Climate change in the 21st century simulated by HadGEM2-AO under representative concentration pathways

We present climate responses of Representative Concentration Pathways (RCPs) using the coupled climate model HadGEM2-AO for the Coupled Model Intercomparison Project phase 5 (CMIP5). The RCPs are selected as standard scenarios for the IPCC Fifth Assessment Report and these scenarios include time paths for emissions and concentrations of greenhouse gas and aerosols and land-use/land cover. The global average warming and precipitation increases for the last 20 years of the 21st century relative to the period 1986-2005 are +1.1°C/+2.1% for RCP2.6, +2.4°C/+4.0% for RCP4.5, +2.5°C/+3.3% for RCP6.0 and +4.1°C/+4.6% for RCP8.5, respectively. The climate response on RCP 2.6 scenario meets the UN Copenhagen Accord to limit global warming within two degrees at the end of 21st century, the mitigation effect is about 3°C between RCP2.6 and RCP8.5. The projected precipitation changes over the 21st century are expected to increase in tropical regions and at high latitudes, and decrease in subtropical regions associated with projected poleward expansions of the Hadley cell. Total soil moisture change is projected to decrease in northern hemisphere high latitudes and increase in central Africa and Asia whereas near-surface soil moisture tends to decrease in most areas according to the warming and evaporation increase. The trend and magnitude of future climate extremes are also projected to increase in proportion to radiative forcing of RCPs. For RCP 8.5, at the end of the summer season the Arctic is projected to be free of sea ice.     

Effects of freshwater runoff on a tropical pacific climate in the HadGEM2

This paper investigates the effects of river discharge on simulated climatology from 1979 to 1988 using the Hadley Centre Global Environmental Model version 2. Two experiments are performed with and without the inclusion of Total Runoff Integrating Pathways. The results show that the inclusion of flow routing can lead to the decrease of salinity over the coastal region due to freshwater. This reduction results in a shallower mixed layer depth, which in turn leads to the weakening of trade winds and a decrease in vertical mixing in the ocean. The enhanced sensible and latent heat fluxes over warmed SST improve the simulated precipitation and thermodynamic circulation. As a result, the experiment with flow routing is capable of improving the large-scale climate feature with an increase in precipitation over the eastern tropical equatorial Pacific region.     

集合同化方法在黄海海域海表面温度同化中的应用

The effects of sea surface temperature(SST) data assimilation in two regional ocean modeling systems were examined for the Yellow Sea(YS). The SST data from the Operational Sea Surface Temperature and Sea Ice Analysis(OSTIA) were assimilated. The National Marine Environmental Forecasting Center(NMEFC) modeling system uses the ensemble optimal interpolation method for ocean data assimilation and the Kunsan National University(KNU) modeling system uses the ensemble Kalman filter. Without data assimilation, the NMEFC modeling system was better in simulating the subsurface temperature while the KNU modeling system was better in simulating SST. The disparity between both modeling systems might be related to differences in calculating the surface heat flux, horizontal grid spacing, and atmospheric forcing data. The data assimilation reduced the root mean square error(RMSE) of the SST from 1.78°C(1.46°C) to 1.30°C(1.21°C) for the NMEFC(KNU) modeling system when the simulated temperature was compared to Optimum Interpolation Sea Surface Temperature(OISST) SST dataset. A comparison with the buoy SST data indicated a 41%(31%) decrease in the SST error for the NMEFC(KNU) modeling system by the data assimilation. In both data assimilative systems, the RMSE of the temperature was less than 1.5°C in the upper 20 m and approximately 3.1°C in the lower layer in October. In contrast, it was less than 1.0°C throughout the water column in February. This study suggests that assimilations of the observed temperature profiles are necessary in order to correct the lower layer temperature during the stratified season and an ocean modeling system with small grid spacing and optimal data assimilation method is preferable to ensure accurate predictions of the coastal ocean in the YS.     

Acidification at the Surface in the East Sea: A Coupled Climate-carbon Cycle Model Study

This modeling study investigates the impacts of increasing atmospheric CO₂ concentration on acidification in the East Sea. A historical simulation for the past three decades (1980 to 2010) was performed using the Hadley Centre Global Environmental Model (version 2), a coupled climate model with atmospheric, terrestrial and ocean cycles. As the atmospheric CO₂ concentration increased, acidification progressed in the surface waters of the marginal sea. The acidification was similar in magnitude to observations and models of acidification in the global ocean. However, in the global ocean, the acidification appears to be due to increased in-situ oceanic CO₂ uptake, whereas local processes had stronger effects in the East Sea. pH was lowered by surface warming and by the influx of water with higher dissolved inorganic carbon (DIC) from the northwestern Pacific. Due to the enhanced advection of DIC, the partial pressure of CO₂ increased faster than in the overlying air; consequently, the in-situ oceanic uptake of CO₂ decreased.     

Evaluation of Simulated CO_2 Concentrations from the CarbonTracker-Asia Model Using In-situ Observations over East Asia for 2009–2013

The CarbonTracker(CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO_2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO_2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO_2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO_2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model's performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO_2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within-0.3 and 1.3 ppm, except for inland stations(7.7 ppm).     

Effects of precipitation physics algorithms on a simulated climate in a general circulation model

The purpose of this study is to investigate the effects of precipitation physics in a general circulation model (GCM) on a simulated climate. Experiments are performed under the single column model (SCM) framework to examine basic features and under the general circulation model framework to investigate the impact on seasonal simulation. The SCM simulation shows that convection processes in the model have a considerable influence on the change in vertical thermodynamic structure, resulting in a change in precipitation, whereas in the GCM framework stratiform precipitation physics play a distinct role in changing the atmospheric structure. The GCM experiments also show that the overall reduction of precipitation in simulations with prognostic stratiform precipitation physics is highly related to changes in cloudiness and corresponding changes in radiative flux, which in turn leads to the reduction of convective activities.