Bias evaluation in rainfall over Southeast Asia in CMIP6 models

Liu, Senfeng; Raghavan, Srivatsan V.; Ona, Bhenjamin Jordan; Nguyen, Ngoc Son

doi:10.1016/j.jhydrol.2023.129593

Cited by 7 publications

(3 citation statements)

References 51 publications

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“…This is consistent with other highresolution coupled models of the Maritime Continent region (e.g. Roberts et al, 2019) with both parametrised and explicit convection, especially in DJF (Liu et al, 2023). The wet bias over the ocean is stronger in MC12 than in MC2 and has a typical magnitude of around 3 mm d −1 (panels c, e).…”

Section: Mean Statesupporting

confidence: 90%

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Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent

Howard,

Woolnough,

Klingaman

et al. 2024

Geosci. Model Dev.

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Abstract. A multi-season convection-permitting regional climate simulation of the Maritime Continent (MC) using the Met Office Unified Model (MetUM) with 2.2 km grid spacing is presented and evaluated. The simulations pioneer the use of atmosphere–ocean coupling with the multi-column K profile parametrisation (KPP) mixed-layer ocean model in atmospheric convection-permitting climate simulations. Comparisons are made against a convection-parametrised simulation in which it is nested and which in turn derives boundary conditions from the ERA5 reanalysis. This paper describes the configuration, performance of the mean state and variability in the two simulations compared against observational datasets. The models have both minor sea surface temperature (SST) and wet precipitation biases. The diurnal cycle, representation of equatorial waves, and relationship between SST and precipitation are all improved in the convection-permitting model compared to the convection-parametrised model. The Madden–Julian oscillation (MJO) is present in both models with a faster-than-observed propagation speed. However, it is unclear whether fidelity of the MJO simulation is inherent to the model or whether it predominantly arises from the forcing at the boundaries.

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Section: Mean Statesupporting

confidence: 90%

“…Neale and Slingo, 2003;Toh et al, 2018), while coupled models tend to overestimate it (e.g. Inness and Slingo, 2003;Liu et al, 2023).…”

Section: Air-sea Couplingmentioning

confidence: 99%

Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent

Howard,

Woolnough,

Klingaman

et al. 2024

Geosci. Model Dev.

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“…To date, multiple authors have undertaken evaluations of the performance of CMIP6 G GCMs within the Indonesian and South Asian region context (Almazroui et al, 2020;Iqbal et al, 2021;Liu et al, 2023). These evaluations have primarily aimed to identify GCMs with high precision in simulating meteorological parameters.…”

Section: Discussionmentioning

confidence: 99%

Identification of optimal CMIP6 GCMs for future typical meteorological year in major cities of Indonesia using multi-criteria decision analysis

Bhanage,

Lee,

Cabrera

et al. 2024

Front. Environ. Sci.

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Many studies often use a single global climate model (GCM) across multiple cities to develop future Typical Meteorological Year (TMY), without emphasizing city-specific selection of GCM. The present investigation employs the Analytical Hierarchy Process (AHP) to assess city-specific GCMs for generating future TMY datasets across 29 Indonesian cities. Six GCMs from the coupled model intercomparison project phase 6 (CMIP6) were evaluated against Modern-Era Retrospective Analysis for Research Applications (MERRA-2) to assess their performance in simulating surface air temperature, precipitation, wind speed, and relative humidity. Six statistical measures were used to recognize the systematic biases. Further, AHP was applied to integrate these statistical measures to calculate the city-specific total relative error for each meteorological parameter. Results of total relative error show that TaiESM, 6-Model Ensemble (6ME), NorMM, and MPI-HR were best for simulating surface air temperature, precipitation, wind speed, and relative humidity in most cities, respectively. TMY recognizes distinctive importance among meteorological parameters. Thus, it is essential to reflect the parameter-specific importance while selecting GCMs for future TMY. Hence, AHP was reapplied on total relative errors accounting for differing weights of each meteorological parameter. Outcomes show that TaiESM, 6ME, and MPI-HR were found suitable for generating future TMY datasets in 18, 5, and 3 cities, respectively, while MPI-LR, NorLM, and NorMM were recommended for Boven Digoel, Medan, and Bengkulu cities, respectively. Using city-specific GCMs ensures precise and cost-effective future TMY generation, assisting urban planners and policymakers in designing environmentally sustainable buildings for anticipated climatic changes.

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Expansion of winter ENSO‐associated rainfall affected area in Southeast Asia under warmer climate

Leong,

Juneng,

Tangang

et al. 2024

Intl Journal of Climatology

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This paper examines the changes of El Niño–Southern Oscillation (ENSO) associated winter rainfall relationship in Southeast Asia (SEA) in the historical period (1981–2010) and future period (2071–2100) based on the Coupled Model Intercomparison Project Phase 6 (CMIP6) models simulations. Twenty general circulation models (GCMs) are chosen from the Scenario Model Intercomparison Project (ScenarioMIP) highest emission scenario—Shared Socioeconomic Pathway (SSP) 5‐8.5. This study focuses only on the GCMs that have been able to replicate the consistent associated patterns observed, referred to as “teleconnection‐consistent models” (TCMs). During historical period, ENSO has significant negative association with SEA winter rainfall, particularly over Indochina mainland, Maritime Continent (MC) and northern Borneo. The significant negative‐associated teleconnection affected area has increased under future climate, particularly over southern part of South China Sea (SCS). The weakening of south westerlies at Western North Pacific (WNP) centred near 20°N reduces the moisture transport from Indochina into south of China, increase the negative correlated affected area in the SEA regions above equator. The northeasterlies/easterlies that prevailed from the WNP anticyclone (AC) brings significant moisture flux into southern Borneo, causing increment of significant positive‐associated moisture flux convergence to that region. The weakening of upward motion in TCM results in less warm and moist air rising over SEA MC, reducing the rainfall availability. The 1° eastward expansion of WC downward branch eastern edge leads to suppression of convective activities, increasing the dry affected area. The results suggest that the ENSO has a larger influence on the negative‐associated SEA rainfall and atmospheric circulation in the December–January–February (DJF) late‐21st century when compared to the 1980–2010.

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Bias evaluation in rainfall over Southeast Asia in CMIP6 models

Cited by 7 publications

References 51 publications

Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent

Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent

Identification of optimal CMIP6 GCMs for future typical meteorological year in major cities of Indonesia using multi-criteria decision analysis

Expansion of winter ENSO‐associated rainfall affected area in Southeast Asia under warmer climate

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