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.

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, hnportantly, 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.

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.

Ensemble Data Assimilation in a Simple Coupled Climate Model: The Role of Ocean-Atmosphere Interaction

A conceptual coupled ocean-atmosphere model was used to study coupled ensemble data assimilation schemes with a focus on the role of ocean-atmosphere interaction in the assimilation. The optimal scheme was the fully coupled data assimilation scheme that employs the coupled covariance matrix and assimilates observations in both the atmosphere and ocean. The assimilation of synoptic atmospheric variability that captures the temporal fluctuation of the weather noise was found to be critical for the estimation of not only the atmospheric, but also oceanic states. The synoptic atmosphere observation was especially important in the mid-latitude system, where oceanic variability is driven by weather noise. The assimilation of synoptic atmospheric variability in the coupled model improved the atmospheric variability in the analysis and the subsequent forecasts, reducing error in the surface forcing and, in turn, in the ocean state. Atmospheric observation was able to further improve the oceanic state estimation directly through the coupled covariance between the atmosphere and ocean states. Relative to the mid-latitude system, the tropical system was influenced more by ocean atmosphere interaction and, thus, the assimilation of oceanic observation becomes more important for the estimation of the ocean and atmosphere.

Modeling and analyzing supply-demand relationships of water resources in Xinjiang from a perspective of ecosystem services

Water shortage is one bottleneck that limits economic and social developments in arid and semi-arid areas.As the impacts of climate change and human disturbance intensify across time,uncertainties in both water resource supplies and demands increase in arid and semi-arid areas.Taking a typical arid region in China,Xinjiang Uygur Autonomous Region,as an example,water yield depth(WYD)and water utilization depth(WUD)from 2002 to 2018 were simulated using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model and socioeconomic data.The supply-demand relationships of water resources were analyzed using the ecosystem service indices including water supply-demand difference(WSDD)and water supply rate(WSR).The internal factors in changes of WYD and WUD were explored using the controlled variable method.The results show that the supplydemand relationships of water resources in Xinjiang were in a slight deficit,but the deficit was alleviated due to increased precipitation and decreased WUD of irrigation.WYD generally experienced an increasing trend,and significant increase mainly occurred in the oasis areas surrounding both the Junggar Basin and Tarim Basin.WUD had a downward trend with a decline of 20.70%,especially in oasis areas.Water resources in most areas of Xinjiang were fully utilized and the utilization efficiency of water resources increased.The water yield module in the InVEST model was calibrated and validated using gauging station data in Xinjiang,and the result shows that the use of satellite-based water storage data helped to decrease the bias error of the InVEST model by 0.69×10^(8)m^(3).This study analyzed water resource supplies and demands from a perspective of ecosystem services,which expanded the scope of the application of ecosystem services and increased the research perspective of water resource evaluation.The results could provide guidance for water resource management such as spatial allocation and structural optimization of water resources in arid and semi-arid areas.

Implementation of a One-Dimensional Enthalpy Sea-Ice Model in a Simple Pycnocline Prediction Model for Sea-Ice Data Assimilation Studies

To further explore enthalpy-based sea-ice assimilation, a one-dimensional （1D） enthalpy sea-ice model is implemented into a simple pycnocline prediction model. The 1D enthalpy sea-ice model includes the physical processes such as brine expulsion, flushing, and salt diffusion. After being coupled with the atmosphere and ocean components, the enthalpy sea-ice model can be integrated stably and serves as an important modulator of model variability. Results from a twin experiment show that the sea-ice data assimilation in the enthalpy space can produce smaller root-mean-square errors of model variables than the traditional scheme that assimilates the observations of ice concentration, especially for slow-varying states. This study provides some insights into the improvement of sea-ice data assimilation in a coupled general circulation model.

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.

Impacts of Systematic Precipitation Bias on Simulations of Water and Energy Balances in Northwest America

At high latitudes and in mountainous areas, evaluation and validation of water and energy flux simu-lations are greatly affected by systematic precipitation errors. These errors mainly come from topographic effects and undercatch of precipitation gauges. In this study, the Land Dynamics （LAD） land surface model is used to investigate impacts of systematic precipitation bias from topography and wind-blowing on water and energy flux simulation in Northwest America. The results show that topographic and wind adjustment reduced bias of streamflow simulations when compared with observed streamflow at 14 basins. These systematic biases resulted in a -50%-100% bias for runoff simulations, a -20%-20% bias for evapotranspiration, and a -40%-40% bias for sensible heat flux, subject to different locations and adjustments, when compared with the control run. Uncertain gauge adjustment leads to a 25% uncertainty for precipitation, a 20% 100% uncertainty for runoff simulation, a less-than-10% uncertainty for evapotranspiration, and a less-than-20% uncertainty for sensible heat flux.

Study of Initial Vorticity Forcing for Block Onset by a 4-Dimensional Variational Approach

With the aid of a global barotropic model, the role of the interaction of the synoptic-scale disturbance and the planetary flow in block onset is examined by a 4-dimensional variational approach. A cost function is defined to measure the squared errors of the forecasted stream functions during block onset period (day 4 and day 5 in this study) over a selected blocking domain. The sensitivity of block onset with respect to the initial synoptic-scale disturbance is studied by examining the gradient of the defined cost function with respect to the initial (during the first 24 hours) vorticity forcing, which is evaluated by the adjoint integration. Furthermore, the calculated cost function and gradient are connected with the limited-memory quasi-Newton optimization algorithm for solving the optimal initial vorticity forcing for block onset. For two studied cases of block onset (northern Atlantic and northern Pacific) introducing the optimal initial vorticity forcing, the nonlinear barotropic advection process mostly reconstructs these blocking onset processes. The results show that the formation of blocking can be correctly described by a barotropic nonlinear advection process, in which the wave- (synoptic-scale) flow (planetary-scale) interaction plays a very important role. On an appropriate planetary-scale flow, a certain synoptic-scale disturbance can cause the blocking onset by the interaction between the synoptic scale perturbations and the planetary scale basic flows. The extended forecasts show that the introduction of the optimal initial vorticity forcing can predict the blocking process up to the 7th or 8th day in this simple model case. The experimental results in this study show that the 4-dimensional variational approach has a good potential to be applied to study the dynamics of the medium-range weather processes. This simple model case study is only an initial trial. Applying the framework in this study to a complex model will further our understanding of the mechanism of the atmospheric/oceanic processes and improve their prediction.

A New Semi-Lagrangian Finite Volume Advection Scheme Combines the Best of Both Worlds

Advection,or transport by wind,is fundamental to numerical weather and climate modeling.It is especially important to solve the equations governing the distribution of heat,moisture,pollutants,and so on.Two classes of advection schemes have become dominant in recent years.Semi-Lagrangian (SL;Diamantakis,2013) methods form the advection equation in its"Lagrangian"or flow-following form and use the winds (either prescribed or predicted) to trace trajectories backwards from a grid point to their original location on the previous time step.

Mechanisms for the hiatus in global warming

The observed global mean temperature is the highest on record for the past decade but has plateaued to form an apparent"hiatus"in global temperature rise,with an almost zero short-term trend. Several speakers presented results on the hiatus and suggested possible mechanisms.

海洋-大气耦合模型对大气二氧化碳增加的响应

本文研究一个气候模型对大气CO_2每年增加1%的响应。该模型是耦合海洋-大气-陆面系统的大气环流模型,具有全球计算域,进行了地理上的修匀,并包含了日射的季节变化。模拟得到的海面增温在北大西洋北部和南半球的绕极海区非常缓慢,在这些海区水体的垂直混合可以达到很深的深度,深层水的交换速度也较快。为将这一工作深入下去,我们研究了过去几百年间该耦合模型对大气CO_2浓度增至2倍和4倍时的瞬时响应。在整个500年实验期间,当CO_2增至2倍时,全球平均地面气温增加3.5C,当CO_2增至4倍时升高7C。在后一项实验中,所研究的海洋的热力结构和动力特征都经历了剧烈的变化,例如,模型所选取的海洋大多数都发生了温盐环流的终止,斜温层也显著变深,在北大西洋,这些变化尤其明显。这些变化阻碍了深层海水的交换,如果这些变化实际发生,将对海洋-大气耦合系统的碳循环和生物地球化学过程产生深远影响。

海洋中继器促进了青藏高原热源的全球气候效应

以往研究多关注青藏高原对亚洲季风的影响,然而青藏高原对全球气候的影响范围及强度尚不明确.本研究揭示青藏高原热源对全球气候具有广泛的影响,且多模式的结果高度一致.例如,1℃的青藏高原增暖可以引起0.73℃的北美洲增暖.然而,没有海-气相互作用时,青藏高原热源的远程影响随距离快速衰减.海-气相互作用可以显著放大青藏高原热源的远程影响,其方式与无线信号中继器类似.因此,太平洋和大西洋作为高效的海洋中继器,增强了青藏高原热源对全球气候的影响.海洋中继器对青藏高原气候效应的促进作用是通过增强全球尺度的热量和水汽输送及其对应的西风带环流、定常波波列、垂直-纬向翻转环流的大气环流途径,以及太平洋和大西洋区域的局地海-气正反馈过程.

南大洋增暖及其气候影响

过去几十年南大洋在南极平流层臭氧消耗和大气二氧化碳浓度增加的共同作用下大幅增暖,显著影响着南极冰架和冰盖的融化、海平面上升、南北半球的降水分配以及热带海洋和大气环流等,引发了深远的气候效应.全球变暖背景下南大洋西风表现为极向加强,同时进入南大洋的热辐射和淡水通量持续增加,由此上翻的海水可吸收更多的热量和碳,经由更强的平均流向北输送,更多地在45°S附近海域下沉并存储.当前对南大洋增暖背后诸多复杂的物理过程仍缺乏足够的理解,比如来自冰架、冰盖及海洋涡旋的作用、热带-极地相互作用、南大洋本身对全球变暖的响应等,尤其是有限的观测数据和较低分辨率的模式无法准确呈现快速变化的物理现象和机理.因此,南大洋的未来增暖存在很大的不确定性且可能长期持续,但近期的进展为深入认知南大洋增暖及其气候影响奠定了坚实的基础.

An update on the influence of natural climate variability and anthropogenic climate change on tropical cyclones

A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones(IWTC-9)in 2018,improving our understanding of the effect of climate change on tropical cyclones(TCs)and associated hazards and risks.These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change.New modeling and observational studies suggested the potential influence of anthropogenic climate forcings,including greenhouse gases and aerosols,on global and regional TC activity at the decadal and century time scales.However,there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic,and the limitations of observed TC records.The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models.A new paradigm,TC seeds,has been proposed,and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency.New studies also highlighted the importance of large-scale environmental fields on TC activity,such as snow cover and air-sea interactions.Future projections on TC translation speed and medicanes are new additional focus topics in our report.Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers.

Recent advances in seasonal and multi-annual tropical cyclone forecasting

Seasonal tropical cyclone(TC)forecasting has evolved substantially since its commencement in the early 1980s.However,present operational seasonal TC forecasting services still do not meet the requirements of society and stakeholders:current operational products are mainly basin-scale information,while more detailed sub-basin scale information such as potential risks of TC landfall is anticipated for decision making.To fill this gap and make the TC science and services move forward,this paper reviews recent research and development in seasonal tropical cyclone(TC)forecasting.In particular,this paper features new research topics on seasonal TC predictability in neutral conditions of El Ni˜no–Southern Oscillation(ENSO),emerging forecasting techniques of seasonal TC activity including Machine Learning/Artificial Intelligence,and multi-annual TC predictions.We also review the skill of forecast systems at predicting landfalling statistics for certain regions of the North Atlantic,Western North Pacific and South Indian oceans and discuss the gap that remains between current products and potential user's expectations.New knowledge and advanced forecasting techniques are expected to further enhance the capability of seasonal TC forecasting and lead to more actionable and fit-for-purpose products.

SEASONAL TROPICAL CYCLONE FORECASTING

This paper summarizes the forecast methods,outputs and skill offered by twelve agencies for seasonal tropical cyclone(TC)activity around the world.These agencies use a variety of techniques ranging from statistical models to dynamical models to predict basinwide activity and regional activity.In addition,several dynamical and hybrid statistical/dynamical models now predict TC track density as well as landfall likelihood.Realtime Atlantic seasonal hurricane forecasts have shown low skill in April modest skill in June and good skill in August at predicting basinwide TC activity when evaluated over 2003-2018.Real-time western North Pacific seasonal TC forecasts have shown good skill by July for basinwide intense typhoon numbers and the ACE index when evaluated for 2003-2018.Both hindcasts and real-time forecasts have shown skill for other TC basins.A summary of recent research into forecasting TC activity beyond seasonal(e.g.,multi-year)timescales is included.Recommendations for future areas of research are also discussed.

Third assessment on impacts of climate change on tropical cyclones in the Typhoon Committee Region——Part Ⅰ:Observed changes, detection and attribution

Published findings on climate change impacts on tropical cyclones(TCs)in the ESCAP/WMO Typhoon Committee Region are assessed.We focus on observed TC changes in the western North Pacific(WNP)basin,including frequency,intensity,precipitation,track pattern,and storm surge.Results from an updated survey of impacts of past TC activity on various Members of the Typhoon Committee are also reported.Existing TC datasets continue to show substantial interdecadal variations in basin-wide TC frequency and intensity in the WNP.There has been encouraging progress in improving the consensus between different datasets concerning intensity trends.A statistically significant northwestward shift in WNP TC tracks since the 1980s has been documented.There is low-to-medium confidence in a detectable poleward shift since the 1940s in the average latitude where TCs reach their peak intensity in the WNP.A worsening of storm inundation levels is believed to be occurring due to sea level rise-due in part to anthropogenic influence-assuming all other factors equal.However,we are not aware that any TC climate change signal has been convincingly detected in WNP sea level extremes data.We also consider detection and attribution of observed changes based on an alternative Type II error avoidance perspective.

IMPACTS OF CLIMATE CHANGE ON TROPICAL CYCLONES IN THE WESTERN NORTH PACIFIC BASIN. PART Ⅱ: LATE TWENTY-FIRST CENTURY PROJECTIONS

This paper reviews the latest studies on the relationship between projected late 21 st century climate changes and tropical cyclone(TC) activity in the western North Pacific(WNP) basin, which is the region of the United Nations Economic and Social Commission for Asia and the Pacific(ESCAP)/World Meteorological Organization(WMO) Typhoon Committee members. Existing studies of projected changes of TC activity in this basin, such as frequency, intensity, precipitation, genesis location and track pattern are summarized, based on an assumed A1 B future climate change scenario. A review of available studies on projected future changes in WNP landfalling TC activity is also included.While it remains uncertain whether there has been any detectable human influence on tropical cyclone frequency, intensity, precipitation, track, or related aggregated storm activity metrics in the basin, modeling studies suggest changes in future tropical cyclone activity for the WNP basin. More models project decreases than increases in tropical storm frequency(range-70% to +60%);most studies project an increase in the TC intensity(range-3% to +18%);and all six available studies that include the WNP basin project increases in TC precipitation rates(range +5 to +30%).

IMPACT OF DIABATIC PROCESSES IN AGCM ON 4-DIMENSIONAL VARIATIONAL DATA ASSIMILATION

The impact of diabatic processes on 4-dimensional variational data assimilation (4D-Var) was studied using the 1995 version of NCEP's global spectral model with and without full physics.The adjoint was coded manually.A cost function measuring spectral errors of 6-hour forecasts to 'observation' (the NCEP reanalysis data) was minimized using the L-BFGS (the limited memory quasi-Newton algorithm developed by Broyden,Fletcher,Goldfard and Shanno) for optimizing parameters and initial conditions.Minimization of the cost function constrained by an adiabatic version of the NCEP global model converged to a minimum with a significant amount of decrease in the value of the cost function.Minimization of the cost function using the diabatic model, however,failed after a few iterations due to discontinuities introduced by physical parameterizations.Examination of the convergence of the cost function in different spectral domains reveals that the large-scale flow is adjusted during the first 10 iterations,in which discontinuous diabatic parameterizations play very little role.The adjustment produced by the minimization gradually moves to relatively smaller scales between 10-20th iterations.During this transition period,discontinuities in the cost function produced by 'on-off' switches in the physical parameterizations caused the cost function to stay in a shallow local minimum instead of continuously decreasing toward a deeper minimum. Next,a mixed 4D-Var scheme is tested in which large-scale flows are first adiabatically adjusted to a sufficient level,followed by a diabatic adjustment introduced after 10 to 20 iterations. The mixed 4D-Var produced a closer fit of analysis to observations,with 38% and 41% more decrease in the values of the cost function and the norm of gradient,respectively,than the standard diabatic 4D-Var,while the CPU time is reduced by 21%.The resulting optimal initial conditions improve the short-range forecast skills of 48-hour statistics.The detrimental effect of parameterization discontinuities on minimization was also reduced.