Exploring the Future of Rainfall Extremes Over CONUS: The Effects of High Emission Climate Change Trajectories on the Intensity and Frequency of Rare Precipitation Events

Emmanouil, Stergios; Langousis, Andreas; Nikolopoulos, Efthymios I.; Anagnostou, Emmanouil N.

doi:10.1029/2022ef003039

Cited by 7 publications

(3 citation statements)

References 106 publications

(166 reference statements)

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“…For example, Callitris columellaris radial growt Here we presented the first extreme precipitation reconstruction in the region and contextualized long-term changes in moisture during 1770-2020. Previous work has indicated the importance of intense and extreme precipitation on tree radial growth (e.g., [10,35]) and other measures of plant growth (e.g., [36][37][38]) during a period of increased intense rainfall events for most of the US (e.g., [14]), a trend that is projected to increase over time [39,40]. These results suggest that increases in precipitation could become more important for plant growth in future climate change scenarios, particularly as some studies find no negative threshold for increased growth with increasing intense rainfall event size [37].…”

Section: Discussionmentioning

confidence: 99%

Reconstructing Historical Intense and Total Summer Rainfall in Central North Carolina Using Tree-Ring Data (1770–2020)

Mitchell,

Knapp

2024

Water

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Contextualizing historic hydroclimate variability in the southeastern USA has relied significantly on proxy indicators such as tree-ring data, and while previous studies have reconstructed total precipitation, less is known about the historic variability of intense rainfall events, which are climatologically and ecologically important and distinct from non-intense rainfall events. Here, a combined longleaf pine and shortleaf pine adjusted latewood chronology spanning 1770–2020 was used to reconstruct July–September total precipitation and intense rainfall event precipitation in central North Carolina, USA. The adjusted latewood chronology explains 46% of the variance in July–September total precipitation and 37% of the variance in July–September intense rainfall event precipitation during the 1940–2020 instrumental period with intense rainfall event precipitation amounts comprising 52% of total precipitation amounts. The models provide context about historic hydroclimate variability at this location and suggest overall stability in both total and intense rainfall event precipitation amounts during the instrumental and reconstruction periods with three identical significant regime shifts during 1770–2020: 1770–1935, 1936–1959 (above-average moisture), 1960–2020 (below-average moisture). To compare model strength, the models were split into early (1940–1980) and late (1981–2020) analysis periods with the intense rainfall event precipitation model exhibiting greater skill during the early analysis period. The early analysis period has a greater frequency and magnitude of intense rainfall events, and these results suggest the influence of intense rainfall event precipitation on latewood growth and the potential susceptibility of reconstruction models to decreased skill and/or error with differing frequencies of extreme events, a finding of particular importance to future dendroclimatic research.

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Section: Discussionmentioning

confidence: 99%

Reconstructing Historical Intense and Total Summer Rainfall in Central North Carolina Using Tree-Ring Data (1770–2020)

Mitchell,

Knapp

2024

Water

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“…Recent flash floods in many countries showcase the direct impact of climate change on the hydrological cycle. Some countries are experiencing having higher and more intensified rainfalls [50][51][52][53] while some other countries are experiencing droughts [54][55][56][57] due to ongoing climate change. Each scenario is harmful or causes many adverse impacts on livelihood.…”

Section: Climate Change and Importance Of Flood Modelingmentioning

confidence: 99%

Evaluating the Efficacy of Different DEMs for Application in Flood Frequency and Risk Mapping of the Indian Coastal River Basin

Gangani,

Mangukiya,

Mehta

et al. 2023

Climate

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Floods are among the most occurring natural hazards that cause severe damage to infrastructure and loss of life. In India, southern Gujarat is affected during the monsoon season, facing multiple flood events in the Damanganga basin. As the basin is one of the data-scarce regions, evaluating the globally available dataset for flood risk mitigation studies in the Damanganga basin is crucial. In the present study, we compared four open-source digital elevation models (DEMs) (SRTM, Cartosat-1, ALOS-PALSAR, and TanDEMX) for hydrodynamic (HD) modeling and flood risk mapping. The simulated HD models for multiple flood events using HEC-RAS v6.3 were calibrated by adopting different roughness coefficients based on land-use land cover, observed water levels at gauge sites, and peak flood depths in the flood plain. In contrast to the previous studies on the Purna river basin (the neighboring basin of Damanganga), the present study shows that Cartosat-1 DEM provides reliable results with the observed flood depth. Furthermore, the calibrated HD model was used to determine the flood risk corresponding to 10, 25, 50, and 100-year return period floods calculated using Gumbel’s extreme value (GEV) and log-Pearson type III (LP-III) distribution techniques. Comparing the obtained peak floods corresponding to different return periods with the observed peak floods revealed that the LP-III method gives more reliable estimates of flood peaks for lower return periods, while the GEV method gives comparatively more reliable estimates for higher return period floods. The study shows that evaluating different open-source data and techniques is crucial for developing reliable flood mitigation plans with practical implications.

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“…With the increasing frequency and intensity of extreme weather events [27][28][29][30][31], it is necessary to refine our meteorological models for more precise forecasts. The main goal is not just to understand the behavior of this specific event but also to distill insights that could enhance the operational reliability of the application of the WRF system in future events.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Accuracy of 3D-VAR in Supercell Thunderstorm Forecasting: A Regional Background Error Covariance Study

Samos,

Louka,

Flocas

2023

Atmosphere

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Data assimilation (DA) integrates observational data with numerical weather predictions to enhance weather forecast accuracy. This study evaluates three regional background error (BE) covariance statistics for numerical weather prediction (NWP) via a variational data assimilation (VAR) scheme. The best practices in DA are highlighted, as well as the impact of BE covariance calculation in DA procedures by employing the Weather Research and Forecasting (WRF) model. Forecasts initialized at different intervals were used to compute distinct regional background error statistics utilizing three control variable (CV) methodologies over a span of 20 days. These statistics are used by the three-dimensional VAR DA process of WRF DA software, producing analysis fields that lead to forecasts for a distinct convective supercell event during the summer of 2019 over northern Greece. This high-impact convective event underscores the importance of selecting appropriate BE over complex terrain areas. The results emphasize the significance of BE usage in DA, proposing the optimal DA approach for simulations of convective systems.

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Exploring the Future of Rainfall Extremes Over CONUS: The Effects of High Emission Climate Change Trajectories on the Intensity and Frequency of Rare Precipitation Events

Abstract: Numerous research efforts over the last three decades have reported that the anthropogenic influence on climate, driven by high greenhouse gas concentrations, is linked to undesirable effects on the characteristics of hydrometeorological extremes (see e.g.,

Cited by 7 publications

References 106 publications

Reconstructing Historical Intense and Total Summer Rainfall in Central North Carolina Using Tree-Ring Data (1770–2020)

Reconstructing Historical Intense and Total Summer Rainfall in Central North Carolina Using Tree-Ring Data (1770–2020)

Evaluating the Efficacy of Different DEMs for Application in Flood Frequency and Risk Mapping of the Indian Coastal River Basin

Assessing the Accuracy of 3D-VAR in Supercell Thunderstorm Forecasting: A Regional Background Error Covariance Study

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