Climate change impact on sea surface winds in Southeast Asia

Abstract

Numerical representation and climate projections of sea surface winds over Southeast Asia (SEA) are assessed here using an ensemble of the Coupled Model Intercomparison Project Phase 5 (CMIP5) downscaled simulations performed over the 20th and 21st centuries under Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios within the Coordinated Regional Climate Downscaling EXperiment (CORDEX)‐SEA project. The ensemble is based on two regional climate models (RCMs: RegCM4 and RCA4), and CMIP5 simulations are performed with five global climate models (GCMs: CNRM_CM5, HadGEM2, GFDL, MPI‐ESM‐MR, EC‐Earth). Comparison with QuikSCAT satellite data shows that dynamical downscaling improves sea surface wind speed representation, mainly by reducing its underestimation. The level of improvement depends on the RCM choice, GCM performance, and wind strength. Our results reveal significant differences in modelled projections of sea surface wind, depending on the model, RCP, region, and season. GCMs simulate weak and contrasted changes, stronger for RCP8.5, with no clear common trend. RCA4 simulates weak changes, with high similarities between pairs, but contrasted results between RCPs. RegCM4 simulate stronger changes, with a weakening of average and intense winds for all seasons, stronger in June–August, and in RCP8.5 than in RCP4.5. RCA4 and RegCM4 simulate different changes, with no clear common trend except a weakening of seasonal and intense winds and an increase of seasonal wind interannual variability for June–August in RCP4.5, stronger for RegCM4. This corresponds to a weakening of the boreal summer monsoon and a slight increase of its interannual variability and presumably to a decrease of the tropical cyclone frequency. Differences in seasonal sea surface wind changes between models are related to differences in sea level pressure gradient changes. For a given RCM, those differences are partly related to the differences between parent GCMs. Finally, results suggest that uncertainties related to the RCM choice are larger than those related to the GCM choice.

Intraseasonal variability of the South Vietnam Upwelling, South China Sea: influence of atmospheric forcing and ocean intrinsic variability

“…Second, Ekman pumping-induced upwelling (OFU hereafter) develops offshore in the area of strong positive wind and surface current vorticity (Liu et al, 2012;Da et al, 2019;Ngo and Hsin, 2021). Third, recent studies have revealed that coastal upwelling (NCU hereafter) can develop along the northern part of the central Vietnamese coast (Da et al, 2019;Ngo and Hsin, 2021;To Duy et al, 2022). Last, To Duy et al (2022) showed for the first time that upwelling develops off the Mekong Delta in the wake of Con Dao islands (see Fig.…”

“…The interannual variability of the SVU has been investigated in numerous previous studies. In the SCU, OFU and MKU regions, the interannual variability of summer wind intensity is related to and in phase with the intensity of the summer monsoon, and is the main driver of the interannual variability of upwelling intensity (Wang et al, 2006;Chen et al, 2014;Li et al, 2014;Da et al, 2019;Ngo and Hsin, 2021;To Duy et al, 2022). ENSO (El Niño Southern Oscillation) also impacts the upwelling in those regions, due to its influence on summer monsoon wind (Wang et al, 2006;Kuo et al, 2004;Loick-Wilde et al, 2017;Da et al, 2019).…”

“…The interannual variability of NCU shows a completely different behavior. Ngo and Hsin (2021) and To Duy et al (2022) concluded that wind conditions favorable to SCU, MKU and OFU were unfavorable to NCU, and vice versa. To Duy et al (2022) moreover showed that the influence of wind is weaker for NCU than for the other areas, and that the influence of circulation, in particular of the spatial organization of the strongly chaotic submesoscale to mesoscale circulation that prevails over the area, is stronger: on a seasonal average, NCU is inhibited when alongshore currents prevail, and enhanced when offshore circulation prevails.…”

“…The effect of tides and rivers will be examined in a future study. A fine-resolution realistic model including tides and already presented and evaluated in To Duy et al (2022) for the period 2009-2018 is used. Ensemble simulations with perturbed initial conditions are performed to study the case of summer 2018, which was an exceptionally strong summer of upwelling for SCU, OFU and MKU (Ngo and Hsin, 2021;To Duy et al, 2022).…”

The role of wind, mesoscale dynamics, and coastal circulation in the interannual variability of the South Vietnam Upwelling, South China Sea – answers from a high-resolution ocean model

“…Ocean circulation in the South China Sea (SCS), one of the largest semi-enclosed seas in the world (Fig. 1), is under the influence of several factors of variability at different scales: typhoons, seasonal monsoon, interannual to decadal variability, and climate change (Wyrtki, 1961;Herrmann et al, 2020Herrmann et al, , 2021. The SCS is moreover impacted by human activities, with highly densely populated coastal areas (Center for International Earth Science Information Network -CIESIN -Columbia University, 2018), which generate problems such as marine pollution (release of industrial, agricultural or domestic contaminants, such as pharmaceuticals, pesticides, heavy metals, or plastics).…”