The Application of Flux-Form Semi-Lagrangian Transport Scheme in a Spectral Atmosphere Model

A flux-form semi-Lagrangian transport scheme(FFSL) was implemented in a spectral atmospheric GCM developed and used at IAP/LASG.Idealized numerical experiments show that the scheme is good at shape preserving with less dissipation and dispersion,in comparison with other conventional schemes.Importantly,FFSL can automatically maintain the positive definition of the transported tracers,which was an underlying problem in the previous spectral composite method(SCM).To comprehensively investigate the impact of FFSL on GCM results,we conducted sensitive experiments.Three main improvements resulted:first,rainfall simulation in both distribution and intensity was notably improved,which led to an improvement in precipitation frequency.Second,the dry bias in the lower troposphere was significantly reduced compared with SCM simulations.Third,according to the Taylor diagram,the FFSL scheme yields simulations that are superior to those using the SCM:a higher correlation between model output and observation data was achieved with the FFSL scheme,especially for humidity in lower troposphere.However,the moist bias in the middle and upper troposphere was more pronounced with the FFSL scheme.This bias led to an over-simulation of precipitable water in comparison with reanalysis data.Possible explanations,as well as solutions,are discussed herein.     

2008年北京奥运会期间污染控制效果数值模拟——以个例分析为例

利用2007和2008年北京地区空气质量监测资料和NCEP再分析资料,分析了北京地区空气动力学当量直径小于等于10μm颗粒物(PM10)污染过程与天气形势及天气系统之间的关系。结果表明:西太平洋热带气旋路径对北京地区发生PM10污染具有预示作用,即当热带气旋北上并在朝鲜半岛或日本登陆的情况下,北京地区一般受持续均压场等弱中尺度天气系统控制,这种中尺度天气系统不利于污染物的扩散,因此北京地区经常发生区域性的PM10空气污染事件。在2007年9次台风北上登陆朝鲜半岛或日本的过程中,北京地区伴随发生了9次PM10污染过程,预示准确率达100%,2008年的预示准确率也达到了80%以上。为了说明北京奥运会期间污染控制措施对改善北京空气质量有实际效果,利用中国科学院大气物理研究所区域空气质量模式NAQPMS,采用无控制措施源和有控制措施源,对2008年北京残奥会期间一次西太平洋北上型热带气旋天气条件下的空气质量状况进行了数值模拟试验,揭示了此次过程北京地区未发生PM10空气污染的原因。     

一个海洋环流模式模拟的北印度洋经向环流及其热输送

对比两个同化资料GODAS（Global Ocean Data Assimilation System）和SODA（Simple Ocean Data Assimilation）,考察中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室发展的气候系统海洋模式LICOM（LASG/IAP Climate system Ocean Model）模拟的北印度洋经向环流及热输送的气候态。LICOM能抓住北印度洋大尺度环流的季节变化特征,模拟的年平均越赤道热输送为-0.24 PW （1 PW=1015W）,较之以往的数值模式结果更接近观测和同化资料。与同化资料的差异主要体现在季节变化强度,北半球夏季在赤道以南偏弱0.5 PW,这与模式夏季的纬向风应力偏弱,热输送中的大项Ekman热输送模拟偏弱,从而模拟的经圈翻转环流较浅有关。     

Evaluation of Surface Air Temperature Change over China and the Globe during the Twentieth Century in IAP AGCM4.0

Based on time series and linear trend analysis, the authors evaluated the performance of the fourth generation atmospheric general circulation model developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP AGCM4.0), in simulating surface air temperature (SAT) during the twentieth century over China and the globe. The numerical experiment is conducted by driving the model with the observed sea surface temperature and sea ice. It is shown that IAP AGCM4.0 can simulate the warming trend of the global SAT, with the major warming regions in the high latitudes of the Northern Hemisphere and the mid-latitudes of the Southern Hemisphere. While the simulated trend over the whole globe is close to the observation, the model under-estimates the observed trend over the continents. More-over, the model simulates the spatial distribution of SAT in China, with a bias of approximately-2°C in eastern China, but with a more serious bias in western China. Compared with the global mean, however, the correlation coefficient between the simulation and observation in China is significantly lower, indicating that there is large uncertainty in simulating regional climate change.     

The Impact of Volcanic Eruption on Decadal-Scale Climate Prediction Skill of Pacic Sea Surface Temperatures in the IAP Near-Term Climate Prediction System(IAP DecPreS)

Explosive volcanic eruptions are known to be a leading cause of natural climate change. There has been a growing recognition that there is a measurable climate system response even to moderate-sized volcanic eruptions. In this study, we investigated the hindcast skills of the Pacific Sea Surface Temperatures (SSTs) using the hindcast experiments based on the near-term climate prediction system DecPreS developed by the Institute of Atmospheric Physics (IAP)(hereafter DP-EnOI-IAU experiments). The DP-EnOI-IAU experiments were run for initial years from 1960 to 2005. These hindcasts took into account observed stratospheric aerosol concentrations that included the four large tropical volcanic eruptions during that period. The time evolution over the entire hindcast period for skill in predicting the patterns of the 3~7 year prediction averages for Pacific SSTs showed that there was statistically significant skill for most years except for a dramatic drop in skill during the 1980s and 1990s. Decadal hindcast skill is reduced if the post-eruption model response deviates the internal El Niño variability in the observations. The simulations showed a post-eruption SST of a La Niña-like pattern in the third northern winter after the 1982 El Chichon eruption and a El Niño-like pattern after the 1991 Pinatubo eruption, which were opposite in sign to what was in the observations. This lead to the loss of hindcast skill for years in the 1980s and 1990s affected by the eruptions. Agung (1963) happened to have post-eruption Pacific SSTs more similar to the observations and thus did not degrade prediction skill in the hindcasts.     

IAP AGCM 4.1对淮河流域夏季降水的预报技巧评估

基于中国科学院大气物理研究所新一代大气环流模式IAP AGCM 4.1共30 a(1981—2010年)的集合回报试验结果,评估了模式对淮河流域夏季降水的预报技巧。分析结果表明,模式总体上可以较好地再现出淮河流域夏季平均降水南多北少的空间分布特征,其中模式模拟的6月降水量与观测值的空间相关可达0.93。但降水强度与观测相比具有系统性的偏差,且模式模拟的降水年际变率显著偏弱。基于降水距平相关系数的确定性预报技巧分析表明,模式对流域西南部夏季降水的预测技巧较高,达到0.2以上,且模式对6月降水异常的预测能力相对最好,7月次之。针对淮河不同子流域的预报技巧分析表明,IAP AGCM 4. 1对蚌埠、鲁台子、王家坝水文控制站以上集水面积的夏季面雨量异常具有一定的预报技巧,30 a集合回报的时间相关系数分别为0. 11、0. 13、0. 16。基于降水等级的概率预报技巧评估表明,模式对7月淮河流域南部少雨事件具有很好的预报能力,同时对6月流域中部多雨事件的预报技巧也较高。     

Simulating the intraseasonal variation of the East Asian summer monsoon by IAP AGCM4.0

ABSTRACT This study focuses on the intraseasonal variation of the East Asian summer monsoon （EASM） simulated by IAP AGCM 4.0, the fourth-generation atmospheric general circulation model recently developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences. In general, the model simulates the intraseasonal evolution of the EASM and the related rain belt. Besides, the model also simulates the two northward jumps of the westem Pacific subtropical high （WPSH）, which are closely related to the convective activities in the warm pool region and Rossby wave activities in high latitudes. Nevertheless, some evident biases in the model were found to exist. Due to a stronger WPSH, the model fails to simulate the rain belt in southern China during May and June. Besides, the model simulates a later retreat of the EASM, which is attributed to the overestimated land-sea thermal contrast in August. In particular, the timing of the two northward jumps of the WPSH in the model is not coincident with the observation, with a later jump by two pentads for the first jump and an earlier jump by one pentad for the second, i.e., the interval between the two jumps is shorter than the observation. This bias is mainly ascribed to a shorter oscillating periodicity of convection in the tropical northwestern Pacific.     

Performance of a parallel finite difference atmospheric general circulation model 1

A new version of the Institute of Atmospheric Physics (IAP) 9-Layer (9L) atmospheric general circulation model (AGCM) suitable for Massively Parallel Processor (MPP) has been developed. This paper presents the principles of the parallel code design and examines its performance on a variety of state-of-the-art parallel computers in China. Domain decomposition strategy is used to achieve parallelism that is implemented by Message Passing Interface (MPI). Only the one dimensional domain decomposition algorithm is shown to scale favorably as the number of processors is increased. This work is partly supported by the National Natural Science Foundation of China (Grant Nos. 49775268 and 49823002), the China National Key Development Planning Project for Basic Research (Grant No. G1998040905) and the CAS Key Innovation Direction Project (Grant No. KZCX2208).