High-resolution ensemble projections and uncertainty assessment of regional climate change over China in CORDEX East Asia

Abstract

Abstract. An ensemble simulation of five regional climate models (RCMs) from the coordinated regional downscaling experiment in East Asia is evaluated and used to project future regional climate change in China. The influences of model uncertainty and internal variability on projections are also identified. The RCMs simulate the historical climate and future climate projections under the Representative Concentration Pathway (RCP) RCP4.5 scenario. The simulations for five subregions in China, including northeastern China, northern China, southern China, northwestern China, and the Tibetan Plateau, are highlighted in this study. Results show that (1) RCMs can capture the climatology, annual cycle, and interannual variability of temperature and precipitation and that a multimodel ensemble (MME) outperforms that of an individual RCM. The added values for RCMs are confirmed by comparing the performance of RCMs and global climate models (GCMs) in reproducing annual and seasonal mean precipitation and temperature during the historical period. (2) For future (2030)(2031)(2032)(2033)(2034)(2035)(2036)(2037)(2038)(2039)(2040)(2041)(2042)(2043)(2044)(2045)(2046)(2047)(2048)(2049) climate, the MME indicates consistent warming trends at around 1 • C in the entire domain and projects pronounced warming in northern and western China. The annual precipitation is likely to increase in most of the simulation region, except for the Tibetan Plateau. (3) Generally, the future projected change in annual and seasonal mean temperature by RCMs is nearly consistent with the results from the driving GCM. However, changes in annual and seasonal mean precipitation exhibit significant inter-RCM differences and possess a larger magnitude and variability than the driving GCM. Even opposite signals for projected changes in average precipitation between the MME and the driving GCM are shown over southern China, northeastern China, and the Tibetan Plateau. (4) The uncertainty in projected mean temperature mainly arises from the internal variability over northern and southern China and the model uncertainty over the other three subregions. For the projected mean precipitation, the dominant uncertainty source is the internal variability over most regions, except for the Tibetan Plateau, where the model uncertainty reaches up to 60 %. Moreover, the model uncertainty increases with prediction lead time across all subregions.

Survival of the Qaidam mega-lake system under mid-Pliocene climates and its restoration under future climates

“…During the mid-Pliocene, climates were generally warmer and less dry (or wetter) than today in many regions of the world (Haywood et al, 2013(Haywood et al, , 2016. The studies of R. and Mutz et al (2018) provide quantitative estimates of mid-Pliocene changes in mean annual air temperature and precipitation with respect to preindustrial climates from various global paleoclimate simulations.…”

Projected Changes in Hydrological Extremes in the Yangtze River Basin with an Ensemble of Regional Climate Simulations

“…The higher resolution simulation from the RCMs provides a much better reproduction of the precipitation pattern over the regions with complex terrain, land-sea, and other contrasts. For example, the overestimated precipitation at the eastern edge of the Tibetan Plateau is usually simulated by coarse resolution GCMs, but it is removed by most RCMs [37].The aim of this study is to project changes in hydrological extremes in the first half of the 21st century in the Yangtze River basin by using multi-model high-resolution regional climate simulations. These future climate projections are obtained from CORDEX-EA simulations under RCP4.5 (medium radiative forcing scenario) and RCP8.5 (high radiative forcing scenario) emission scenarios.…”

“…The higher resolution simulation from the RCMs provides a much better reproduction of the precipitation pattern over the regions with complex terrain, land-sea, and other contrasts. For example, the overestimated precipitation at the eastern edge of the Tibetan Plateau is usually simulated by coarse resolution GCMs, but it is removed by most RCMs [37].…”

Declines in Common and Migratory Breeding Landbird Species in South Korea Over the Past Two Decades

“…While declines in the global population of once-common species of buntings in Asia have recently been documented (Kamp et al, 2015;Tamada et al, 2017), the population status of most species is uncertain (Yong et al, 2015). Given past and current changes in land use (Song et al, 2018) and global climate change effects in this region (Gu et al, 2018), systematic monitoring and analysis are necessary for detecting changes which could inform conservation and management actions.…”