Selecting regional climate models based on their skill could give more credible precipitation projections over the complex Southeast Asia region

Nguyen, Phuong‐Loan; Bador, Margot; Alexander, Lisa V.; Lane, Todd P.

doi:10.1007/s00382-023-06751-5

Cited by 3 publications

(2 citation statements)

References 53 publications

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“…This study suggests the care of use of RCM driven by IPSL-CM5A-LR given its contrasting output compared to other models available. This finding aligns with other studies in Southeast Asia using RCMs, which reported profound bias of the downscaled IPSL-CM5A-LR due to overall model disparity from the other COR-DEX SEA simulations (Magnaye et al, 2023;Nguyen et al, 2023). In addition, other extreme indices show a relatively similar pattern of wet bias of model output.…”

Section: Rcm Evaluationsupporting

confidence: 90%

Future exposure of rainfall and temperature extremes to the most populous island of Indonesia: A projection based on CORDEX simulation

Hendrawan,

Mawandha,

Sakti

et al. 2024

Intl Journal of Climatology

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The study focuses on understanding the future exposure to rainfall and temperature extremes in one of the world's most populous islands, Java, Indonesia. We use the high‐resolution climate projections from the Coordinated Regional Climate Downscaling Experiment (CORDEX) simulation for Southeast Asia by 2100 under RCP4.5 and RCP8.5 scenarios. Results show that the island will likely experience drying in the lowlands due to annual rainfall decline by approximately 13%–18%, potentially exposing around 27%–73% of the population (varying under different scenarios) during the end of the century (2060–2099). Additionally, the future drying condition may be exacerbated by extreme temperatures with a 1.7–3.1°C increase in maximum daily temperature, linked with more than half of the population (63%) likely to experience at least an unprecedented temperature of 3°C under RCP8.5. Our seasonal analysis also suggests that dry seasons get even drier, and wet seasons get wetter. In terms of landuse areas exposed, we show a higher fraction of crop and forest areas may face both drying and warming, which can potentially lead to crop failure and wildfire. Our study indicates that compound drought and heat may be a common threat in lowland Java in the future, while intensifying rainfall extremes in the uplands may lead to flash flooding downstream and landslides. These findings highlight the urgent need for adaptation and mitigation strategies to reduce the risks associated with climate change in Java as one of Indonesia's most critical regions in the future.

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Section: Rcm Evaluationsupporting

confidence: 90%

Future exposure of rainfall and temperature extremes to the most populous island of Indonesia: A projection based on CORDEX simulation

Hendrawan,

Mawandha,

Sakti

et al. 2024

Intl Journal of Climatology

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“…Several academic studies have utilized Regional Climate Models (RCMs) such as ICTP-RegCM4-3, MPI-CSC-REMO2009, and CCCma-CanRCM4 to analyze regional climate variations, impacts, and projections 48 , 49 . These RCMs are regarded as valuable tools for downscaling global climate model outputs to provide more detailed climate information at regional and local levels.…”

Section: Methodsmentioning

confidence: 99%

Future climate projection across Tanzania under CMIP6 with high-resolution regional climate model

Magang,

Ojara,

Yunsheng

et al. 2024

Sci Rep

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Climate change is one of the most pressing challenges faced by developing countries due to their lower adaptive capacity, with far-reaching impacts on agriculture. The mid-century period is widely regarded as a critical moment, during which adaptation is deemed essential to mitigating the associated impacts. This study presents future climate projections across Tanzania using the latest generation of global climate models (CMIP6) combined with a high-resolution regional climate model. The findings indicate that, the trends in temperature and precipitation in Tanzania from 1991 to 2020, minimum temperatures showed the highest variability with a trend of 0.3 °C, indicating significant fluctuations in minimum temperature over the decades. Maximum temperatures also showed high variability with a trend of 0.4 °C. There is a range of variability in precipitation per decade for different regions in Tanzania, with some regions experiencing significant decreases in precipitation of up to − 90.3 mm and − 127.6 mm. However, there were also regions that experienced increases in precipitation, although these increases were generally less than 4.8 mm over the decades. The projections of minimum and maximum temperatures from 2040 to 2071 under the Shared Socioeconomic Pathways (SSP) 2–4.5 and SSP 5–8.5 are projected to increase by 0.14 °C to 0.21 °C per decade, across different regions. The average projected precipitation changes per decade vary across regions. Some regions are projected to experience increases in precipitation. Other regions are projected to show decreases in precipitation within the range of − 0.6 mm to 15.5 mm and − 1.5 mm to 47.4 mm under SSP2–4.5 and SSP5–8.5 respectively. Overall, both scenarios show an increase in projected temperatures and precipitation for most regions in Tanzania, with some areas experiencing more significant increases compared to others. The changes in temperatures and precipitation are expected to have significant impacts on agriculture and water resources in Tanzania.

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Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework

Nguyen,

Alexander,

Thatcher

et al. 2024

Geosci. Model Dev.

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Abstract. Downscaling global climate models (GCMs) provides crucial high-resolution data needed for informed decision-making at regional scales. However, there is no uniform approach to select the most suitable GCMs. Over Southeast Asia (SEA), observations are sparse and have large uncertainties, complicating GCM selection especially for rainfall. To guide this selection, we apply a standardised benchmarking framework to select CMIP6 GCMs for dynamical downscaling over SEA, addressing current observational limitations. This framework identifies fit-for-purpose models through a two-step process: (a) selecting models that meet minimum performance requirements in simulating the fundamental characteristics of rainfall (e.g. bias, spatial pattern, annual cycle and trend) and (b) selecting models from (a) to further assess whether key precipitation drivers (monsoon) and teleconnections from modes of variability are captured, i.e. the El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). GCMs generally exhibit wet biases, particularly over the complex terrain of the Maritime Continent. Evaluations from the first step identify 19 out of 32 GCMs that meet our minimum performance expectations in simulating rainfall. These models also consistently capture atmospheric circulations and teleconnections with modes of variability over the region but overestimate their strength. Ultimately, we identify eight GCMs meeting our performance expectations. There are obvious, high-performing GCMs from allied modelling groups, highlighting the dependency of the subset of models identified from the framework. Therefore, further tests of model independence, data availability and future climate change spread are conducted, resulting in a final subset of two independent models that align with our a priori expectations for downscaling over the Coordinated Regional Climate Downscaling Experiment –Southeast Asia (CORDEX-SEA).

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Selecting regional climate models based on their skill could give more credible precipitation projections over the complex Southeast Asia region

Cited by 3 publications

References 53 publications

Future exposure of rainfall and temperature extremes to the most populous island of Indonesia: A projection based on CORDEX simulation

Future exposure of rainfall and temperature extremes to the most populous island of Indonesia: A projection based on CORDEX simulation

Future climate projection across Tanzania under CMIP6 with high-resolution regional climate model

Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework

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