A Regional Modeling Study Of Climate Change Impacts On Warm-Season Precipitation In The U.S.

Changes in the character of precipitation have already been observed over much of the United States. In a warming climate, the impacts of these changes will likely be felt most strongly through changes in the intensity and frequency of climate extremes. With precipitation, this has potential to be highly disruptive to the environment and the economy. However, while current global climate models may provide acceptable simulations of precipitation on a continental scale, they are lacking when it comes to properly portraying the characteristics of warm-season precipitation over the U.S., creating uncertainty in the projections of future precipitation in this area of the world. Because predicting climate change is essential for mitigation, adaptation, and planning purposes, assessing the uncertainty associated with climate change projections and producing adequate simulations of present climate is important.This study proceeds in several parts to address this issue. It asks the overarching question of how climate change will impact warm-season precipitation over the U.S., focusing on precipitation extremes and the central U.S. region. To do so, the Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to dynamically downscale output from the National Center for Atmospheric Research's (NCAR) Community Climate System Model (CCSM) version 3 and the National Center for Environmental Prediction (NCEP)/NCAR global reanalysis (NNRP). The latter is used for verification of late 20th century climate simulations from the WRF. In theory, the increase in horizontal resolution and sophistication of physical parameterizations in the WRF should improve the simulation of warm-season precipitation over the U.S., allowing a better representation of present climate and more reliable projections of future climate. As background, warm-season precipitation over the U.S. from current global climate models is assessed, as well as precipitation from current reanalyses in order to provide a basis for the comparison of model precipitation of the late 20th century.This study finds that the WRF is able to produce precipitation that is more realistic than that from the sources of its forcing (the CCSM and NNRP). It also diagnoses potential issues with and differences between all of the simulations completed. Specifically, the magnitude of heavy 6h average precipitation events and the frequency distribution of precipitation over the central U.S. is greatly improved. Projections from the WRF for late 21st century precipitation show decreases in average May-August (MJJA) precipitation, but an increase in the intensity of both heavy precipitation events and rain in general when it does fall. A decrease in the number of 6h periods with rainfall accounts for the overall decrease in average precipitation. The WRF also shows an increase in the frequency of very heavy to extreme 6h average events, but a decrease in the frequency of all events lighter than those over the central U.S. Overall, projections from this study suggest an increase in the frequency of both floods and droughts during the warm-season in the central U.S

Modeling the impacts of climate change on nitrogen losses and crop yield in a subsurface drained field

The effect of climate change on crop production and nitrate-nitrogen (NO3-N) pollution from subsurface drained fields is of a great concern. Using the calibrated and validated RZWQM2 (coupled with CERES-Maize and CROPGRO in DSSAT), the potential effects of climate change and elevated atmospheric CO2 concentrations (CO2) on tile drainage volume, NO3-N losses, and crop production were assessed integrally for the first time for a corn-soybean rotation cropping system near Gilmore City, Iowa. RZWQM2 simulated results under 20-year observed historical weather data (1990–2009) and ambient CO2 were compared to those under 20-year projected future meteorological data (2045–2064) and elevated CO2, with all management practices unchanged. The results showed that, under the future climate, tile drainage, NO3-N loss and flow-weighted average NO3-N concentration (FWANC) increased by 4.2 cm year−1 (+14.5 %), 11.6 kg N ha−1 year−1 (+33.7 %) and 2.0 mg L−1 (+16.4 %), respectively. Yields increased by 875 kg ha−1 (+28.0 %) for soybean [Glycine max (L.) Merr.] but decreased by 1380 kg ha−1(−14.7 %) for corn (Zea mays L.). The yield of the C3 soybean increased mostly due to CO2enrichment but increased temperature had negligible effect. However, the yield of C4 corn decreased largely because of fewer days to physiological maturity due to increased temperature and limited benefit of elevated CO2 to corn yield under subhumid climate. Relative humidity, short wave radiation and wind speed had small or negligible impacts on FWANC or grain yields. With the predicted trend, this study suggests that to mitigate NO3-N pollution from subsurface drained corn-soybean field in Iowa is a more challenging task in the future without changing current management practices. This study also demonstrates the advantage of an agricultural system model in assessing climate change impacts on water quality and crop production. Further investigation on management practice adaptation is needed

Simulating North American Weather Types With Regional Climate Models

Regional climate models (RCMs) are able to simulate small-scale processes that are missing in their coarser resolution driving data and thereby provide valuable climate information for climate impact assessments. Less attention has been paid to the ability of RCMs to capture large-scale weather types (WTs). An inaccurate representation of WTs can result in biases and uncertainties in current and future climate simulations that cannot be easily detected by standard model evaluation metrics. Here we define 12 hydrologically important WTs in the contiguous United States (CONUS). We test if RCMs from the North American CORDEX (NA-CORDEX) and the Weather Research and Forecasting (WRF) model large physics ensembles (WRF36) can capture those WTs in the current climate and how they simulate changes in the future. Our results show that the NA-CORDEX RCMs are able to simulate WTs more accurately than members of the WRF36 ensemble. The much larger WRF36 domain in combination with not constraining large-scale conditions by spectral nudging results in lower WT skill. The selection of the driving global climate model (GCM) has a large effect on the skill of NA-CORDEX simulations but a smaller impact on the WRF36 runs. The formulation of the RCM is of minor importance except for capturing the variability within WTs. Changing the model physics or increasing the RCM horizontal grid spacing has little effect. These results highlight the importance of selecting GCMs with accurate synoptic-scale variability for downscaling and to find a balance between large domains that can result in biased WT representations and small domains that inhibit the realistic development of mesoscale processes. At the end of the century, monsoonal flow conditions increase systematically by up to 30% and a WT that is a significant source of moisture for the Northern Plains during the growing seasons decreases systematically up to –30%

Reply to “Comments on ‘The North American Regional Climate Change Assessment Program: Overview of Phase I Results\u27”

The authors of Mearns et al. (2012) are aware of the role of driving RCMs with reanalyses and have written extensively on the roles of different types of regional climate models (RCMs) simulations (e.g., Giorgi and Mearns 1999; Leung et al. 2003). Thus, we agree that the skill of dynamical downscaling in which global reanalysis is used to provide boundary conditions in general indicates an upper bound of skill compared to dynamical downscaling in which the boundary conditions come from global climate model simulations. This finding has long been established, as global climate model simulations cannot outperform global reanalysis in providing boundary conditions since the latter is constrained by observations through data assimilation (that is, unless the reanalyses themselves have been shown to have serious deficiences; e.g., Cerezo-Mota et al 2011). The classification of different types of dynamical downscaling introduced by Castro et al. (2005) further adds clarity to this point

The worldwide C3S CORDEX grand ensemble: A major contribution to assess regional climate change in the IPCC AR6 Atlas

peer reviewedAbstract The collaboration between the Coordinated Regional Climate Downscaling Experiment (CORDEX) and the Earth System Grid Federation (ESGF) provides open access to an unprecedented ensemble of Regional Climate Model (RCM) simulations, across the 14 CORDEX continental-scale domains, with global coverage. These simulations have been used as a new line of evidence to assess regional climate projections in the latest contribution of the Working Group I (WGI) to the IPCC Sixth Assessment Report (AR6), particularly in the regional chapters and the Atlas. Here, we present the work done in the framework of the Copernicus Climate Change Service (C3S) to assemble a consistent worldwide CORDEX grand ensemble, aligned with the deadlines and activities of IPCC AR6. This work addressed the uneven and heterogeneous availability of CORDEX ESGF data by supporting publication in CORDEX domains with few archived simulations and performing quality control. It also addressed the lack of comprehensive documentation by compiling information from all contributing regional models, allowing for an informed use of data. In addition to presenting the worldwide CORDEX dataset, we assess here its consistency for precipitation and temperature by comparing climate change signals in regions with overlapping CORDEX domains, obtaining overall coincident regional climate change signals. The C3S CORDEX dataset has been used for the assessment of regional climate change in the IPCC AR6 (and for the interactive Atlas) and is available through the Copernicus Climate Data Store (CDS)

2007: A brief evaluation of precipitation from the North American Regional Reanalysis

Abstract Several aspects of the precipitation climatology from the North American Regional Reanalysis (NARR) are analyzed and compared with two other reanalyses and one set of gridded observations over a domain encompassing the United States. The spatial distribution, diurnal cycle, and annual cycle of precipitation are explored to establish the reliability of the reanalyses and to judge their usefulness. While the NARR provides a much improved representation of precipitation over that of the other reanalyses examined, some inaccuracies are found and have been highlighted as a warning to potential users of the data.

A regional modeling study of climate change impacts on warm-season precipitation in the Central United States

© Copyright 2011 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected] this study, the Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to dynamically downscale output from the National Center for Atmospheric Research’s (NCAR’s) Community Climate SystemModel (CCSM) version 3 and the National Centers for Environmental Prediction (NCEP)–NCARglobal reanalysis (NNRP). The latter is used for verification of late-twentieth-century climate simulations from the WRF

Modeling the impacts of climate change on nitrogen losses and crop yield in a subsurface drained field

The effect of climate change on crop production and nitrate-nitrogen (NO3-N) pollution from subsurface drained fields is of a great concern. Using the calibrated and validated RZWQM2 (coupled with CERES-Maize and CROPGRO in DSSAT), the potential effects of climate change and elevated atmospheric CO2 concentrations (CO2) on tile drainage volume, NO3-N losses, and crop production were assessed integrally for the first time for a corn-soybean rotation cropping system near Gilmore City, Iowa. RZWQM2 simulated results under 20-year observed historical weather data (1990–2009) and ambient CO2 were compared to those under 20-year projected future meteorological data (2045–2064) and elevated CO2, with all management practices unchanged. The results showed that, under the future climate, tile drainage, NO3-N loss and flow-weighted average NO3-N concentration (FWANC) increased by 4.2 cm year−1 (+14.5 %), 11.6 kg N ha−1 year−1 (+33.7 %) and 2.0 mg L−1 (+16.4 %), respectively. Yields increased by 875 kg ha−1 (+28.0 %) for soybean [Glycine max (L.) Merr.] but decreased by 1380 kg ha−1(−14.7 %) for corn (Zea mays L.). The yield of the C3 soybean increased mostly due to CO2enrichment but increased temperature had negligible effect. However, the yield of C4 corn decreased largely because of fewer days to physiological maturity due to increased temperature and limited benefit of elevated CO2 to corn yield under subhumid climate. Relative humidity, short wave radiation and wind speed had small or negligible impacts on FWANC or grain yields. With the predicted trend, this study suggests that to mitigate NO3-N pollution from subsurface drained corn-soybean field in Iowa is a more challenging task in the future without changing current management practices. This study also demonstrates the advantage of an agricultural system model in assessing climate change impacts on water quality and crop production. Further investigation on management practice adaptation is needed.This article is published as Wang, Zhaozhi, Zhiming Qi, Lulin Xue, Melissa Bukovsky, and Matthew J. Helmers. "Modeling the impacts of climate change on nitrogen losses and crop yield in a subsurface drained field." Climatic Change 129, no. 1-2 (2015): 323-335. 10.1007/s10584-015-1342-1. Posted with permission.</p