@misc{schlef_kunkel_brown_demissie_lettenmaier_wagner_wigmosta_karl_easterling_wang_et al._2023, title={Incorporating non-stationarity from climate change into rainfall frequency and intensity-duration-frequency (IDF) curves}, volume={616}, ISSN={["1879-2707"]}, DOI={10.1016/j.jhydrol.2022.128757}, abstractNote={Intensity-duration-frequency (IDF) curves – sometimes also called precipitation frequency estimates – are used to design urban drainage systems for stormwater control and, when combined with hydrologic modeling, to design flood control infrastructure and other structures. However, common approaches to estimating IDF curves need to be revised to account for non-stationarity from global climate change. This review synthesizes the current knowledge and on-going research regarding IDF curves under non-stationarity. In particular, this review briefly summarizes known and projected changes in extreme precipitation at the global scale, describes approaches for IDF curve estimation under non-stationarity (focusing on the covariate-based approach and including a brief overview of the specific challenges facing snow-dominated regions), addresses the topic of regionalization under non-stationarity (which has been overlooked in previous reviews), explores the challenges of design values and uncertainty in the context of non-stationarity, provides details on these topics in the context of the United States, and finishes by enumerating needed avenues of future research.}, journal={JOURNAL OF HYDROLOGY}, author={Schlef, Katherine E. and Kunkel, Kenneth E. and Brown, Casey and Demissie, Yonas and Lettenmaier, Dennis P. and Wagner, Anna and Wigmosta, Mark S. and Karl, Thomas R. and Easterling, David R. and Wang, Kimberly J. and et al.}, year={2023}, month={Jan} }
 @article{crossett_dupigny-giroux_kunkel_betts_bomblies_2023, title={Synoptic Typing of Multiduration, Heavy Precipitation Records in the Northeastern United States: 1895-2017}, volume={62}, ISSN={["1558-8432"]}, DOI={10.1175/JAMC-D-22-0091.1}, abstractNote={Abstract Much of the previous research on total and heavy precipitation trends across the northeastern United States (herein, the Northeast) used daily precipitation totals over relatively short periods of record, which do not capture the full range of climate variability and change. Less well understood are the characteristics of long-term changes and synoptic patterns in longer-duration heavy precipitation events across the Northeast. A multiduration (1, 2, 3, 7, 14, and 30 days), multi-return-interval (2, 5, 10, and 50 years) precipitation dataset was used to diagnose changes in various types of precipitation events across the Northeast from 1895 to 2017. Increasing trends were found in all duration and return-interval event combinations with the rarest, longest duration events increasing at faster rates than more-frequent, shorter-duration ones. Daily 850-hPa geopotential height patterns associated with precipitation events were extracted from rotated principal component analysis and k -means clustering analysis, which allowed for the main synoptic types present as well as their structure and evolution to be analyzed. The daily synoptic patterns thus identified were found to be similar across all durations and return intervals and included coastal low (Northeasters, tropical cyclones, and predecessor rain events), deep trough, East Coast trough, zonal, and high pressure patterns.}, number={6}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={Crossett, Caitlin C. and Dupigny-Giroux, Lesley-Ann L. and Kunkel, Kenneth E. and Betts, Alan K. and Bomblies, Arne}, year={2023}, month={Jun}, pages={721–736} }
 @article{barsugli_easterling_arndt_coates_delworth_hoerling_johnson_kapnick_kumar_kunkel_et al._2022, title={Development of a Rapid Response Capability to Evaluate Causes of Extreme Temperature and Drought Events in the United States}, volume={103}, ISSN={["1520-0477"]}, DOI={10.1175/BAMS-D-21-0237.1}, abstractNote={© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). CORRESPONDING AUTHOR: Joseph J. Barsugli, joseph.barsugli@colorado.edu A supplement to this article is available online (10.1175/BAMS-D-21-0237.2)}, number={3}, journal={BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY}, author={Barsugli, Joseph J. and Easterling, David R. and Arndt, Derek S. and Coates, David A. and Delworth, Thomas L. and Hoerling, Martin P. and Johnson, Nathaniel and Kapnick, Sarah B. and Kumar, Arun and Kunkel, Kenneth E. and et al.}, year={2022}, month={Mar}, pages={S14–S20} }
 @article{kunkel_yin_sun_champion_stevens_johnson_2022, title={Extreme Precipitation Trends and Meteorological Causes Over the Laurentian Great Lakes}, volume={4}, ISSN={["2624-9375"]}, DOI={10.3389/frwa.2022.804799}, abstractNote={Trends in extreme precipitation and their causes were analyzed for events within the Laurentian Great Lakes for several periods: 1908–2020, 1949–2020, 1980–2019, and 1980–2020. Upward trends in extreme precipitation were found for multiple metrics, including the number of exceedances of return period thresholds for several durations and average recurrence intervals (ARI), the number of extreme basin-average 4-day precipitation totals, and the annual maximum daily station precipitation. The causes of extreme events were classified into 5 meteorological categories: fronts of extratropical cyclones (ETC-FRT), extratropical cyclones but not proximate to the fronts (ETC-NFRT), mesoscale convective systems (MCS), tropical cyclones (TC), and air mass convection (AMC). For daily events exceeding the threshold for 5-yr ARI, ETC-FRTs account for 78% of all events, followed by ETC-NFRTs (12%), MCSs (6%), TCs (2%), and AMC (1%). Upward trends in the number of events by cause were found for all categories except AMC. An examination of basin-wide 4-day extreme events (40 largest events during 1980–2019) found that all events were caused by ETC-FRTs (85%) or ETC-NFRTs (15%).}, journal={FRONTIERS IN WATER}, author={Kunkel, Kenneth E. and Yin, Xungang and Sun, Liqiang and Champion, Sarah M. and Stevens, Laura E. and Johnson, Katharine M.}, year={2022}, month={May} }
 @article{dagon_truesdale_biard_kunkel_meehl_molina_2022, title={Machine Learning-Based Detection of Weather Fronts and Associated Extreme Precipitation in Historical and Future Climates}, volume={127}, ISSN={["2169-8996"]}, DOI={10.1029/2022JD037038}, abstractNote={Extreme precipitation events, including those associated with weather fronts, have wide-ranging impacts across the world. Here we use a deep learning algorithm to identify weather fronts in high resolution Community Earth System Model (CESM) simulations over the contiguous United States (CONUS), and evaluate the results using observational and reanalysis products. We further compare results between CESM simulations using present-day and future climate forcing, to study how these features might change with climate change. We find that detected front frequencies in CESM have seasonally varying spatial patterns and responses to climate change and are found to be associated with modeled changes in large scale circulation such as the jet stream. We also associate the detected fronts with precipitation and find that total and extreme frontal precipitation mostly decreases with climate change, with some seasonal and regional differences. Decreases in Northern Hemisphere summer frontal precipitation are largely driven by changes in the frequency of different front types, especially cold and stationary fronts. On the other hand, Northern Hemisphere winter exhibits some regional increases in frontal precipitation that are largely driven by changes in frontal precipitation intensity. While CONUS mean and extreme precipitation generally increase during all seasons in these climate change simulations, the likelihood of frontal extreme precipitation decreases, demonstrating that extreme precipitation has seasonally varying sources and mechanisms that will continue to evolve with climate change.}, number={21}, journal={JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES}, author={Dagon, Katherine and Truesdale, John and Biard, James C. and Kunkel, Kenneth E. and Meehl, Gerald A. and Molina, Maria J.}, year={2022}, month={Nov} }
 @article{shiva_chandler_kunkel_2022, title={Mapping Heat Wave Hazard in Urban Areas: A Novel Multi-Criteria Decision Making Approach}, volume={13}, ISSN={["2073-4433"]}, DOI={10.3390/atmos13071037}, abstractNote={Global population is experiencing more frequent, longer, and more severe heat waves due to global warming and urbanization. Episodic heat waves increase mortality and morbidity rates and demands for water and energy. Urban managers typically assess heat wave risk based on heat wave hazard, population exposure, and vulnerability, with a general assumption of spatial uniformity of heat wave hazard. We present a novel analysis that demonstrates an approach to determine the spatial distribution of a set of heat wave properties and hazard. The analysis is based on the Livneh dataset at a 1/16-degree resolution from 1950 to 2009 in Maricopa County, Arizona, USA. We then focused on neighborhoods with the most frequent, severe, earlier, and extended periods of heat wave occurrences. On average, the first heat wave occurs 40 days earlier in the eastern part of the county; the northeast part of this region experiences 12 days further extreme hot days and 30 days longer heat wave season than other regions of the area. Then, we applied a multi-criteria decision-making (MCDM) tool (TOPSIS) to evaluate the total hazard posed by heat wave components. We found that the northern and central parts of the metropolitan area are subject to the greatest heat wave hazard and that individual heat wave hazard components did not necessarily indicate heat hazard. This approach is intended to support local government planning for heat wave adaptation and mitigation strategies, where cooling centers, heat emergency water distribution networks, and electrical energy delivery can be targeted based on current and projected local heat wave characteristics.}, number={7}, journal={ATMOSPHERE}, author={Shiva, Javad Shafiei and Chandler, David G. and Kunkel, Kenneth E.}, year={2022}, month={Jul} }
 @article{dong_wang_kunkel_shao_xing_wei_2021, title={Heterogeneous response of global precipitation concentration to global warming}, volume={41}, ISSN={["1097-0088"]}, DOI={10.1002/joc.6851}, journal={INTERNATIONAL JOURNAL OF CLIMATOLOGY}, author={Dong, Qing and Wang, Weiguang and Kunkel, Kenneth E. and Shao, Quanxi and Xing, Wanqiu and Wei, Jia}, year={2021}, month={Jan}, pages={E2347–E2359} }
 @article{russell_risser_smith_kunkel_2020, title={Investigating the association between late spring Gulf of Mexico sea surface temperatures and US Gulf Coast precipitation extremes with focus on Hurricane Harvey}, volume={31}, ISSN={["1099-095X"]}, DOI={10.1002/env.2595}, abstractNote={Abstract Hurricane Harvey brought extreme levels of rainfall to the Houston, Texas, area over a 7‐day period in August 2017, resulting in catastrophic flooding that caused loss of human life and damage to personal property and public infrastructure. In the wake of this event, there has been interest in understanding the degree to which this event was unusual and estimating the probability of experiencing a similar event in other locations. Additionally, researchers have aimed to better understand the ways in which the sea surface temperature (SST) in the Gulf of Mexico (GoM) is associated with precipitation extremes in this region. This work addresses all of these issues through the development of a multivariate spatial extreme value model. Our analysis indicates that warmer GoM SSTs are associated with higher precipitation extremes in the western Gulf Coast region during hurricane season and that the precipitation totals observed during Hurricane Harvey are less unusual based on the warm GoM SST in 2017. As SSTs in the GoM are expected to steadily increase over the remainder of this century, this analysis suggests that western Gulf Coast locations may experience more severe precipitation extremes during hurricane season.}, number={2}, journal={ENVIRONMETRICS}, author={Russell, Brook T. and Risser, Mark D. and Smith, Richard L. and Kunkel, Kenneth E.}, year={2020}, month={Mar} }
 @article{kunkel_stevens_stevens_karl_2020, title={Observed Climatological Relationships of Extreme Daily Precipitation Events With Precipitable Water and Vertical Velocity in the Contiguous United States}, volume={47}, ISSN={["1944-8007"]}, DOI={10.1029/2019GL086721}, number={12}, journal={GEOPHYSICAL RESEARCH LETTERS}, author={Kunkel, Kenneth E. and Stevens, Scott E. and Stevens, Laura E. and Karl, Thomas R.}, year={2020}, month={Jun} }
 @article{kunkel_karl_squires_yin_stegall_easterling_2020, title={Precipitation Extremes: Trends and Relationships with Average Precipitation and Precipitable Water in the Contiguous United States}, volume={59}, ISSN={["1558-8432"]}, DOI={10.1175/JAMC-D-19-0185.1}, abstractNote={Abstract Trends of extreme precipitation (EP) using various combinations of average return intervals (ARIs) of 1, 2, 5, 10, and 20 years with durations of 1, 2, 5, 10, 20, and 30 days were calculated regionally across the contiguous United States. Changes in the sign of the trend of EP vary by region as well as by ARI and duration, despite the statistically significant upward trends for all combinations of EP thresholds when area averaged across the contiguous United States. Spatially, there is a pronounced east-to-west gradient in the trends of the EP with strong upward trends east of the Rocky Mountains. In general, upward trends are larger and more significant for longer ARIs, but the contribution to the trend in total seasonal and annual precipitation is significantly larger for shorter ARIs because they occur more frequently. Across much of the contiguous United States, upward trends of warm-season EP are substantially larger than those for the cold season and have a substantially greater effect on the annual trend in total precipitation. This result occurs even in areas where the total precipitation is nearly evenly divided between the cold and warm seasons. When compared with short-duration events, long-duration events—for example, 30 days—contribute the most to annual trends. Coincident statistically significant upward trends of EP and precipitable water (PW) occur in many regions, especially during the warm season. Increases in PW are likely to be one of several factors responsible for the increase in EP (and average total precipitation) observed in many areas across the contiguous United States.}, number={1}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={Kunkel, Kenneth E. and Karl, Thomas R. and Squires, Michael F. and Yin, Xungang and Stegall, Steve T. and Easterling, David R.}, year={2020}, month={Jan}, pages={125–142} }
 @article{kunkel_champion_2019, title={An Assessment of Rainfall from Hurricanes Harvey and Florence Relative to Other Extremely Wet Storms in the United States}, volume={46}, ISSN={["1944-8007"]}, DOI={10.1029/2019GL085034}, abstractNote={Abstract The top 100 largest area‐averaged, multiday precipitation events in the U.S. historical record for the period 1949–2018 were identified by calculating box‐average precipitation using a network of observing stations with minimal missing data. Hurricane Harvey was the single largest event for an area sized 50,000 km 2 and a duration of 4 days. Rainfall associated with Hurricane Florence ranked seventh. Almost all of the top 100 events occurred in the southeastern United States or along the Pacific coast. The predominant meteorological cause (in 59% of the events) was fronts associated with extratropical cyclones, including 15% that were also associated with atmospheric rivers. Tropical cyclones were a significant cause, representing 25% of all events. The spatial locations, the seasonal distribution, and the spectrum of meteorological causes of these events are characteristics of the precipitation climatology that could be used as metrics to evaluate climate models.}, number={22}, journal={GEOPHYSICAL RESEARCH LETTERS}, author={Kunkel, Kenneth E. and Champion, Sarah M.}, year={2019}, month={Nov}, pages={13500–13506} }
 @article{rennie_bell_kunkel_herring_cullen_abadi_2019, title={Development of a Submonthly Temperature Product to Monitor Near-Real-Time Climate Conditions and Assess Long-Term Heat Events in the United States}, volume={58}, ISSN={["1558-8432"]}, DOI={10.1175/JAMC-D-19-0076.1}, abstractNote={Abstract Land surface air temperature products have been essential for monitoring the evolution of the climate system. Before a temperature dataset is included in such analyses, it is important that nonclimatic influences be removed or changed so that the dataset is considered to be homogenous. These inhomogeneities include changes in station location, instrumentation, and observing practices. Many homogenized products exist on the monthly time scale, but few daily and weekly products exist. Recently, a submonthly homogenized dataset has been developed using data and software from NOAA’s National Centers for Environmental Information. Homogeneous daily data are useful for identification and attribution of extreme heat events. Projections of increasing temperatures are expected to result in corresponding increases in the frequency, duration, and intensity of such events. It is also established that heat events can have significant public health impacts, including increases in mortality and morbidity. The method to identify extreme heat events using daily homogeneous temperature data is described and used to develop a climatology of heat event onset, length, and severity. This climatology encompasses nearly 3000 extreme maximum and minimum temperature events across the United States since 1901. A sizeable number of events occurred during the Dust Bowl period of the 1930s; however, trend analysis shows an increase in heat event number and length since 1951. Overnight extreme minimum temperature events are increasing more than daytime maximum temperatures, and regional analysis shows that events are becoming much more prevalent in the western and southeastern parts of the United States.}, number={12}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={Rennie, Jared and Bell, Jesse E. and Kunkel, Kenneth E. and Herring, Stephanie and Cullen, Heidi and Abadi, Azar M.}, year={2019}, month={Dec}, pages={2653–2674} }
 @article{lee_waliser_lee_loikith_kunkel_2019, title={Evaluation of CMIP5 ability to reproduce twentieth century regional trends in surface air temperature and precipitation over CONUS}, volume={53}, ISSN={["1432-0894"]}, DOI={10.1007/s00382-019-04875-1}, number={9-10}, journal={CLIMATE DYNAMICS}, author={Lee, Jinny and Waliser, Duane and Lee, Huikyo and Loikith, Paul and Kunkel, Kenneth E.}, year={2019}, month={Nov}, pages={5459–5480} }
 @article{shiva_chandler_kunkel_2019, title={Localized Changes in Heat Wave Properties Across the United States}, volume={7}, ISSN={["2328-4277"]}, DOI={10.1029/2018EF001085}, abstractNote={Abstract Heat waves are an important type of extreme climate event and directly result in more than 130 deaths per year across the United States. Heat waves have been described by several attributes and combinations which constitute various event typologies. Attributes of heat waves from 10 cities are analyzed over the period 1950–2016 to understand how these attributes determine variability in local heat waves and how climate change affects heat waves across the United States. This study uses eight definitions to differentiate heat waves and tests for temporal trends in key properties of heat waves over the period 1950–2016. At least five harmful attributes of heat waves have increased simultaneously for Dallas, Miami, New York, Phoenix, and Portland.Miami showed the greatest change in heat wave season length, frequency, and timing over the study period. Surprisingly, the greatest mean heat wave intensities above daily thresholds were for Bismarck, ND (+8.2 °C) and Syracuse, NY (+6.5 °C). Similar results across Baltimore, MD, Colorado Springs, CO, Dallas, TX, Des Moines, IA, Miami, FL, New York, NY, Phoenix, AZ, and Portland, OR, are presented to clarify the many quantitative differences in heat wave attributes and variance in quantification approaches across climates. This work explores the nexus of quantitative description and social construction of heat waves through the lens of the various regional metrics to describe heat waves. Ultimately, this assessment will guide the development of various strategies to help communities understand and prepare for heat resilience based on local heat wave components.}, number={3}, journal={EARTHS FUTURE}, author={Shiva, Javad Shafiei and Chandler, David G. and Kunkel, Kenneth E.}, year={2019}, month={Mar}, pages={300–319} }
 @article{stevens_schreck_saha_bell_kunkel_2019, title={Precipitation and Fatal Motor Vehicle Crashes: Continental Analysis with High-Resolution Radar Data}, volume={100}, ISSN={["1520-0477"]}, DOI={10.1175/BAMS-D-18-0001.1}, abstractNote={Abstract Motor vehicle crashes remain a leading cause of accidental death in the United States, and weather is frequently cited as a contributing factor in fatal crashes. Previous studies have investigated the link between these crashes and precipitation typically using station-based observations that, while providing a good estimate of the prevailing conditions on a given day or hour, often fail to capture the conditions present at the actual time and location of a crash. Using a multiyear, high-resolution radar reanalysis and information on 125,012 fatal crashes spanning the entire continental United States over a 6-yr period, we find that the overall risk of a fatal crash increases by approximately 34% during active precipitation. The risk is significant in all regions of the continental United States, and it is highest during the morning rush hour and during the winter months.}, number={8}, journal={BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY}, author={Stevens, Scott E. and Schreck, Carl J., III and Saha, Shubhayu and Bell, Jesse E. and Kunkel, Kenneth E.}, year={2019}, month={Aug}, pages={1453–1462} }
 @article{stegall_kunkel_2019, title={Simulation of Daily Extreme Precipitation over the United States in the CMIP5 30-Yr Decadal Prediction Experiment}, volume={58}, ISSN={["1558-8432"]}, DOI={10.1175/JAMC-D-18-0057.1}, abstractNote={Abstract The CMIP5 decadal hindcast (“Hindcast”) and prediction (“Predict”) experiment simulations from 11 models were analyzed for the United States with respect to two metrics of extreme precipitation: the 10-yr return level of daily precipitation, derived from the annual maximum series of daily precipitation, and the total precipitation exceeding the 99.5th percentile of daily precipitation. Both Hindcast simulations and observations generally show increases for the 1981–2010 historical period. The multimodel-mean Hindcast trends are statistically significant for all regions while the observed trends are statistically significant for the Northeast, Southeast, and Midwest regions. An analysis of CMIP5 simulations driven by historical natural (“HistoricalNat”) forcings shows that the Hindcast trends are generally within the 5th–95th-percentile range of HistoricalNat trends, but those outside that range are heavily skewed toward exceedances of the 95th-percentile threshold. Future projections for 2006–35 indicate increases in all regions with respect to 1981–2010. While there is good qualitative agreement between the observations and Hindcast simulations regarding the direction of recent trends, the multimodel-mean trends are similar for all regions, while there is considerable regional variability in observed trends. Furthermore, the HistoricalNat simulations suggest that observed historical trends are a combination of natural variability and anthropogenic forcing. Thus, the influence of anthropogenic forcing on the magnitude of near-term future changes could be temporarily masked by natural variability. However, continued observed increases in extreme precipitation in the first decade (2006–15) of the “future” period partially confirm the Predict results, suggesting that incorporation of increases in planning would appear prudent.}, number={4}, journal={JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY}, author={Stegall, Steve T. and Kunkel, Kenneth E.}, year={2019}, month={Apr}, pages={875–886} }
 @misc{bell_brown_conlon_herring_kunkel_lawrimore_luber_schreck_smith_uejio_2018, title={Changes in extreme events and the potential impacts on human health}, volume={68}, ISSN={["2162-2906"]}, DOI={10.1080/10962247.2017.1401017}, abstractNote={Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future.Implications: Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.}, number={4}, journal={JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION}, author={Bell, Jesse E. and Brown, Claudia Langford and Conlon, Kathryn and Herring, Stephanie and Kunkel, Kenneth E. and Lawrimore, Jay and Luber, George and Schreck, Carl and Smith, Adam and Uejio, Christopher}, year={2018}, pages={265–287} }
 @article{hallar_molotch_hand_livneh_mccubbin_petersen_michalsky_lowenthal_kunkel_2017, title={Impacts of increasing aridity and wildfires on aerosol loading in the intermountain Western US}, volume={12}, ISSN={["1748-9326"]}, DOI={10.1088/1748-9326/aa510a}, abstractNote={Feedbacks between climate warming, land surface aridity, and wildfire-derived aerosols represent a large source of uncertainty in future climate predictions. Here, long-term observations of aerosol optical depth, surface level aerosol loading, fire-area burned, and hydrologic simulations are used to show that regional-scale increases in aridity and resulting wildfires have significantly increased summertime aerosol loading in remote high elevation regions of the Intermountain West of the United States. Surface summertime organic aerosol loading and total aerosol optical depth were both strongly correlated (p < 0.05) with aridity and fire area burned at high elevation sites across major western US mountain ranges. These results demonstrate that surface-level organic aerosol loading is dominated by summertime wildfires at many high elevation sites. This analysis provides new constraints for climate projections on the influence of drought and resulting wildfires on aerosol loading. These empirical observations will help better constrain projected increases in organic aerosol loading with increased fire activity under climate change.}, number={1}, journal={ENVIRONMENTAL RESEARCH LETTERS}, author={Hallar, A. Gannet and Molotch, Noah P. and Hand, Jenny L. and Livneh, Ben and McCubbin, Ian B. and Petersen, Ross and Michalsky, Joseph and Lowenthal, Douglas and Kunkel, Kenneth E.}, year={2017}, month={Jan} }
 @article{bhowmik_sankarasubramanian_sinha_patskoski_mahinthakumar_kunkel_2017, title={Multivariate Downscaling Approach Preserving Cross Correlations across Climate Variables for Projecting Hydrologic Fluxes}, volume={18}, ISSN={1525-755X 1525-7541}, url={http://dx.doi.org/10.1175/JHM-D-16-0160.1}, DOI={10.1175/jhm-d-16-0160.1}, abstractNote={Abstract Most of the currently employed procedures for bias correction and statistical downscaling primarily consider a univariate approach by developing a statistical relationship between large-scale precipitation/temperature with the local-scale precipitation/temperature, ignoring the interdependency between the two variables. In this study, a multivariate approach, asynchronous canonical correlation analysis (ACCA), is proposed and applied to global climate model (GCM) historic simulations and hindcasts from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to downscale monthly precipitation and temperature over the conterminous United States. ACCA is first applied to the CNRM-CM5 GCM historical simulations for the period 1950–99 and compared with the bias-corrected dataset based on quantile mapping from the Bureau of Reclamation. ACCA is also applied to CNRM-CM5 hindcasts and compared with univariate asynchronous regression (ASR), which applies regular regression to sorted GCM and observed variables. ACCA performs better than ASR and quantile mapping in preserving the cross correlation at grid points where the observed cross correlations are significant while reducing fractional biases in mean and standard deviation. Results also show that preservation of cross correlation increases the bias in standard deviation slightly, but estimates observed precipitation and temperature with increased likelihood, particularly for months exhibiting significant cross correlation. ACCA also better estimates the joint likelihood of observed precipitation and temperature under hindcasts since hindcasts estimate the observed variability in precipitation better. Implications of preserving cross correlations across climate variables for projecting runoff and other land surface fluxes are also discussed.}, number={8}, journal={Journal of Hydrometeorology}, publisher={American Meteorological Society}, author={Bhowmik, Rajarshi Das and Sankarasubramanian, A. and Sinha, Tushar and Patskoski, Jason and Mahinthakumar, G. and Kunkel, Kenneth E.}, year={2017}, month={Aug}, pages={2187–2205} }
 @article{sankarasubramanian_sabo_larson_seo_sinha_bhowmik_vidal_kunkel_mahinthakumar_berglund_et al._2017, title={Synthesis of public water supply use in the United States: Spatio‐temporal patterns and socio‐economic controls}, volume={5}, ISSN={2328-4277 2328-4277}, url={http://dx.doi.org/10.1002/2016EF000511}, DOI={10.1002/2016ef000511}, abstractNote={Recent U.S. Geological Survey water-use report suggests that increasing water-use efficiency could mitigate the supply-and-demand imbalance arising from changing climate and growing population. However, this rich data have neither analyzed to understand the underlying patterns, nor have been investigated to identify the factors contributing to this increased efficiency. A national-scale synthesis of public supply withdrawals (“withdrawals”) reveals a strong North–south gradient in public supply water use with the increasing population in the South contributing to increased withdrawal. Contrastingly, a reverse South–north gradient exists in per capita withdrawals (“efficiency”), with northern states consistently improving the efficiency, while the southern states' efficiency declined. Our analyses of spatial patterns of per capita withdrawals further demonstrate that urban counties exhibit improved efficiency over rural counties. Improved efficiency is also demonstrated over high-income and well-educated counties. Given the potential implications of the findings in developing long-term water conservation measures (i.e., increasing block rates), we argue the need for frequent updates, perhaps monthly to annual, of water-use data for identifying effective strategies that control the water-use efficiency in various geographic settings under a changing climate.}, number={7}, journal={Earth's Future}, publisher={American Geophysical Union (AGU)}, author={Sankarasubramanian, A. and Sabo, J. L. and Larson, K. L. and Seo, S. B. and Sinha, T. and Bhowmik, R. and Vidal, A. Ruhi and Kunkel, K. and Mahinthakumar, G. and Berglund, E. Z. and et al.}, year={2017}, month={Jul}, pages={771–788} }
 @article{easterling_kunkel_wehner_sun_2016, title={Detection and attribution of climate extremes in the observed record}, volume={11}, ISSN={2212-0947}, url={http://dx.doi.org/10.1016/J.WACE.2016.01.001}, DOI={10.1016/J.WACE.2016.01.001}, abstractNote={We present an overview of practices and challenges related to the detection and attribution of observed changes in climate extremes. Detection is the identification of a statistically significant change in the extreme values of a climate variable over some period of time. Issues in detection discussed include data quality, coverage, and completeness. Attribution takes that detection of a change and uses climate model simulations to evaluate whether a cause can be assigned to that change. Additionally, we discuss a newer field of attribution, event attribution, where individual extreme events are analyzed for the express purpose of assigning some measure of whether that event was directly influenced by anthropogenic forcing of the climate system.}, journal={Weather and Climate Extremes}, publisher={Elsevier BV}, author={Easterling, David R. and Kunkel, Kenneth E. and Wehner, Michael F. and Sun, Liqiang}, year={2016}, month={Mar}, pages={17–27} }
 @article{paquin_frigon_kunkel_2016, title={Evaluation of Total Precipitable Water from CRCM4 using the NVAP-MEaSUREs Dataset and ERA-Interim Reanalysis Data}, volume={54}, ISSN={["1480-9214"]}, DOI={10.1080/07055900.2016.1230043}, abstractNote={Abstract The fourth-generation Canadian Regional Climate Model’s (CRCM4) precipitable water is evaluated and compared with observational data and ERA-Interim reanalysis data over five Canadian basins with simulations driven by ERA-Interim (two) and global climate models (two). Considering the 22 years of data available in the observations, we analyze precipitable water’s behaviour through its annual cycle, its daily distribution, and its annual daily maxima. For the simulations driven by reanalyses, differences in annual daily maximum values and their correlations with observations are examined. In general, the values for precipitable water simulated by CRCM4 are similar to those observed, and the model reproduces both the interannual and inter-basin variabilities. The simulation at 15 km resolution produces higher extreme values than simulations performed at 45 km resolution and higher than the observations taken at coarser resolution (1°), without much influence on the mean behaviour. Some underestimati...}, number={5}, journal={ATMOSPHERE-OCEAN}, author={Paquin, D. and Frigon, A. and Kunkel, K. E.}, year={2016}, month={Dec}, pages={541–548} }
 @article{waple_champion_kunkel_tilmes_2016, title={Innovations in information management and access for assessments}, volume={135}, DOI={10.1007/s10584-015-1588-7}, abstractNote={The third National Climate Assessment (NCA3) included goals for becoming a more timely, inclusive, rigorous, and sustained process, and for serving a wider variety of decision makers. In order to accomplish these goals, it was necessary to deliberately design an information management strategy that could serve multiple stakeholders and manage different types of information - from highly mature government-supported climate science data, to isolated practitioner-generated case study information - and to do so in ways that are consistent and appropriate for a highly influential assessment. Meeting the information management challenge for NCA3 meant balancing relevance and authority, complexity and accessibility, inclusivity and rigor. Increasing traceability of data behind figures and graphics, designing a public-facing website, managing hundreds of technical inputs to the NCA, and producing guidance for over 300 participants on meeting the Information Quality Act were all aspects of a deliberate, multi-faceted, and strategic information management approach that nonetheless attempted to be practical and usable for a variety of participants and stakeholders.}, number={1}, journal={Climatic Change}, author={Waple, A. M. and Champion, S. M. and Kunkel, K. E. and Tilmes, C.}, year={2016}, pages={69–83} }
 @article{kunkel_moss_parris_2016, title={Innovations in science and scenarios for assessment}, volume={135}, ISSN={["1573-1480"]}, DOI={10.1007/s10584-015-1494-z}, abstractNote={Scenarios for the Third National Climate Assessment (NCA3) were produced for physical climate and sea level rise with substantial input from disciplinary and regional experts. These scenarios underwent extensive review and were published as NOAA Technical Reports. For land use/cover and socioeconomic conditions, scenarios already developed by other agencies were specified for use in the NCA3. Efforts to enhance participatory scenario planning as an assessment activity were pursued, but with limited success. Issues and challenges included the timing of availability of scenarios, the need for guidance in use of scenarios, the need for approaches to nest information within multiple scales and sectors, engagement and collaboration of end users in scenario development, and development of integrated scenarios. Future assessments would benefit from an earlier start to scenarios development, the provision of training in addition to guidance documents, new and flexible approaches for nesting information, ongoing engagement and advice from both scientific and end user communities, and the development of consistent and integrated scenarios.}, number={1}, journal={CLIMATIC CHANGE}, author={Kunkel, Kenneth E. and Moss, Richard and Parris, Adam}, year={2016}, month={Mar}, pages={55–68} }
 @article{janssen_sriver_wuebbles_kunkel_2016, title={Seasonal and regional variations in extreme precipitation event frequency using CMIP5}, volume={43}, ISSN={["1944-8007"]}, DOI={10.1002/2016gl069151}, abstractNote={Abstract Understanding how the frequency and intensity of extreme precipitation events are changing is important for regional risk assessments and adaptation planning. Here we use observational data and an ensemble of climate change model experiments (from the Coupled Model Intercomparison Project Phase 5 (CMIP5)) to examine past and potential future seasonal changes in extreme precipitation event frequency over the United States. Using the extreme precipitation index as a metric for extreme precipitation change, we find key differences between models and observations. In particular, the CMIP5 models tend to overestimate the number of spring events and underestimate the number of summer events. This seasonal shift in the models is amplified in projections. These results provide a basis for evaluating climate model skill in simulating observed seasonality and changes in regional extreme precipitation. Additionally, we highlight key sources of variability and uncertainty that can potentially inform regional impact analyses and adaptation planning.}, number={10}, journal={GEOPHYSICAL RESEARCH LETTERS}, author={Janssen, E. and Sriver, R. L. and Wuebbles, D. J. and Kunkel, K. E.}, year={2016}, month={May}, pages={5385–5393} }
 @article{kunkel_robinson_champion_yin_estilow_frankson_2016, title={Trends and Extremes in Northern Hemisphere Snow Characteristics}, volume={2}, ISSN={2198-6061}, url={http://dx.doi.org/10.1007/S40641-016-0036-8}, DOI={10.1007/S40641-016-0036-8}, abstractNote={Recent studies of snow climatology show a mix of trends but a preponderance of evidence suggest an overall tendency toward decreases in several metrics of snow extremes. The analysis performed herein on maximum seasonal snow depth points to a robust negative trend in this variable for the period of winter 1960/1961–winter 2014/2015. This conclusion is applicable to North America. Maximum snow depth is also mostly decreasing for those European stations analyzed. Research studies show generally negative trends in snow cover extent and snow water equivalent across both North America and Eurasia. These results are mostly, but not fully, consistent with simple hypotheses for the effects of global warming on snow characteristics.}, number={2}, journal={Current Climate Change Reports}, publisher={Springer Science and Business Media LLC}, author={Kunkel, Kenneth E. and Robinson, David A. and Champion, Sarah and Yin, Xungang and Estilow, Thomas and Frankson, Rebekah M.}, year={2016}, month={Apr}, pages={65–73} }
 @article{jacobs_moore_kunkel_sun_2015, title={A framework for examining climate-driven changes to the seasonality and geographical range of coastal pathogens and harmful algae}, volume={8}, ISSN={2212-0963}, url={http://dx.doi.org/10.1016/J.CRM.2015.03.002}, DOI={10.1016/J.CRM.2015.03.002}, abstractNote={Abstract Climate change is expected to alter coastal ecosystems in ways which may have predictable consequences for the seasonality and geographical distribution of human pathogens and harmful algae. Here we demonstrate relatively simple approaches for evaluating the risk of occurrence of pathogenic bacteria in the genus Vibrio and outbreaks of toxin-producing harmful algae in the genus Alexandrium, with estimates of uncertainty, in U.S. coastal waters under future climate change scenarios through the end of the 21st century. One approach forces empirical models of growth, abundance and the probability of occurrence of the pathogens and algae at specific locations in the Chesapeake Bay and Puget Sound with ensembles of statistically downscaled climate model projections to produce first order assessments of changes in seasonality. In all of the case studies examined, the seasonal window of occurrence for Vibrio and Alexandrium broadened, indicating longer annual periods of time when there is increased risk for outbreaks. A second approach uses climate model projections coupled with GIS to identify the potential for geographic range shifts for Vibrio spp. in the coastal waters of Alaska. These two approaches could be applied to other coastal pathogens that have climate sensitive drivers to investigate potential changes to the risk of outbreaks in both time (seasonality) and space (geographical distribution) under future climate change scenarios.}, journal={Climate Risk Management}, publisher={Elsevier BV}, author={Jacobs, John and Moore, Stephanie K. and Kunkel, Kenneth E. and Sun, Liqiang}, year={2015}, pages={16–27} }
 @article{kibler_tester_kunkel_moore_litaker_2015, title={Effects of ocean warming on growth and distribution of dinoflagellates associated with ciguatera fish poisoning in the Caribbean}, volume={316}, ISSN={["1872-7026"]}, DOI={10.1016/j.ecolmodel.2015.08.020}, abstractNote={Projected water temperatures at six sites in the Gulf of Mexico and Caribbean Sea were used to forecast potential effects of climate change on the growth, abundance and distribution of Gambierdiscus and Fukuyoa species, dinoflagellates associated with ciguatera fish poisoning (CFP). Data from six sites in the Greater Caribbean were used to create statistically downscaled projections of water temperature using an ensemble of eleven global climate models and simulation RCP6.0 from the WCRP Coupled Model Intercomparison Project Phase 5 (CMIP5). Growth rates of five dinoflagellate species were estimated through the end of the 21st century using experimentally derived temperature vs. growth relationships for multiple strains of each species. The projected growth rates suggest the distribution and abundance of CFP-associated dinoflagellate species will shift substantially through 2099. Rising water temperatures are projected to increase the abundance and diversity of Gambierdiscus and Fukuyoa species in the Gulf of Mexico and along the U.S. southeast Atlantic coast. In the Caribbean Sea, where the highest average temperatures correlate with the highest rates of CFP, it is projected that Gambierdiscus caribaeus, Gambierdiscus belizeanus and Fukuyoa ruetzleri will become increasingly dominant. Conversely, the lower temperature-adapted species Gambierdiscus carolinianus and Gambierdiscus ribotype 2 are likely to become less prevalent in the Caribbean Sea and are expected to expand their ranges in the northern Gulf of Mexico and farther into the western Atlantic. The risks associated with CFP are also expected to change regionally, with higher incidence rates in the Gulf of Mexico and U.S. southeast Atlantic coast, with stable or slightly lower risks in the Caribbean Sea.}, journal={ECOLOGICAL MODELLING}, author={Kibler, Steven R. and Tester, Patricia A. and Kunkel, Kenneth E. and Moore, Stephanie K. and Litaker, R. Wayne}, year={2015}, month={Nov}, pages={194–210} }
 @article{kunkel_vose_stevens_knight_2015, title={Is the monthly temperature climate of the United States becoming more extreme?}, volume={42}, ISSN={["1944-8007"]}, DOI={10.1002/2014gl062035}, abstractNote={Abstract A new data set of monthly temperatures, adjusted for detected inhomogeneities, was used to examine whether the monthly temperature climate of the U.S. has become more extreme. During the past two to three decades, there has been a shift toward more frequent very warm months, but less frequent very cold months. Thus, overall the monthly temperature climate has not become more extreme. Midtwentieth century including the 1930s was an earlier period of frequent very warm months, a result of very warm daytime temperatures, while nighttime temperatures were not unusual. Regionally, there is a lack of century‐scale warming in the southeast U.S. annually and in parts of the central U.S. in the summer, characterized by lack of daytime warming while there has been nighttime warming. Compared to the earlier midcentury warm period, recent decades have been more (less) extreme in the summer (winter) in the west while Midwest summers have been less extreme.}, number={2}, journal={GEOPHYSICAL RESEARCH LETTERS}, author={Kunkel, Kenneth E. and Vose, Russell S. and Stevens, Laura E. and Knight, Richard W.}, year={2015}, month={Jan}, pages={629–636} }
 @misc{kossin_karl_knutson_emanuel_kunkel_o'brien_2015, title={Reply to "Comments on 'Monitoring and Understanding Trends in Extreme Storms: State of Knowledge'"}, volume={96}, ISSN={["1520-0477"]}, DOI={10.1175/bams-d-14-00261.1}, number={7}, journal={BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY}, author={Kossin, James P. and Karl, Thomas R. and Knutson, Thomas R. and Emanuel, Kerry A. and Kunkel, Kenneth E. and O'Brien, James J.}, year={2015}, month={Jul} }
 @article{frei_kunkel_matonse_2015, title={The Seasonal Nature of Extreme Hydrological Events in the Northeastern United States}, volume={16}, ISSN={["1525-7541"]}, DOI={10.1175/jhm-d-14-0237.1}, abstractNote={Abstract Recent analyses of extreme hydrological events across the United States, including those summarized in the recent U.S. Third National Climate Assessment (May 2014), show that extremely large (extreme) precipitation and streamflow events are increasing over much of the country, with particularly steep trends over the northeastern United States. The authors demonstrate that the increase in extreme hydrological events over the northeastern United States is primarily a warm season phenomenon and is caused more by an increase in frequency than magnitude. The frequency of extreme warm season events peaked during the 2000s; a secondary peak occurred during the 1970s; and the calmest decade was the 1960s. Cold season trends during the last 30–50 yr are weaker. Since extreme precipitation events in this region tend to be larger during the warm season than during the cold season, trend analyses based on annual precipitation values are influenced more by warm season than by cold season trends. In contrast, the magnitude of extreme streamflow events at stations used for climatological analyses tends to be larger during the cold season: therefore, extreme event analyses based on annual streamflow values are overwhelmingly influenced by cold season, and therefore weaker, trends. These results help to explain an apparent discrepancy in the literature, whereby increasing trends in extreme precipitation events appear to be significant and ubiquitous across the region, while trends in streamflow appear less dramatic and less spatially coherent.}, number={5}, journal={JOURNAL OF HYDROMETEOROLOGY}, author={Frei, Allan and Kunkel, Kenneth E. and Matonse, Adao}, year={2015}, month={Oct}, pages={2065–2085} }
 @article{janssen_wuebbles_kunkel_olsen_goodman_2014, title={Observational- and model-based trends and projections of extreme precipitation over the contiguous United States}, volume={2}, ISSN={2328-4277}, url={http://dx.doi.org/10.1002/2013EF000185}, DOI={10.1002/2013EF000185}, abstractNote={Historical and projected trends in extreme precipitation events are examined in Coupled Model Intercomparison Project 5 (CMIP5) models and observations, over the contiguous United States (CONUS), using several approaches. This study updates earlier studies that have used the extreme precipitation index (EPI) to assess observations and goes further by using the EPI to evaluate available climate model simulations. An increasing trend over the CONUS was found in the EPI, with large differences among seven subregions of the United States. Median of CMIP5 simulations also finds an increasing trend in the EPI, but with a smaller magnitude than the observations. Model spread is large and in most cases bigger than the model signal itself. Statistically significant (95th confidence level) increasing trends in the observational-based EPI occur over the Midwest and Eastern regions, while most decreasing trends occur over Western regions. Some models give negative correlation coefficients relative to observations. However, some ensemble members, for most models, show correlation coefficients greater than 0.5. Projections of extreme precipitation event frequency, for representative concentration pathway (RCP) scenarios 4.5 and 8.5, show increasing trends over the CONUS. Both scenarios give a steady increase throughout the period but the RCP 4.5 signal is smaller in magnitude. Overall, the RCP scenarios show an increase across all regions with the exception of some variability between decades in some regions for RCP 4.5. For the CONUS model spread is smaller than the projected signal. Regional analyses show overall agreement among models of a future increase in extreme precipitation event frequency over most regions.}, number={2}, journal={Earth's Future}, publisher={American Geophysical Union (AGU)}, author={Janssen, Emily and Wuebbles, Donald J. and Kunkel, Kenneth E. and Olsen, Seth C. and Goodman, Alex}, year={2014}, month={Feb}, pages={99–113} }
 @article{peterson_karl_kossin_kunkel_lawrimore_mcmahon_vose_yin_2013, title={Changes in weather and climate extremes: State of knowledge relevant to air and water quality in the United States}, volume={64}, ISSN={1096-2247 2162-2906}, url={http://dx.doi.org/10.1080/10962247.2013.851044}, DOI={10.1080/10962247.2013.851044}, abstractNote={Air and water quality are impacted by extreme weather and climate events on time scales ranging from minutes to many months. This review paper discusses the state of knowledge of how and why extreme events are changing and are projected to change in the future. These events include heat waves, cold waves, floods, droughts, hurricanes, strong extratropical cyclones such as nor'easters, heavy rain, and major snowfalls. Some of these events, such as heat waves, are projected to increase, while others, with cold waves being a good example, will decrease in intensity in our warming world. Each extreme's impact on air or water quality can be complex and can even vary over the course of the event.}, number={2}, journal={Journal of the Air & Waste Management Association}, publisher={Informa UK Limited}, author={Peterson, Thomas C. and Karl, Thomas R. and Kossin, James P. and Kunkel, Kenneth E. and Lawrimore, Jay H. and McMahon, James R. and Vose, Russell S. and Yin, Xungang}, year={2013}, month={Oct}, pages={184–197} }
 @article{kunkel_karl_brooks_kossin_lawrimore_arndt_bosart_changnon_cutter_doesken_et al._2013, title={Monitoring and understanding trends in extreme storms state of knowledge}, volume={94}, number={4}, journal={Bulletin of the American Meteorological Society}, author={Kunkel, K. E. and Karl, T. R. and Brooks, H. and Kossin, J. and Lawrimore, J. H. and Arndt, D. and Bosart, L. and Changnon, D. and Cutter, S. L. and Doesken, N. and et al.}, year={2013}, pages={499–514} }
 @article{kunkel_karl_easterling_redmond_young_yin_hennon_2013, title={Probable maximum precipitation and climate change}, volume={40}, ISSN={["1944-8007"]}, DOI={10.1002/grl.50334}, abstractNote={[1] Probable maximum precipitation (PMP) is the greatest accumulation of precipitation for a given duration meteorologically possible for an area. Climate change effects on PMP are analyzed, in particular, maximization of moisture and persistent upward motion, using both climate model simulations and conceptual models of relevant meteorological systems. Climate model simulations indicate a substantial future increase in mean and maximum water vapor concentrations. For the RCP8.5 scenario, the changes in maximum values for the continental United States are approximately 20%–30% by 2071–2100. The magnitudes of the maximum water vapor changes follow temperature changes with an approximate Clausius-Clapeyron relationship. Model-simulated changes in maximum vertical and horizontal winds are too small to offset water vapor changes. Thus, our conclusion is that the most scientifically sound projection is that PMP values will increase in the future due to higher levels of atmospheric moisture content and consequent higher levels of moisture transport into storms.}, number={7}, journal={GEOPHYSICAL RESEARCH LETTERS}, author={Kunkel, Kenneth E. and Karl, Thomas R. and Easterling, David R. and Redmond, Kelly and Young, John and Yin, Xungang and Hennon, Paula}, year={2013}, month={Apr} }
 @article{liang_xu_gao_reddy_kunkel_schmoldt_samel_2012, title={A Distributed Cotton Growth Model Developed from GOSSYM and Its Parameter Determination}, volume={104}, ISSN={["1435-0645"]}, DOI={10.2134/agronj2011.0250}, abstractNote={Prediction of cotton ( Gossypium hirsutum L.) production under a changing climate requires a coupled modeling system that represents climate–cotton interactions. The existing cotton growth model GOSSYM has drawbacks that prohibit its effective coupling with climate models. We developed a geographically distributed cotton growth model from the original GOSSYM and optimized it for coupling with the regional Climate–Weather Research Forecasting model (CWRF). This included software redesign, physics improvement, and parameter specification for consistent coupling of CWRF and GOSSYM. Through incorporation of the best available physical representations and observational estimates, the long list of inputs in the original GOSSYM was reduced to two parameters, the initial NO 3 amount in the top 2 m of soil and the ratio of irrigated water amount to potential evapotranspiration. The geographic distributions of these two parameters are determined by optimization that minimizes model errors in simulating cotton yields. The result shows that the redeveloped GOSSYM realistically reproduces the geographic distribution of mean cotton yields in 30‐km grids, within ± 10% of observations across most of the U.S. Cotton Belt, whereas the original GOSSYM overestimated yields by 27 to 135% at the state level and 92% overall. Both models produced interannual yield variability with comparable magnitude; however, the temporal correspondence between modeled and observed interannual anomalies was much more realistic in the redeveloped than the original GOSSYM because significant ( P = 0.05) correlations were identified in 87 and 40% of harvest grids, respectively. The redeveloped GOSSYM provides a starting point for additional improvements and applications of the coupled CWRF–GOSSYM system to study climate–cotton interactions.}, number={3}, journal={AGRONOMY JOURNAL}, author={Liang, Xin-Zhong and Xu, Min and Gao, Wei and Reddy, K. Raja and Kunkel, Kenneth and Schmoldt, Daniel L. and Samel, Arthur N.}, year={2012}, pages={661–674} }
 @article{kunkel_easterling_kristvich_gleason_stoecker_smith_2012, title={Meteorological Causes of the Secular Variations in Observed Extreme Precipitation Events for the Conterminous United States}, volume={13}, ISSN={["1525-755X"]}, DOI={10.1175/jhm-d-11-0108.1}, abstractNote={Abstract Daily extreme precipitation events, exceeding a threshold for a 1-in-5-yr occurrence, were identified from a network of 935 Cooperative Observer stations for the period of 1908–2009. Each event was assigned a meteorological cause, categorized as extratropical cyclone near a front (FRT), extratropical cyclone near center of low (ETC), tropical cyclone (TC), mesoscale convective system (MCS), air mass (isolated) convection (AMC), North American monsoon (NAM), and upslope flow (USF). The percentage of events ascribed to each cause were 54% for FRT, 24% for ETC, 13% for TC, 5% for MCS, 3% for NAM, 1% for AMC, and 0.1% for USF. On a national scale, there are upward trends in events associated with fronts and tropical cyclones, but no trends for other meteorological causes. On a regional scale, statistically significant upward trends in the frontal category are found in five of the nine regions. For ETCs, there are statistically significant upward trends in the Northeast and east north central. For the NAM category, the trend in the West is upward. The central region has seen an upward trend in events caused by TCs.}, number={3}, journal={JOURNAL OF HYDROMETEOROLOGY}, author={Kunkel, Kenneth E. and Easterling, David R. and Kristvich, David A. R. and Gleason, Byron and Stoecker, Leslie and Smith, Rebecca}, year={2012}, month={Jun}, pages={1131–1141} }
 @article{liang_xu_gao_reddy_kunkel_schmoldt_samel_2012, title={Physical Modeling of US Cotton Yields and Climate Stresses during 1979 to 2005}, volume={104}, ISSN={["0002-1962"]}, DOI={10.2134/agronj2011.0251}, abstractNote={Climate variability and changes affect crop yields by causing climatic stresses during various stages of the plant life cycle. A crop growth model must be able to capture the observed relationships between crop yields and climate stresses before its credible use as a prediction tool. This study evaluated the ability of the geographically distributed cotton growth model redeveloped from GOSSYM in simulating U.S. cotton ( Gossypium hirsutum L.) yields and their responses to climate stresses during 1979 to 2005. Driven by realistic climate conditions, the model reproduced long‐term mean cotton yields within ± 10% of observations at the 30‐km model resolution across virtually the entire U.S. Cotton Belt and correctly captured the critical dependence of their geographic distributions on regional climate characteristics. Significant correlations between simulated and observed interannual variations were found across 87% of the total harvest grids. The model also faithfully represented the predictive role of July to August air temperature and August to September soil temperature anomalies on interannual cotton yield changes on unirrigated lands, with a similar but weaker predictive signal for irrigated lands as observed. The modeled cotton yields exhibited large, positive correlations with July to August leaf area index. These results indicate the model's ability to depict the regional impact of climate stresses on cotton yields and suggest the potential predictive value of satellite retrievals. They also provide a baseline reference for further model improvements and applications in the future study of climate–cotton interactions.}, number={3}, journal={AGRONOMY JOURNAL}, author={Liang, Xin-Zhong and Xu, Min and Gao, Wei and Reddy, K. Raja and Kunkel, Kenneth and Schmoldt, Daniel L. and Samel, Arthur N.}, year={2012}, pages={675–683} }
 @article{liang_xu_yuan_ling_choi_zhang_chen_liu_su_qiao_et al._2012, title={REGIONAL CLIMATE-WEATHER RESEARCH AND FORECASTING MODEL}, volume={93}, ISSN={["1520-0477"]}, DOI={10.1175/bams-d-11-00180.1}, abstractNote={The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.}, number={9}, journal={BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY}, author={Liang, Xin-Zhong and Xu, Min and Yuan, Xing and Ling, Tiejun and Choi, Hyun I. and Zhang, Feng and Chen, Ligang and Liu, Shuyan and Su, Shenjian and Qiao, Fengxue and et al.}, year={2012}, month={Sep}, pages={1363–1387} }
 @article{kunkel_easterling_kristovich_gleason_stoecker_smith_2010, title={Recent increases in U.S. heavy precipitation associated with tropical cyclones}, volume={37}, ISSN={["0094-8276"]}, DOI={10.1029/2010gl045164}, abstractNote={Precipitation time series for 935 long‐term U.S. climate stations were analyzed to identify daily extreme events associated with tropical cyclones (TCs). Extremes were defined as daily amounts exceeding a threshold for a 1 in 5‐yr occurrence. TCs account for 30% or more of all such extreme events at a number of stations and about 6% of the national annual total. During 1994–2008, the number of TC‐associated events was more than double the long‐term average while the total annual national number of events was about 25% above the long‐term (1895–2008) average. Despite the limited spatial area and portion of the annual cycle affected by TCs, the anomalous number of events associated with TCs accounted for over one‐third of the overall national anomaly for 1994–2008. While there has been a recent increase in the number of landfalling U.S. hurricances, the increase in TC‐associated heavy events is much higher than would be expected from the pre‐1994 association between the two.}, journal={GEOPHYSICAL RESEARCH LETTERS}, author={Kunkel, Kenneth E. and Easterling, David R. and Kristovich, David A. R. and Gleason, Byron and Stoecker, Leslie and Smith, Rebecca}, year={2010}, month={Dec} }
 @article{angel_kunkel_2010, title={The response of Great Lakes water levels to future climate scenarios with an emphasis on Lake Michigan-Huron}, volume={36}, ISSN={0380-1330}, url={http://dx.doi.org/10.1016/j.jglr.2009.09.006}, DOI={10.1016/j.jglr.2009.09.006}, abstractNote={Future climate change and its impact on Lake Michigan is an important issue for water supply planning in Illinois. To estimate possible future levels of the Great Lakes due to climate change, the output of 565 model runs from 23 Global Climate Models were applied to a lake-level model developed by the Great Lakes Environmental Research Laboratory (GLERL). In this study, three future emission scenarios were considered: the B1, A1B, and A2 emission scenarios representing relatively low, moderate, and high emissions, respectively. The results showed that the A2 emission scenario yielded the largest changes in lake levels of the three emission scenarios. Of the three periods examined, lake levels in 2080–2094 exhibited the largest changes. The response of Lake Superior was the smallest of the Great Lakes, while lakes Michigan-Huron, Erie, and Ontario were similar in their response over time and between emission scenarios. For Lake Michigan-Huron, the median changes in lake levels at 2080–2094 were − 0.25, − 0.28, and − 0.41 m for the B1, A1B, and A2 emission scenarios, respectively. However, the range in lake levels was considerable. The wide range of results is due to the differences in emission scenarios and the uncertainty in the model simulations. Selecting model simulations based on their historical performance does little to reduce the uncertainty. The wide range of lake-level changes found here make it difficult to envision the level of impacts that change in future lake levels would cause.}, journal={Journal of Great Lakes Research}, publisher={Elsevier BV}, author={Angel, James R. and Kunkel, Kenneth E.}, year={2010}, month={Jan}, pages={51–58} }
 @article{kunkel_ensor_palecki_easterling_robinson_hubbard_redmond_2009, title={A new look at lake-effect snowfall trends in the Laurentian Great Lakes using a temporally homogeneous data set}, volume={35}, ISSN={0380-1330}, url={http://dx.doi.org/10.1016/j.jglr.2008.11.003}, DOI={10.1016/j.jglr.2008.11.003}, abstractNote={Snowfall data are subject to quality issues that affect their usefulness for detection of climate trends. A new analysis of lake-effect snowfall trends utilizes a restricted set of stations identified as suitable for trends analysis based on a careful quality assessment of long-term observation stations in the lake-effect snowbelts of the Laurentian Great Lakes. An upward trend in snowfall was found in two (Superior and Michigan) of the four snowbelt areas. The trends for Lakes Erie and Ontario depended on the period of analysis. Although these results are qualitatively similar to outcomes of other recent studies, the magnitude of the upward trend is about half as large as trends in previous findings. The upward trend in snowfall was accompanied by an upward trend in liquid water equivalent for Superior and Michigan, while no trend was observed for Erie and Ontario. Air temperature has also trended upward for Superior and Michigan, suggesting that warmer surface waters and less ice cover are contributing to the upward snowfall trends by enhancing lake heat and moisture fluxes during cold air outbreaks. However, a more comprehensive study is needed to definitely determine cause and effect. Overall, this study finds that trends in lake-effect snowfall are not as large as was believed based on prior research.}, number={1}, journal={Journal of Great Lakes Research}, publisher={Elsevier BV}, author={Kunkel, Kenneth E. and Ensor, Leslie and Palecki, Michael and Easterling, David and Robinson, David and Hubbard, Kenneth G. and Redmond, Kelly}, year={2009}, month={Mar}, pages={23–29} }
 @article{pryor_howe_kunkel_2009, title={How spatially coherent and statistically robust are temporal changes in extreme precipitation in the contiguous USA?}, volume={29}, ISSN={0899-8418 1097-0088}, url={http://dx.doi.org/10.1002/joc.1696}, DOI={10.1002/joc.1696}, abstractNote={Century-long precipitation records from stations in the contiguous USA indicate an increased frequency of rainy days over the past century and some evolution in the probability distributions of precipitation amount. Temporal trends in eight metrics of the precipitation climate are of similar magnitude and sign regardless of whether they are derived from bootstrapping of regression residuals or using the Kendall's tau statistic, though the bootstrap technique generally resolved a larger number of ‘significant’ trends. There is substantial variability in terms of the magnitude, significance and sign of the linear trends with specific metrics, and they are sensitive to recording bias of light precipitation events in the early part of the 20th century. The majority of stations that exhibit significant linear trends show evidence of increases in the intensity of events above the 95th percentile. The resolved trends tend to have a larger magnitude at the end of the century. Spatial variability as manifest in the spatial autocorrelation in the interannual variability and trends in extreme metrics is manifest at a range of scales, but in general the correlation between stations is significant only for separation of distances of a few tens of kilometres. The largest trends towards increased annual total precipitation, number of rainy days and intense precipitation (e.g. fraction of precipitation derived from events in excess of the 90th percentile value) are focussed on the Central Plains/northwestern Midwest. Copyright © 2008 Royal Meteorological Society}, number={1}, journal={International Journal of Climatology}, publisher={Wiley}, author={Pryor, S. C. and Howe, J. A. and Kunkel, K. E.}, year={2009}, month={Jan}, pages={31–45} }
 @article{huang_lin_tao_choi_patten_kunkel_xu_zhu_liang_williams_et al._2008, title={Impacts of long-range transport of global pollutants and precursor gases on U.S. air quality under future climatic conditions}, volume={113}, ISSN={0148-0227}, url={http://dx.doi.org/10.1029/2007JD009469}, DOI={10.1029/2007JD009469}, abstractNote={[1] The U.S. air quality is impacted by emissions both within and outside the United States. The latter impact is manifested as long-range transport (LRT) of pollutants across the U.S. borders, which can be simulated by lateral boundary conditions (LBC) into a regional modeling system. This system consists of a regional air quality model (RAQM) that integrates local-regional source emissions and chemical processes with remote forcing from the LBC predicted by a nesting global chemical transport model (model for ozone and related chemical tracers (MOZART)). The present-day simulations revealed important LRT effects, varying among the five major regions with ozone problems, i.e., northeast United States, midwest United States, Texas, California, and southeast United States. To determine the responses of the LRT impacts to projected global climate and emissions changes, the MOZART and RAQM simulations were repeated for future periods (2048–2052 and 2095–2099) under two emissions scenarios (IPCC A1Fi and B1). The future U.S. air quality projected by the MOZART is less sensitive to the emissions scenarios than that simulated by the RAQM with or without incorporating the LRT effects via the LBC from the MOZART. The result of RAQM with the LRT effects showed that the southeast United States has the largest sensitivity of surface ozone mixing ratio to the emissions changes in the 2095–2099 climate (−24% to +25%) followed by the northeast and midwest United States. The net increase due to the LRT effects in 2095–2099 ranges from +4% to +13% in daily mean surface ozone mixing ratio and +4% to +11% in mean daily maximum 8-h average ozone mixing ratios. Correspondingly, the LRT effects in 2095–2099 cause total column O3 mixing ratio increases, ranging from +7% to +16%, and also 2 to 3 more days with the surface ozone exceeding the national standard. The results indicate that future U.S. air quality changes will be substantially affected by global emissions.}, number={D19}, journal={Journal of Geophysical Research}, publisher={American Geophysical Union (AGU)}, author={Huang, Ho-Chun and Lin, Jintai and Tao, Zhining and Choi, Hyun and Patten, Kenneth and Kunkel, Kenneth and Xu, Min and Zhu, Jinhong and Liang, Xin-Zhong and Williams, Allen and et al.}, year={2008}, month={Oct} }
 @article{liang_kunkel_meehl_jones_wang_2008, title={Regional climate models downscaling analysis of general circulation models present climate biases propagation into future change projections}, volume={35}, ISSN={0094-8276}, url={http://dx.doi.org/10.1029/2007GL032849}, DOI={10.1029/2007GL032849}, abstractNote={[1] A suite of eighteen simulations over the U.S. and Mexico, representing combinations of two mesoscale regional climate models (RCMs), two driving global general circulation models (GCMs), and the historical and four future anthropogenic forcings were intercompared. The RCMs' downscaling reduces significantly driving GCMs' present-climate biases and narrows inter-model differences in representing climate sensitivity and hence in simulating the present and future climates. Very high spatial pattern correlations of the RCM minus GCM differences in precipitation and surface temperature between the present and future climates indicate that major model present-climate biases are systematically propagated into future-climate projections at regional scales. The total impacts of the biases on trend projections also depend strongly on regions and cannot be linearly removed. The result suggests that the nested RCM-GCM approach that offers skill enhancement in representing the present climate also likely provides higher credibility in downscaling the future climate projection.}, number={8}, journal={Geophysical Research Letters}, publisher={American Geophysical Union (AGU)}, author={Liang, Xin-Zhong and Kunkel, Kenneth E. and Meehl, Gerald A. and Jones, Richard G. and Wang, Julian X. L.}, year={2008}, month={Apr} }
 @article{kunkel_huang_liang_lin_wuebbles_tao_williams_caughey_zhu_hayhoe_2008, title={Sensitivity of future ozone concentrations in the northeast USA to regional climate change}, volume={13}, ISSN={1381-2386 1573-1596}, url={http://dx.doi.org/10.1007/S11027-007-9137-Y}, DOI={10.1007/S11027-007-9137-Y}, abstractNote={An air quality modeling system was used to simulate the effects on ozone concentration in the northeast USA from climate changes projected through the end of the twenty-first century by the National Center for Atmospheric Research’s (NCAR’s) parallel climate model, a fully coupled general circulation model, under a higher and a lower scenario of future global changes in concentrations of radiatively active constituents. The air quality calculations were done with both a global chemistry-transport model and a regional air quality model focused on the northeast USA. The air quality simulations assumed no changes in regional anthropogenic emissions of the chemical species primarily involved in the chemical reactions of ozone creation and destruction, but only accounted for changes in the climate. Together, these idealized global and regional model simulations provide insights into the contribution of possible future climate changes on ozone. Over the coming century, summer climate is projected to be warmer and less cloudy for the northeast USA. These changes are considerably larger under the higher scenario as compared with the lower. Higher temperatures also increase biogenic emissions. Both mean daily and 8-h maximum ozone increase from the combination of three factors that tend to favor higher concentrations: (1) higher temperatures change the rates of reactions and photolysis rates important to the ozone chemistry; (2) lower cloudiness (higher solar radiation) increases the photolysis reaction rates; and (3) higher biogenic emissions increase the concentration of reactive species. Regional model simulations with two cumulus parameterizations produce ozone concentration changes that differ by approximately 10%, indicating that there is considerable uncertainty in the magnitude of changes due to uncertainties in how physical processes should be parameterized in the models. However, the overall effect of the climate changes simulated by these models – in the absence of reductions in regional anthropogenic emissions – would be to increase ozone concentrations.}, number={5-6}, journal={Mitigation and Adaptation Strategies for Global Change}, publisher={Springer Science and Business Media LLC}, author={Kunkel, K. E. and Huang, H.-C. and Liang, X.-Z. and Lin, J.-T. and Wuebbles, D. and Tao, Z. and Williams, A. and Caughey, M. and Zhu, J. and Hayhoe, K.}, year={2008}, month={Jun}, pages={597–606} }
 @article{liang_pan_zhu_kunkel_wang_dai_2006, title={Regional climate model downscaling of the U.S. summer climate and future change}, volume={111}, ISSN={0148-0227}, url={http://dx.doi.org/10.1029/2005JD006685}, DOI={10.1029/2005JD006685}, abstractNote={A mesoscale model (MM5)–based regional climate model (CMM5) integration driven by the Parallel Climate Model (PCM), a fully coupled atmosphere‐ocean‐land‐ice general circulation model (GCM), for the present (1986–1995) summer season climate is first compared with observations to study the CMM5's downscaling skill and uncertainty over the United States. The results indicate that the CMM5, with its finer resolution (30 km) and more comprehensive physics, simulates the present U.S. climate more accurately than the driving PCM, especially for precipitation, including summer mean patterns, diurnal cycles, and daily frequency distributions. Hence the CMM5 downscaling provides a credible means to improve GCM climate simulations. A parallel CMM5 integration driven by the PCM future (2041–2050) projection is then analyzed to determine the downscaling impact on regional climate changes. It is shown that the CMM5 generates climate change patterns very different from those predicted by the driving PCM. A key difference is a summer “warming hole” over the central United States in the CMM5 relative to the PCM. This study shows that the CMM5 downscaling can significantly reduce GCM biases in simulating the present climate and that this improvement has important consequences for future projections of regional climate changes. For both the present and future climate simulations, the CMM5 results are sensitive to the cumulus parameterization, with strong regional dependence. The deficiency in representing convection is likely the major reason for the PCM's unrealistic simulation of U.S. precipitation patterns and perhaps also for its large warming in the central United States.}, number={D10}, journal={Journal of Geophysical Research: Atmospheres}, publisher={American Geophysical Union (AGU)}, author={Liang, Xin-Zhong and Pan, Jianping and Zhu, Jinhong and Kunkel, Kenneth E. and Wang, Julian X. L. and Dai, Aiguo}, year={2006}, month={May}, pages={n/a-n/a} }
 @article{woodhouse_kunkel_easterling_cook_2005, title={The twentieth-century pluvial in the western United States}, volume={32}, ISSN={0094-8276}, url={http://dx.doi.org/10.1029/2005GL022413}, DOI={10.1029/2005GL022413}, abstractNote={[1] Persistent, widespread wet conditions in the western United States in the early twentieth century have been noted in a number of studies. Here, we investigate the character of this pluvial, which covered a roughly 9-state region and lasted about 13 years. Paleoclimatic data used to evaluate the period in a long-term context indicate that the twentieth-century pluvial is an extremely rare event, as previous studies have suggested, even when assessed in the context of a 1186-year reconstruction of regional drought. An analysis of twentieth-century climate data, characterizing precipitation seasonality, intensity, and frequency, shows that the pluvial was primarily a result of winter season, heavy to moderately heavy precipitation events, during a handful of extremely wet winters. Temperatures were also anomalously cool. The combination of duration, intensity, and spatial extent make this an unusual event, not only in twentieth century, but in the past 12 centuries.}, number={7}, journal={Geophysical Research Letters}, publisher={American Geophysical Union (AGU)}, author={Woodhouse, Connie A. and Kunkel, Kenneth E. and Easterling, David R. and Cook, Edward R.}, year={2005}, month={Apr}, pages={n/a-n/a} }
 @article{kunkel_2004, title={Temporal variations in frost-free season in the United States: 1895–2000}, volume={31}, ISSN={0094-8276}, url={http://dx.doi.org/10.1029/2003GL018624}, DOI={10.1029/2003GL018624}, abstractNote={[1] A newly available data set of daily temperature observations was used to study the temporal variability of the frost-free season, based on an inclusive 0°C threshold, for 1895-2000 in the conterminous United States. A national average time series of the length of the frost-free season is characterized by 3 distinct regimes. The period prior to 1930 was notable for decreasing frost-free season length from 1895 to a minimum around 1910, followed by a marked increase in length of about 1 week from 1910 to 1930. During 1930-1980, frost-free season length was near the period average with relatively little decadal-scale variability. Since 1980, frost-free season length has increased by about 1 week. The national average increase in frost-free season length from the beginning to the end of the 20th Century is about 2 weeks. Frost-free season length has increased much more in the western U.S. than in the eastern U.S.}, number={3}, journal={Geophysical Research Letters}, publisher={American Geophysical Union (AGU)}, author={Kunkel, Kenneth E.}, year={2004} }