scholarly journals Seasonal Simulation of Tropospheric Ozone over the Midwestern and Northeastern United States: An Application of a Coupled Regional Climate and Air Quality Modeling System

2007 ◽  
Vol 46 (7) ◽  
pp. 945-960 ◽  
Author(s):  
Ho-Chun Huang ◽  
Xin-Zhong Liang ◽  
Kenneth E. Kunkel ◽  
Michael Caughey ◽  
Allen Williams
Keyword(s):  
United States ◽  
Air Quality ◽  
Tropospheric Ozone ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Future Climate ◽  
Climate Projections ◽  
Northeastern United States ◽  
Ozone Episodes

Abstract The impacts of air pollution on the environment and human health could increase as a result of potential climate change. To assess such possible changes, model simulations of pollutant concentrations need to be performed at climatic (seasonal) rather than episodic (days) time scales, using future climate projections from a general circulation model. Such a modeling system was employed here, consisting of a regional climate model (RCM), an emissions model, and an air quality model. To assess overall model performance with one-way coupling, this system was used to simulate tropospheric ozone concentrations in the midwestern and northeastern United States for summer seasons between 1995 and 2000. The RCM meteorological conditions were driven by the National Centers for Environmental Prediction/Department of Energy global reanalysis (R-2) using the same procedure that integrates future climate model projections. Based on analyses for several urban and rural areas and regional domains, fairly good agreement with observations was found for the diurnal cycle and for several multiday periods of high ozone episodes. Even better agreement occurred between monthly and seasonal mean quantities of observed and model-simulated values. This is consistent with an RCM designed primarily to produce good simulations of monthly and seasonal mean statistics of weather systems.

scholarly journals Impacts of Climate Change on the Water Availability, Seasonality and Extremes in the Upper Indus Basin (UIB)

2020 ◽  
Vol 12 (4) ◽  
pp. 1283 ◽  
Author(s):  
Asim Khan ◽  
Manfred Koch ◽  
Adnan Tahir
Keyword(s):  
General Circulation ◽  
Extreme Values ◽  
Regional Climate ◽  
Total Duration ◽  
Future Climate ◽  
Indus Basin ◽  
Mean Annual Precipitation ◽  
Climate Projections ◽  
Climatic Data ◽  
Upper Indus Basin

Projecting future hydrology for the mountainous, highly glaciated upper Indus basin (UIB) is a challenging task because of uncertainties in future climate projections and issues with the coverage and quality of available reference climatic data and hydrological modelling approaches. This study attempts to address these issues by utilizing the semi-distributed hydrological model “Soil and water assessment tool” (SWAT) with new climate datasets and better spatial and altitudinal representation as well as a wider range of future climate forcing models (general circulation model/regional climate model combinations (GCMs_RCMs) from the “Coordinated Regional Climate Downscaling Experiment-South Asia (CORDEX-SA) project to assess different aspects of future hydrology (mean flows, extremes and seasonal changes). Contour maps for the mean annual flow and actual evapotranspiration as a function of the downscaled projected mean annual precipitation and temperatures are produced and can serve as a “hands-on” forecast tool of future hydrology. The overall results of these future SWAT hydrological projections indicate similar trends of changes in magnitudes, seasonal patterns and extremes of the UIB—stream flows for almost all climate scenarios/models/periods—combinations analyzed. In particular, all but one GCM_RCM model—the one predicting a very high future temperature rise—indicated mean annual flow increases throughout the 21st century, wherefore, interestingly, these are stronger for the middle years (2041–2070) than at its end (2071–2100). The seasonal shifts as well as the extremes follow also similar trends for all climate scenario/model/period combinations, e.g., an earlier future arrival (in May–June instead of July–August) of high flows and increased spring and winter flows, with upper flow extremes (peaks) projected to drastically increase by 50 to >100%, and with significantly decreased annual recurrence intervals, i.e., a tremendously increased future flood hazard for the UIB. The future low flows projections also show more extreme values, with lower-than-nowadays-experienced minimal flows occurring more frequently and with much longer annual total duration.

scholarly journals Projections of mid-century summer air-quality for North America: effects of changes in climate and precursor emissions

2012 ◽  
Vol 12 (12) ◽  
pp. 5367-5390 ◽  
Author(s):  
J. Kelly ◽  
P. A. Makar ◽  
D. A. Plummer
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Air Quality ◽  
North American ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Future Climate ◽  
Climate Simulation ◽  
Ammonia Emissions

Abstract. Ten year simulations of North American current and future air-quality were carried out using a regional air-quality model driven by a regional climate model, in turn driven by a general circulation model. Three separate summer scenarios were performed: a scenario representing the years 1997 to 2006, and two SRES A2 climate scenarios for the years 2041 to 2050. The first future climate scenario makes use of 2002 anthropogenic precursor emissions, and the second applied emissions scaling factors derived from the IPCC Representative Concentration Pathway 6 (RCP 6) scenario to estimate emissions for 2050 from existing 2020 projections. Ten-year averages of ozone and PM2.5 at North American monitoring network stations were used to evaluate the model's current chemical climatology. The model was found to have a similar performance for ozone as when driven by an operational weather forecast model. The PM2.5 predictions had larger negative biases, likely resulting from the absence of rainwater evaporation, and from sub-regional negative biases in the surface temperature fields, in the version of the climate model used here. The differences between the two future climate simulations and the current climate simulation were used to predict the changes to air-quality that might be expected in a future warmer climate, if anthropogenic precursor emissions remain constant at their current levels, versus if the RCP 6 emissions controls were adopted. Metrics of concentration, human health, and ecosystem damage were compared for the simulations. The scenario with future climate and current anthropogenic emissions resulted in worse air-quality than for current conditions – that is, the effect of climate-change alone, all other factors being similar, would be a worsening of air-quality. These effects are spatially inhomogeneous, with the magnitude and sign of the changes varying with region. The scenario with future climate and RCP 6 emissions for 2050 resulted in an improved air-quality, with decreases in key pollutant concentrations, in acute human mortality associated with air-pollution, and in sulphur and ozone deposition to the ecosystem. The positive outcomes of the RCP 6 emissions reductions were found to be of greater magnitude than the negative outcomes of climate change alone. The RCP 6 scenario however resulted in an increase in the deposition of nitrogen, as a result of increased ammonia emissions expected in that scenario, compared to current ammonia emissions levels. The results of the study raise the possibility that simultaneous reductions of greenhouse gases and air pollution precursors may further reduce air pollution levels, with the added benefits of an immediate reduction in the impacts of air pollution on human and ecosystem health. Further scenarios to investigate this possibility are therefore recommended.

scholarly journals Vegetation–climate feedbacks modulate rainfall patterns in Africa under future climate change

2016 ◽  
Vol 7 (3) ◽  
pp. 627-647 ◽  
Author(s):  
Minchao Wu ◽  
Guy Schurgers ◽  
Markku Rummukainen ◽  
Benjamin Smith ◽  
Patrick Samuelsson ◽  
...  
Keyword(s):  
Surface Energy ◽  
General Circulation ◽  
Hydrological Cycle ◽  
Regional Climate ◽  
Circulation Model ◽  
Future Climate ◽  
Tree Cover ◽  
Future Climate Change ◽  
Climate Projections ◽  
Area Index

Abstract. Africa has been undergoing significant changes in climate and vegetation in recent decades, and continued changes may be expected over this century. Vegetation cover and composition impose important influences on the regional climate in Africa. Climate-driven changes in vegetation structure and the distribution of forests versus savannah and grassland may feed back to climate via shifts in the surface energy balance, hydrological cycle and resultant effects on surface pressure and larger-scale atmospheric circulation. We used a regional Earth system model incorporating interactive vegetation–atmosphere coupling to investigate the potential role of vegetation-mediated biophysical feedbacks on climate dynamics in Africa in an RCP8.5-based future climate scenario. The model was applied at high resolution (0.44 × 0.44°) for the CORDEX-Africa domain with boundary conditions from the CanESM2 general circulation model. We found that increased tree cover and leaf-area index (LAI) associated with a CO2 and climate-driven increase in net primary productivity, particularly over subtropical savannah areas, not only imposed important local effect on the regional climate by altering surface energy fluxes but also resulted in remote effects over central Africa by modulating the land–ocean temperature contrast, Atlantic Walker circulation and moisture inflow feeding the central African tropical rainforest region with precipitation. The vegetation-mediated feedbacks were in general negative with respect to temperature, dampening the warming trend simulated in the absence of feedbacks, and positive with respect to precipitation, enhancing rainfall reduction over the rainforest areas. Our results highlight the importance of accounting for vegetation–atmosphere interactions in climate projections for tropical and subtropical Africa.

scholarly journals Quantifying Sources of Uncertainty in Projections of Future Climate*

2014 ◽  
Vol 27 (23) ◽  
pp. 8793-8808 ◽  
Author(s):  
Paul J. Northrop ◽  
Richard E. Chandler
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Internal Variability ◽  
Future Climate ◽  
First Century ◽  
Climate Projections ◽  
Large Contribution ◽  
Sources Of Uncertainty ◽  
Twenty First Century ◽  
Emissions Scenario

Abstract A simple statistical model is used to partition uncertainty from different sources, in projections of future climate from multimodel ensembles. Three major sources of uncertainty are considered: the choice of climate model, the choice of emissions scenario, and the internal variability of the modeled climate system. The relative contributions of these sources are quantified for mid- and late-twenty-first-century climate projections, using data from 23 coupled atmosphere–ocean general circulation models obtained from phase 3 of the Coupled Model Intercomparison Project (CMIP3). Similar investigations have been carried out recently by other authors but within a statistical framework for which the unbalanced nature of the data and the small number (three) of scenarios involved are potentially problematic. Here, a Bayesian analysis is used to overcome these difficulties. Global and regional analyses of surface air temperature and precipitation are performed. It is found that the relative contributions to uncertainty depend on the climate variable considered, as well as the region and time horizon. As expected, the uncertainty due to the choice of emissions scenario becomes more important toward the end of the twenty-first century. However, for midcentury temperature, model internal variability makes a large contribution in high-latitude regions. For midcentury precipitation, model internal variability is even more important and this persists in some regions into the late century. Implications for the design of climate model experiments are discussed.

scholarly journals Regional Climate Model Projections and Uncertainties of U.S. Summer Heat Waves

2010 ◽  
Vol 23 (16) ◽  
pp. 4447-4458 ◽  
Author(s):  
Kenneth E. Kunkel ◽  
Xin-Zhong Liang ◽  
Jinhong Zhu
Keyword(s):  
United States ◽  
Regional Climate Model ◽  
Heat Wave ◽  
General Circulation ◽  
Climate Model ◽  
Heat Waves ◽  
Regional Climate ◽  
General Circulation Models ◽  
Threshold Temperature ◽  
Wave Characteristics

Abstract Regional climate model (RCM) simulations, driven by low and high climate-sensitivity coupled general circulation models (CGCMs) under various future emissions scenarios, were compared to projected changes in heat wave characteristics. The RCM downscaling reduces the CGCM biases in heat wave threshold temperature by a factor of 2, suggesting a higher credibility in the future projections. All of the RCM simulations suggest that there is a high probability of heat waves of unprecedented severity by the end of the twenty-first century if a high emissions path is followed. In particular, the annual 3-day heat wave temperature increases generally by 3°–8°C; the number of heat wave days increases by 30–60 day yr−1 over much of the western and southern United States with slightly smaller increases elsewhere; the variance spectra for intermediate, 3–7 days (prolonged, 7–14 days), temperature extremes increase (decrease) in the central (western) United States. If a lower emissions path is followed, then the outcomes range from quite small changes to substantial increases. In all cases, the mean temperature climatological shift is the dominant change in heat wave characteristics, suggesting that adaptation and acclimatization could reduce effects.

scholarly journals An Analysis of Regional Climate Simulations for Western Australia’s Wine Regions—Model Evaluation and Future Climate Projections

2017 ◽  
Vol 56 (7) ◽  
pp. 2113-2138 ◽  
Author(s):  
Rebecca Firth ◽  
Jatin Kala ◽  
Thomas J. Lyons ◽  
Julia Andrys
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Climate Indices ◽  
Climate Projections ◽  
Model Errors ◽  
Current Climate ◽  
Temperature Indices

AbstractThe Weather Research and Forecasting (WRF) Model is evaluated as a regional climate model for the simulation of climate indices that are relevant to viticulture in Western Australia’s wine regions at a 5-km resolution under current and future climate. WRF is driven with ERA-Interim reanalysis for the current climate and three global climate models (GCMs) for both current and future climate. The focus of the analysis is on a selection of climate indices that are commonly used in climate–viticulture research. Simulations of current climate are evaluated against an observational dataset to quantify model errors over the 1981–2010 period. Changes to the indices under future climate based on the SRES A2 emissions scenario are then assessed through an analysis of future (2030–59) minus present (1970–99) climate. Results show that when WRF is driven with ERA-Interim there is generally good agreement with observations for all of the indices although there is a noticeable negative bias for the simulation of precipitation. The results for the GCM-forced simulations were less consistent. Namely, while the GCM-forced simulations performed reasonably well for the temperature indices, all simulations performed inconsistently for the precipitation index. Climate projections showed significant warming for both of the temperature indices and indicated potential risks to Western Australia’s wine growing regions under future climate, particularly in the north. There was disagreement between simulations with regard to the projections of the precipitation indices and hence greater uncertainty as to how these will be characterized under future climate.

scholarly journals Future Crop Yield Projections Using a Multi-model Set of Regional Climate Models and a Plausible Adaptation Practice in the Southeast United States

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1300
Author(s):  
D. W. Shin ◽  
Steven Cocke ◽  
Guillermo A. Baigorria ◽  
Consuelo C. Romero ◽  
Baek-Min Kim ◽  
...  
Keyword(s):  
United States ◽  
Crop Yield ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Future Climate ◽  
Large Temperature ◽  
Climate Projections ◽  
Southeast United States ◽  
The Future

Since maize, peanut, and cotton are economically valuable crops in the southeast United States, their yield amount changes in a future climate are attention-grabbing statistics demanded by associated stakeholders and policymakers. The Crop System Modeling—Decision Support System for Agrotechnology Transfer (CSM-DSSAT) models of maize, peanut, and cotton are, respectively, driven by the North American Regional Climate Change Assessment Program (NARCCAP) Phase II regional climate models to estimate current (1971–2000) and future (2041–2070) crop yield amounts. In particular, the future weather/climate data are based on the Special Report on Emission Scenarios (SRES) A2 emissions scenario. The NARCCAP realizations show on average that there will be large temperature increases (~2.7 °C) and minor rainfall decreases (~−0.10 mm/day) with pattern shifts in the southeast United States. With these future climate projections, the overall future crop yield amounts appear to be reduced under rainfed conditions. A better estimate of future crop yield amounts might be achievable by utilizing the so-called weighted ensemble method. It is proposed that the reduced crop yield amounts in the future could be mitigated by altering the currently adopted local planting dates without any irrigation support.

scholarly journals Regional Interdependency of Precipitation Indices across Denmark in Two Ensembles of High-Resolution RCMs

2013 ◽  
Vol 26 (20) ◽  
pp. 7912-7928 ◽  
Author(s):  
Maria Antonia Sunyer ◽  
Henrik Madsen ◽  
Dan Rosbjerg ◽  
Karsten Arnbjerg-Nielsen
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
General Circulation Models ◽  
Primary Data ◽  
Climate Projections ◽  
Effective Number ◽  
Precipitation Indices ◽  
Ensembles Project

Abstract Outputs from climate models are the primary data source in climate change impact studies. However, their interpretation is not straightforward. In recent years, several methods have been developed in order to quantify the uncertainty in climate projections. One of the common assumptions in almost all these methods is that the climate models are independent. This study addresses the validity of this assumption for two ensembles of regional climate models (RCMs) from the Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) project based on the land cells covering Denmark. Daily precipitation indices from an ensemble of RCMs driven by the 40-yr ECMWF Re-Analysis (ERA-40) and an ensemble of the same RCMs driven by different general circulation models (GCMs) are analyzed. Two different methods are used to estimate the amount of independent information in the ensembles. These are based on different statistical properties of a measure of climate model error. Additionally, a hierarchical cluster analysis is carried out. Regardless of the method used, the effective number of RCMs is smaller than the total number of RCMs. The estimated effective number of RCMs varies depending on the method and precipitation index considered. The results also show that the main cause of interdependency in the ensemble is the use of the same RCM driven by different GCMs. This study shows that the precipitation outputs from the RCMs in the ENSEMBLES project cannot be considered independent. If the interdependency between RCMs is not taken into account, the uncertainty in the RCM simulations of current regional climate may be underestimated. This will in turn lead to an underestimation of the uncertainty in future precipitation projections.

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