Species are expected to shift their distributions to higher latitudes, greater elevations, and deeper depths in response to climate change, reflecting an underlying hypothesis that species will move to cooler locations. However, there is significant variability in observed species range shifts and differences in exposure to climate change may explain some of the variability amongst species. But this requires identifying regions that have experienced detectable changes in those aspects of the climate system that species are sensitive to.
To better understand species exposure to climate change, we estimate the time of emergence of climate change for 19 biologically relevant climate variables using observations and initial condition large ensembles from five different climate models. The time of emergence (ToE) is calculated using Signal/Noise (S/N) thresholds. The S/N threshold applied in this study is >=2, but this threshold can be easily modified to represent species that are more or less sensitive to climate change. Preliminary findings from the initial condition large ensembles indicates the strongest emergence for the temperature metrics within the tropical oceanic regions in the absence of upwelling. The earliest emergence over the oceans is found within the western warm pool of the Pacific. Notable places that haven’t emerged for the temperature metrics include both the North Atlantic and Pacific. The ToE of a climate change signal for the temperature metrics over land is spatially complex, which may partially explain the complex observed range shifts for terrestrial species. For instance, multiple initial condition large ensembles indicate a signal has emerge in the most recent decades only for the western and northeastern parts United States.
}, publisher={Copernicus GmbH}, author={Bowden, Jared and Suarez-Gutierrez, Laura and Terando, Adam J. and Rubenstein, Madeleine and Carter, Shawn and Weiskopf, Sarah and Nguyen, Hai Thanh}, year={2022}, month={Mar} } @article{pedruzzi_andreao_baek_hudke_glotfelty_freitas_martins_bowden_pinto_alonso_et al._2022, title={Update of land use/land cover and soil texture for Brazil: Impact on WRF modeling results over Sao Paulo}, volume={268}, ISSN={["1873-2844"]}, DOI={10.1016/j.atmosenv.2021.118760}, abstractNote={Land Use/Land Cover (LULC) and soil texture play a key role in meteorological models because they determine the vegetation and soil proprieties that interfere in the exchange of energy, moisture, and momentum between the land surface and the atmosphere. Additionally, LULC and soil texture are relevant input datasets in meteorological models affecting their results and future applicability as in weather researches and air quality modeling. Brazil has a complex and heterogeneous LU, and it has faced significant LULC changes in the past years. Therefore, this paper aims to update the LULC, using the national product MapBiomas, and soil texture data, by SoilGrids, to replace the default input data in the Weather Research and Forecast (WRF) model for São Paulo, Brazil. Aiming to evaluate the impact of those input data on WRF simulations, five cases were simulated using WRF v4.1.3 with 1 km of grid resolution, and combinations of “Default” and “Updated” input data. Sixty-days simulations from March 15th to May 15th of 2015, covering the transition of wet to dry season, were performed and evaluated with observational data over São Paulo State. The results showed significant differences in the classifications of LULC and soil texture in the entire domain between the default and updated data. The updated data is more realistic and coherent with local characteristics, being more representative, as an example over Santos city area being correctly classified as urban and built-in updated LULC and not water, as in the default. The comparison between the modeled results with observations data has shown a similar behavior for temperature and humidity for the five cases at the monitoring stations grid cells because the LULC changes were between classes with similar land parameters, such as albedo, roughness length, and soils moisture, although the Default classes are not accurate. However, the latent and sensible heat fluxes were ways more sensitive to the LULC/soil texture changes in the WRF model. Additionally, reasonable differences were observed over the entire modeling domain for these two variables. The updated land surface data provoked low temperatures at 9h and 17h UTC, less humidity at 9h UTC, and more humidity at 17h UTC, especially in the north part of the modeling domain, the area which has faced more LULC and soil changes. The PBL height was also affected by the updated data, probably caused by the impact at heat flux over the domain, causing a variation from 30% to 70% over the modeled grid cell, which may have a higher impact on air quality modeling. Thus, it is recommended to update the land surface data for Brazil to avoid misclassification of LULC and soil texture, even if the comparison at monitoring stations has shown similar behavior between the default and updated land surface data. Additionally, updates in the land parameter inside the model are required to represent each LULC/soil class better.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Pedruzzi, Rizzieri and Andreao, Willian Lemker and Baek, Bok Haeng and Hudke, Anderson Paulo and Glotfelty, Timothy William and Freitas, Edmilson Dias and Martins, Jorge Alberto and Bowden, Jared H. and Pinto, Janaina Antonino and Alonso, Marcelo Felix and et al.}, year={2022}, month={Jan} } @article{bowden_terando_misra_wootten_bhardwaj_boyles_gould_collazo_spero_2021, title={High‐resolution dynamically downscaled rainfall and temperature projections for ecological life zones within Puerto Rico and for the U.S. Virgin Islands}, url={https://doi.org/10.1002/joc.6810}, DOI={10.1002/joc.6810}, abstractNote={The Weather Research and Forecasting (WRF) model and a combination of the Regional Spectral Model (RSM) and the Japanese Meteorological Agency Non-Hydrostatic Model (NHM) were used to dynamically downscale selected CMIP5 global climate models to provide 2-km projections with hourly model output for Puerto Rico and the U.S. Virgin Islands. Two 20-year time slices were downscaled for historical (1986-2005) and future (2041-2060) periods following RCP8.5. Projected changes to mean and extreme temperature and precipitation were quantified for Holdridge life zones within Puerto Rico and for the U.S. Virgin Islands. The evaluation reveals a persistent cold bias for all islands in the U.S. Caribbean, a dry bias across Puerto Rico, and a wet bias on the windward side of mountains within the U.S. Virgin Islands. Despite these biases, model simulations show a robust drying pattern for all islands that is generally larger for Puerto Rico (25% annual rainfall reduction for some life zones) than the U.S. Virgin Islands (12% island average). The largest precipitation reductions are found during the more convectively active afternoon and evening hours. Within Puerto Rico, the model uncertainty increases for the wetter life zones, especially for precipitation. Across the life zones, both models project unprecedented maximum and minimum temperatures that may exceed 200 days annually above the historical baseline with only small changes to the frequency of extreme rainfall. By contrast, in the U.S. Virgin Islands, there is no consensus on the location of the largest drying relative to the windward and leeward side of the islands. However, the models project the largest increases in maximum temperature on the southern side of St. Croix and in higher elevations of St. Thomas and St. John.}, journal={International Journal of Climatology}, author={Bowden, Jared H. and Terando, Adam J. and Misra, Vasu and Wootten, Adrienne and Bhardwaj, Amit and Boyles, Ryan and Gould, William and Collazo, Jaime A. and Spero, Tanya L.}, year={2021}, month={Feb} } @article{glotfelty_ramirez-mejia_bowden_ghilardi_west_2021, title={Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)}, volume={14}, ISSN={["1991-9603"]}, url={https://doi.org/10.5194/gmd-14-3215-2021}, DOI={10.5194/gmd-14-3215-2021}, abstractNote={Abstract. Land use and land cover change (LULCC) impacts local and regional climates through various biogeophysical processes. Accurate representation of land surface parameters in land surface models (LSMs) is essential to accurately predict these LULCC-induced climate signals. In this work, we test the applicability of the default Noah, Noah-MP, and Community Land Model (CLM) LSMs in the Weather Research and Forecasting (WRF) model over Sub-Saharan Africa. We find that the default WRF LSMs do not accurately represent surface albedo, leaf area index, and surface roughness in this region due to various flawed assumptions, including the treatment of the MODIS woody savanna land use and land cover (LULC) category as closed shrubland. Consequently, we developed a WRF CLM version with more accurate African land surface parameters (CLM-AF), designed such that it can be used to evaluate the influence of LULCC. We evaluate meteorological performance for the default LSMs and CLM-AF against observational datasets, gridded products, and satellite estimates. Further, we conduct LULCC experiments with each LSM to determine if differences in land surface parameters impact the LULCC-induced climate responses. Despite clear deficiencies in surface parameters, all LSMs reasonably capture the spatial pattern and magnitude of near-surface temperature and precipitation. However, in the LULCC experiments, inaccuracies in the default LSMs result in illogical localized temperature and precipitation changes. Differences in thermal changes between Noah-MP and CLM-AF indicate that the temperature impacts from LULCC are dependent on the sensitivity of evapotranspiration to LULCC in Sub-Saharan Africa. Errors in land surface parameters indicate that the default WRF LSMs considered are not suitable for LULCC experiments in tropical or Southern Hemisphere regions and that proficient meteorological model performance can mask these issues. We find CLM-AF to be suitable for use in Sub-Saharan Africa LULCC studies, but more work is needed by the WRF community to improve its applicability to other tropical and Southern Hemisphere climates.}, number={6}, journal={GEOSCIENTIFIC MODEL DEVELOPMENT}, author={Glotfelty, Timothy and Ramirez-Mejia, Diana and Bowden, Jared and Ghilardi, Adrian and West, J. Jason}, year={2021}, month={Jun}, pages={3215–3249} } @article{jalowska_spero_bowden_2021, title={Projecting changes in extreme rainfall from three tropical cyclones using the design-rainfall approach}, volume={4}, ISSN={["2397-3722"]}, url={https://doi.org/10.1038/s41612-021-00176-9}, DOI={10.1038/s41612-021-00176-9}, abstractNote={Abstract In the past quarter-century, Eastern North Carolina (ENC) experienced several devastating tropical cyclones that led to widespread flooding and damage. Historical climate records reflect an increasing trend in the frequency and intensity of extreme rainfall events across the eastern U.S., which is projected to continue to increase throughout the twenty-first century. Potential changes to extreme rainfall across ENC are explored and quantified for 2025–2100 for three tropical cyclones using an approach based on relative changes in future extreme rainfall frequencies (return periods) from dynamically downscaled projections. Maximum rainfall intensities at ‘2100’ could increase locally by 168%, with widespread regional increases in total rainfall up to 44%. Although these magnitudes exceed the consensus in the literature, the values here are comparable to the most extreme rainfall events observed in the U.S. during the early twenty-first century, which suggests that the intensity of projected future events is already a present-day reality.}, number={1}, journal={NPJ CLIMATE AND ATMOSPHERIC SCIENCE}, author={Jalowska, Anna M. and Spero, Tanya L. and Bowden, Jared H.}, year={2021}, month={Mar} } @misc{nolte_spero_bowden_sarofim_martinich_mallard_2021, title={Regional temperature-ozone relationships across the US under multiple climate and emissions scenarios}, volume={71}, ISSN={["2162-2906"]}, DOI={10.1080/10962247.2021.1970048}, abstractNote={The potential effects of 21st century climate change on ozone (O3) concentrations in the United States are investigated using global climate simulations to drive higher-resolution regional meteorological and chemical transport models. Community Earth System Model (CESM) and Coupled Model version 3 (CM3) simulations of the Representative Concentration Pathway 8.5 scenario are dynamically downscaled using the Weather Research and Forecasting model, and the resulting meteorological fields are used to drive the Community Multiscale Air Quality model. Air quality is modeled for five 11-year periods using both a 2011 air pollutant emission inventory and a future projection accounting for full implementation of promulgated regulatory controls. Across the U.S., CESM projects daily maximum temperatures during summer to increase 1–4°C by 2050 and 2–7°C by 2095, while CM3 projects warming of 2–7°C by 2050 and 4–11°C by 2095. The meteorological changes have geographically varying impacts on O3 concentrations. Using the 2011 emissions dataset, O3 increases 1–5 ppb in the central Great Plains and Midwest by 2050 and more than 10 ppb by 2095, but it remains unchanged or even decreases in the Gulf Coast, Maine, and parts of the Southwest. Using the projected emissions, modeled increases are attenuated while decreases are amplified, indicating that planned air pollution control measures ameliorate the ozone climate penalty. The relationships between changes in maximum temperature and changes in O3 concentrations are examined spatially and quantified to explore the potential for developing an efficient approach for estimating air quality impacts of other future climate scenarios.Implications: The effects of climate change on ozone air quality in the United States are investigated using two global climate model simulations of a high warming scenario for five decadal periods in the 21st century. Warming summer temperatures simulated under both models lead to higher ozone concentrations in some regions, with the magnitude of the change increasing with temperature over the century. The magnitude and spatial extent of the increases are attenuated under a future emissions projection that accounts for regulatory controls. Regional linear regression relationships are developed as a first step toward development of a reduced form model for efficient estimation of the health impacts attributable to changes in air quality resulting from a climate change scenario.}, number={10}, journal={JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION}, author={Nolte, Christopher G. and Spero, Tanya L. and Bowden, Jared H. and Sarofim, Marcus C. and Martinich, Jeremy and Mallard, Megan S.}, year={2021}, month={Oct}, pages={1251–1264} } @article{aircraft landing and takeoff emission impacts on surface o3 and pm2.5 through aerosol direct feedback effects estimated by the coupled wrf-cmaq model_2020, url={http://dx.doi.org/10.1016/j.atmosenv.2020.117859}, DOI={10.1016/j.atmosenv.2020.117859}, abstractNote={Abstract The aerosol direct feedback effects (ADFEs) are neglected in traditional air quality modeling studies (where meteorology is used as input and not affected by the chemistry and aerosol microphysics) for estimating the impacts of aircraft emissions on air quality. In this study, aircraft landing and take-off (LTO) attributable change of O3 and PM2.5 concentrations through ADFEs for the year 2005 within the contiguous United States (CONUS) are quantified by a coupled meteorology-chemistry modeling system: Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ) model. We first quantified the effects of ADFEs of all aerosols within the CONUS (not the effects of aircraft LTO emissions) on surface meteorology and air quality and found that ADFEs changed on average the downward short-wave radiation (SWR), 2-m temperature (T2), planetary boundary layer (PBL) height, O3 and PM2.5 by −7.38 W/m2, −0.47 K, −20.72 m, −0.41 ppb and +0.28 μg/m3 in 2005. We also found a seasonal influence where ADFE-influenced change (decrease) of SWR, T2, PBL, O3 and change (increase) of PM2.5 were higher in summer than in winter. We found that the aircraft LTO emissions’ contribution to domain average surface concentration of O3 and PM2.5 were +0.0065 ppb and +0.0022 μg/m3 respectively when ADFEs are accounted for. The ADFEs decrease aircraft LTO attributable surface O3 and PM2.5 change by 21% and 23% respectively comparing with that without ADFE in 2005. We also found that in both without-and-with ADFE cases, the aircraft LTO emissions increases domain average of O3 from April to October and decreases from November to March showing a strong seasonal pattern. Our modeling study revealed that use of a coupled model with ADFE shows localized changes in air quality by aircraft LTO emissions across the domain which were masked when looking at domain averages for both O3 and PM2.5, and which may be important for accurately quantifying health risk due to air pollution exposures in densely populated areas.}, journal={Atmospheric Environment}, year={2020}, month={Aug} } @article{glotfelty_ramírez-mejía_bowden_ghilardi_west_2020, title={Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)}, volume={8}, url={https://doi.org/10.5194/gmd-2020-193}, DOI={10.5194/gmd-2020-193}, abstractNote={Abstract. Land use and land cover change (LULCC) impacts local and regional climates through various biogeophysical processes. Accurate representation of land surface parameters in land surface models (LSMs) is essential to accurately predict these LULCC-induced climate signals. In this work, we test the applicability of the default Noah, Noah-MP, and CLM LSMs in the Weather Research and Forecasting Model (WRF) over Sub-Saharan Africa. We find that the default WRF LSMs do not accurately represent surface albedo, leaf area index, and surface roughness in this region due to various flawed assumptions, including the treatment of the MODIS woody savanna LULC category as closed shrubland. Consequently, we developed a WRF CLM version with more accurate African land surface parameters (CLM-AF), designed such that it can be used to evaluate the influence of LULCC. We evaluate meteorological performance for the default LSMs and CLM-AF against observational datasets, gridded products, and satellite estimates. Further, we conduct LULCC experiments with each LSM to determine if differences in land surface parameters impact the LULCC-induced climate signals. Despite clear deficiencies in surface parameters, all LSMs reasonably capture the spatial pattern and magnitude of near surface temperature and precipitation. However in the LULCC experiments, inaccuracies in the default LSMs result in illogical localized temperature and precipitation climate signals. Differences in thermal climate signals between Noah-MP and CLM-AF indicate that the temperature impacts from LULCC are dependent on the sensitivity of evapotranspiration to LULCC in Sub-Saharan Africa. Errors in land surface parameters indicate that the default WRF LSMs considered are not suitable for LULCC experiments in tropical or Southern Hemisphere regions, and that proficient meteorological model performance can mask these issues. We find CLM-AF to be suitable for use in Sub-Saharan Africa LULCC studies, but more work is needed by the WRF community to improve its applicability to other tropical and Southern Hemisphere climates.}, publisher={Copernicus GmbH}, author={Glotfelty, Timothy and Ramírez-Mejía, Diana and Bowden, Jared and Ghilardi, Adrián and West, J. Jason}, year={2020}, month={Aug} } @article{glotfelty_ramírez-mejía_bowden_ghilardi_west_2020, title={Supplementary material to "Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)"}, volume={8}, url={https://doi.org/10.5194/gmd-2020-193-supplement}, DOI={10.5194/gmd-2020-193-supplement}, publisher={Copernicus GmbH}, author={Glotfelty, Timothy and Ramírez-Mejía, Diana and Bowden, Jared and Ghilardi, Adrián and West, J. Jason}, year={2020}, month={Aug} } @article{perspective: developing flow policies to balance the water needs of humans and wetlands requires a landscape scale approach inclusive of future scenarios and multiple timescales_2019, url={http://dx.doi.org/10.1007/s13157-019-01184-5}, DOI={10.1007/s13157-019-01184-5}, journal={Wetlands}, year={2019}, month={Jul} } @article{a maieutic exploration of nudging strategies for regional climate applications using the wrf model_2018, url={http://dx.doi.org/10.1175/jamc-d-17-0360.1}, DOI={10.1175/jamc-d-17-0360.1}, abstractNote={Abstract The use of nudging in the Weather Research and Forecasting (WRF) Model to constrain regional climate downscaling simulations is gaining in popularity because it can reduce error and improve consistency with the driving data. While some attention has been paid to whether nudging is beneficial for downscaling, very little research has been performed to determine best practices. In fact, many published papers use the default nudging configuration (which was designed for numerical weather prediction), follow practices used by colleagues, or adapt methods developed for other regional climate models. Here, a suite of 45 three-year simulations is conducted with WRF over the continental United States to systematically and comprehensively examine a variety of nudging strategies. The simulations here use a longer test period than did previously published works to better evaluate the robustness of each strategy through all four seasons, through multiple years, and across nine regions of the United States. The analysis focuses on the evaluation of 2-m temperature and precipitation, which are two of the most commonly required downscaled output fields for air quality, health, and ecosystems applications. Several specific recommendations are provided to effectively use nudging in WRF for regional climate applications. In particular, spectral nudging is preferred over analysis nudging. Spectral nudging performs best in WRF when it is used toward wind above the planetary boundary layer (through the stratosphere) and temperature and moisture only within the free troposphere. Furthermore, the nudging toward moisture is very sensitive to the nudging coefficient, and the default nudging coefficient in WRF is too high to be used effectively for moisture.}, journal={Journal of Applied Meteorology and Climatology}, year={2018}, month={Aug} } @book{díaz_gould_álvarez-berríos_aponte-gonzalez_archibald_bowden_carrubba_crespo_fain_gonzález_et al._2018, title={Chapter 20 : US Caribbean. Impacts, Risks, and Adaptation in the United States: The Fourth National Climate Assessment, Volume II}, url={http://dx.doi.org/10.7930/nca4.2018.ch20}, DOI={10.7930/nca4.2018.ch20}, journal={[]}, institution={U.S. Global Change Research Program}, author={Díaz, Ernesto L. and Gould, William A. and Álvarez-Berríos, Nora and Aponte-Gonzalez, Felix and Archibald, Wayne and Bowden, Jared H. and Carrubba, Lisamarie and Crespo, Wanda and Fain, Stephen J. and González, Grizelle and et al.}, year={2018} } @article{bhardwaj_misra_mishra_wootten_boyles_bowden_terando_2018, title={Downscaling future climate change projections over Puerto Rico using a non-hydrostatic atmospheric model}, volume={147}, ISSN={["1573-1480"]}, url={http://dx.doi.org/10.1007/s10584-017-2130-x}, DOI={10.1007/s10584-017-2130-x}, number={1-2}, journal={CLIMATIC CHANGE}, author={Bhardwaj, Amit and Misra, Vasubandhu and Mishra, Akhilesh and Wootten, Adrienne and Boyles, Ryan and Bowden, J. H. and Terando, Adam J.}, year={2018}, month={Mar}, pages={133–147} } @article{nolte_spero_bowden_mallard_dolwick_2018, title={Supplementary material to "The potential effects of climate change on air quality across the conterminous U.S. at 2030 under three Representative Concentration Pathways (RCPs)"}, volume={6}, url={https://doi.org/10.5194/acp-2018-510-supplement}, DOI={10.5194/acp-2018-510-supplement}, publisher={Copernicus GmbH}, author={Nolte, Christopher G. and Spero, Tanya L. and Bowden, Jared H. and Mallard, Megan S. and Dolwick, Patrick D.}, year={2018}, month={Jun} } @article{nolte_spero_bowden_mallard_dolwick_2018, title={The potential effects of climate change on air quality across the conterminous U.S. at 2030 under three Representative Concentration Pathways (RCPs)}, volume={6}, url={https://doi.org/10.5194/acp-2018-510}, DOI={10.5194/acp-2018-510}, abstractNote={Abstract. The potential impacts of climate change on regional ozone (O3) and fine particulate (PM2.5) air quality in the United States are investigated by downscaling Community Earth System Model (CESM) global climate simulations with the Weather Research and Forecasting (WRF) model, then using the downscaled meteorological fields with the Community Multiscale Air Quality (CMAQ) model. Regional climate and air quality change between 2000 and 2030 under three Representative Concentration Pathways (RCPs) is simulated using 11-year time slices from CESM. The regional climate fields represent historical daily maximum and daily minimum temperatures well, with mean biases less than 2 K for most regions of the U.S. and most seasons of the year and good representation of the variability. Precipitation in the central and eastern U.S. is well simulated for the historical period, with seasonal and annual biases generally less than 25 %, and positive biases in the western U.S. throughout the year and in part of the eastern U.S. during summer. Maximum daily 8-h ozone (MDA8 O3) is projected to increase during summer and autumn in the central and eastern U.S. The increase in summer mean MDA8 O3 is largest under RCP8.5, exceeding 4 ppb in some locations, with smaller seasonal mean increases of up to 2 ppb simulated during autumn and changes during spring generally less than 1 ppb. Increases are magnified at the upper end of the O3 distribution, particularly where projected increases in temperature are greater. Annual average PM2.5 concentration changes range from −1.0 to 1.0 μg m−3. Organic PM2.5 concentrations increase during summer and autumn due to increased biogenic emissions. Decreases in aerosol nitrate occur during winter, accompanied by lesser decreases in ammonium and sulfate, due to warmer temperatures causing increased partitioning to the gas phase. Among meteorological factors examined to account for modeled changes in pollution, temperature and isoprene emissions are found to have the largest changes and the greatest impact on O3 concentrations.}, publisher={Copernicus GmbH}, author={Nolte, Christopher G. and Spero, Tanya L. and Bowden, Jared H. and Mallard, Megan S. and Dolwick, Patrick D.}, year={2018}, month={Jun} } @article{nolte_spero_bowden_mallard_dolwick_2018, title={The potential effects of climate change on air quality across the conterminous US at 2030 under three Representative Concentration Pathways}, volume={18}, ISSN={["1680-7324"]}, url={http://dx.doi.org/10.5194/acp-18-15471-2018}, DOI={10.5194/acp-18-15471-2018}, abstractNote={Abstract. The potential impacts of climate change on regional ozone (O3) and fine particulate (PM2.5) air quality in the United States (US) are investigated by linking global climate simulations with regional-scale meteorological and chemical transport models. Regional climate at 2000 and at 2030 under three Representative Concentration Pathways (RCPs) is simulated by using the Weather Research and Forecasting (WRF) model to downscale 11-year time slices from the Community Earth System Model (CESM). The downscaled meteorology is then used with the Community Multiscale Air Quality (CMAQ) model to simulate air quality during each of these 11-year periods. The analysis isolates the future air quality differences arising from climate-driven changes in meteorological parameters and specific natural emissions sources that are strongly influenced by meteorology. Other factors that will affect future air quality, such as anthropogenic air pollutant emissions and chemical boundary conditions, are unchanged across the simulations. The regional climate fields represent historical daily maximum and daily minimum temperatures well, with mean biases of less than 2 K for most regions of the US and most seasons of the year and good representation of variability. Precipitation in the central and eastern US is well simulated for the historical period, with seasonal and annual biases generally less than 25 %, with positive biases exceeding 25 % in the western US throughout the year and in part of the eastern US during summer. Maximum daily 8 h ozone (MDA8 O3) is projected to increase during summer and autumn in the central and eastern US. The increase in summer mean MDA8 O3 is largest under RCP8.5, exceeding 4 ppb in some locations, with smaller seasonal mean increases of up to 2 ppb simulated during autumn and changes during spring generally less than 1 ppb. Increases are magnified at the upper end of the O3 distribution, particularly where projected increases in temperature are greater. Annual average PM2.5 concentration changes range from −1.0 to 1.0 µg m−3. Organic PM2.5 concentrations increase during summer and autumn due to increased biogenic emissions. Aerosol nitrate decreases during winter, accompanied by lesser decreases in ammonium and sulfate, due to warmer temperatures causing increased partitioning to the gas phase. Among meteorological factors examined to account for modeled changes in pollution, temperature and isoprene emissions are found to have the largest changes and the greatest impact on O3 concentrations.}, number={20}, journal={ATMOSPHERIC CHEMISTRY AND PHYSICS}, publisher={Copernicus GmbH}, author={Nolte, Christopher G. and Spero, Tanya L. and Bowden, Jared H. and Mallard, Megan S. and Dolwick, Patrick D.}, year={2018}, month={Oct}, pages={15471–15489} } @article{zhang_smith_bowden_adelman_west_2017, title={Co-benefits of global, domestic, and sectoral greenhouse gas mitigation for US air quality and human health in 2050}, volume={12}, ISSN={["1748-9326"]}, url={http://dx.doi.org/10.1088/1748-9326/aa8f76}, DOI={10.1088/1748-9326/aa8f76}, abstractNote={Reductions in greenhouse gas (GHG) emissions can bring ancillary benefits of improved air quality and reduced premature mortality, in addition to slowing climate change. Here we study the co-benefits of global and domestic GHG mitigation on US air quality and human health in 2050 at fine resolution using dynamical downscaling of meteorology and air quality from global simulations to the continental US, and quantify for the first time the co-benefits from foreign GHG mitigation. Relative to the reference scenario from which Representative Concentration Pathway 4.5 (RCP4.5) was created, global GHG reductions in RCP4.5 avoid 16 000 PM2.5-related all-cause deaths yr−1 (90% confidence interval, 11 700–20 300), and 8000 (3600–12 400) O3-related respiratory deaths yr−1 in the US in 2050. Foreign GHG mitigation avoids 15% and 62% of PM2.5-and O3-related total avoided deaths, highlighting the importance of foreign mitigation for US health. GHG mitigation in the US residential sector brings the largest co-benefits for PM2.5-related deaths (21% of total domestic co-benefits), and industry for O3 (17%). Monetized benefits for avoided deaths from ozone and PM2.5 are $137 ($87–$187) per ton CO2 at high valuation and $45 ($29–62) at low valuation, of which 31% are from foreign GHG reductions. These benefits likely exceed the marginal cost of GHG reductions in 2050. The US gains significantly greater air quality and health co-benefits when its GHG emission reductions are concurrent with reductions in other nations. Similarly, previous studies estimating co-benefits locally or regionally may greatly underestimate the full co-benefits of coordinated global actions.}, number={11}, journal={ENVIRONMENTAL RESEARCH LETTERS}, author={Zhang, Yuqiang and Smith, Steven J. and Bowden, Jared H. and Adelman, Zachariah and West, J. Jason}, year={2017}, month={Nov} } @article{co-benefits of global and regional greenhouse gas mitigation for us air quality in 2050_2016, url={http://dx.doi.org/10.5194/acp-16-9533-2016}, DOI={10.5194/acp-16-9533-2016}, abstractNote={Abstract. 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 for US 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 US 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 vs. mitigation in foreign countries. We use the Weather Research and Forecasting (WRF) model to dynamically downscale future global climate to the regional scale and the Sparse Matrix Operator Kernel Emissions (SMOKE) program to directly process global anthropogenic emissions to the regional domain, and we provide dynamical boundary conditions from global simulations to the regional Community Multi-scale Air Quality (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 US (ranging from 0.6 to 1.0 µg m−3) than the west (0–0.4 µg m−3) for fine particulate matter (PM2.5), with an average of 0.47 µg m−3 over the US; for O3, the total co-benefits are more uniform at 2–5 ppb, with a US average of 3.55 ppb. Comparing the two mechanisms of co-benefits, we find that reductions in 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 US 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 US can gain significantly greater domestic air quality co-benefits by engaging with other nations to control GHGs.}, journal={Atmospheric Chemistry and Physics}, year={2016}, month={Aug} } @article{the impact of incongruous lake temperatures on regional climate extremes downscaled from the cmip5 archive using the wrf model_2016, url={http://dx.doi.org/10.1175/jcli-d-15-0233.1}, DOI={10.1175/jcli-d-15-0233.1}, abstractNote={Abstract The 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 areas remote from the lakes.}, journal={Journal of Climate}, year={2016}, month={Jan} } @article{wootten_bowden_boyles_terando_2016, title={The Sensitivity of WRF Downscaled Precipitation in Puerto Rico to Cumulus Parameterization and Interior Grid Nudging}, volume={55}, ISSN={["1558-8432"]}, url={http://dx.doi.org/10.1175/jamc-d-16-0121.1}, DOI={10.1175/jamc-d-16-0121.1}, abstractNote={Abstract The 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) and grid nudging at non-convective-permitting scales (>4 km) improves the island average correlation of precipitation by 0.05–0.2 and reduces the island average RMSE by up to 40 mm on average over relying on the explicit microphysics at convective-permitting scales with grid nudging. Projected changes in summer precipitation between 2040–42 and 1985–87 using WRF to downscale CCSM4 range from a 2.6-mm average increase to an 81.9-mm average decrease, depending on the choice of CP scheme. The differences are only associated with differences between WRF configurations, which indicates the importance of CP scheme for projected precipitation change as well as historical accuracy.}, number={10}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={Wootten, A. and Bowden, J. H. and Boyles, R. and Terando, A.}, year={2016}, month={Oct}, pages={2263–2281} } @article{technical challenges and solutions in representing lakes when using wrf in downscaling applications_2015, url={http://dx.doi.org/10.5194/gmd-8-1085-2015}, DOI={10.5194/gmd-8-1085-2015}, abstractNote={Abstract. The Weather Research and Forecasting (WRF) model is commonly used to make high-resolution future projections of regional climate by downscaling global climate model (GCM) outputs. Because the GCM fields are typically at a much coarser spatial resolution than the target regional downscaled fields, lakes are often poorly resolved in the driving global fields, if they are resolved at all. In such an application, using WRF's default interpolation methods can result in unrealistic lake temperatures and ice cover at inland water points. Prior studies have shown that lake temperatures and ice cover impact the simulation of other surface variables, such as air temperatures and precipitation, two fields that are often used in regional climate applications to understand the impacts of climate change on human health and the environment. Here, alternative methods for setting lake surface variables in WRF for downscaling simulations are presented and contrasted.}, journal={Geoscientific Model Development}, year={2015}, month={Apr} } @article{improving the representation of clouds, radiation, and precipitation using spectral nudging in the weather research and forecasting model_2014, url={http://dx.doi.org/10.1002/2014jd022173}, DOI={10.1002/2014jd022173}, abstractNote={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.}, journal={Journal of Geophysical Research: Atmospheres}, year={2014}, month={Oct} } @article{regional climate variations and change for terrestrial ecosystems workshop review_2014, url={http://dx.doi.org/10.1890/0012-9623-95.1.96}, DOI={10.1890/0012-9623-95.1.96}, abstractNote={North Carolina State University, the University of North Carolina at Chapel Hill, and the U.S. Environmental Protection Agency, in partnership with the U.S. Department of the Interior Southeast Climate Science Center (SECSC), hosted the Regional Climate Variations and Change for Terrestrial Ecosystems Workshop. The workshop was held at North Carolina State University in Raleigh on 16–17 May 2013. The workshop assembled ~40 climate and ecosystem scientists to discuss challenges and uncertainties of understanding the interactions of climate and ecosystems across the Carolinas. This multidisciplinary effort sought to bridge the knowledge gap between climate and ecosystems scientists. Another objective of this workshop was to identify climate-related variables that can be used to evaluate projections of climate change for the ecology community in the Carolinas. This workshop was the first in the Carolinas to engage both disciplines to discuss the needs of the ecology community with regard to regional projections of climate change. The workshop facilitated a discussion of the needs of ecologists from the regional projections of climate change, and the abilities and limitations of these projections, with guidance for appropriate use of projection information. High-level scientific presentations were given from the two disciplines to create a foundation for discussion. Climate presentations focused on data needs for ecosystem scientists and included talks on global climate modeling, dynamical and statistical downscaling, and synthesizing currently available climate change projections. The open discussion on climate model data sets provided expert guidance on using climate change projections for ecosystems applications. The ecologists' presentations focused on ecosystems needs and challenges, including different ecosystems modeling techniques, uncertainties associated with ecosystem modeling, and examples of climate adaptation practices for ecosystem decisions with respect to climate change. The final discussion addressed the general needs of ecologists with regard to climate information, followed by the climate sensitivities that are drivers for ecological applications in the Southeast. During the discussion, ecologists identified that extreme weather events and potential changes to the spatial and temporal distribution of those events are important for ecosystems. The extremes mentioned most often by the group included temperature extremes, rainfall extremes, and storm frequency. Ecologists also identified that the downscaling does not provide the resolution needed for many applications, and interpolation is typically used to supplement downscaled data. For instance, topoclimatic models are applied to increase the resolution of downscaled climate change data sets. However, climate scientists stress that these techniques are not appropriate for extremes or spatially discontinuous variables such as precipitation. More solicitations on collaborative research between ecosystems scientists and climate modelers on discrete decision-based projects are encouraged. More documentation and guidance from the climate science community regarding: Appropriate use of downscaled climate change data sets, including strengths and weaknesses Error and uncertainty propagation in climate modeling Integrating climate data with land use change information. Further engagement is encouraged between the ecologists, hydrologists, biologists, managers, and climate scientists through similar workshops held at least annually. It was acknowledged that some applications cannot use a small-project, decision-based approach; rather they require immediate action to integrate climate change information. In those instances, decision makers rely on the best available data for decisions, which further emphasizes need to document the strengths and weaknesses of climate data and provide expert guidance. As recommended, follow-on workshops will provide updates on the states of the scientific fields alongside discussions of priority needs. An in-depth summary of this workshop will become available through SECSC and the U.S. Geological Survey in early 2014, as part of an open technical report currently in review. That report will include the summary and guidance for the appropriate use based on comparisons of six publicly available regional climate data sets.}, journal={Bulletin of the Ecological Society of America}, year={2014}, month={Jan} } @article{simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology_2013, url={http://dx.doi.org/10.1007/s00382-012-1440-y}, DOI={10.1007/s00382-012-1440-y}, journal={Climate Dynamics}, year={2013}, month={Apr} } @article{does nudging squelch the extremes in regional climate modeling?_2012, url={http://dx.doi.org/10.1175/jcli-d-12-00048.1}, DOI={10.1175/jcli-d-12-00048.1}, abstractNote={Abstract An 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 performed using coarse reanalysis fields as proxies for global climate model fields. The results demonstrate that applying interior nudging improves the accuracy of simulated monthly means, variability, and extremes over the multidecadal period. The results in this case indicate that interior nudging does not inappropriately squelch the prediction of temperature and precipitation extremes and is essential for simulating extreme events that are faithful in space and time to the driving large-scale fields.}, journal={Journal of Climate}, year={2012}, month={Oct} } @article{examining interior grid nudging techniques using two-way nesting in the wrf model for regional climate modeling_2012, url={http://dx.doi.org/10.1175/jcli-d-11-00167.1}, DOI={10.1175/jcli-d-11-00167.1}, abstractNote={Abstract This 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 precipitation totals, and intensity and frequency of precipitation that are closer to observed fields than spectral nudging. The spectrum of 250-hPa zonal winds simulated by the WRF model is also compared to that of the R-2 and NARR. The spatial variability in the WRF model is reduced by using either form of interior nudging, and analysis nudging suppresses that variability more strongly than spectral nudging. Reducing the nudging strengths on the inner domain increases the variability but generates larger biases. The results support the use of interior nudging on both domains of a two-way nest to reduce error when the inner nest is not otherwise dominated by the lateral boundary forcing. Nevertheless, additional research is required to optimize the balance between accuracy and variability in choosing a nudging strategy.}, journal={Journal of Climate}, year={2012}, month={Apr} } @article{davis_bowden_semazzi_xie_onol_2009, title={Customization of RegCM3 Regional Climate Model for Eastern Africa and a Tropical Indian Ocean Domain}, volume={22}, ISSN={["1520-0442"]}, url={http://dx.doi.org/10.1175/2009jcli2388.1}, DOI={10.1175/2009JCLI2388.1}, abstractNote={Abstract Rainfall is a driving factor of climate in the tropics and needs to be properly represented within a climate model. This study customizes the precipitation processes over the tropical regions of eastern Africa and the Indian Ocean using the International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM3). The convective schemes of Grell with closures Arakawa–Schubert (Grell–AS)/Fritch–Chappel (Grell–FC) and Massachusetts Institute of Technology–Emanuel (MIT–EMAN) were compared to determine the most realistic spatial distribution of rainfall and partitioning of convective/stratiform rainfall when compared to observations from the Tropical Rainfall Measuring Mission (TRMM). Both Grell–AS and Grell–FC underpredicted convective rainfall rates over land, while over the ocean Grell–FC (Grell–AS) over- (under-) estimates convective rainfall. MIT–EMAN provides the most realistic pardoning and spatial distribution of convective rainfall despite the tendency for overestimating total rainfall. MIT–EMAN was used to further customize the subgrid explicit moisture scheme (SUBEX). Sensitivity tests were performed on the gridbox relative humidity threshold for cloudiness (RHmin) and the autoconversion scale factor (Cacs). An RHmin value of 60% (RHmin-60) reduced the amount of total rainfall over five heterogeneous rainfall regions in eastern Africa, with most of the reduction coming from the convective rainfall. Then, Cacs sensitivity tests improved upon the total rainfall amounts and convective stratiform partitioning compared to RHmin-60. Based upon all sensitivity simulations performed, the combination of the MIT–EMAN convective scheme, RHmin-60, and halving the model default value (0.4) of Cacs provided the most realistic simulation in terms of spatial distribution, convective partition, rainfall totals, and temperature bias when compared to observations.}, number={13}, journal={JOURNAL OF CLIMATE}, author={Davis, Neil and Bowden, Jared and Semazzi, Fredrick and Xie, Lian and Onol, Baris}, year={2009}, month={Jul}, pages={3595–3616} } @article{bowden_semazzi_2007, title={Empirical analysis of intraseasonal climate variability over the greater horn of Africa}, volume={20}, ISSN={["1520-0442"]}, url={http://dx.doi.org/10.1175/2007jcli1587.1}, DOI={10.1175/2007JCLI1587.1}, abstractNote={Abstract This study examines the intraseasonal climate variability over the Greater Horn of Africa (GHA) during the rainy season of October–December (OND). The investigation is primarily based on empirical orthogonal function (EOF) analysis of the pentad Climate Prediction Center Merged Analysis of Precipitation (CMAP) data for the period 1979–2001. The EOF analysis reveals two dominant modes of intraseasonal variability for the OND season: mixed El Niño–Southern Oscillation–Indian Ocean dipole (ENSO-IOD) and a decadal mode. The leading mode is associated with ENSO–IOD covariability. Case studies of several intraseasonal ENSO–IOD events within the recent decades indicate that during the warm (positive) events pentad rainfall is consistently above normal during the entire season despite fluctuations between pentads. However, case study analyses of negative ENSO–IOD events show that the negative cases are not mirror images of the warm events. The negative events exhibit pronounced wet and dry spells superimposed on the consistent dry anomaly background conditions. There is no large signal regarding the onset for either case, but the withdrawal of the positive (negative) events is anomalously wet (dry). The second mode of variability is associated with a decadal shift in the rainfall with the northern (southern) GHA becoming wetter (drier) in the recent decade. The decadal change in individual pentads can be quite different across the season and has a tendency to manifest itself through extreme events. The analysis underscores the need to exercise caution when applying seasonal-average-based statistics to infer the long-term behavior on subseasonal time scales. Additional analyses further confirm the decadal rainfall shift using four different rainfall datasets. Averaging the datasets to help aid in removing bias of individual datasets shows that, on average, northern (southern) portions of GHA are 29% (19%) wetter (drier) in the recent decade.}, number={23}, journal={JOURNAL OF CLIMATE}, author={Bowden, Jared H. and Semazzi, Fredrick H. M.}, year={2007}, month={Dec}, pages={5715–5731} } @article{fall_semazzi_dutta_niyogi_anyah_bowden_2006, title={The spatiotemporal climate variability over Senegal and its relationship to global climate}, volume={26}, ISSN={["1097-0088"]}, url={http://dx.doi.org/10.1002/joc.1355}, DOI={10.1002/joc.1355}, abstractNote={Climate variability over Senegal (West Africa) and its relationship to global climate are examined for the period 1979–1998. Monthly observed rainfall for 20 stations and monthly CPC merged analysis precipitation (CMAP) over Senegal were averaged for the months of June, July, August, and September in order to generate seasonal rainfall totals for the wet season, as well as climate indices averaged over the study period. The spatial distribution patterns are mapped and analyzed using ArcGIS Spatial Analyst. Rainfall distribution over Senegal is dominated by a N–S gradient. To investigate the climate variability over Senegal, an empirical orthogonal function (EOF) analysis is performed for the 1979–1998 period, using rain-gauge and CMAP rainfall data over Senegal, and CMAP data only for West Africa. The first West African mode agrees strongly with Lamb’s rainfall index. One of our major findings is that EOF2 for West Africa is well correlated with EOF1 for rainfall in Senegal. This relationship is supported by the projection of winds on the EOF2 mode by the National Centers for Environmental Prediction (NCEP), as well as the grid-point correlation between the time series of EOF2 over West Africa and the Atlantic sea-surface temperature (SST). The typical circulation associated with positive anomalies over Senegal is a moisture convergence, which takes place over the Guinea Gulf, in conjunction with the warm waters in this area. The time series for rainfall over Senegal show positive correlations with the South Atlantic SST. Over the Pacific Ocean, the greatest correlation coefficients (up to −0.72) are observed during the April–July period, which provide a modest possibility of predicting Senegal’s rainy season. Given the specificity of coastal West Africa, the traditional indices used by policy makers and end users for the whole Sahel–Sudan region will not work for Senegal. The CMAP data are robust and suitable for analyses over West Africa. On the basis of its reliability, CMAP data has proven to be a good validation for analyses based on rain-gauge precipitation. Copyright 2006 Royal Meteorological Society.}, number={14}, journal={INTERNATIONAL JOURNAL OF CLIMATOLOGY}, author={Fall, Souleymane and Semazzi, Fredrick H. M. and Dutta, Dev and Niyogi, S. and Anyah, Richard O. and Bowden, Jared}, year={2006}, month={Nov}, pages={2057–2076} }