Convection‐permitting modeling with regional climate models: Latest developments and next steps

Wiley Interdisciplinary Reviews Climate Change, Год журнала: 2021, Номер 12(6)

Опубликована: Авг. 16, 2021

Abstract Approximately 10 years ago, convection‐permitting regional climate models (CPRCMs) emerged as a promising computationally affordable tool to produce fine resolution (1–4 km) decadal‐long simulations with explicitly resolved deep convection. This explicit representation is expected reduce projection uncertainty related convection parameterizations found in most models. A recent surge CPRCM decadal over larger domains, sometimes covering continents, has led important insights into advantages and limitations. Furthermore, new observational gridded datasets spatial temporal (~1 km; ~1 h) resolutions have leveraged additional knowledge through evaluations of the added value CPRCMs. With an improved coordination frame ongoing international initiatives, production ensembles provide more robust projections better identification their associated uncertainties. review paper presents overview methodology latest research on current future climates. Impact studies that are already taking advantage these highlighted. ends by proposing next steps could be accomplished continue exploiting full potential article categorized under: Climate Models Modeling > Earth System

Язык: Английский

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Bias-corrected CMIP6 global dataset for dynamical downscaling of the historical and future climate (1979–2100)

Scientific Data, Год журнала: 2021, Номер 8(1)

Опубликована: Ноя. 4, 2021

Dynamical downscaling is an important approach to obtaining fine-scale weather and climate information. However, dynamical simulations are often degraded by biases in the large-scale forcing itself. We constructed a bias-corrected global dataset based on 18 models from Coupled Model Intercomparison Project Phase 6 (CMIP6) European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) dataset. The data have ERA5-based mean interannual variance, but with non-linear trend ensemble of CMIP6 models. spans historical time period 1979–2014 future scenarios (SSP245 SSP585) 2015–2100 horizontal grid spacing (1.25° × 1.25°) at six-hourly intervals. Our evaluation suggests that better quality than individual terms climatological mean, variance extreme events. This will be useful projections Earth's climate, atmospheric environment, hydrology, agriculture, wind power, etc. Machine-accessible metadata file describing reported data: https://doi.org/10.6084/m9.figshare.16802326

Язык: Английский

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Climate Change and Rainfall Intensity–Duration–Frequency Curves: Overview of Science and Guidelines for Adaptation

Journal of Hydrologic Engineering, Год журнала: 2021, Номер 26(10)

Опубликована: Авг. 3, 2021

One of the most important impacts a future warmer climate is projected increase in frequency and intensity extreme rainfall events. This increasing trend seen both observational record model projections. However, thorough review recent scientific literature paints complex picture which intensification extremes depends on multitude factors. While some indices follow Clausius-Clapeyron relationship scaling an ∼7% per 1°C warming, there substantial evidence that this frequency, with longer return period events seeing larger increases, leading to super cases. The now well documented at daily scale but less clear subdaily scale. In years, simulations finer spatial temporal resolution, including convection-permitting models, have provided more reliable projections rainfall. Recent analyses indicate may also as function duration, such shorter-duration, will likely see largest increases climate. has broad implications design use intensity–duration–frequency (IDF) curves, for overall magnitude steepening can be predicted. paper presents overview measures been adopted by various governing bodies adapt IDF curves changing Current vary from multiplying historical simple constant percentage modulating correction factors based periods them temperature increases. All these current fail recognize possible and, perhaps importantly, toward shorter-duration significantly impact stormwater runoff cities small rural catchments. discusses remaining gaps offers technical recommendations practitioners how improve resilience.

Язык: Английский

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The pseudo-global-warming (PGW) approach: methodology, software package PGW4ERA5 v1.1, validation, and sensitivity analyses

Geoscientific model development, Год журнала: 2023, Номер 16(3), С. 907 - 926

Опубликована: Фев. 6, 2023

Abstract. The term “pseudo-global warming” (PGW) refers to a simulation strategy in regional climate modeling. consists of directly imposing large-scale changes the system on control (usually representing current conditions) by modifying boundary conditions. This differs from traditional dynamic downscaling technique where output global model (GCM) is used drive models (RCMs). PGW are usually derived transient simulation. approach offers several benefits, such as lowering computational requirements, flexibility design, and avoiding biases models. However, implementing non-trivial, care must be taken not deteriorate physics when To simplify preparation simulations, we present detailed description methodology provide companion software PGW4ERA5 facilitating simulations. In describing methodology, particular attention devoted adjustment pressure geopotential fields. Such an required ensuring consistency between thermodynamical (temperature humidity) one hand dynamical other hand. It demonstrated that this important extratropics highly essential tropical subtropical regions. We show projections simulations prepared using presented closely comparable for most climatological variables.

Язык: Английский

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Deep learning in statistical downscaling for deriving high spatial resolution gridded meteorological data: A systematic review

ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2024, Номер 208, С. 14 - 38

Опубликована: Янв. 9, 2024

Язык: Английский

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Correction of ERA5 Wind for Regional Climate Projections of Sea Waves

Water, Год журнала: 2022, Номер 14(10), С. 1590 - 1590

Опубликована: Май 16, 2022

This paper proposes a method to infer the future change in wind-wave climate using reanalysis wind corrected statistically match data from regional model (RCM). The is applied sea surface speed of ERA5 European Centre for Medium-Range Weather Forecasts. correction determined quantile mapping between and RCM at any given point geographical space. issues that need be addressed better understand apply are discussed. Corrected fields eventually used force spectral wave numerical simulate significant height. strategy implemented over Adriatic Sea (a semi-enclosed basin Mediterranean Sea) includes present-day period (1981–2010) near-future (2021–2050) under two IPCC RCP4.5 RCP8.5 concentration scenarios. Evaluation against observations waves gives confidence reliability proposed approach. Results confirm evolution toward an overall decrease storm severity basin, especially its northern area. It expected methodology may other reanalyses, RCMs (including multi-model ensembles), or seas with similar characteristics.

Язык: Английский

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Downscaling of environmental indicators: A review

The Science of The Total Environment, Год журнала: 2024, Номер 916, С. 170251 - 170251

Опубликована: Янв. 21, 2024

Язык: Английский

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Diffusion model-based probabilistic downscaling for 180-year East Asian climate reconstruction

npj Climate and Atmospheric Science, Год журнала: 2024, Номер 7(1)

Опубликована: Июнь 13, 2024

Abstract As our planet is entering into the “global boiling” era, understanding regional climate change becomes imperative. Effective downscaling methods that provide localized insights are crucial for this target. Traditional approaches, including computationally-demanding dynamical models or statistical frameworks, often susceptible to influence of uncertainty. Here, we address these limitations by introducing a diffusion probabilistic model (DPDM) meteorological field. This can efficiently transform data from 1° 0.1° resolution. Compared with deterministic schemes, it not only has more accurate local details, but also generate large number ensemble members based on probability distribution sampling evaluate uncertainty downscaling. Additionally, apply 180-year dataset monthly surface variables in East Asia, offering detailed perspective scale over past centuries.

Язык: Английский

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Urban climate risk assessment under climate and land use changes impact: A multi-dimensional approach

Urban Climate, Год журнала: 2025, Номер 61, С. 102379 - 102379

Опубликована: Март 17, 2025

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Statistical downscaling and projection of future temperatures across the Loess Plateau, China

Weather and Climate Extremes, Год журнала: 2021, Номер 32, С. 100328 - 100328

Опубликована: Май 7, 2021

The Loess Plateau in China is one of the most erosive regions world, especially under warming climate conditions, which are aggravating evapotranspiration and water scarcity. Thus, there a need to better understand historical future change patterns Plateau, global models (GCMs) key tool achieve this. Because mismatch spatial resolution between GCMs requirements regional applications, Statistical Downscaling Model (SDSM) combination with two bias-correction methods was employed for first time downscale modeled values from Phase 5 Coupled Intercomparison Project daily maximum temperature (TMAX), mean (TMEAN), minimum (TMIN) over Plateau. After evaluation model capability, bias-corrected downscaled temperatures forced by GCM outputs period 2010–2099 were then projected. results show that SDSM cumulative density function matching technique produced more accurate estimates than integration delta correction, reduced root square errors (and associated standard deviations) 59.2% (88.6%), 45.3% (78.8%), 48.8% (43.4%) TMAX, TMEAN, TMIN, respectively. projected will increase entire plateau relative 1961–1990 period, greatest changes northern eastern regions. Another finding can reduce uncertainties projection obtain reliable projections.

Язык: Английский

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