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1. Linkage between Projected Precipitation and Atmospheric Thermodynamic Changes

   https://doi.org/10.1175/JCLI-D-19-0785.1  

   Chen, Jiao ; Dai, Aiguo ; Zhang, Yaocun ( August 2020 , Journal of Climate)

   null (Ed.)

   Abstract Light–moderate precipitation is projected to decrease whereas heavy precipitation may increase under greenhouse gas (GHG)-induced global warming, while atmospheric convective available potential energy (CAPE) over most of the globe and convective inhibition (CIN) over land are projected to increase. The underlying processes for these precipitation changes are not fully understood. Here, projected precipitation changes are analyzed using 3-hourly data from simulations by a fully coupled climate model, and their link to the CAPE and CIN changes is examined. The model approximately captures the spatial patterns in the mean precipitation frequencies and the significant correlation between the precipitation frequencies or intensity and CAPE over most of the globe or CIN over tropical oceans seen in reanalysis, and it projects decreased light–moderate precipitation (0.01 < P ≤ 1 mm h −1 ) but increased heavy precipitation ( P > 1 mm h −1 ) in a warmer climate. Results show that most of the light–moderate precipitation events occur under low-CAPE and/or low-CIN conditions, which are projected to decrease greatly in a warmer climate as increased temperature and humidity shift many of such cases into moderate–high CAPE or CIN cases. This results in large decreases in the light–moderate precipitation events. In contrast, increases in heavy precipitation result primarily from its increased probability under given CAPE and CIN, with a secondary contribution from the CAPE/CIN frequency changes. The increased probability for heavy precipitation partly results from a shift of the precipitation histogram toward higher intensity that could result from a uniform percentage increase in precipitation intensity due to increased water vapor in a warmer climate. 

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2. Extreme Precipitation Events in Alaska: Historical Trends and Projected Changes

   https://doi.org/10.3390/atmos13030388  

   Bachand, Claire L. ; Walsh, John E. ( March 2022 , Atmosphere)

   While recent increases in heavy precipitation events in some midlatitude regions are consistent with climate model simulations, evidence of such increases in high latitudes is more tenuous, partly because of data limitations. The present study evaluates historical and future changes in extreme precipitation events in Alaska. Using the ERA5 reanalysis, station data, and output from two downscaled global climate models, we examine precipitation-driven flood events at five diverse locations in Alaska where major historical floods provide benchmarks: Fairbanks (August 1967), Seward (October 1986), Allakaket/Bettles (August 1994), Kivalina (August 2012), and Haines (December 2020). We place these precipitation events into a framework of historical trends and end-of-century (2065–2100) model projections. In all but one of the flood events, the amount of rainfall was the highest on record for the event duration, and precipitation events of this magnitude are generally projected by the models to remain infrequent. All of the cases had subtropical or tropical moisture sources. None of the locations show statistically significant historical trends in the magnitude of extreme precipitation events. However, the frequencies of heavy precipitation events are projected to increase at most of the locations. The frequency of events with 2 year and 5 year historical return intervals is projected to become more frequent, especially in the Interior, and in some cases increase to several times per year. Decreases are projected only for Seward along Alaska’s southern coast. 

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3. Quantitative scenarios for future hydrologic extremes in the U.S. Southern Great Plains

   https://doi.org/10.1002/joc.5979  

   Mullens, Esther D. ; McPherson, Renee A. ( February 2019 , International Journal of Climatology)

   Decision‐makers using climate projection information are often faced with the problem of data breadth, complexity, and uncertainty, which complicates the translation of climate science products in addressing management challenges. Recently, the concept of climate scenario planning attempts to simplify climate information by developing a series of plausible future “storylines.” In some cases, however, these storylines lack quantitative detail on extremes that may be useful to decision‐makers. Here, we analyse a large suite of statistically downscaled climate projections from two methods to develop quantitative projections for hydrologic extremes (heavy precipitation and drought) across Oklahoma and Texas in the United States. Downscaled projections are grouped into four specific temperature/precipitation scenarios, including “Warm/Wet,” “Hot/Dry,” “Central Tendency,” and the full multi‐model ensemble average. The region is split into three sub‐domains spanning the region's west–east precipitation gradient, and projections are examined throughout the mid‐ and late‐21st century, using two emissions scenarios (“mid‐range” and “high”). Most scenarios project increased frequency and duration of moderate or greater drought across the whole domain, with the high‐emissions Hot/Dry projections showing the most severe examples. The Warm/Wet scenario also increases the frequency of dry months, particularly in the Southern High Plains, but does not discernably alter duration, and retains a similar frequency of pluvial (wet) periods. The mid‐range projections generally retain similar evolutions among scenarios, but they reduce drought intensity and project no change in drought/pluvial frequency with the Warm/Wet scenario. Notably, the occurrence of intense precipitation increases across all scenarios and emissions categories and does not significantly differ between any of the scenarios, including Hot/Dry versus Warm/Wet. Some observed differences in extreme precipitation magnitudes between the two downscaled data sets are briefly discussed.

    

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4. Heat wave Intensity Duration Frequency Curve: A Multivariate Approach for Hazard and Attribution Analysis

   https://doi.org/10.1038/s41598-019-50643-w  

   Mazdiyasni, Omid ; Sadegh, Mojtaba ; Chiang, Felicia ; AghaKouchak, Amir ( October 2019 , Scientific Reports)

   Atmospheric warming is projected to intensify heat wave events, as quantified by multiple descriptors, including intensity, duration, and frequency. While most studies investigate one feature at a time, heat wave characteristics are often interdependent and ignoring the relationships between them can lead to substantial biases in frequency (hazard) analyses. We propose a multivariate approach to construct heat wave intensity, duration, frequency (HIDF) curves, which enables the concurrent analysis of all heat wave properties. Here we show how HIDF curves can be used in various locations to quantitatively describe the likelihood of heat waves with different intensities and durations. We then employ HIDF curves to attribute changes in heat waves to anthropogenic warming by comparing GCM simulations with and without anthropogenic emissions. For example, in Los Angeles, CA, HIDF analysis shows that we can attribute the 21% increase in the likelihood of a four-day heat wave (temperature > 31 °C) to anthropogenic emissions.

    

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5. Spatiotemporal Evolution of Heat Wave Severity and Coverage Across the United States

   https://doi.org/10.1029/2020GL087097  

   Keellings, David ; Moradkhani, Hamid ( April 2020 , Geophysical Research Letters)

   Heat waves have pronounced impacts on human health, ecosystems, and society. Heat waves have become more frequent and intense globally and are likely to intensify further in a warming climate. Across the United States there is a warming trend in average surface temperatures, but concordant increase in heat wave severity appears absent. Limitations in heat waves studies may be responsible for limited detection of a heat wave warming signal. We track daily spatiotemporal evolution of heat waves using geometric concepts and clustering algorithms to investigate how heat manifests on the land surface. We develop a spatial metric combining heat wave frequency, magnitude, duration, and areal extent. We find mixed trends in some individual heat wave characteristics across the United States during 1981–2018. However, exploration of the spatiotemporal evolution of combined heat wave characteristics shows considerable increases during this period and indicates a substantial increase in heat wave hazard across the United States.

    

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