LASG Global AGCM with a Two-moment Cloud Microphysics Scheme:Energy Balance and Cloud Radiative Forcing Characteristics

Cloud dominates influence factors of atmospheric radiation, while aerosol–cloud interactions are of vital importance in its spatiotemporal distribution. In this study, a two-moment(mass and number) cloud microphysics scheme, which significantly improved the treatment of the coupled processes of aerosols and clouds, was incorporated into version 1.1 of the IAP/LASG global Finite-volume Atmospheric Model(FAMIL1.1). For illustrative purposes, the characteristics of the energy balance and cloud radiative forcing(CRF) in an AMIP-type simulation with prescribed aerosols were compared with those in observational/reanalysis data. Even within the constraints of the prescribed aerosol mass, the model simulated global mean energy balance at the top of the atmosphere(TOA) and at the Earth's surface, as well as their seasonal variation, are in good agreement with the observational data. The maximum deviation terms lie in the surface downwelling longwave radiation and surface latent heat flux, which are 3.5 W m-2(1%) and 3 W m-2(3.5%), individually. The spatial correlations of the annual TOA net radiation flux and the net CRF between simulation and observation were around 0.97 and 0.90, respectively. A major weakness is that FAMIL1.1 predicts more liquid water content and less ice water content over most oceans. Detailed comparisons are presented for a number of regions, with a focus on the Asian monsoon region(AMR). The results indicate that FAMIL1.1 well reproduces the summer–winter contrast for both the geographical distribution of the longwave CRF and shortwave CRF over the AMR. Finally, the model bias and possible solutions, as well as further works to develop FAMIL1.1 are discussed.     

全球海洋模式对不同强迫场的响应

使用中国科学院大气物理研究所研制的全球海洋环流模式(LASG/IAP Climate system Ocean Model,LICOM),通过设计三个试验,即以德国马克斯—普朗克气象研究所整理的海洋模式比较计划(OMIP)资料和美国国家海洋资料中心(NODC)发布的《世界海洋图集2009》(WOA09)资料为强迫场的试验W,用美国环境预报中心(NCEP)和国家大气研究中心(NCAR)联合推出的NCEP/NCAR再分析资料(简称NCEP资料)中的风应力资料代替试验W中的风应力资料的试验M,以及用NCEP资料中的热力强迫代替试验M中的热力强迫资料的试验N,来研究不同的热力和动力强迫场对模式的影响。三个试验的模拟结果均模拟出了水团和流场的分布型和极值区。从三个试验的结果对比可以看出,NCEP资料较弱的风应力使得试验M环流场明显偏弱,减弱了大洋内部的温盐输送,加大了深海温盐模拟结果与观测资料的偏差,但对原模式过强的南极中层水的输送有所改善。NCEP的短波辐射通量和非短波热通量弱于OMIP,且在两极区域NCEP资料的海表温度比WOA09资料最多低 4℃以上。试验N的模拟结果改善了南大洋60°S以南海区试验W 模拟的海表温度偏高问题,减小了北冰洋部分海域以及副热带大洋东部海表温度的偏差。此外,试验N高纬度较低的海表温度增强了北大西洋深水以及南极底层水的输送,因而改善了深海的温盐模拟结果。三个试验在一些关键海区得到的经向热输送在观测估计及前人模拟结果的范围中,总体上试验M的输送最弱。综合三个试验的模拟结果,可以认为OMIP风应力资料和NCEP海表温度资料更适合作为LICOM模式的强迫场。     

利用LAS资料估算能量平衡各分量

一般气象台站都没有能量平衡射观测.而能量平衡各分量是判别下垫面状况的重要因子,本文利用乐至县LAS(Large Aperture Scintillometer)观测资料计算了显热通量,并通过能量平衡方程求得能量平衡各分量,揭示了能量平衡各分量的日变化和年变化规律,以及与下垫面干湿状况的关系.     

利用LAS资料估算能量平衡各分量

一般气象台站都没有能量平衡射观测。而能量平衡各分量是判别下垫面状况的重要因子，本文利用乐至县LAS（Large Aperture Scintillometer）观测资料计算了显热通量，并通过能量平衡方程求得能量平衡各分量，揭示了能量平衡分量的日变化和年变化规律，以及与下垫面干湿状况的关系。     

Impact of Spin-up Forcing on Vegetation States Simulated by a Dynamic Global Vegetation Model Coupled with a Land Surface Model

A dynamic global vegetation model (DGVM) coupled with a land surface model (LSM) is generally initialized using a spin-up process to derive a physically-consistent initial condition. Spin-up forcing, which is the atmospheric forcing used to drive the coupled model to equilibrium solutions in the spin-up process, varies across earlier studies. In the present study, the impact of the spin-up forcing in the initialization stage on the fractional coverages (FCs) of plant functional type (PFT) in the subsequent simulation stage are assessed in seven classic climate regions by a modified Community Land Model’s Dynamic Global Vegetation Model (CLM-DGVM). Results show that the impact of spin-up forcing is considerable in all regions except the tropical rainforest climate region (TR) and the wet temperate climate region (WM). In the tropical monsoon climate region (TM), the TR and TM transition region (TR-TM), the dry temperate climate region (DM), the highland climate region (H), and the boreal forest climate region (BF), where FCs are affected by climate non-negligibly, the discrepancies in initial FCs, which represent long-term cumulative response of vegetation to different climate anomalies, are large. Moreover, the large discrepancies in initial FCs usually decay slowly because there are trees or shrubs in the five regions. The intrinsic growth timescales of FCs for tree PFTs and shrub PFTs are long, and the variation of FCs of tree PFTs or shrub PFTs can affect that of grass PFTs.     

Parallelization Load Balance Strategy for a Global Grid-Point Model

The Global/Regional Assimilation and PrEdiction System (GRAPES) is a new-generation operational numerical weather prediction (NWP) model developed by the China Meteorological Administration (CMA).It is a grid-point model with a code structure different from that of spectral models used in other operational NWP centers such as the European Centre for Medium-Range Weather Forecasts (ECMWF),National Centers for Environmental Prediction (NCEP),and Japan Meteorological Agency (JMA),especially in the context of p...     

一种城市地表能量平衡模式在上海的模拟评估

利用一整年的上海城区常规气象和地表能量平衡观测资料,驱动和检验了局地城市地表能量(水分)平衡模式(SUEWS/LUMPS)在上海地区的模拟能力,并对模式输入参数进行了部分本地化。模拟结果表明,SUEWS模式较好地再现了各辐射通量的日变化形态,对净辐射通量(Q~*)中午日峰值低估约为25 W·m~(-2);模式对四个季节向下长波辐射通量(L_↓)的日变化幅度均被低估,对向上长波辐射通量(L_↑)的模拟明显优于L_↓。SUEWS/LUMPS模式对感热通量(Q_H)各季节(春季除外)日峰值出现时次均有准确模拟,而对Q_H量值各季节均为低估;SUEWS模式在夏、秋季对白天潜热通量(Q_E)的模拟均优于LUMPS模式,而在冬、春季的模拟情况两者接近;SUEWS模式成功再现了储热通量(△Q_S)冬、春、秋季早、晚正负值转换时间,而在夏季滞后了2 h,模拟的△Q_S量值季节差异性较大。对模式误差随气温、风速及风向变化进行分析表明,在较高气温和较大风速下,Q_H、Q_E均表现为低估误差增大,而△Q_S则相反,表现为更显著地高估;风向的影响主要表现为模式未考虑东面密集建筑群而使得Q_H较明显低估约为-50 W·m~(-2),而西侧公园绿地的存在使得Q_H高估约15 W·m~(-2)。     

评估43个CMIP5模式模拟全球能量平衡能力

<正>地球气候系统的能量平衡决定了地球气候及其变化的状况,因此全球能量平衡的研究一直受到重视,而地球气候系统模式对全球能量平衡的模拟效果也是研究的重要问题之一~([1-2])。IPCC第五次评估报告(AR5)指出~([1]),目前第五次模式对比计划(CMIP5)发展的地球系统模式在模拟气候系统5个圈层方面     

Understanding the Global Surface-Atmosphere Energy Balance in FGOALS-s2 through an Attribution Analysis of the Global Temperature Biases

Based on an attribution analysis of the global mean temperature biases in the Flexible Global OceanAtmosphere-Land System model, spectral version 2(FGOALS-s2) through a coupled atmosphere-surface climate feedback-response analysis method(CFRAM), the model's global surface-atmosphere energy balance in boreal winter and summer is examined. Within the energy-balance-based CFRAM system, the model temperature biases are attributed to energy perturbations resulting from model biases in individual radiative and non-radiative processes in the atmosphere and at the surface. The results show that, although the global mean surface temperature(Ts) bias is only 0.38 K in January and 1.70 K in July, and the atmospheric temperature(Ta) biases from the troposphere to the stratosphere are only around ±3 K at most, the temperature biases due to model biases in representing the individual radiative and non-radiative processes are considerably large(over ±10 K at most). Specifically, the global cold radiative Ts bias, mainly due to the overestimated surface albedo, is compensated for by the global warm non-radiative Ts bias that is mainly due to the overestimated downward surface heat fluxes. The model biases in non-radiative processes in the lower troposphere(up to 5–15 K) are relatively much larger than in upper levels, which are mainly responsible for the warm Ta biases there. In contrast, the global mean cold Ta biases in the mid-to-upper troposphere are mainly dominated by radiative processes. The warm/cold Ta biases in the lower/upper stratosphere are dominated by non-radiative processes, while the warm Ta biases in the mid-stratosphere can be attributed to the radiative ozone feedback process.     

Thermal Energy Balance Analysis of the Tokyo Metropolitan Area Using a Mesoscale Meteorological Model Incorporating an Urban Canopy Model

The summer climate around the Tokyo metropolitan area has been analysed on an urban scale, and the regional characteristics of the thermal energy balance of a bayside business district in the centre of Tokyo (Otemachi) have been compared with an inland residential district (Nerima), using a mesoscale meteorological model incorporating an urban canopy model. From the results of the analysis, the mechanism of diurnal change in air temperature and absolute humidity in these areas is quantitatively demonstrated, with a focus on the thermal energy balance. Moreover, effective countermeasures against urban heat-islands are considered from the viewpoint of each region’s thermal energy balance characteristics. In addition to thermal energy outflux by turbulent diffusion, advection by sea-breezes from Tokyo Bay discharges sensible heat in Otemachi. This mitigates temperature increases during the day. On the other hand, because all sea-breezes must first cross the centre of Tokyo, it has less of a cooling effect in Nerima. As a result, the air temperature during the day in Nerima is higher than that in Otemachi.     

GRAPES全球模式的动能谱分析

大量的观测资料表明在对流层高层和平流层低层,大气动能谱在大尺度范围(800 km以上)与波数呈现出-3的斜率关系,而过渡到中尺度范围(400 km以下)二者呈现出-5/3的斜率关系。模式预报结果能否展现大气动能谱的这种斜率转折特征已经成为模式评估的有效方法。本文采用GRAPES全球中期数值预报模式2013年5月的预报结果,计算了模式一维和二维动能谱,并分析了二维谱的旋转分量与辐散分量、平均分量与扰动分量的关系。结果表明,GRAPES模式的一维谱和二维谱结果均能较好地表现出动能谱的斜率转折特征,但该模式动能谱在中尺度范围的斜率绝对值明显比观测结果和其它模式结果偏大;二维谱的旋转分量和辐散分量、平均分量和扰动分量在总动能谱中的比重关系及其随高度的变化均与文献结果较为一致。总之,GRAPES模式整体上较好地再现了大气动能谱的各种特征,但是可能由于模式分辨率和耗散作用的影响,模式对大气中尺度波动的描述还不够充分。     

基于深度学习的全球平均表面温度年际信号时间序列的预测北大核心CSCD

利用集合经验模态分解(Ensemble Empirical Mode Decomposition,EEMD)有效地分解了全球平均表面温度(Global Mean Surface Temperature,GMST)时间序列,得到其不同尺度的、不同特征的子序列(Intrinsic Mode Function,IMF)。在此基础上,利用在预测长期、复杂、非线性变化的时间序列上具有显著优势的滑动自回归机器学习(Autoregressive Integrated Moving Average,ARIMA)模型和长短期记忆网络(Long Short-Term Memory,LSTM)模型开展GMST年际信号预测研究。结果表明:深度学习模型LSTM能很好地拟合并预测了长程相关性强的子序列(第2~6个IMF),而代表GMST年际尺度变化的IMF1则在一定程度上受到太平洋大西洋多重气候信号的影响和调制,因此进一步将3个气候指数作为预报前兆因子加入预测模型来更准确地预测IMF1的时间演变。通过利用多套GMST数据的对比,最终选定了考虑实时ENSO信息的LSTM(ENSO)模型来提前预测年际GMST信号,并预测2020年将有较大概率会成为史上最热的年份之一。     

各种物理强迫激发的平均经圈环流特征及其对数值天气预报模式系统误差的贡献

本文证明7种强迫作用激发经圈环流的线性叠加性，分项考察了各种物理强迫激发经圈环流的特征，通过考察一个数值模式的模式大气和实际大气各种物理强迫激发经圈环流的差异，分析了模式系统误差的成因，这种建立在动力背景之上的模式误差分析方法，其物理意义明确，具有较为普遍的适用性。     

Modeling Study of the Global Distribution of Radiative Forcing by Dust Aerosol

To quantitatively understand the dust aerosol effects on climate change,we calculated the global distribution of direct radiative forcing due to dust aerosol under clear and cloudy skies in both winter and summer,by using an improved radiative transfer model and the global distribution of dust mass concentration given by GADS (Global Aerosol Data Set).The results show that the global means of the solar forcing due to dust aerosol at the tropopause for winter and summer are –0.48 and –0.50 W m-2 ,respectivel...     

冷平流强迫背景下攀枝花市一次雷暴过程综合分析

基于欧洲中心ERA5再分析资料、NCEP再分析资料、卫星和雷达资料以及MICAPS气象资料,运用天气学方法对2020年4月13日四川省攀枝花市发生的冷平流强迫类雷暴天气过程进行综合分析。结果表明：本次雷暴过程混合了冰雹、短时强降水、雷暴大风等多种天气,其主要影响系统为200 hPa高空急流、500 hPa高原槽、700 hPa切变线和西南急流以及地面辐合线。200~500 hPa西北干冷空气顺高原槽南下对本次过程起主导作用,弱的700 hPa西南急流为本地输送了水汽和不稳定能量,中低层切变线和地面辐合线促进了暖湿气流的辐合抬升。此外,“上冷下暖”的气层结构、中低层较强的垂直风切变、气流的低层辐合与高层辐散、适宜的0℃和-20℃层高度、较强的CAPE和K指数、较大的700~500 hPa温度垂直递减率等因素也是本次雷暴天气过程发生发展的关键。     

一次大暴雨天气过程的能量分析

利用数值预报产品及能量方法分析了１９９５年８月２１－２３是鲁南和山东半财区大暴雨天气过程。结果表明：暴雨产生在低层高能舌准饱能舌，准饱和及对流不稳定的区域；５００ｈＰａ正涡度舌与８５０ｈＰａ暖切变及需所了旋中心相配合，产生较强的上升运动，触发对流不稳定能量释放，产生大暴雨。     

一维辐射-对流模式对云辐射强迫的数值模拟研究

利用一维辐射－对流气候模式, 详细研究了云量、云光学厚度以及云高等要素的变化对大气顶和地面太阳短波辐射和红外长波辐射通量以及云的辐射强迫的影响, 给出了计算这些物理量的经验拟合公式。结果表明, 云具有极为重要的辐射－气候效应。云量、云光学厚度以及云高即使只有百分之几的变化, 所带来的辐射强迫也可以与大气二氧化碳浓度加倍所产生的辐射强迫（3.75 W/m2）相比拟。例如, 当分别给它们+3%的扰动时, 即取云量变化0.015, 云光学厚度变化0.27, 以及云高变化0.15 km时（在实际的地球大气中, 这种尺度的变化是完全可能发生的）, 那么,可以得到地气系统的太阳短波辐射强迫-3.10 W/m2以及红外长波辐射强迫-1.77 W/m2, 二者之和为-4.78 W/m2, 已经完全可以抵消大气二氧化碳浓度加倍所产生的辐射强迫。但是, 当云量、云光学厚度以及云高向相反方向产生类似扰动时, 所产生的辐射强迫可能极大地放大二氧化碳浓度增加所产生的增强温室效应。因此, 研究结果揭示出, 不管是为了解释过去的气候变化, 还是预测未来的气候变化, 亟待加强在一个变化了的气候环境（例如地面温度升高）下, 云将发生何种变化的研究。     

Responses of Mean and Extreme Precipitation to Different Climate Forcing Under Radiative-Convective Equilibrium

Understanding the responses of mean and extreme precipitation to climate change is of great importance.Previous studies have mainly focused on the responses to prescribed sea surface warming or warming due to increases of CO2.This study uses a cloud-resolving model under the idealization of radiative-convective equilibrium to examine the responses of mean and extreme precipitation to a variety of climate forcings,including changes in prescribed sea surface temperature,CO2,solar insolation,surface albedo,stratospheric volcanic aerosols,and several tropospheric aerosols.The different responses of mean precipitation are understood by examining the changes in the surface energy budget.It is found that the cancellation between shortwave scattering and longwave radiation leads to a small dependence of the mean precipitation response on forcings.The responses of extreme precipitation are decomposed into three components(thermodynamic,dynamic,and precipitation efficiency).The thermodynamic components for all climate forcings are similar.The dynamic components and the precipitation-efficiency components,which have large spreads among the cases,are negatively correlated,leading to a small dependence of the extreme precipitation response on the forcings.     

Analytical Model for Mean Flow and Fluxes of Momentum and Energy in Very Large Wind Farms

As wind-turbine arrays continue to be installed and the array size continues to grow, there is an increasing need to represent very large wind-turbine arrays in numerical weather prediction models, for wind-farm optimization, and for environmental assessment. We propose a simple analytical model for boundary-layer flow in fully-developed wind-turbine arrays, based on the concept of sparsely-obstructed shear flows. In describing the vertical distribution of the mean wind speed and shear stress within wind farms, our model estimates the mean kinetic energy harvested from the atmospheric boundary layer, and determines the partitioning between the wind power captured by the wind turbines and that absorbed by the underlying land or water. A length scale based on the turbine geometry, spacing, and performance characteristics, is able to estimate the asymptotic limit for the fully-developed flow through wind-turbine arrays, and thereby determine if the wind-farm flow is fully developed for very large turbine arrays. Our model is validated using data collected in controlled wind-tunnel experiments, and its usefulness for the prediction of wind-farm performance and optimization of turbine-array spacing are described. Our model may also be useful for assessing the extent to which the extraction of wind power affects the land–atmosphere coupling or air–water exchange of momentum, with implications for the transport of heat, moisture, trace gases such as carbon dioxide, methane, and nitrous oxide, and ecologically important oxygen.