Shallow Convection Dataset Simulated by Three Different Large Eddy Models

Shallow convection plays an important role in transporting heat and moisture from the near-surface to higher altitudes,yet its parameterization in numerical models remains a great challenge,partly due to the lack of high-resolution observations.This study describes a large eddy simulation(LES)dataset for four shallow convection cases that differ primarily in inversion strength,which can be used as a surrogate for real data.To reduce the uncertainty in LES modeling,three different large eddy models were used,including SAM(System for Atmospheric Modeling),WRF(Weather Research and Forecasting model),and UCLA-LES.Results show that the different models generally exhibit similar behavior for each shallow convection case,despite some differences in the details of the convective structure.In addition to grid-averaged fields,conditionally sampled variables,such as in-cloud moisture and vertical velocity,are also provided,which are indispensable for calculation of the entrainment/detrainment rate.Considering the essentiality of the entraining/detraining process in the parameterization of cumulus convection,the dataset presented in this study is potentially useful for validation and improvement of the parameterization of shallow convection.

Analysis of surface temperature bias over the Tibetan plateau in the CAS FGOALS-f3-L model

The Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System atmospheric component model(FGOALS-f3-L)participated in Phase 6 of the Coupled Model Intercomparison Project,but its reproducibility of surface temperature(T_(s))over the Tibetan Plateau(TP)as a key climatically sensitive region remains unclear.This study evaluates the capability of FGOALS-f3-L in reproducing the climatological T_(s)over the TP relative to the Climate Forecast System Reanalysis.The results show that FGOALS-f3-L can reasonably capture the spatial pattern of T_(s)but underestimates the annual mean T_(s)for the whole TP.The simulated T_(s)for the whole TP shows a cold bias in winter and spring and a warm bias in summer and autumn.Further quantitative analysis based on the surface energy budget equation shows that the surface albedo feedback(SAF)term strongly contributes to the annual,winter,and spring mean cold bias in the western TP and to the warm bias in the eastern TP.Compared with the SAF term,the surface sensible and latent heat flux terms make nearly opposite contributions to the T_(s)bias and considerably offset the bias due to the SAF term.The cloud radiative forcing term strongly contributes to the annual and seasonal mean weak cold bias in the eastern TP.The longwave radiation term associated with the overestimated water vapor content accounts for a large portion of the warm bias over the whole TP in summer and autumn.Improving land surface and cloud processes in FGOALS-f3-L is critical to reduce the T_(s)bias over the TP.

CAS FGOALS-f3-L Model Datasets for CMIP6 Historical Atmospheric Model Intercomparison Project Simulation

The outputs of the Chinese Academy of Sciences(CAS) Flexible Global Ocean–Atmosphere–Land System(FGOALS-f3-L) model for the baseline experiment of the Atmospheric Model Intercomparison Project simulation in the Diagnostic,Evaluation and Characterization of Klima common experiments of phase 6 of the Coupled Model Intercomparison Project(CMIP6) are described in this paper. The CAS FGOALS-f3-L model, experiment settings, and outputs are all given. In total,there are three ensemble experiments over the period 1979–2014, which are performed with different initial states. The model outputs contain a total of 37 variables and include the required three-hourly mean, six-hourly transient, daily and monthly mean datasets. The baseline performances of the model are validated at different time scales. The preliminary evaluation suggests that the CAS FGOALS-f3-L model can capture the basic patterns of atmospheric circulation and precipitation well, including the propagation of the Madden–Julian Oscillation, activities of tropical cyclones, and the characterization of extreme precipitation. These datasets contribute to the benchmark of current model behaviors for the desired continuity of CMIP.

CAS FGOALS-f3-L Model Datasets for CMIP6 GMMIP Tier-1 and Tier-3 Experiments

The Chinese Academy of Sciences(CAS)Flexible Global Ocean Atmosphere Land System(FGOALS-f3-L)model datasets prepared for the sixth phase of the Coupled Model Intercomparison Project(CMIP6)Global Monsoons Model Intercomparison Project(GMMIP)Tier-1 and Tier-3 experiments are introduced in this paper,and the model descriptions,experimental design and model outputs are demonstrated.There are three simulations in Tier-1,with different initial states,and five simulations in Tier-3,with different topographies or surface thermal status.Specifically,Tier-3 contains four orographic perturbation experiments that remove the Tibetan Iranian Plateau,East African and Arabian Peninsula highlands,Sierra Madre,and Andes,and one thermal perturbation experiment that removes the surface sensible heating over the Tibetan Iranian Plateau and surrounding regions at altitudes above 500 m.These datasets will contribute to CMIP6’s value as a benchmark to evaluate the importance of long-term and short-term trends of the sea surface temperature in monsoon circulations and precipitation,and to a better understanding of the orographic impact on the global monsoon system over highlands.

The FGOALS climate system model as a modeling tool for supporting climate sciences:An overview

Climate system models are useful tools for understanding the interactions among the components of the climate system and predicting/projecting future climate change. The development of climate models has been a central focus of the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences(LASG/IAP) since the establishment of the laboratory in 1985. In China, many pioneering component models and fully coupled models of the climate system have been developed by LASG/IAP. The fully coupled climate system developed in the recent decade is named FGOALS(Flexible Global Ocean-Atmosphere-Land System Model). In this paper, an application-oriented review of the LASG/IAP FGOALS model is presented. The improved model performances are demonstrated in the context of cloud-radiation processes, Asian monsoon, ENSO phenomena, Atlantic Meridional Overturning Circulation(AMOC) and sea ice. The FGOALS model has contributed to both CMIP5(Coupled Model Intercomparison Project-phase 5) and IPCC(Intergovernmental Panel on Climate Change) AR5(the Fifth Assessment Report). The release of FGOALS data has supported the publication of nearly 500 papers around the world. The results of FGOALS are cited ~106 times in the IPCC WG1(Working Group 1) AR5. In addition to the traditional long-term simulations and projections, near-term decadal climate prediction is a new set of CMIP experiment, progress of LAGS/IAP in the development of nearterm decadal prediction system is reviewed. The FGOALS model has supported many Chinese national-level research projects and contributed to the national climate change assessment report. The crucial role of FGOALS as a modeling tool for supporting climate sciences is highlighted by demonstrating the model's performances in the simulation of the evolution of Earth's climate from the past to the future.

Cellulose-based materials in wastewater treatment of petroleum industry

The most abundant natural biopolymer on earth, cellulose fiber, may offer a highly efficient, low-cost, and chemical-free option for wastewater treatment. Cellulose is widely distributed in plants and several marine animals. It is a carbohydrate polymer consisting of β-1,4-linked anhydro-D-glucose units with three hydroxyl groups per anhydroglucose unit(AGU). Cellulose-based materials have been used in food, industrial, pharmaceutical, paper, textile production, and in wastewater treatment applications due to their low cost, renewability,biodegradability, and non-toxicity. For water treatment in the oil and gas industry, cellulose-based materials can be used as adsorbents, flocculants, and oil/water separation membranes. In this review, the uses of cellulose-based materials for wastewater treatment in the oil & gas industry are summarized, and recent research progress in the following aspects are highlighted: crude oil spill cleaning, flocculation of solid suspended matter in drilling or oil recovery in the upstream oil industry, adsorption of heavy metal or chemicals, and separation of oil/water by cellulosic membrane in the downstream water treatment.

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.

Characterization of cloud microphysical properties in different cloud types over East Asia based on CloudSat/CALIPSO satellite products

By using four-year CloudSat/CALIPSO satellite data,the authors investigated cloud microphysical properties in three representative regions over East Asia,where models commonly suffer from great biases in simulations of cloud radiative effects.This study aims to provide an observational basis of cloud microphysical properties for the modeling community,against which the model simulations can be validated.The analyzed cloud microphysical properties include mass,number concentration,and effective radius for both liquid and ice phases.For liquid clouds,both cloud mass and number concentration gradually decrease with height,leading to the effective radius being nearly uniformly spread in the range of 8-14μm.For ice clouds,the cloud mass and effective radius decrease with height,whereas the number concentration is nearly uniform in the vertical.The cloud microphysical properties show remarkable differences among different cloud types.Cloud mass and number concentration are larger in cumuliform clouds,whereas smaller in cirrus clouds.By comparing cloud properties among the Tibetan Plateau,East China,and the western North Pacific,results show the values are overall smaller for liquid clouds but larger for ice clouds over the Tibetan Plateau.

Pressure level of maximum radiative heating enhancement in response to increasing CO_(2) over the global monsoon area

Based on the 1%CO_(2) experiment of CMIP6,in response to increasing CO_(2),the summer-mean radiative heating(RH)over the global monsoon area(MA)generally features an increasing response in the mid-troposphere and a decreasing response in the lower and upper troposphere.The pressure level of the maximum RH increase over the Asian MA is the highest and largest in range(500–775 hPa);the maximum increases over the North African,South American,and Australian MA are at 550–600 hPa;throughout the North American MA,the maximum heating increase is at 600 hPa;and the levels of the maximum over South Africa are 600 and 775 hPa.For most of the global MA,the maximum enhancement of RH is at 500,550,and 600 hPa.It is mainly led by the increase in cloud water at and above the maximum level and the decrease in cloud water below,which leads to similar changes in total cloud mass.Because of the longwave heating(cooling)effect at the cloud base(top),the RH enhancements peak at those levels.For the northeast part of the Asian MA and southeast part of the South African MA,RH enhancement peaks at 700 and 775 hPa,mainly attributable to the cloud water reduction below.The reduction leads to similar changes in total cloud.Due to the longwave cooling effect at the cloud top,the reduction contributes to the RH enhancement at the corresponding maximum levels.

2018～2019年秋冬季厄尔尼诺和印度洋偶极子的预测

热带太平洋厄尔尼诺/南方涛动(ENSO)和热带印度洋的偶极子(IOD)是全球季节到年际尺度的重要自然变率.本研究利用中国科学院大气物理研究所FGOALS-f2季节内-季节预测系统开展2018/2019年秋冬季气候异常预测.基于该预测系统从2017年7月起进行的预测显示:(1) 2018年秋冬季节IOD维持正位相,正IOD事件在10月达到最强,比常年偏高0.4℃;(2) 2018年秋冬季节赤道中东太平洋将逐渐发展成一次中等强度的厄尔尼诺事件,Ni?o3.4指数冬季达到1.3;(3) 2018年中国冬季风强度可能偏弱,冬季大部分地区气温较常年偏高,冷空气活动较弱,据此推测北方地区气象条件不利于大气污染物扩散,而南方受印度洋低层气流偏强的影响,出现暖湿气候特征.

Development of a toy column model and its application in testing cumulus convection parameterizations

A single-column model is constructed based on parameterizations inherited from the Finite-volume/Spectral Atmospheric Model F/SAMIL and tested in simulations of tropical convective systems. Two representative convection schemes are compared in terms of their performances on precipitation types, individual physical tendencies, and temperature and moisture fields. The main difference between the two selected schemes is in their representation of entraining/detraining process. The Tiedtke scheme assumes bulk entrainment, while the Zhang–Mc Farlane scheme parameterizes entrainment/detrainment rates under the spectrum concept. Large-scale forcing and verification data are taken from the GATE phase III field campaign, during which abundant convective events were observed. Given the same triggering function and closure assumption, results show that entrainment/detrainment representation remains the dominant factor on the simulation of cumulus mass flux and of temperature and moisture fields. By analyzing sources and sinks of heat and moisture, this study reveals how parameterization components compensate for each other and make model results insensitive to parameterization changes in certain fields, thus suggesting the need to treat parameterizations as systems rather than individual components.