, Georgia and Florida. These rivers had available downscaled global circulation model (GCM) data and allowed us to analyse the effects of future climate scenarios on rivers with (1) different hydrographs, (2) high future water demands, and (3) a river-floodplain system. We compared observed flow regimes to those predicted under future climate scenarios to describe the extent and type of changes predicted to occur. Daily stream flow under future climate scenarios was created by either statistically downscaling GCMs (Cle Elum) or creating a regression model between climatological parameters predicted from GCMs and stream flow (Chattahoochee-Apalachicola). Flow regimes were examined for changes from current conditions with respect to ecologically relevant features including the magnitude and timing of minimum and maximum flows. The Cle Elum's hydrograph under future climate scenarios showed a dramatic shift in the timing of peak flows and lower low flow of a longer duration. These changes could mean higher summer water temperatures, lower summer dissolved oxygen, and reduced survival of larval fishes. The Chattahoochee-Apalachicola basin is heavily impacted by dams and water withdrawals for human consumption; therefore, we made comparisons between pre-large dam conditions, current conditions, current conditions with future demand, and future climate scenarios with future demand to separate climate change effects and other anthropogenic impacts. Dam construction, future climate, and future demand decreased the flow variability of the river. In addition, minimum flows were lower under future climate scenarios. These changes could decrease the connectivity of the channel and the floodplain, decrease habitat availability, and potentially lower the ability of the river to assimilate wastewater treatment plant effluent. Our study illustrates the types of changes that river ecosystems might experience under future climates.
ABSTRACT: The introduction of complex land surface parameterization schemes into regional climate models (RCMs) has been focused on improving the modeling of land surface feedbacks to the atmosphere. As such the modeling of streamflow was considered a by-product of the water balance and until recently it received relatively little attention. Comparison of four RCMs (RegCM2, MM5/BATS, MM5/SHEELS and MM5/OSU) and a simple hydrology model, Catchment Moisture Deficit–Identification of unit Hydrographs And Component flows from Rainfall, Evaporation and Streamflow data (CMD-IHACRES) demonstrates the improvement in the characteristics of the streamflow prediction, which may be achieved using CMD-IHACRES. The conceptual structure of CMD-IHACRES allows it to be `incorporated' into the RCMs, improving their streamflow predictions, as is demonstrated for the FIFE region of central USA.
ABSTRACT: Spring snowmelt is the most important contribution of many rivers in western North America. If climate changes, this contribution may change. A shift in the timing of springtime snowmelt towards earlier in the year already is observed during 1948–2000 in many western rivers. Streamflow timing changes for the 1995–2099 period are projected using regression relations between observed streamflow-timing responses in each river, measured by the temporal centroid of streamflow (CT) each year, and local temperature (TI) and precipitation (PI) indices. Under 21st century warming trends predicted by the Parallel Climate Model (PCM) under business-as-usual greenhouse-gas emissions, streamflow timing trends across much of western North America suggest even earlier springtime snowmelt than observed to date. Projected CT changes are consistent with observed rates and directions of change during the past five decades, and are strongest in the Pacific Northwest, Sierra Nevada, and Rocky Mountains, where many rivers eventually run 30–40 days earlier. The modest PI changes projected by PCM yield minimal CT changes. The responses of CT to the simultaneous effects of projected TI and PI trends are dominated by the TI changes. Regression-based CT projections agree with those from physically-based simulations of rivers in the Pacific Northwest and Sierra Nevada.
B.H. Hurd, M. Calloway, J. Smith, P. Kirshen (2004). Climatic change and U.S. water resources: from modeled watershed impacts to national estimates. Journal of the American Water Resources Association 40 (1): 129-148
ABSTRACT: Water is potentially one of the most affected resources as climate changes. Though knowledge and understanding has steadily evolved about the nature and extent of many of the physical effects of possible climate change on water resources, much less is known about the economic responses and impacts that may emerge. Methods and results are presented that examine and quantify many of the important economic consequences of possible climate change on U.S. water resources. At the core of the assessment is the simulation of multiple climate change scenarios in economic models of four watersheds. These Water Allocation and Impact Models (Water-AIM) simulate the effects of modeled runoff changes under various climate change scenarios on the spatial and temporal dimensions of water use, supply, and storage and on the magnitude and distribution of economic consequences. One of the key aspects and contributions of this approach is the capability of capturing economic response and adaptation behavior of water users to changes in water scarcity. By reflecting changes in the relative scarcity (and value) of water, users respond by changing their patterns of water use, intertemporal storage in reservoirs, and changes in the pricing of water. The estimates of economic welfare change that emerge from the Water-AIM models are considered lowerbound estimates owing to the conservative nature of the model formulation and key assumptions. The results from the Water-AIM models form the basis for extrapolating impacts to the national level. Differences in the impacts across the regional models are carried through to the national assessment by matching the modeled basins with basins with similar geographical, climatic, and water use characteristics that have not been modeled and by using hydrologic data across all U.S. water resources regions. The results from the national analysis show that impacts are borne to a great extent by nonconsumptive users that depend on river flows, which rise and fall with precipitation, and by agricultural users, primarily in the western United States, that use a large share of available water in relatively low-valued uses. Water used for municipal and industrial purposes is largely spared from reduced availability because of its relatively high marginal value. In some cases water quality.
Pierce, D. W., Barnett, T. P., Santer, B. D., Gleckler, P. J. (2009). Selecting global climate models for regional climate change studies. Proceedings of the National Academy of Sciences 106 (21): 8441-8446
ABSTRACT: Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures.
Salathé, E. P., Jr., Steed, R., Mass, C. F., Zahn, P. H. (2008). A high-resolution climate model for the U.S. Pacific Northwest: mesoscale feedbacks and local responses to climate change. Journal of Climate 21 (21): 5708-5726
ABSTRACT: Simulations of future climate scenarios produced with a high-resolution climate model show markedly different trends in temperature and precipitation over the Pacific Northwest than in the global model in which it is nested, apparently because of mesoscale processes not being resolved at coarse resolution. Present-day (1990–99) and future (2020–29, 2045–54, and 2090–99) conditions are simulated at high resolution (15-km grid spacing) using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) system and forced by ECHAM5 global simulations. Simulations use the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2 emissions scenario, which assumes a rapid increase in greenhouse gas concentrations. The mesoscale simulations produce regional alterations in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land–water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. Warming is significantly amplified through snow–albedo feedback in regions where snow cover is lost. Increased onshore flow in the spring reduces the daytime warming along the coast. Precipitation increases in autumn are amplified over topography because of changes in the large-scale circulation and its interaction with the terrain. The robustness of the modeling results is established through comparisons with the observed and simulated seasonal variability and with statistical downscaling results.