Jared H. Bowden

Does Nudging Squelch the Extremes in Regional Climate Modeling

AbstractAn important question in regional climate downscaling is whether to constrain (nudge) the interior of the limited-area domain toward the larger-scale driving fields. Prior research has demonstrated that interior nudging can increase the skill of regional climate predictions originating from historical data. However, there is concern that nudging may also inhibit the regional model’s ability to properly develop and simulate mesoscale features, which may reduce the value added from downscaling by altering the representation of local climate extremes. Extreme climate events can result in large economic losses and human casualties, and regional climate downscaling is one method for projecting how climate change scenarios will affect extreme events locally. In this study, the effects of interior nudging are explored on the downscaled simulation of temperature and precipitation extremes. Multidecadal, continuous Weather Research and Forecasting model simulations of the contiguous United States are perfo...

Examining Interior Grid Nudging Techniques Using Two-Way Nesting in the WRF Model for Regional Climate Modeling

AbstractThis study evaluates interior nudging techniques using the Weather Research and Forecasting (WRF) model for regional climate modeling over the conterminous United States (CONUS) using a two-way nested configuration. NCEP–Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis (R-2) data are downscaled to 36 km × 36 km by nudging only at the lateral boundaries, using gridpoint (i.e., analysis) nudging and using spectral nudging. Seven annual simulations are conducted and evaluated for 1988 by comparing 2-m temperature, precipitation, 500-hPa geopotential height, and 850-hPa meridional wind to the 32-km North American Regional Reanalysis (NARR). Using interior nudging reduces the mean biases for those fields throughout the CONUS compared to the simulation without interior nudging. The predictions of 2-m temperature and fields aloft behave similarly when either analysis or spectral nudging is used. For precipitation, however, analysis nudging generates monthly precipitatio...

Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting model

Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.

Co-benefits of global and regional greenhouse gas mitigation for US air quality in 2050

Policies to mitigate greenhouse gas (GHG) emissions will not only slow climate change, but can also have ancillary benefits of improved air quality. Here we examine the co-benefits of both global and regional GHG mitigation on U.S. air quality in 2050 at fine resolution, using dynamical downscaling methods, building on a previous global co-benefits study (West et al., 2013). The co-benefits for U.S. air quality are quantified via two mechanisms: through reductions in co-emitted air pollutants from the same sources, and by slowing climate change and its influence on air quality, following West et al. (2013). Additionally, we separate the total co-benefits into contributions from domestic GHG mitigation versus mitigation in foreign countries. We use the WRF model to dynamically downscale future global climate to the regional scale, the SMOKE program to directly process global anthropogenic emissions into the regional domain, and we provide dynamical boundary conditions from global simulations to the regional CMAQ model. The total co-benefits of global GHG mitigation from the RCP4.5 scenario compared with its reference are estimated to be higher in the eastern U.S. (ranging from 0.6-1.0 μg m-3) than the west (0-0.4 μg m-3) for PM2.5, with an average of 0.47 μg m-3 over U.S.; for O3, the total co-benefits are more uniform at 2-5 ppb with U.S. average of 3.55 ppb. Comparing the two mechanisms of co-benefits, we find that reductions of co-emitted air pollutants have a much greater influence on both PM2.5 (96% of the total co-benefits) and O3 (89% of the total) than the second co-benefits mechanism via slowing climate change, consistent with West et al. (2013). GHG mitigation from foreign countries contributes more to the U.S. O3 reduction (76% of the total) than that from domestic GHG mitigation only (24%), highlighting the importance of global methane reductions and the intercontinental transport of air pollutants. For PM2.5, the benefits of domestic GHG control are greater (74% of total). Since foreign contributions to co-benefits can be substantial, with foreign O3 benefits much larger than those from domestic reductions, previous studies that focus on local or regional co-benefits may greatly underestimate the total co-benefits of global GHG reductions. We conclude that the U.S. can gain significantly greater domestic air quality co-benefits by engaging with other nations to control GHGs.

Assessing the Added Value of Dynamical Downscaling Using the Standardized Precipitation Index

In this study, the Standardized Precipitation Index (SPI) is used to ascertain the added value of dynamical downscaling over the contiguous United States. WRF is used as a regional climate model (RCM) to dynamically downscale reanalysis fields to compare values of SPI over drought timescales that have implications for agriculture and water resources planning. The regional climate generated by WRF has the largest improvement over reanalysis for SPI correlation with observations as the drought timescale increases. This suggests that dynamically downscaled fields may be more reliable than larger-scale fields for water resource applications (e.g., water storage within reservoirs). WRF improves the timing and intensity of moderate to extreme wet and dry periods, even in regions with homogenous terrain. This study also examines changes in SPI from the extreme drought of 1988 and three “drought busting” tropical storms. Each of those events illustrates the importance of using downscaling to resolve the spatial extent of droughts. The analysis of the “drought busting” tropical storms demonstrates that while the impact of these storms on ending prolonged droughts is improved by the RCM relative to the reanalysis, it remains underestimated. These results illustrate the importance and some limitations of using RCMs to project drought.

The Impact of Incongruous Lake Temperatures on Regional Climate Extremes Downscaled from the CMIP5 Archive Using the WRF Model

AbstractThe impact of incongruous lake temperatures is demonstrated using the Weather Research and Forecasting (WRF) Model to downscale global climate fields. Unrealistic lake temperatures prescribed by the default WRF configuration cause obvious biases near the lakes and also affect predicted extremes hundreds of kilometers from the lakes, especially during winter. Using these default temperatures for the Great Lakes in winter creates a thermally induced wave in the modeled monthly average sea level pressure field, which reaches southern Florida. Differences of more than 0.5 K in monthly average daily maximum 2-m temperature occur along that wave during winter. Noteworthy changes to temperature variability, precipitation, and mesoscale circulation also occur when the default method is used for downscaling. Consequently, improperly setting lake temperatures for downscaling could result in misinterpreting changes in regional climate and adversely affect applications reliant on downscaled data, even in area...

The Sensitivity of WRF Downscaled Precipitation in Puerto Rico to Cumulus Parameterization and Interior Grid Nudging

AbstractThe sensitivity of the precipitation over Puerto Rico that is simulated by the Weather Research and Forecasting (WRF) Model is evaluated using multiple combinations of cumulus parameterization (CP) schemes and interior grid nudging. The NCEP–DOE AMIP-II reanalysis (R-2) is downscaled to 2-km horizontal grid spacing both with convective-permitting simulations (CP active only in the middle and outer domains) and with CP schemes active in all domains. The results generally show lower simulated precipitation amounts than are observed, regardless of WRF configuration, but activating the CP schemes in the inner domain improves the annual cycle, intensity, and placement of rainfall relative to the convective-permitting simulations. Furthermore, the use of interior-grid-nudging techniques in the outer domains improves the placement and intensity of rainfall in the inner domain. Incorporating a CP scheme at convective-permitting scales ( 4 km) im...

Cobenefits of global and domestic greenhouse gas emissions for air quality and human health

Abstract Background Reductions in greenhouse gas emissions often reduce emissions of coemitted air pollutants, yielding cobenefits for air quality and human health. Here, we report results of a global cobenefits study—the first to use a global atmospheric model and consistent future scenarios—and results from follow-on studies that downscale those global results to focus on the continental US. Methods We use the RCP4.5 scenario as an aggressive global greenhouse gas mitigation scenario, and compare it with its associated reference case, the difference between these scenarios is uniquely attributable to the global carbon policy. Findings In the global study, we find that global greenhouse gas mitigation avoids roughly 0·5 million air pollution-related deaths per year in 2030, 1·3 million air pollution-related deaths per year in 2050, and 2·2 million air pollution-related deaths per year in 2100. Global average cobenefits are US

Downscaling future climate change projections over Puerto Rico using a non-hydrostatic atmospheric model

50–380 per ton of CO2 reduced, which exceeds previous estimates. These cobenefits also exceed the marginal abatement costs in 2030 and 2050. Cobenefits here are higher than in previous studies because we account for global air pollution transport, and because of projected population, and baseline mortality growth. We then downscale these results in 2050 to the continental USA to project these cobenefits at fine resolution, using the WRF, SMOKE and CMAQ models, and we separate the contributions of domestic and foreign reductions to US cobenefits. We find that for PM2.5, most of the air quality and health cobenefits are from domestic emissions. By contrast, for ozone, most of the cobenefits results from foreign emissions, including global methane reductions. Interpretation These results suggest that the air quality and health cobenefits realised by one country will be much greater if foreign countries also reduce greenhouse gas emissions in a coordinated effort. We also conclude that previous studies that focus on domestic or local cobenefits might significantly underestimate the total cobenefits of global greenhouse gas reductions. Funding US Environmental Protection Agency, the Integrated Assessment Research Program in the US Department of Energy, Office of Science, the National Institute of Environmental Health Sciences, the Portuguese Foundation for Science and Technology, and an EPA STAR Graduate Fellowship.

Future Year Air Quality Change Due to Growth in Aircraft Emissions and Changes in Climate

We present results from 20-year “high-resolution” regional climate model simulations of precipitation change for the sub-tropical island of Puerto Rico. The Japanese Meteorological Agency Non-Hydrostatic Model (NHM) operating at a 2-km grid resolution is nested inside the Regional Spectral Model (RSM) at 10-km grid resolution, which in turn is forced at the lateral boundaries by the Community Climate System Model (CCSM4). At this resolution, the climate change experiment allows for deep convection in model integrations, which is an important consideration for sub-tropical regions in general, and on islands with steep precipitation gradients in particular that strongly influence local ecological processes and the provision of ecosystem services. Projected precipitation change for this region of the Caribbean is simulated for the mid-twenty-first century (2041–2060) under the RCP8.5 climate-forcing scenario relative to the late twentieth century (1986–2005). The results show that by the mid-twenty-first century, there is an overall rainfall reduction over the island for all seasons compared to the recent climate but with diminished mid-summer drought (MSD) in the northwestern parts of the island. Importantly, extreme rainfall events on sub-daily and daily time scales also become slightly less frequent in the projected mid-twenty-first-century climate over most regions of the island.