Forecasts of MJO Events during DYNAMO with a Coupled Atmosphere–Ocean Model:Sensitivity to Cumulus Parameterization Scheme

An operational weather forecast model, coupled to an oceanic model, was used to predict the initiation and propagation of two major Madden–Julian Oscillation(MJO) events during the dynamics of the MJO(DYNAMO)campaign period. Two convective parameterization schemes were used to understand the sensitivity of the forecast to the model cumulus scheme. The first is the Tiedtke(TDK) scheme, and the second is the Simplified Arakawa–Schubert(SAS) scheme. The TDK scheme was able to forecast the MJO-1 and MJO-2 initiation at 15-and45-day lead, respectively, while the SAS scheme failed to predict the convection onset in the western equatorial Indian Ocean(WEIO). The diagnosis of the forecast results indicates that the successful prediction with the TDK scheme is attributed to the model capability to reproduce the observed intraseasonal outgoing longwave radiation–sea surface temperature(OLR–SST) relationship. On one hand, the SST anomaly(SSTA) over the WEIO was induced by surface heat flux anomalies associated with the preceding suppressed-phase MJO. The change of SSTA, in turn,caused boundary layer convergence and ascending motion, which further induced a positive column-integrated moist static energy(MSE) tendency, setting up a convectively unstable stratification for MJO initiation. The forecast with the SAS scheme failed to reproduce the observed OLR–SST–MSE relation. The propagation characteristics differed markedly between the two forecasts. Pronounced eastward phase propagation in the TDK scheme is attributed to a positive zonal gradient of the MSE tendency relative to the MJO center, similar to the observed, whereas a reversed gradient appeared in the forecast with the SAS scheme with dominant westward propagation. The difference is primarily attributed to anomalous vertical and horizontal MSE advection.     

Impacts of SST and SST Anomalies on Low-Frequency Oscillation in the Tropical Atmosphere

Considering the multiscale character of LFO effects of SST on LFO in the tropical atmosphere （low-frequency oscillation） in the tropical atmosphere, the are discussed by using an absolute ageostrophic, baroclinic model. Here, SST effects include sea surface heating and forcing of SST anomalies （SSTAs）. Studies of the influences of sea surface heating on LFO frequency and stability show that sea surface heating can slow the speed of waves and lower their frequency when SST is comparatively low; while higher SST leads to unstable waves and less periods of LFO. Since the impact of a SSTA on ultra-long waves is more evident than that on kilometer-scale waves, long-wave approximation is used when we continue to study the effect of SSTAs. Results indicate that SSTAs can lead to a longer period of LFO, and make waves unstable. In other words, positive （negative） SSTAs can make waves decay （grow）.     

Evaluation of Snow Depth and Snow Cover Fraction Simulated by Two Versions of the Flexible Global Ocean–Atmosphere–Land System Model简

Based on historical runs,one of the core experiments of the fifth phase of the Coupled Model Intercomparison Project （CMIP5）,the snow depth （SD） and snow cover fraction （SCF） simulated by two versions of the Flexible Global OceanAtmosphere-Land System （FGOALS） model,Grid-point Version 2 （g2） and Spectral Version 2 （s2）,were validated against observational data.The results revealed that the spatial pattern of SD and SCF over the Northern Hemisphere （NH） are simulated well by both models,except over the Tibetan Plateau,with the average spatial correlation coefficient over all months being around 0.7 and 0.8 for SD and SCF,respectively.Although the onset of snow accumulation is captured wellby the two models in terms of the annual cycle of SD and SCF,g2 overestimates SD/SCF over most mid-and high-latitude areas of the NH.Analysis showed that g2 produces lower temperatures than s2 because it considers the indirect effects of aerosols in its atmospheric component,which is the primary driver for the SD/SCF difference between the two models.In addition,both models simulate the significant decreasing trend of SCF well over （30°-70°N） in winter during the period 1971-94.However,as g2 has a weak response to an increase in the concentration of CO2 and lower climate sensitivity,it presents weaker interannual variation compared to s2.     

Impacts of SST and SST Anomalies on Low-Prequency Oscillation in the Tropical Atmosphere

Considering the multiscale character of LFO (low-frequency oscillation) in the tropical atmosphere, the effects of SST on LFO in the tropical atmosphere are discussed by using an absolute ageostrophic, baroclinic model. Here, SST effects include sea surface heating and forcing of SST anomalies (SSTAs). Studies of the influences of sea surface heating on LFO frequency and stability show that sea surface heating can slow the speed of waves and lower their frequency when SST is comparatively low; while higher SST leads to unstable waves and less periods of LFO. Since the impact of a SSTA on ultra-long waves is more evident than that on kilometer-scale waves, long-wave approximation is used when we continue to study the effect of SSTAs. Results indicate that SSTAs can lead to a longer period of LFO, and make waves unstable. In other words, positive (negative) SSTAs can make waves decay (grow).     

A Model Evaluation of Biological Effects on Seasonal Variation of Air–Sea CO2 Flux in the Yellow and East China Seas

Based on a coupled physical-biogeochemical model of the Yellow and East China Seas (YECS), the influence of biological activity on the seasonal variation of the air–sea CO₂ flux is evaluated. The solution of a sensitivity experiment that excludes biological activity is compared with that of a reference experiment that includes the full processes. The comparison reveals that biological activity results in a much stronger seasonal variation of surface dissolved inorganic carbon (DIC) and, hence, the ratio of total alkalinity to DIC in the northern parts of the YECS. The increased ratio resulting from biological DIC consumption contributes to the undersaturated partial pressure of CO₂ at the sea surface with respect to the atmosphere, causing the central Yellow Sea in summer and autumn to shift from being a CO₂ source to a sink; this same shift also occurs over the Changjiang Bank in summer. In the southern YECS, the biological effect is relatively weak. The comparison further reveals that low water temperature, instead of biological activity, is the dominant factor causing the YECS to become a carbon sink in spring. The biological effect on the variation of DIC (both at the surface and in the water column) differs greatly among the three representative regions of the YECS because of differences in primary production and hydrodynamic conditions. Particle-tracking simulations quantify the regional difference in horizontal advection. In the northern region, weaker horizontal advection causes the longer residence time of low DIC water induced by biological consumption. Over the entire YECS, biological activity contributes to about one-third of the total annual absorption of atmospheric CO₂.     

Evaluation of Atmosphere–Land Interactions in an LES from the Perspective of Heterogeneity Propagation

Atmosphere–land interactions simulated by an LES model are evaluated from the perspective of heterogeneity propagation by comparison with airborne measurements. It is found that the footprints of surface heterogeneity, though as 2D patterns can be dissipated quickly due to turbulent mixing, as 1D projections can persist and propagate to the top of the atmospheric boundary layer. Direct comparison and length scale analysis show that the simulated heterogeneity patterns are comparable to the observation. The results highlight the model's capability in simulating the complex effects of surface heterogeneity on atmosphere–land interactions.     

The SST–Wind Coupling Pattern in the East China Sea Based on a Regional Coupled Ocean–Atmosphere Model

To study the interaction between sea surface temperature (SST) and surface wind in the East China Sea (ECS), the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modelling system is used to downscale a global atmospheric reanalysis product over the study area in 2013. A singular value decomposition (SVD) method is applied to SST and surface wind speed to study their coupling relationship in the ECS. The heterogeneous correlation map indicates that the surface wind has a negative correlation with the SST, especially in the Kuroshio Current. From lead-lag correlations between the first principal component of SST and surface wind SVD (filtered using a Lanczos high-pass filter with a 90-day cut-off), a correlation of about 0.1 is found at lag ?6, and a negative correlation of about ?0.3 is also found around lag 1. The results indicate a negative feedback between SST and wind fluctuations at short time-scales. Air–sea heat ?uxes contribute little to the SST variability in the ECS section of the Kuroshio and the analysis of the mixed-layer heat budget shows that the contribution of horizontal advection is dominant in determining the intraseasonal SST signals.     

Direct Climatic Effect of Dust Aerosol in the NCAR Community Atmosphere Model Version 3 （CAM3）

Direct climate responses to dust shortwave and longwave radiative forcing (RF) are studied using the NCAR Community Atmosphere Model Version 3 (CAM3). The simulated RF at the top of the atmosphere (TOA) is-0.45 W m-2 in the solar spectrum and +0.09 W m-2 in the thermal spectrum on a global average. The magnitude of surface RF is larger than the TOA forcing, with global mean shortwave forcing of-1.76 W m-2 and longwave forcing of +0.31 W m-2 . As a result, dust aerosol causes the absorption of 1.1 W m-2 in t...     

A Numerical Study of Sensitivity of the Physical Dissipative Technique to Precipitation Parameterization in a Mesoscale Model

1. IntroductionRecently, the improvement of accuracy in the out-puts of a numerical mesoscale model by the physi-cal dissipative technique is reached (Liu et al., 2002;Liu and Liu, 2003). The effect of improvement ofthis technique differs not only from model to model,but from scheme to scheme of parameterization em-ployed in the same model. The rapid developmentof the computer technology makes possible the com-plicated numerical experiments by a model with highresolution and multiple domains …     

Evaluation of a climate simulation in Europe based on the WRF–NOAH model system: precipitation in Germany

The Weather Research and Forecast (WRF) model with its land surface model NOAH was set up and applied as regional climate model over Europe. It was forced with the latest ERA-interim reanalysis data from 1989 to 2008 and operated with 0.33° and 0.11° resolution. This study focuses on the verification of monthly and seasonal mean precipitation over Germany, where a high quality precipitation dataset of the German Weather Service is available. In particular, the precipitation is studied in the orographic terrain of southwestern Germany and the dry lowlands of northeastern Germany. In both regions precipitation data is very important for end users such as hydrologists and farmers. Both WRF simulations show a systematic positive precipitation bias not apparent in ERA-interim and an overestimation of wet day frequency. The downscaling experiment improved the annual cycle of the precipitation intensity, which is underestimated by ERA-interim. Normalized Taylor diagrams, i.e., those discarding the systematic bias by normalizing the quantities, demonstrate that downscaling with WRF provides a better spatial distribution than the ERA interim precipitation analyses in southwestern Germany and most of the whole of Germany but degrades the results for northeastern Germany. At the applied model resolution of 0.11°, WRF shows typical systematic errors of RCMs in orographic terrain such as the windward–lee effect. A convection permitting case study set up for summer 2007 improved the precipitation simulations with respect to the location of precipitation maxima in the mountainous regions and the spatial correlation of precipitation. This result indicates the high value of regional climate simulations on the convection-permitting scale.     

Improved Parameterization of Snow Albedo in WRF + Noah: Methodology Based on a Severe Snow Event on the Tibetan Plateau

Snowfall and the subsequent evolution of the snowpack have a large effect on the surface energy balance and water cycle of the Tibetan Plateau (TP). The effects of snow cover can be represented by the WRF coupled with a land surface scheme. The widely used Noah scheme is computationally efficient, but its poor representation of albedo needs considerable improvement. In this study, an improved albedo scheme is developed using a satellite-retrieved albedo that takes snow depth and age into account. Numerical experiments were then conducted to simulate a severe snow event in March 2017. The performance of the coupled WRF/Noah model, which implemented the improved albedo scheme, is compared against the model’s performance using the default Noah albedo scheme and against the coupled WRF/CLM that applied CLM albedo scheme. When the improved albedo scheme is implemented, the albedo overestimation in the southeastern TP is reduced, reducing the RMSE of the air temperature by 0.7°C. The improved albedo scheme also attains the highest correlation between the satellite-derived and the model-estimated albedo, which provides for a realistic representation of both the snow water equivalent (SWE) spatial distribution in the heavy snowbelt (SWE > 6 mm) and the maximum SWE in the eastern TP. The underestimated albedo in the coupled WRF/CLM leads to underestimating the regional maximum SWE and a consequent failure to estimate SWE in the heavy snowbelt accurately. Our study demonstrates the feasibility of improving the Noah albedo scheme and provides a theoretical reference for researchers aiming to improve albedo schemes further.     

Role of Black Carbon-Induced Changes in Snow Albedo in Predictions of Temperature and Precipitation during a Snowstorm

In this study the authors apply the chemistry version of the Weather Research and Forecasting model （WRF-Chem） to examine the impacts of black carbon （BC）-induced changes in snow albedo on simulated temperature and precipitation during the severe snowstorm that occurred in southern China during 0800 26 January to 0800 29 January 2008 （Note that all times are local time except when otherwise stated）. Black carbon aerosol was simulated online within the WRF-Chem. The model resuits showed that surface-albedo, averaged over 27-28 January, can be reduced by up to 10% by the deposition of BC. As a result, relative to a simulation that does not consider deposition of BC on snow/ice, the authors predicted surface air temperatures during 27-28 January can differ by -1.95 to 2.70 K, and the authors predicted accumulated precipitation over 27-28 January can differ by -2.91 to 3.10 mm over Areas A and B with large BC deposition. Different signs of changes are determined by the feedback of clouds and by the availability of water vapor in the atmosphere.     

有关雪盖模型内部及界面过程的参数化方案的敏感试验

In order to develop a seasonal snow model of land surface process as accurately as possible for climatic study, it is necessary to fully understand the effects of important snow internal processes and interaction with air and to get an insight into influence of several relevant parameterization schemes with parameters＇ uncertainty to some degree. Using the snow model (SAST) developed by first author and other one and some useful field observation data, this paper has conducted a series of sensitivity studies on the parameterization schemes. They are relative to compaction process, snow thermal conduction, methodology of layering snow pack and to key parameters such as snow albedo, water holding capacity. Then, based on the results from the sensitivity studies, some useful conclusions for snow cover model improvement are ob tained from the analysis of the results.     

用于气候研究的雪盖模型参数化方案敏感性研究

为了得到一个适用于气候研究简化的季节性雪盖模式最佳方案,必须对雪盖内部的重要物理过程、其与上大气相互作用、相应模型的参数化方案和有关的参数选取以及模型的分层结构进行深入研究.利用作者的雪盖模型(SAST),对其中的一些关键性过程的有关参数化方案(如压实、相变、融化雪水流动及分层方案考虑等)及关键的参数(如雪面反照率、有效热传导系数及持水能力等)进行了分析和敏感性试验,得到若干有意义的结论,为雪盖模式改进提供有用的结论.     

Significant Variations of Surface Albedo during a Snowy Period at Xianghe Observatory, China

Surface albedo over typical types of surfaces in the North China Plain was observed using a Multi-field Albedo Observation System before and after several snowfalls from 13 to 27 February 2005.Dramatic variations of the surface albedos of bare land,a frozen pond,and withered grassland during that period were analyzed.Under cloudy sky,the mean surface albedo of bare land was about 0.23,but it immediately rose to 0.85 when the surface was covered by fresh snow.The albedo decreased gradually to normal levels a...     

欧亚大陆积雪两种物理效应对2010年春末夏初华南降水的影响

本文基于欧亚大陆积雪深度资料和中国台站降水资料的奇异值分析 (SVD) 结果, 使用大气环流模式 (CAM3.1) 分别进行三组集合试验来研究欧亚大陆积雪的反照率效应和水文效应对2010年5～6月华南降水的影响: 第一组试验综合考虑积雪的两种物理效应, 既有反照率效应又有水文效应; 第二组试验仅考虑积雪反照率效应, 忽略水文效应; 第三组试验只考虑积雪水文效应, 忽略反照率效应。试验结果表明, 积雪的两种物理效应都会对后期华南降水产生影响, 但是三组试验中积雪不同物理效应所导致的异常幅度和范围存在较大差异, 其中积雪水文效应比反照率效应引起的变化幅度大。当两种效应共同作用时产生的异常与统计分析结果最为接近, 变化幅度也最大, 但是并不等于单纯反照率效应和单纯水文效应作用之和。     

Assessing the Impacts of Eurasian Snow Conditions on Climate Predictability with a Global Climate Model

On the basis of two ensemble experiments conducted by a general atmospheric circulation model (Institute of Atmospheric Physics nine-level atmospheric general circulation model coupled with land surface model, hereinafter referred to as IAP9L_CoLM), the impacts of realistic Eurasian snow conditions on summer climate predictability were investigated. The predictive skill of sea level pressures (SLP) and middle and upper tropospheric geopotential heights at mid-high latitudes of Eurasia was enhanced when improved Eurasian snow conditions were introduced into the model. Furthermore, the model skill in reproducing the interannual variation and spatial distribution of the surface air temperature (SAT) anomalies over China was improved by applying realistic (prescribed) Eurasian snow conditions. The predictive skill of the summer precipitation in China was low; however, when realistic snow conditions were employed, the predictability increased, illustrating the effectiveness of the application of realistic Eurasian snow conditions. Overall, the results of the present study suggested that Eurasian snow conditions have a significant effect on dynamical seasonal prediction in China. When Eurasian snow conditions in the global climate model (GCM) can be more realistically represented, the predictability of summer climate over China increases.     

Comparison of Aerosol Single Scattering Albedo Derived from the Ozone Monitoring Instrument with Aerosol Robotic Network Observations

The single-scattering albedo (SSA), which quantifies radiative absorption capability, is an important optical property of aerosols. Ground-based methods have been extensively exploited to determine aerosol SSA but there were no satellite-based SSA measurements available until the advent of advanced remote sensing techniques, such as the Ozone Monitoring Instrument (OMI). Although the overall accuracy of OMI SSA is estimated to approach 0.1, its regional availability is unclear. Four-year SSA daily measurements from three Aerosol Robotic Network (AERONET) sites in China (Xianghe, Taihu, and Hong Kong) are chosen to determine the accuracy of OMI SSA in specific locations. The results show that on a global scale, the OMI SSA is systematically higher (with a mean relative bias of 3.5% and a RMS difference of ~0.06) and has poor correlation with the AERONET observations. In the Xianghe, Taihu, and Hong Kong sites, the correlation coefficients are 0.16, 0.47, and 0.44, respectively, suggesting that the distinct qualities of OMI SSA depend on geographic locations and/or dominant aerosol environments. The two types of SSA data yield the best agreement in Taihu and the worst in Hong Kong; the differing behavior is likely caused by varying levels of cloud contamination. The good consistency of the aerosol variation between the two SSA datasets on a seasonal scale is promising. These findings suggest that the current-version OMI SSA product can be applied to qualitatively characterize climatological variations of aerosol properties despite its limited accuracy as an instantaneous measurement.     

A Study on Parameterization of Surface Albedo over Grassland Surface in the Northern Tibetan Plateau

The relationship of surface albedo with the solar altitude angle and soil moisture is analyzed based on two-year (January 2002 to December 2003) observational data from the AWS (Automatic Weather Station) at MS3478 in the northern Tibetan Plateau during the experimental period of CEOP/CAMP-Tibet (Coordinated Enhanced Observing Period Asia-Australia Monsoon Project on the Tibetan Plateau). As a double-variable (solar altitude angle and soil moisture) function, surface albedo varies inconspicuously with any single factor. By using the method of approximately separating the double-variable function into two, one-factor functions (product and addition), the relationship of albedo with these two factors presents much better. The product and additional empirical formulae of albedo are then preliminarily fitted based on long-term experimental data. By comparison with observed values, it is found that the parameterization formulae fitted by using observational data are mostly reliable and their correlation coefficients are both over 0.6. The empirical formulae of albedo though, for the northern Tibetan Plateau, need to be tested by much more representative observational data with the help of numerical models and the retrieval of remote sensing data. It is practical until it is changed into effective parameterization formulae representing a grid scale in models.     

欧亚大陆积雪对我国春季气候可预报性的影响

利用大气环流模式IAP9L_CoLM,通过两组集合后报试验,考察了欧亚大陆积雪对我国春季气候可预报性的影响。一组试验为常规后报试验,积雪是由模式陆面过程预报得到的,另一组试验为积雪试验,模式积分过程中欧亚大陆雪水当量由微波遥感积雪资料替代,一天替换一次。通过分析两组试验后报结果的差异,来考察欧亚大陆积雪对我国春季（3~5月）气候可预报性的影响。分析表明:欧亚大陆积雪模拟水平的改善能提高春季欧亚大陆中高纬环流场（海平面气压场和中、高层位势高度场）的可预报性,模式对我国春季气温异常的年际变化和空间分布的可预报能力也有显著增强。对我国春季降水,虽然预报技巧较低,但引入较真实的欧亚积雪作用后,由于中高纬环流场预报技巧的改进导致降水的预测能力也有所改进。个例分析也表明,欧亚中高纬春季积雪异常模拟水平的改善导致了欧亚中高纬贝加尔湖及以南区域环流场可预报性的提高,最终使中国东部区域春季气候异常模拟技巧得以改善。以上结果也证实,欧亚大陆积雪是影响东亚区域春季气候的一个重要因子,要提高模式对中国春季气候的预报技巧,积雪模拟水平的改进是非常必要的。