A52A-01 10:24h
Modeling the Impact of Regional Climate Change on Ozone Air Quality Over the Eastern United States
Regional climate change has the potential to influence the concentration and distribution of air pollutants such as ozone through a variety of direct and indirect processes, including the modification of biogenic emissions, the change of chemical reaction rates, changes in mixed-layer heights that affect vertical mixing of pollutants, and modifications of synoptic flow patterns that govern pollutant transport. We present results of a modeling study aimed at simulating such effects of regional climate change on ozone air quality over the northeastern United States. The modeling system used for this study consists of the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the PennState/NCAR MM5 mesoscale meteorological model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); and the Community Multiscale Air Quality (CMAQ) model for simulating air quality. Simulations were performed for five summer seasons each during the 1990s and the 2020s, 2050s and 2080s. Different MM5 model configurations and different greenhouse gas scenarios were used to test the sensitivity of the air quality predictions towards these parameters. Analysis of future-year simulations shows an increase in mean and extreme ozone concentrations as a result of regional climate change under all scenarios, with increases in average summertime daily maximum ozone concentrations ranging from two to eight ppb. However, the magnitude and spatial patterns of ozone increases are sensitive to model configurations in the MM5 regional climate model and the greenhouse gas scenarios. To investigate this dependency, we present a detailed analysis of the relationship between variability and changes in ozone concentrations and those in meteorological variables such as temperature, wind speed, and boundary layer height. Finally, it is shown through a series of sensitivity studies that changes in chemical boundary conditions contribute less to increases in extreme ozone concentrations than changes in U.S. anthropogenic emissions and especially changes in regional climate for the 2050s under the IPCC/SRES A2 greenhouse gas scenario.
A52A-02 10:36h
Downscaling Global Climate Change Scenarios for Air Quality Assessment
Downscaling is particularly important in assessing the potential effects of global climate change on regional air quality because air quality is affected by meteorological processes at small spatial and temporal scales. In this study, a regional climate model based on the Penn State/NCAR Mesoscale Model MM5 was used to downscale the NASA Goddard Institute for Space Studies (GISS) global climate simulations of the current (1995-2005) and future (2045-2055) climate conditions for the continental U.S. Simulation of the future climate followed the IPCC SRES A1B scenario for greenhouse gas and aerosol emissions. The regional simulations were performed at 36 km spatial resolution for the U.S. Model outputs were archived at an hourly interval three-dimensionally for inputs to air quality models. Analysis of the downscaled control and future climate showed significant changes over the western U.S. during summer and fall with a warming of 2-4 degree C and reduced rainfall. Consistent with the warmer and dryer climate, there is an increase in downward solar radiation and boundary layer depth and reduced ventilation that may increase the likelihood of air pollution episodes. In contrast, changes in the Midwest and Southeastern U.S. during summer are less favorable for air pollution events. More analyses are being performed to evaluate the meteorological conditions of the control run that are important for air quality assessment and to examine the change in mean and interannual variability of those conditions.
A52A-03 10:48h
Model Investigations of the Role of Indian Emissions in Climate Variability Over the INDOEX Region
Observations of aerosol properties in the Southern Indian Ocean region during the Indian Ocean Experiment (INDOEX) of 1999 have provided evidence that continental emissions from South Asia may be modifying climate patterns in the region. During the INDOEX intensive period of January-March 1999 the predominantly northeasterly winds associated with the winter monsoon carried continental emissions of anthropogenic aerosols and their precursors to pristine areas in the Southern Indian Ocean. Model applications with METCHEM, a coupled meteorology-chemistry model driven by recently compiled fine-resolution (0.25 deg x 0.25 deg) emissions data over all of India, examine the effects of these emissions on the aerosol radiative feedbacks to climate variables over the region. Preliminary results of aerosol properties and radiative effects are presented and compared with available INDOEX surface and shipboard measurements from the January-March 1999 intensive period.
A52A-04 INVITED 11:00h
Air Pollution Induced Suppression of Orographic Precipitation and Loss of Water Resources in the Western USA
Suppression of orographic precipitation was observed over the California Sierra and over the hills in Israel, as published by Rosenfeld and Givati (J. Appl. Met., 2004). The suppression was detected as a reduction of the orographic enhancement factor downwind of major urban areas during the last century, which occurred along with the urban development and associated emissions. In contrast, stability in the orographic enhancement factor was observed in pristine coastal ranges. Additional analyses of the whole western USA during wintertime show that the reduction in the orographic precipitation extends eastward all the way to the continental divide. The suppressed precipitation over the hills is compensated by enhanced precipitation over the downwind low lands. We propose the following mechanism: Orographic precipitation occurs from relatively short living and shallow clouds, where slowing down the conversion of cloud water to precipitation can actually reduce the total precipitation falling from the clouds. With less precipitation more water vapor remains in the air downstream. Winter clouds over lowland can be induced only by synoptic uplifting, which creates long-living and relatively deep clouds in which aerosols do not play a major role in the precipitation efficiency. The added water vapor therefore would cause similar addition of precipitation. In the bottom line, precipitation is redistributed from the hills, where it contributes to snow pack and runoff, to the semi-desert low lands where it mostly evaporates. This kind of redistribution leads to a net loss of available hydrological water, in spite of area rainfall depth average not decreasing and even somewhat increasing. Model simulations of this effect are being performed, and initial results will be shown, if already available by the time of the presentation.
A52A-05 11:20h
A Reduced Form Model for Assessing Future Climate and Air Quality
We present an easily transferable, low-cost tool for assessing first-order interactions between climate, air quality, and health. This work complements the framework of the Columbia-University-based New York Climate and Health Project (NYCHP), in which linked, dynamical models simulate interactions among climate change, atmospheric chemistry, land use, and public health. While the NYCHP approach serves as a state-of-the-art example for other regional studies of climate and health, it demands extensive computational resources, high levels of expertise, and multi-disciplinary teamwork. The reduced form approach will permit cost-effective analysis of health impacts from climate, while advancing understanding of system uncertainties and the appropriate use of statistical methods. Our reduced form model takes input from the NASA Goddard Institute for Space Studies General Circulation Model (GISS GCM) at 4 x 5 degree resolution [Russell, 1995], parallel to the NYCHP. Past and projected temperatures are downscaled by multiple linear regression on common empirical orthogonal functions, based on the clim.pact downscaling algorithm of Benestad, [2004], parallel to the role of the MM5 dynamical model in the NYCHP. Downscaled temperatures provide input to a series of static box models of ozone photochemistry, e.g. that described in Klonecki [1997], parallel to the role of the CMAQ air quality model in the NYCHP. Because the reduced form structure follows that of the NYCHP, results from two modeling approaches are compared at each step. For example, the statistical and dynamical downscaling approaches exhibit comparable skill and convergence of results, and both techniques consistently produce greater warming than the GCM. References: Benestad, R. E. (2004) The clim.pact Package. http://cran.r-project.org Klonecki, A.A., and H. Levy II. (1997) Tropospheric chemical ozone tendencies in CO-CH4-NOy-H2O systems: Their sensitivity to variations in environmental parameters and their application to a global chemistry transport model study. J. Geophys. Res., 102: D17, 21, 221-21, 237. Russell, G.L., J.R. Miller, and D. Rind. (1995) A coupled atmosphere-ocean model for transient climate change studies. Atmos.-Ocean, 33: 683-730.
A52A-06 11:32h
Elevation Dependence of the Direct Aerosol Radiative Forcing on Spring Snowmelt in the Southern Sierra Nevada
Aerosol radiative forcing plays an important role in determining the energy cycle within the climate system, but its role remains uncertain. The impact of aerosol radiative forcing on spring snowmelt is a particular concern in the western US as changes in the surface insolation can alter the amount and timing of snowmelt that are crucial for projecting warm season water resources. In addition, changes in snowmelt produced by aerosol radiative forcing can significantly affect the energy and hydrological cycles via snow-albedo feedback. We examined the direct aerosol radiative forcing and its impact on snowmelt in the southern Sierra Nevada region during March-May 1998, using a regional climate model that included a state-of-the-art radiation parameterization scheme developed by Fu and Liou (1993) and improved by Gu and Liou (2003) for efficient use in climate models. The southern Sierra-Nevada region is characterized by large elevation change and heavy winter snowfall that are important sources of water supply for California during the dry warm season. Simulation results showed that the magnitude of aerosol radiative forcing on the surface insolation and its impact on snowmelt depended on terrain elevation. For clear sky, the magnitude of the surface insolation change due to the direct aerosol radiative forcing was similar in all elevation ranges. The effect of aerosols on the surface insolation averaged over the 3-month period, however, decreased with increasing terrain elevation as both the frequency and amount of cloud cover increased with increasing terrain elevation. Elevation dependence of the aerosol impacts on snowmelt was related with the low-level air temperature changes associated with terrain elevation changes. The effect of aerosol radiative forcing on snowmelt via the surface-insolation change was largest at elevations higher than 2000 m. We further found that the largest effect of aerosol radiative forcing on snowmelt occurred in a temperature range from -3 to 5 C. Outside this temperature range, lower (higher) temperatures tend to control snowmelt by means of suppressing (enhancing) its growth.
A52A-07 11:44h
A Local Perspective on Climate
We analyze the climatology of a 6 kilometer resolution, eight-year simulation of the atmosphere over the southern third of California. We find that all climatologically-significant quantities exhibit large variations on spatial scales of tens of kilometers. These include the amplitudes of the diurnal and seasonal cycles as well as mean precipitation and its interannual variability. These small-scale variations are comparable in magnitude to those seen on spatial scales of thousands of kilometers in the current generation of climate models and reanalysis products. We also elucidate the local processes maintaining these small-scale variations. Finally, we identify the primary modes of circulation variability in the region. We find three distinct modes, one corresponding to intense offshore flow (so-called "Santa Ana" events), and two corresponding to vacillations of the climatological alongshore flow. Surprisingly, none of these modes exhibits any correlation with any of the well-known large-scale modes of variability thought to influence the climate of the western United States, such as the Pacific/North American teleconnection pattern. Taken together, our results indicate that local processes play at least as large a role as large-scale processes in determining the climate of the region, including its mean state and interannual variability. This, in turn, suggests local processes must be understood and taken into account in assessing not only the impacts of anthropogenic climate change, but also the signatures of climate variability seen in paleo-records.
http://www.atmos.ucla.edu/csrl
A52A-08 11:56h
Regional Climate Model Simulated Timing and Character of Seasonal Rains in South America
Seasonal rainfall prediction, while useful for some planning, does not have the temporal resolution needed for many applications. Information regarding sub-seasonal variations in rainfall are often needed for sectors such as water management and agriculture. In this paper we will present sub-seasonal statistics including rainy season onset/demise, wet/dry days, and wet/dry spells from high resolution model simulations and compare the results with a daily gridded observational dataset and the low resolution driving general circulation model (GCM). These statistics will be computed from an ensemble nested model climatology for South America, which is performed using a regional climate model (RegCM3) driven with lateral boundary conditions from a general circulation model (ECHAM4.5) and reanalyses, and using observed sea surface temperatures (SSTs) for the period 1982-2003. Our discussion will focus on the potential value of the one-way nested approach in providing useful information on sub-seasonal time scales.
A52A-09 12:08h
Experimental Wildfire Threat Forecast
Climate shifts due to El Nino (warmer than normal ocean temperatures in the tropical Pacific Ocean) and La Nina (cooler than normal) are used to predict seasonal temperature and precipitation trends up to 12 months. These climate shifts are strong in the Southeast United States. El Nino brings plentiful rainfall and lower temperatures to Florida, and La Nina is associated with warm and dry winter and spring. Given that temperature and rainfall affects wildfire activity, it follows that the interannual drivers of climate influences wildfire. Studies have shown a strong connection between wildfire activity in Florida and La Nina, with the average number of acres burned more than doubling (Brenner, 1991; Jones, Shriver, and O'Brien, 1999). While this relationship is important and lends a degree of predictability to the activity of future wildfire seasons, human activities such as effective suppression and prescribed burns can play an important role. For this reason, we are forecasting wildfire POTENTIAL rather than burn statistics. This wildfire threat potential uses the Keetch-Byram Drought Index (KBDI). The KBDI is well-suited as a seasonal forecast medium because daily temperature and rainfall responding to changing climate and weather conditions influences KBDI. This index is high during dry warm weather patterns and low during wet cool patterns. The KBDI is widely used in forestry in the Southeast since its development with foresters and firefighters having familiarity with the KBDI and its applications. The Southeast Climate Consortium will also be issuing wildfire risk forecast for Florida and parts of Alabama and Georgia based on ENSO phase and KBDI. Climate information and ENSO predictions are better served by incorporating them with known climate indices that are used in the forestry sector. The KBDI reflects these seasonal shifts. The U.S. Forest Service and state agencies operationally use the KBDI to monitor and predict wildfires, and meteorologists at the Florida Division of Forestry have demonstrated the validity of the KBDI as an indicator of potential wildfire activity. They showed that the deviation from the seasonal norm is more important than absolute KBDI. The wildfire risk forecast will present the probabilities associated with KBDI anomalies.