@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{peng_matthews_wang_vose_sun_2020, title={What Do Global Climate Models Tell Us about Future Arctic Sea Ice Coverage Changes?}, volume={8}, ISSN={["2225-1154"]}, url={https://doi.org/10.3390/cli8010015}, DOI={10.3390/cli8010015}, abstractNote={The prospect of an ice-free Arctic in our near future due to the rapid and accelerated Arctic sea ice decline has brought about the urgent need for reliable projections of the first ice-free Arctic summer year (FIASY). Together with up-to-date observations and characterizations of Arctic ice state, they are essential to business strategic planning, climate adaptation, and risk mitigation. In this study, the monthly Arctic sea ice extents from 12 global climate models are utilized to obtain projected FIASYs and their dependency on different emission scenarios, as well as to examine the nature of the ice retreat projections. The average value of model-projected FIASYs is 2054/2042, with a spread of 74/42 years for the medium/high emission scenarios, respectively. The earliest FIASY is projected to occur in year 2023, which may not be realistic, for both scenarios. The sensitivity of individual climate models to scenarios in projecting FIASYs is very model-dependent. The nature of model-projected Arctic sea ice coverage changes is shown to be primarily linear. FIASY values predicted by six commonly used statistical models that were curve-fitted with the first 30 years of climate projections (2006–2035), on other hand, show a preferred range of 2030–2040, with a distinct peak at 2034 for both scenarios, which is more comparable with those from previous studies.}, number={1}, journal={CLIMATE}, publisher={MDPI AG}, author={Peng, Ge and Matthews, Jessica L. and Wang, Muyin and Vose, Russell and Sun, Liqiang}, year={2020}, month={Jan} }
 @article{dai_li_sun_2018, title={The Simulation of East Asian Summer Monsoon Precipitation With a Regional Ocean-Atmosphere Coupled Model}, volume={123}, ISSN={["2169-8996"]}, DOI={10.1029/2018JD028541}, abstractNote={AbstractA fully coupled regional ocean‐atmosphere model was used to simulate the East Asian summer monsoon (EASM) precipitation. This coupled regional climate modeling system consists of the Regional Spectral Model (RSM) for the atmosphere and the Regional Ocean Modeling System for the ocean. The ocean and atmosphere share the same horizontal grid resolution. The coupled model is forced by the National Centers for Environmental Prediction‐Department of Energy (R‐2) global atmospheric reanalysis and Simplified Ocean Data Assimilation global oceanic reanalysis through the lateral boundary. This study examines EASM surface oceanic state and precipitation variability from a 22‐year (1984–2005) integration with a horizontal resolution of 40 km. The coupled model captures the features of observed sea surface temperature (SST), sea surface height, and ocean surface currents. Compared with the control run of the uncoupled RSM forced with observed SSTs, the coupled model shows more realistic simulation of the EASM precipitation climatology. The coupled model also improves the simulation of precipitation variability at both interannual and intraseasonal scales. It is the coupled model, not the uncoupled RSM, represents the observed SST‐precipitation and SST‐evaporation relationships. This study indicates that the ocean‐atmosphere coupling is essential for model simulations of the EASM precipitation.}, number={20}, journal={JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES}, author={Dai, Yongjiu and Li, Haiqin and Sun, Liqiang}, year={2018}, month={Oct}, pages={11362–11376} }