Reply on RC1 DOI Creative Commons

Emma Howard

Published: Nov. 30, 2023

Abstract. Anthropogenic climate change is changing the earth system processes that control characteristics of natural hazards both globally and across Australia. Model projections under future are necessary for effective adaptation. This paper presents BARPA-R (the Bureau Meteorology Atmospheric Regional Projections Australia), a regional model designed to downscale over Australasian region with purpose investigate hazards. BARPA-R, limited area model, has 17 km horizontal grid-spacing makes use Met Office Unified (MetUM) atmospheric Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility in compliance Coordinated Climate Downscaling Experiment (CORDEX) experiment design, framework been used ERA-5 reanalysis. Here, an assessment this evaluation provided. First, examination BARPA-R’s representation Australia’s air temperature, rainfall 10-m winds finds good performance overall, biases including 1 K cold bias daily maximum temperatures, reduced diurnal temperature range, wet up 25 mm/month inland Recent trends temperatures consistent observational products, while minimum show overestimated warming underestimated wetting northern Rainfall teleconnections effectively represented when present driving boundary conditions, 10-metre improved ERA5 six out eight Australian regions considered. The second section considers large-scale circulation features weather systems. While generally well represented, convection-related such as tropical cyclones, SPCZ, Northwest Cloud-Bands monsoon westerlies more divergence from observations internal interannual variability than mid-latitude phenomena westerly jets extra-tropical cyclones. Having simulated realistic climate, will be two scenarios seven CMIP6 GCMs.

Language: Английский

TMC-Net: A temporal multivariate correction network in temperature forecasting DOI
Wei Fang, Yuan Zhong,

Binglun Wang

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127015 - 127015

Published: Feb. 1, 2025

Language: Английский

Citations

1
Deep learning-based bias correction of ISMR simulated by GCM DOI
Sumanta Chandra Mishra Sharma, Bipin Kumar, Adway Mitra

et al.

Atmospheric Research, Journal Year: 2024, Volume and Issue: 309, P. 107589 - 107589

Published: July 20, 2024

Language: Английский

Citations

5
Climatology of near-surface wind speed from observational, reanalysis and high-resolution regional climate model data over the Tibetan Plateau DOI Creative Commons
Lorenzo Minola, Gangfeng Zhang, Tinghai Ou

et al.

Climate Dynamics, Journal Year: 2023, Volume and Issue: 62(2), P. 933 - 953

Published: Sept. 16, 2023

Abstract As near-surface wind speed plays a role in regulating surface evaporation and thus the hydrological cycle, it is crucial to explore its spatio-temporal characteristics. However, in-situ measurements are scarce over Tibetan Plateau, limiting understanding of climate across this high-elevation region. This study explores climatology Plateau by using for first time homogenized observations together with reanalysis products regional model simulations. Measuring stations center west plateau at higher elevations display mean standard deviation, confirming that increases increasing altitude. By exploring characteristics focus on seasonal cycle through cluster analysis, three regions distinct regimes can be identified: (1) central characterized high elevation; (2) eastern peripheral areas plateau; (3) Qaidam basin, topographic depression strongly influenced blocking effect surrounding mountainous terrain. Notably, ERA5 reanalysis, improvements horizontal, vertical, temporal spacing, physics data assimilation, demonstrates closer agreement measured conditions than predecessor ERA-Interim. It successfully reproduces identified regimes. newest ERA5-Land product does not show compared ERA5, most likely because they share parametrizations. Furthermore, two dynamical downscalings analyzed here fail capture observed statistics exhibit notable biases discrepancies also when investigating diurnal variations. Consequently, these high-resolution downscaling do add value reproducing Plateau.

Language: Английский

Citations

13
Assessing temperature and precipitation bias nonstationarity of CMIP6 global climate models over Iran DOI

Narges Azad,

Azadeh Ahmadi

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(2)

Published: Jan. 10, 2025

Language: Английский

Citations

0
Assessing the influence of bias correction of boundary conditions, spectral nudging and model parameterisation on model errors and climate change signals for regional climate model simulations DOI Creative Commons
Karuru Wamahiu, Jatin Kala, Jason P. Evans

et al.

Climate Dynamics, Journal Year: 2025, Volume and Issue: 63(3)

Published: Feb. 26, 2025

Language: Английский

Citations

0
Application of High-Resolution Regional Climate Model Simulations for Crop Yield Estimation in Southern Brazil DOI Creative Commons
Santiago Vianna Cuadra, Monique Pires Gravina de Oliveira, D. de C. Victoria

et al.

AgriEngineering, Journal Year: 2025, Volume and Issue: 7(4), P. 108 - 108

Published: April 7, 2025

This study is focused on assessing the impacts of different regional climate model targeted simulations performed at convection-permitting resolution (CPRCM) in AgS crop yield simulations, evaluating to what extent uncertainty modeled yield—considering spatial and temporal variability over central-south Brazil. The ensemble CPRCMs has been produced as part a Flagship Pilot Study (FPS-SESA) framework, endorsed by Coordinated Regional Climate Downscaling Experiment (CORDEX). simulated exhibited significant differences, both space time, among driven well when compared with observations. Rainfall showed highest CPRCM particularly its variability, whereas temperature solar radiation were generally more accurate smaller differences. results evidenced need for multi-model account uncertainty, from models parameterizations, estimations. Inter-institutional collaboration coordinated science are key aspects address these end-to-end studies South America, since there no single institution able produce such CPRCM-CropModels ensembles.

Language: Английский

Citations

0
Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1 DOI Creative Commons
Emma Howard, Chun‐Hsu Su, Christian Stassen

et al.

Geoscientific model development, Journal Year: 2024, Volume and Issue: 17(2), P. 731 - 757

Published: Jan. 29, 2024

Abstract. Anthropogenic climate change is changing the Earth system processes that control characteristics of natural hazards both globally and across Australia. Model projections under future are necessary for effective adaptation. This paper presents BARPA-R (the Bureau Meteorology Atmospheric Regional Projections Australia), a regional model designed to downscale over Australasian region with purpose investigating hazards. BARPA-R, limited-area model, has 17 km horizontal grid spacing makes use Met Office Unified (MetUM) atmospheric Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility in compliance Coordinated Climate Downscaling Experiment (CORDEX) experiment design, framework been used ERA5 reanalysis. Here, an assessment this evaluation provided. Performance-based results benchmarked against ERA5, comparable performance between free-running simulations observationally constrained reanalysis interpreted as good result. First, examination BARPA-R's representation Australia's air temperature, precipitation, 10 m winds finds overall, biases including 1 ∘C cold bias daily maximum temperatures, reduced diurnal temperature range, wet up 25 mm per month inland Recent trends temperatures consistent observational products, while minimum show overestimated warming precipitation underestimated wetting northern Precipitation teleconnections effectively represented when present driving boundary conditions, improved six out eight Australian regions considered. Secondly, considers large-scale circulation features weather systems. While generally well represented, convection-related such tropical cyclones, South Pacific Convergence Zone (SPCZ), Northwest Cloudband, monsoon westerlies more divergence from observations internal interannual variability than mid-latitude phenomena westerly jets extratropical cyclones. Having simulated realistic climate, will be two scenarios seven CMIP6 global models (GCMs).

Language: Английский

Citations

3
Correcting biases in regional climate model boundary variables for improved simulation of high-impact compound events DOI Creative Commons
Youngil Kim, Jason P. Evans, Ashish Sharma

et al.

iScience, Journal Year: 2023, Volume and Issue: 26(9), P. 107696 - 107696

Published: Aug. 21, 2023

Although climate models have been used to assess compound events, the combination of multiple hazards or drivers poses uncertainties because systemic biases present. Here, we investigate multivariate bias correction for correcting in boundaries that form inputs regional (RCMs). This improves representation physical relationships among variables, essential accurate characterization events. We address four types events result from eight different hazards. The results show while RCM simulations presented here exhibit similar performance some event types, broadly compared no univariate correction, particularly coincident high temperature and precipitation. with uncorrected tends produce a negative return period these suggesting tendency over-simulate respect observed

Language: Английский

Citations

6
Ensemble modeling of extreme seasonal temperature trends in Iran under socio-economic scenarios DOI Creative Commons
Muhammad Kamangar,

Mahmud Ahmadi,

Hamidreza Rabiei‐Dastjerdi

et al.

Natural Hazards, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 14, 2024

Abstract In climate science, ensemble modeling has emerged as a powerful tool for addressing the uncertainties inherent in individual models. This approach generates more robust and reliable predictions by harnessing collective insights of multiple Nonetheless, method combining these models to derive an model remains open question. To this end, objectives research are twofold: (i) introduce evaluate weighted average-correlation projecting minimum maximum temperatures Iran, (ii) assess near-term (2021–2040) trends across 95 synoptic stations using socio-economic scenarios derived from five models: GFDL-ESM4, MPI-ESM1-2-HR, IPSL-CM6A-LR, MRI-ESM2, UKESM1-0-LL. The technique effectively reduces Root Mean Square Error (RMSE) (1/3 − 1/10) associated with predicted values temperature similar actual data than temperature. results also indicate significant increase compared during base period. distribution country is influenced mainly its latitude. contrast, both country’s major altitudes latitudes. Surveys that, period, there increasing trend winter, spring, autumn, while decrease observed summer. Notably, pronounced winter.

Language: Английский

Citations

1
Can sub-daily multivariate bias correction of regional climate model boundary conditions improve simulation of the diurnal precipitation cycle? DOI Open Access
Youngil Kim, Jason P. Evans, Ashish Sharma

et al.

Authorea (Authorea), Journal Year: 2023, Volume and Issue: unknown

Published: May 8, 2023

The diurnal cycle is often poorly reproduced in global climate model (GCM) simulations, particularly terms of rainfall frequency and amplitude. While improvements the regional (RCM) with bias-corrected boundaries have been reported previous studies, they assumed that patterns are simulated correctly by GCM, potentially leading to inaccuracies maximum timing magnitude within RCM domain. Here we provide first examination cycle, a domain, achieved through use sophisticated lateral lower boundary conditions. Results show RCMs generally present improvement capturing both magnitude, northern Australia, where strong pattern prevalent. We correcting systematic sub-daily multivariate bias improves which important regions short-term intense precipitation occurs.

Language: Английский

Citations

3