Dominant Sources of Uncertainty for Downscaled Climate: A Military Installation Perspective DOI Creative Commons
Taereem Kim, Gabriele Villarini, J. Done

и другие.

Journal of Geophysical Research Atmospheres, Год журнала: 2024, Номер 129(12)

Опубликована: Июнь 21, 2024

Abstract While the Department of Defense (DoD) infrastructure is no stranger to extremes, recent events have been unprecedented, with climate change acting as a growing risk multiplier. To assess level exposure DoD installations extreme weather and events, site‐specific information needed. One way bridge scale gap between outputs from existing global models (GCMs) sites downscaling. This makes more relevant for impact assessment at installation facility scale. However, downscaling GCMs beset by myriad challenges sources uncertainty, methods were not designed specific planning design needs in mind. Here, we evaluate state‐of‐the‐science dynamical statistical bias correction variables (i.e., temperature precipitation) daily We also combine approaches novel ways optimize computational efficiency reduce uncertainty. Furthermore, examine sensitivity downscaled choice reference data quantify relative uncertainty related approach, data, other factors across aggregation scales. Results show that empirical quantile mapping (EQM), downscaling, consistently performs well has less data. Moreover, hybrid leverages EQM improves performance Our findings highlight dominates uncertainties while their role muted precipitation but still non‐negligible.

Язык: Английский

Understanding the Impact of Precipitation Bias‐Correction and Statistical Downscaling Methods on Projected Changes in Flood Extremes DOI Creative Commons
Alexander Michalek, Gabriele Villarini, Taereem Kim

и другие.

Earth s Future, Год журнала: 2024, Номер 12(3)

Опубликована: Март 1, 2024

Abstract This study evaluates five bias correction and statistical downscaling (BCSD) techniques for daily precipitation examines their impacts on the projected changes in flood extremes (i.e., 1%, 0.5%, 0.2% floods). We use climate model outputs from Coupled Model Intercomparison Project Phase 6 (CMIP6) to conduct hydrologic simulations across watersheds Iowa determine historical future extreme estimates based generalized value distribution fitting. Projected these are examined with respect four Shared Socioeconomic Pathways (SSPs) alongside BCSD techniques. find magnitude of annual exceedance probabilities (AEPs) expected increase under all SSPs, especially emission scenarios higher greenhouse gases concentrations SSP370 SSP585). Our results also suggest choice changes, SSPs that play a more limited role compared method. The variability is similar technique but increases as AEP increases. findings provide insights into impact extremes' projections useful information planning state.

Язык: Английский

Процитировано

6
Projected changes in daily precipitation, temperature and wet‐bulb temperature across Arizona using statistically downscaled CMIP6 climate models DOI Creative Commons
Taereem Kim, Gabriele Villarini

International Journal of Climatology, Год журнала: 2024, Номер 44(6), С. 1994 - 2010

Опубликована: Март 20, 2024

Abstract To evaluate future changes in the climate system, outputs from coarse‐resolution global models (GCMs) need to be downscaled a finer scale, making them more directly applicable for impact assessment. Here we focus on examining projected of three key variables (precipitation, air temperature, and wet bulb temperature) across Arizona (south‐western United States). We use daily GCMs sixth phase Coupled Model Intercomparison Project (CMIP6) bias correct downscale 4‐km resolution. Through leave‐one‐out cross‐validation, compare various correction methods identify that empirical quantile mapping approach performs best regardless variable. Then, analyse bias‐corrected two periods (Mid‐of‐Century: 2015–2048; End‐of‐Century: 2067–2100) with respect 1981–2014 period, under four shared socioeconomic pathway scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 SSP5‐8.5). Our results show Arizona's is become overall warmer wetter, so towards end this century higher emission scenarios. Additionally, our findings project an increase temperature cooling degree days, implying ongoing warming climate's potential impacts public health economy. These provide baseline understanding change state highlight response

Язык: Английский

Процитировано

3
Projecting Multiscale River Flood Changes Across Japan at +2°C and +4°C Climates DOI Creative Commons
Jiachao Chen, Takahiro Sayama, Masafumi YAMADA

и другие.

Earth s Future, Год журнала: 2025, Номер 13(5)

Опубликована: Май 1, 2025

Abstract This study addresses computational challenges in high‐resolution, large‐domain, process‐based flood quantile estimation, focusing on Japan's future risks at 150 m resolution. Using the Aggregating Grid Event (AGE) method, Rainfall‐Runoff‐Inundation (RRI) model, and Peaks‐Over‐Threshold (POT) approach, it incorporates 2,160‐year precipitation data from a 5‐km dynamically downscaled ensemble (d4PDF DDSJP) across three climate stages (historical, +2°C, +4°C). The AGE method identified critical events for estimations POT was employed to estimate 100‐year discharge (Q100) over 2.2 million river grid cells. Key findings include: (a) Nationwide, is projected increase 1.16 times (+2°C) 1.37 (+4°C), with equivalent return periods reduced 45 years 23 (+4°C). Northern regions (Hokkaido Tohoku) are particularly climate‐sensitive, exceeding national averages Q100 increases. (b) Small basins transition zones plains mountains exhibit higher ratios, necessitating targeted prevention measures. (c) Flash expected rise, most seeing flashiness increases of 10% 20% Southern Japan faces further flash intensification, while under +4°C stage anticipates emerging related floods. underscores urgency adaptive management strategies mitigate increasing risks, offering foundation informed policymaking public‐engaged mitigation. Simulation opens pathways research cascading disaster scenarios +2°C climates.

Язык: Английский

Процитировано

0
Identifying the effects of climate change on discharge and sediment transport in a typical alpine basin DOI Creative Commons

Zhou Ya,

Lei Huang,

Huang Liang-wen

и другие.

International Journal of Sediment Research, Год журнала: 2025, Номер unknown

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0
Future Changes in Regional Tropical Cyclone Wind, Precipitation, and Flooding Using Event‐Based Downscaling DOI Creative Commons
Alexander Michalek, J. Done, Gabriele Villarini

и другие.

Earth s Future, Год журнала: 2024, Номер 12(6)

Опубликована: Июнь 1, 2024

Abstract Understanding changes in the hazard component of climate risk is important to inform societal resilience planning a changing climate. Here, we examine local wind speed, rainfall, and flooding related tropical cyclones (TCs) compare them across statistical dynamical modeling approaches. Our focus region Delaware River Basin, located northeastern United States. We pair event‐based downscaling with large ensemble model information capture details extreme TC wind, rain, flooding, their likelihood, identify TCs Community Earth System Model 2 Large Ensemble (CESM2‐LENS). find fewer future, but these future storms have higher speeds are wetter. also that produce heavier 3‐day precipitation distributions than all other summertime weather events, constituting larger percentage upper tail full distribution. With this information, small collection 200‐year return events resulting rain methods. produces peak rates far CESM or method. It can quite different totals for set considered here. This leads vastly flood responses. Overall, our results highlight need interpret simulations context method limitations.

Язык: Английский

Процитировано

1
Evaluation of hydroclimatic biases in the Community Earth System Model (CESM1) within the Mississippi River basin DOI Creative Commons
Michelle O’Donnell, Kelsey Murphy, James Doss‐Gollin

и другие.

Опубликована: Июнь 10, 2024

Abstract. The Mississippi River is a critical waterway in the United States, and hydrologic variability along its course represents perennial threat to trade, agriculture, industry, economy, communities. Community Earth System Model version 1 (CESM1) complements observational records of river discharge by providing fully coupled output from state-of-the-art earth system model that includes transport model. These simulations past, historic, projected have been widely used assess dynamics causes changes hydrology basin. Here, we compare observations reanalysis datasets key variables CESM1 within basin evaluate performance bias. We show seasonality simulated shifted 2–3 months late relative observations. This offset attributed seasonal biases precipitation runoff region. also several CMIP6 models over basin, other — notably CESM2 more closely simulates trends data. Our results implications for selection when assessing hydroclimate on timing can vary between models. findings imply continued improvements representation land surface may improve our ability consequences environmental change terrestrial water resources major systems globally.

Язык: Английский

Процитировано

1
Contiguous United States hydrologic modeling using the Hillslope Link Model TETIS DOI Creative Commons
Alexander Michalek, Felipe Quintero, Gabriele Villarini

и другие.

JAWRA Journal of the American Water Resources Association, Год журнала: 2024, Номер 60(6), С. 1058 - 1079

Опубликована: Авг. 11, 2024

Abstract Large‐scale hydrologic modeling is important for understanding changes in water resources and flood hazard across a broad range of climatic conditions. Parsimonious models, although simple, allow an efficient way to model river systems multiple decades even centuries. Therefore, this study aims assess the ability distributed Hillslope Link Model (HLM) TETIS simulate streamflow observations contiguous United States (CONUS) from 1981 2020. To obtain parameters domain, we partition area into 234 HydroSHEDS level 5 basins calibrate single representative location near outlet each basin using dynamical dimension search 100 realizations. Performance then assessed at 5046 US Geological Survey streamgages with respect Kling Gupta Efficiency (KGE) bias. Our simulations result median KGE 0.43, 89% sites having value above reference 1 − √2 (~ ‐0.41). Furthermore, there dependence performance on climate regions, performing better cold temperate regions than arid ones. While are estimated based daily precipitation inputs, it shown that performs well when forced hourly precipitation, highlighting robustness selected different inputs. Finally, soil related show properties, providing basis future improvement. Overall, highlights model's flexibility vast domain runoff generation mechanisms.

Язык: Английский

Процитировано

1
Disentangling the Sources of Uncertainties in the Projection of Flood Risk Across the Central United States (Iowa) DOI Creative Commons
Alexander Michalek, Gabriele Villarini, Taereem Kim

и другие.

Geophysical Research Letters, Год журнала: 2023, Номер 50(22)

Опубликована: Ноя. 23, 2023

Abstract We explore the projected changes in flood impacts across Iowa (central United States) and associated uncertainties by forcing a hydrologic model with downscaled global climate outputs four Shared Socioeconomic Pathways. Our results point to increasing magnitude variability flooding state, especially for high‐emission scenarios. Next, we partition impacts' projections into: (a) response of models anthropogenic forcing, (b) scenario uncertainty due emissions, (c) internal variability. find plays small role, while dominate projections, contribution toward end this century. Insights from our work can be utilized stakeholders understand current limitations impact provide suggestions about where modelers should focus efforts reduce uncertainty.

Язык: Английский

Процитировано

3
Dominant Sources of Uncertainty for Downscaled Climate: A Military Installation Perspective DOI Creative Commons
Taereem Kim, Gabriele Villarini, J. Done

и другие.

Journal of Geophysical Research Atmospheres, Год журнала: 2024, Номер 129(12)

Опубликована: Июнь 21, 2024

Abstract While the Department of Defense (DoD) infrastructure is no stranger to extremes, recent events have been unprecedented, with climate change acting as a growing risk multiplier. To assess level exposure DoD installations extreme weather and events, site‐specific information needed. One way bridge scale gap between outputs from existing global models (GCMs) sites downscaling. This makes more relevant for impact assessment at installation facility scale. However, downscaling GCMs beset by myriad challenges sources uncertainty, methods were not designed specific planning design needs in mind. Here, we evaluate state‐of‐the‐science dynamical statistical bias correction variables (i.e., temperature precipitation) daily We also combine approaches novel ways optimize computational efficiency reduce uncertainty. Furthermore, examine sensitivity downscaled choice reference data quantify relative uncertainty related approach, data, other factors across aggregation scales. Results show that empirical quantile mapping (EQM), downscaling, consistently performs well has less data. Moreover, hybrid leverages EQM improves performance Our findings highlight dominates uncertainties while their role muted precipitation but still non‐negligible.

Язык: Английский

Процитировано

0