Decreasing Trend in Global Land Monsoon Precipitation over the Past 50 Years Simulated by a Coupled Climate Model

The authors examine the effects of external forcing agents such as greenhouse gases （GHGs） and aerosols, as well as solar variability and ozone, on global land monsoon precipitation by using a coupled climate model HadGEM1, which was developed by the Met Office Hadley Centre for Climate Research. The results indicate that HadGEM1 performs well in simulating the observed decreasing trend of global land monsoon precipitation over the past 50 years. This trend mainly occurred in the Northern Hemisphere and is significantly different from the trend of natural variability due to ocean-atmosphere-land interactions. The coherence between the simulation and the observations indicates that the specified external forcing agents, including GHGs and aerosols as well as solar variability and ozone, are important factors that have affected the decreasing trend of global land monsoon precipitation in the past 50 years.

The Interannual Variability of East Asian Monsoon and Its Relationship with SST in a Coupled Atmosphere-Ocean-Land Climate Model

Based on a 200 year simulation and reanalysis data (1980–1996), the general characteristics of East Asian monsoon (EAM) were analyzed in the first part of the paper. It is clear from this re-search that the South Asian monsoon (SAM) defined by Webster and Yang (1992) is geographically and dynamically different from the East Asian monsoon (EAM). The region of the monsoon defined by Webster and Yang (1992) is located in the tropical region of Asia (40–110°E, 10–20°N), including the Indian monsoon and the Southeast Asian monsoon, while the EAM de-fined in this paper is located in the subtropical region of East Asia (110–125°E, 20–40°N). The components and the seasonal variations of the SAM and EAM are different and they characterize the tropical and subtropical Asian monsoon systems respectively. A suitable index (EAMI) for East Asian monsoon was then defined to describe the strength of EAM in this paper. In the second part of the paper, the interannual variability of EAM and its relationship with sea surface temperature (SST) in the 200 year simulation were studied by using the composite method, wavelet transformation, and the moving correlation coefficient method. The summer EAMI is negatively correlated with ENSO (El Nino and Southern Oscillation) cycle represented by the NINO3 sea surface temperature anomaly (SSTA) in the preceding April and January, while the winter EAM is closely correlated with the succeeding spring SST over the Pacific in the coupled model. The general differences of EAM between El Nino and La Nina cases were studied in the model through composite analysis. It was also revealed that the dominating time scales of EAM variability may change in the long-term variation and the strength may also change. The anoma-lous winter EAM may have some correlation with the succeeding summer EAM, but this relation-ship may disappear sometimes in the long-term climate variation. Such time-dependence was found in the relationship between EAM and SST in the long-term climate simulation as well. Key words East Asian monsoon - Interannual variability - Coupled climate model The author wishes to thank Profs. Wu G.X., Zhang X.H., and Dr. Yu Y.Q. for providing the coupled model re-sults. Dr. Yu also kindly provided assistance in using the model output. This work was supported jointly by the Na-tional Natural Science Foundation of China key project ’ The analysis on the seasonal-to-interannual variation of the general circulation’ under contract 49735160 and Chinese Academy of Sciences key project ’ The Interannual Va-riability and Predictability of East Asian Monsoon’.

Multi-model Projection of July–August Climate Extreme Changes over China under CO_2 Doubling. Part I: Precipitation

Potential changes in precipitation extremes in July–August over China in response to CO 2 doubling are analyzed based on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models （20C3M） experiment and the 1% per year CO 2 increase experiment （to doubling） （1pctto2x） of phase 3 of the Coupled Model Inter-comparison Project （CMIP3）. Evaluation of the models’ performance in simulating the mean state shows that the majority of models fairly reproduce the broad spatial pattern of observed precipitation. However, all the models underestimate extreme precipitation by ～50%. The spread among the models over the Tibetan Plateau is ～2–3 times larger than that over the other areas. Models with higher resolution generally perform better than those with lower resolutions in terms of spatial pattern and precipitation amount. Under the 1pctto2x scenario, the ratio between the absolute value of MME extreme precipitation change and model spread is larger than that of total precipitation, indicating a relatively robust change of extremes. The change of extreme precipitation is more homogeneous than the total precipitation. Analysis on the output of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 （GFDL-CM2.1） indicates that the spatially consistent increase of surface temperature and water vapor content contribute to the large increase of extreme precipitation over contiguous China, which follows the Clausius–Clapeyron relationship. Whereas, the meridionally tri-polar pattern of mean precipitation change over eastern China is dominated by the change of water vapor convergence, which is determined by the response of monsoon circulation to global warming.

Multi-Model Projection of July–August Climate Extreme Changes over China under CO_2 Doubling. Part II: Temperature

This is the second part of the authors’ analysis on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models （20C3M） experiment and 1% per year CO 2 increase experiment （to doubling） （1pctto2x） of phase 3 of the Coupled Model Inter-comparison Project （CMIP3）. The study focuses on the potential changes of July–August temperature extremes over China. The pattern correlation coefficients of the simulated temperature with the observations are 0.6–0.9, which are higher than the results for precipitation. However, most models have cold bias compared to observation, with a larger cold bias over western China （5°C） than over eastern China （2°C）. The multi-model ensemble （MME） exhibits a significant increase of temperature under the 1pctto2x scenario. The amplitude of the MME warming shows a northwest–southeast decreasing gradient. The warming spread among the models （～1°C– 2°C） is less than MME warming （～2°C–4°C）, indicating a relatively robust temperature change under CO 2 doubling. Further analysis of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 （GFDL-CM2.1） simulations suggests that the warming pattern may be related to heat transport by summer monsoons. The contrast of cloud effects also has contributions. The different vertical structures of warming over northwestern China and southeastern China may be attributed to the different natures of vertical circulations. The deep, moist convection over southeastern China is an effective mechanism for ＂transporting＂ the warming upward, leading to more upper-level warming. In northwestern China, the warming is more surface-orientated, possibly due to the shallow, dry convection.

Major Modes of Short-Term Climate Variability in the Newly Developed NUIST Earth System Model(NESM)

A coupled earth system model（ESM） has been developed at the Nanjing University of Information Science and Technology（NUIST） by using version 5.3 of the European Centre Hamburg Model（ECHAM）, version 3.4 of the Nucleus for European Modelling of the Ocean（NEMO）, and version 4.1 of the Los Alamos sea ice model（CICE）. The model is referred to as NUIST ESM1（NESM1）. Comprehensive and quantitative metrics are used to assess the model＇s major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model＇s assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring–fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific（CP）-ENSO and eastern Pacific（EP）-ENSO; however, the equatorial SST variability,biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden–Julian Oscillation（MJO）, and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version（T159） demonstrates improved simulation with respect to the climatology, interannual variance, monsoon–ENSO lead–lag correlation, spatial structures of the leading mode of the Asian–Australian monsoon rainfall variability, and the eastward propagation of the MJO.

Atmosphere-Ocean Coupling Schemes in a One-Dimensional Climate Model

In this paper, the coupling schemes of atmosphere-ocean climate models are discussed with one-dimensional advection equations. The convergence and stability for synchronous and asynchronous schemes are demonstrated and compared.Conclusions inferred from the analysis are given below. The synchronous scheme as well as the asynchronous-implicit scheme in this model are stable for arbitrary integrating time intervals. The asynchronous explicit scheme is unstable under certain conditions, which depend upon advection velocities and heat exchange parameters in the atmosphere and oceans. With both synchronous and asynchronous stable schemes the discrete solutions converge to their unique exact ones. Advections in the atmosphere and ocean accelerate the rate of convergence of the asynchronous-implicit scheme. It is suggusted that the asynchronous-implicit coupling scheme is a stable and efficient method for most climatic simulations.

Evaluation of Arctic sea ice simulation of CMIP6 models from China

Nine coupled climate models from China participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)were evaluated in terms of their capability in ensemble historical Arctic sea ice simulation in the context of 56 CMIP6 models.We evaluated these nine models using satellite observations from 1980 to 2014.This evaluation was conducted comprehensively using 12 metrics covering different aspects of the seasonal cycle and long-term trend of sea ice extent(SIE)and sea ice concentration(SIC).The nine Chinese modelstended to overestimate SIE,especially in March,and underestimate its long-term decline trend.There was less spread in model skill in reproducing the spatial pattern of March SIC than in reproducing the spatial pattern of September SIC.The error of March SIC simulation was distributed at the margins of sea ice cover,such as in the Nordic Seas,the Barents Sea,the Labrador Sea,the Bering Sea,and the Sea of Okhotsk.However,the error of September SIC was distributed both at the margins of sea ice cover and in the central part of the Arctic Basin.Five of these nine models had capabilities comparable with the majority of the CMIP6 models in reproducing the seasonal cycle and long-term trend of Arctic sea ice.

多种代用资料和模型模拟得到的亚洲季风在8.2ka显著气候影响的证据（英文）

Given the likelihood of future reductions in the strength of the Atlantic Meridional Overturning Circulation(AMOC),it is important to document how changes in the AMOC have altered climate patterns in the past and to assess the skill of coupled climate models in reproducing these teleconnections.Of past abrupt changes in the AMOC,the 8.2 ka event provides a particularly useful case study because its duration,magnitude of AMOC reduction and background climate state are closest to conditions expected in the future.In this research,we present an expanded proxy synthesis of the 8.2 ka event in monsoonal Asia,including new high-resolution lake and bog records,more sites from the East Asia monsoon region and proxies of winter monsoon strength.We compare proxy evidence with a new simulation of the 8.2 ka event using the Community Climate System Model version 3(CCSM3) and prescribing North Atlantic freshwater forcing according to the latest reconstructions.We find clear and objectively-determined evidence for 8.2 ka climate anomalies at nearly all of the fourteen proxy sites,emphasizing the strong and widespread impacts of the event in monsoonal Asia during both summer and winter seasons.The model simulation corroborates that these anomalies,described generally as a weakening of the summer monsoon and strengthening of the winter monsoon,were likely caused by a reduction of the AMOC.Examination of regional anomalies in East Asia reveals some spatial heterogeneity,however,that in the model simulation is caused by contraction of the seasonal migration of the subtropical monsoon front.The duration of climate anomalies at 8.2 ka in monsoonal Asia,both in proxy records and the model simulation,generally matches the duration of the event in Greenland ice core δ^(18)O,further supporting a tight connection to the North Atlantic.

Nonlinear changes in cold spell and heat wave arising from Arctic sea-ice loss

Whether Arctic sea-ice loss has significant impacts on climate extremes in mid-and high-latitudes remains uncertain.Here we show the full response of cold and warm extremes under two Arctic sea-ice loss scenarios utilizing a coupled global climate model that permits the air-sea coupling.Our results show that the amount of Arctic sea-ice loss determines the spatial extent and magnitude of the weakening of atmospheric circulation in mid-and high-latitudes of the northern hemisphere,leading to nonlinear changes in cold and warm extremes.A relatively localized and moderate weakening of atmospheric circulation induced by the projected sea-ice loss in the next two decades would contribute to less winter cold extremes over the Northern Hemispheric continents.The risks of winter cold spells would be dramatically reduced as the amount of sea-ice loss is increased to the ice-free state.In contrast,as sea-ice loss increases,the continental regions would have increased risk of heat waves over all mid-and high-latitudes.

Development of a Downscaling Method in China Regional Summer Precipitation Prediction

A downscaling method taking into account of precipitation regionalization is developed and used in the regional summer precipitation prediction （RSPP） in China. The downscaling is realized by utilizing the optimal subset regression based on the hindcast data of the Coupled Ocean-Atmosphere General Climate Model of National Climate Center （CGCM/NCC）, the historical reanalysis data, and the observations. The data are detrended in order to remove the influence of the interannual variations on the selection of predictors for the RSPP. Optimal predictors are selected through calculation of anomaly correlation coefficients （ACCs） twice to ensure that the high-skill areas of the CGCM/NCC are also those of observations, with the ACC value reaching the 0.05 significant level. One-year out cross-validation and independent sample tests indicate that the downscaling method is applicable in the prediction of summer precipitation anomaly across most of China/vith high and stable accuracy, and is much better than the direct CGCM/NCC prediction. The predictors used in the downscaling method for the RSPP are independent and have strong physical meanings, thus leading to the improvements in the prediction of regional precipitation anomalies.