Attributing analysis on the model bias in surface temperature in the climate system model FGOALS-s2 through a process-based decomposition method

This study uses the coupled atmosphere–surface climate feedback–response analysis method(CFRAM) to analyze the surface temperature biases in the Flexible Global Ocean–Atmosphere–Land System model, spectral version 2(FGOALS-s2)in January and July. The process-based decomposition of the surface temperature biases, defined as the difference between the model and ERA-Interim during 1979–2005, enables us to attribute the model surface temperature biases to individual radiative processes including ozone, water vapor, cloud, and surface albedo; and non-radiative processes including surface sensible and latent heat fluxes, and dynamic processes at the surface and in the atmosphere. The results show that significant model surface temperature biases are almost globally present, are generally larger over land than over oceans, and are relatively larger in summer than in winter. Relative to the model biases in non-radiative processes, which tend to dominate the surface temperature biases in most parts of the world, biases in radiative processes are much smaller, except in the sub-polar Antarctic region where the cold biases from the much overestimated surface albedo are compensated for by the warm biases from nonradiative processes. The larger biases in non-radiative processes mainly lie in surface heat fluxes and in surface dynamics,which are twice as large in the Southern Hemisphere as in the Northern Hemisphere and always tend to compensate for each other. In particular, the upward/downward heat fluxes are systematically underestimated/overestimated in most parts of the world, and are mainly compensated for by surface dynamic processes including the increased heat storage in deep oceans across the globe.     

Sensitivity of tropical climate to low-level clouds in the NCEP climate forecast system

In this work, we examine the sensitivity of tropical mean climate and seasonal cycle to low clouds and cloud liquid water path (CLWP) by prescribing them in the NCEP climate forecast system (CFS). It is found that the change of low cloud cover alone has a minor influence on the amount of net shortwave radiation reaching the surface and on the warm biases in the southeastern Atlantic. In experiments where CLWP is prescribed using observations, the mean climate in the tropics is improved significantly, implying that shortwave radiation absorption by CLWP is mainly responsible for reducing the excessive surface net shortwave radiation over the southern oceans in the CFS. Corresponding to large CLWP values in the southeastern oceans, the model generates large low cloud amounts. That results in a reduction of net shortwave radiation at the ocean surface and the warm biases in the sea surface temperature in the southeastern oceans. Meanwhile, the cold tongue and associated surface wind stress in the eastern oceans become stronger and more realistic. As a consequence of the overall improvement of the tropical mean climate, the seasonal cycle in the tropical Atlantic is also improved. Based on the results from these sensitivity experiments, we propose a model bias correction approach, in which CLWP is prescribed only in the southeastern Atlantic by using observed annual mean climatology of CLWP. It is shown that the warm biases in the southeastern Atlantic are largely eliminated, and the seasonal cycle in the tropical Atlantic Ocean is significantly improved. Prescribing CLWP in the CFS is then an effective interim technique to reduce model biases and to improve the simulation of seasonal cycle in the tropics.     

Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble

Warm sea-surface temperature (SST) biases in the southeastern tropical Atlantic (SETA), which is defined by a region from 5°E to the west coast of southern Africa and from 10°S to 30°S, are a common problem in many current and previous generation climate models. The Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble provides a useful framework to tackle the complex issues concerning causes of the SST bias. In this study, we tested a number of previously proposed mechanisms responsible for the SETA SST bias and found the following results. First, the multi-model ensemble mean shows a positive shortwave radiation bias of ~20 W m^?2, consistent with models’ deficiency in simulating low-level clouds. This shortwave radiation error, however, is overwhelmed by larger errors in the simulated surface turbulent heat and longwave radiation fluxes, resulting in excessive heat loss from the ocean. The result holds for atmosphere-only model simulations from the same multi-model ensemble, where the effect of SST biases on surface heat fluxes is removed, and is not sensitive to whether the analysis region is chosen to coincide with the maximum warm SST bias along the coast or with the main SETA stratocumulus deck away from the coast. This combined with the fact that there is no statistically significant relationship between simulated SST biases and surface heat flux biases among CMIP5 models suggests that the shortwave radiation bias caused by poorly simulated low-level clouds is not the leading cause of the warm SST bias. Second, the majority of CMIP5 models underestimate upwelling strength along the Benguela coast, which is linked to the unrealistically weak alongshore wind stress simulated by the models. However, a correlation analysis between the model simulated vertical velocities and SST biases does not reveal a statistically significant relationship between the two, suggesting that the deficient coastal upwelling in the models is not simply related to the warm SST bias via vertical heat advection. Third, SETA SST biases in CMIP5 models are correlated with surface and subsurface ocean temperature biases in the equatorial region, suggesting that the equatorial temperature bias remotely contributes to the SETA SST bias. Finally, we found that all CMIP5 models simulate a southward displaced Angola–Benguela front (ABF), which in many models is more than 10° south of its observed location. Furthermore, SETA SST biases are most significantly correlated with ABF latitude, which suggests that the inability of CMIP5 models to accurately simulate the ABF is a leading cause of the SETA SST bias. This is supported by simulations with the oceanic component of one of the CMIP5 models, which is forced with observationally derived surface fluxes. The results show that even with the observationally derived surface atmospheric forcing, the ocean model generates a significant warm SST bias near the ABF, underlining the important role of ocean dynamics in SETA SST bias problem. Further model simulations were conducted to address the impact of the SETA SST biases. The results indicate a significant remote influence of the SETA SST bias on global model simulations of tropical climate, underscoring the importance and urgency to reduce the SETA SST bias in global climate models.     

An assessment of oceanic variability for 1960–2010 from the GFDL ensemble coupled data assimilation

The Geophysical Fluid Dynamics Laboratory has developed an ensemble coupled data assimilation (ECDA) system based on the fully coupled climate model, CM2.1, in order to provide reanalyzed coupled initial conditions that are balanced with the climate prediction model. Here, we conduct a comprehensive assessment for the oceanic variability from the latest version of the ECDA analyzed for 51 years, 1960–2010. Meridional oceanic heat transport, net ocean surface heat flux, wind stress, sea surface height, top 300 m heat content, tropical temperature, salinity and currents are compared with various in situ observations and reanalyses by employing similar configurations with the assessment of the NCEP’s climate forecast system reanalysis (Xue et al. in Clim Dyn 37(11):2511–2539, 2011). Results show that the ECDA agrees well with observations in both climatology and variability for 51 years. For the simulation of the Tropical Atlantic Ocean and global salinity variability, the ECDA shows a good performance compared to existing reanalyses. The ECDA also shows no significant drift in the deep ocean temperature and salinity. While systematic model biases are mostly corrected with the coupled data assimilation, some biases (e.g., strong trade winds, weak westerly winds and warm SST in the southern oceans, subsurface temperature and salinity biases along the equatorial western Pacific boundary, overestimating the mixed layer depth around the subpolar Atlantic and high-latitude southern oceans in the winter seasons) are not completely eliminated. Mean biases such as strong South Equatorial Current, weak Equatorial Under Current, and weak Atlantic overturning transport are generated during the assimilation procedure, but their variabilities are well simulated. In terms of climate variability, the ECDA provides good simulations of the dominant oceanic signals associated with El Nino and Southern Oscillation, Indian Ocean Dipole, Pacific Decadal Oscillation, and Atlantic Meridional Overturning Circulation during the whole analyzed period, 1960–2010.     

A transitioning Arctic surface energy budget: the impacts of solar zenith angle, surface albedo and cloud radiative forcing

Snow surface and sea-ice energy budgets were measured near 87.5°N during the Arctic Summer Cloud Ocean Study (ASCOS), from August to early September 2008. Surface temperature indicated four distinct temperature regimes, characterized by varying cloud, thermodynamic and solar properties. An initial warm, melt-season regime was interrupted by a 3-day cold regime where temperatures dropped from near zero to ?7°C. Subsequently mean energy budget residuals remained small and near zero for 1 week until once again temperatures dropped rapidly and the energy budget residuals became negative. Energy budget transitions were dominated by the net radiative fluxes, largely controlled by the cloudiness. Variable heat, moisture and cloud distributions were associated with changing air-masses. Surface cloud radiative forcing, the net radiative effect of clouds on the surface relative to clear skies, is estimated. Shortwave cloud forcing ranged between ?50 W m^?2 and zero and varied significantly with surface albedo, solar zenith angle and cloud liquid water. Longwave cloud forcing was larger and generally ranged between 65 and 85 W m^?2, except when the cloud fraction was tenuous or contained little liquid water; thus the net effect of the clouds was to warm the surface. Both cold periods occurred under tenuous, or altogether absent, low-level clouds containing little liquid water, effectively reducing the cloud greenhouse effect. Freeze-up progression was enhanced by a combination of increasing solar zenith angles and surface albedo, while inhibited by a large, positive surface cloud forcing until a new air-mass with considerably less cloudiness advected over the experiment area.     

关于CAS FGOALS-f3-L模式中青藏高原地表温度偏差的归因分析

中国科学院全球海洋-大气-陆地耦合模式(FGOALS-f3-L)参加了耦合模式比较计划的第六阶段(CMIP6)试验,但是其对关键气候敏感地区青藏高原的地表温度的再现能力还不清楚.这项研究用再分析资料CFSR评估了FGOALS-f3-L模式对青藏高原地表温度的再现能力.结果表明,FGOALS-f3-L可以合理模拟整个高原上年平均地表温度的空间分布,但低估了整个高原上年平均地表温度.模拟的地表温度在整个高原上冬春季表现为冷偏差,夏秋季表现为暖偏差.基于地表能量平衡方程的进一步定量分析表明,地表反照率反馈(SAF)项极大地贡献了高原西部年平均,冬春季平均地表温度的冷偏差,而对高原东部是暖偏差贡献.与SAF项相比,地表感热项对地表温度偏差的贡献几乎相反,这大大抵消了SAF项引起的偏差.云辐射强迫项对高原东部的年平均和季节平均弱冷偏差有很大贡献.与高估的水蒸气含量有关的长波辐射项造成了夏秋季整个高原上大部分的暖偏差.该研究表明,提高FGOALS-f3-L中的陆面和云过程对降低高原上地表温度偏差至关重要.     

Simulation and Improvements of Oceanic Circulation and Sea Ice by the Coupled Climate System Model FGOALS-f3-L

This study documents simulated oceanic circulations and sea ice by the coupled climate system model FGOALS-f3-L developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, under historical forcing from phase 6 of the Coupled Model Intercomparison Project (CMIP6). FGOALS-f3-L reproduces the fundamental features of global oceanic circulations, such as sea surface temperature (SST), sea surface salinity (SSS), mixed layer depth (MLD), vertical temperature and salinity, and meridional overturning circulations. There are notable improvements compared with the previous version, FGOALS-s2, such as a reduction in warm SST biases near the western and eastern boundaries of oceans and salty SSS biases in the tropical western Atlantic and eastern boundaries, and a mitigation of deep MLD biases at high latitudes. However, several obvious biases remain. The most significant biases include cold SST biases in the northwestern Pacific (over 4°C), freshwater SSS biases and deep MLD biases in the subtropics, and temperature and salinity biases in deep ocean at high latitudes. The simulated sea ice shows a reasonable distribution but stronger seasonal cycle than observed. The spatial patterns of sea ice are more realistic in FGOALS-f3-L than its previous version because the latitude–longitude grid is replaced with a tripolar grid in the ocean and sea ice model. The most significant biases are the overestimated sea ice and underestimated SSS in the Labrador Sea and Barents Sea, which are related to the shallower MLD and weaker vertical mixing.     

An inter-comparison of regional climate models for Europe: model performance in present-day climate

The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation.     

A Note on the Relationship Between Temperature and Water Vapor over Oceans, Including Sea Surface Temperature Effects

An ideal and simple formulation is successfully derived that well represents a quasi-linear relationship found between the domain-averaged water vapor, Q (mm), and temperature, T (K), fields for the three tropical oceans (i.e., the Pacific, Atlantic and Indian Oceans) based on eleven GEOS-3 [Goddard Earth Observing System (EOS) Version-3] global re-analysis monthly products. A Q ? T distribution analysis is also performed for the tropical and extra-tropical regions based on in-situ sounding data and numerical simulations [GEOS-3 and the Goddard Cumulus Ensemble (GCE) model]. A similar positively correlated Q ? T distribution is found over the entire oceanic and tropical regions; however, Q increases faster with T for the former region. It is suspected that the tropical oceans may possess a moister boundary layer than the Tropics. The oceanic regime falls within the lower bound of the tropical regime embedded in a global, curvilinear Q ? T relationship. A positive correlation is also found between T and sea surface temperature (SST); however, for one degree of increase in T, SST is found to increase 1.1 degrees for a warmer ocean, which is slightly less than an increase of 1.25 degrees for a colder ocean. This seemingly indicates that more (less) heat is needed for an open ocean to maintain an air mass above it with a same degree of temperature rise during a colder (warmer) season [or in a colder (warmer) region]. Q and SST are also found to be positively correlated. Relative humidity (RH) exhibits similar behaviors for oceanic and tropical regions. RH increases with increasing SST and T over oceans, while it increases with increasing T in the Tropics. RH, however, decreases with increasing temperature in the extratropics. It is suspected that the tropical and oceanic regions may possess a moister local boundary layer than the extratropics so that a faster moisture increase than a saturated moisture increase is favored for the former regions. T,Q, saturated water vapor, RH, and SST are also examined with regard to the warm and cold “seasons” over individual oceans. The Indian Ocean warm season dominates in each of the five quantities, while the Atlantic Ocean cold season has the lowest values in most categories. The higher values for the Indian Ocean may be due to its relatively high percentage of tropical coverage compared to the other two oceans. However, Q is found to increase faster for colder months from individual oceans, which differs from the general finding in the global Q?T relationship that Q increases slower for a colder climate. The modified relationship may be attributed to a possible seasonal (warm and cold) variability in boundary layer depth over oceans, or to the small sample size used in each individual oceanic group.     

Cloud albedo feedback and the super greenhouse effect in a global coupled GCM

Two competing cloud-radiative feedbacks identified in previous studies i.e., cloud albedo feedback and the super greenhouse effect, are examined in a sensitivity study with a global coupled ocean-atmosphere general circulation model. Cloud albedo feedback is strengthened in a sensitivity experiment by lowering the sea-surface temperature (SST) threshold in the specified cloud albedo feedback scheme. This simple parameterization requires coincident warm SSTs and deep convection for upper-level cloud albedos to increase. The enhanced cloud albedo feedback in the sensitivity experiment results in decreased maximum values of SST and cooler surface temperatures over most areas of the planet. There is also a cooling of the tropical troposphere with attendant global changes of atmospheric circulation reminiscent of those observed during La Niña or cold events in the Southern Oscillation. The strengthening of the cloud albedo feedback only occurs over warm tropical oceans (e.g., the western Pacific warm pool), where there is increased albedo, decreased absorbed solar radiation at the surface, stronger surface westerlies, enhanced westward currents, lower temperatures, and decreased precipitation and evaporation. However, the weakened convection over the tropical western Pacific Ocean alters the large-scale circulation in the tropics such that there is increased upper-level divergence over tropical land areas and the tropical Indian Ocean. This results in increased precipitation in those regions and intensified monsoonal regimes. The enhanced precipitation over tropical land areas produces increased clouds and albedo and wetter and cooler land surfaces. These additional contributions to decreased absorbed solar input at the surface combine with similar changes over the tropical oceans to produce the global cooling associated with the stronger cloud albedo feedback. Increased low-level moisture convergence and precipitation over the tropical Indian Ocean enhance slightly the super greenhouse effect there. But the stronger cloud albedo feedback is still the dominant effect, although cooling of SSTs in that region is less than in the tropical western Pacific Ocean. The sensitivity experiment demonstrates how a regional change of radiative forcing is quickly transmitted globally through a combination of radiative and dynamical processes in the coupled model. This study points to the uncertainties involved with the parameterization of cloud albedo and the major implications of such parameterizations concerning the maximum values of SST, global climate sensitivity, and climate change.Support is provided by the Office of Health and Environmental Research of the U.S. Department of Energy, as part of its Carbon Dioxide Research Program.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Analysis of the Slab Ocean El Nino atmospheric feedbacks in observed and simulated ENSO dynamics

In a recent study it was illustrated that the El Nino Southern Oscillation (ENSO) mode can exist in the absence of any ocean dynamics. This oscillating mode exists just due to the interaction between atmospheric heat fluxes and ocean heat capacity. The primary purpose of this study is to further explore these atmospheric Slab Ocean ENSO dynamics and therefore the role of positive atmospheric feedbacks in model simulations and observations. The positive solar radiation feedback to sea surface temperature (SST), due to reduced cloud cover for anomalous warm SSTs, is the main positive feedback in the Slab Ocean El Nino dynamics. The strength of this positive cloud feedback is strongly related to the strength of the equatorial cold tongue. The combination of positive latent and sensible heat fluxes to the west and negative ones to the east of positive anomalies leads to the westward propagation of the SST anomalies, which allows for oscillating behavior with a preferred period of 6–7 years. Several indications are found that parts of these dynamics are indeed observed and simulated in other atmospheric or coupled general circulation models (AGCMs or CGCMs). The CMIP3 AGCM-slab ensemble of 13 different AGCM simulations shows unstable ocean–atmosphere interactions along the equatorial Pacific related to stronger cold tongues. In observations and in the CMIP3 and CMIP5 CGCM model ensemble the strength and sign of the cloud feedback is a function of the strength of the cold tongue. In summary, this indicates that the Slab Ocean El Nino dynamics are indeed a characteristic of the equatorial Pacific climate that is only dominant or significantly contributing to the ENSO dynamics if the SST cold tongue is sufficiently strong. In the observations this is only the case during strong La Nina conditions. The presence of the Slab Ocean ENSO atmospheric feedbacks in observations and CGCM model simulations implies that the family of physical ENSO modes does have another member, which is entirely driven by atmospheric processes and does not need to have the same spatial pattern nor the same time scales as the main ENSO dynamics.     

Climate change and the regulation of the surface moisture and energy budgets

The increase in the vigor of the hydrological cycle simulated in a 2 × CO₂ experiment with the Canadian Climate Centre general circulation model is smaller than that obtained by other models which have similar increases in mean surface temperature. The surface energy budget, which encompasses also the moisture budget for the oceans, is analyzed. Changes in the net radiative input to and sensible heat flux from the surface act to warm it. This is balanced, at the new equilibrium, by a change in the latent heat flux which acts to cool it. Although this same general behavior is seen in other models, the increase in radiative input to the surface in the CCC GCM is smaller than in other models while the change in the sensible heat flux is of similar size. As a consequence, the latent heat flux required for balance is smaller. The comparatively small increase in the net radiative input at the surface occurs because of a decrease in the solar component. On average the decrease in solar input in the tropical region outweighs the higher latitude increase associated with the snow/ice albedo feedback. The notable tropical decrease in solar input occurs because the albedo of the clouds increase enough in this region to outweigh a small decrease in cloud amount. The increase in cloud albedo in the warmer and moister tropical atmosphere is a consequence of the parameterized cloud optical properties in the model which play an important role in the regulation of the surface energy and moisture budgets. The results demonstrate some of the consequences of the negative feedback mechanism associated with increasing cloud albedo in the model. They also suggest that the simulated change in the vigor of the hydrological cycle is not a simple function of the average increase in surface temperature but is a consequence of all of the processes in the model which control the available energy at the surface as a function of latitude.     

Improve the simulation of western North Pacific summer monsoon in RegCM3 by suppressing convection

Regional climate models, such as RegCM3, generally show large biases in the simulation of western North Pacific (WNP) summer monsoon (WNPSM). In this study, the authors improved the simulation of WNPSM by applying the convection suppression criterion based on the averaged relative humidity from cloud base to cloud top. The simulated rainfall and monsoon circulation are significantly improved. The suppressed convective heating associated with the decrease in convective rainfall simulates a low-level anomalous anticyclone to its north. The anomalous anticyclone reduces the intensity of low-level southwesterly flow and the wind speed at 10 m. The reduction in wind speed at 10 m decreases the evaporation at sea surface. The less supply of water vapor from underlying ocean in turn favors less convective rainfall. The overestimation of simulated convective percentages and the cold bias of 2 m air temperature are also reduced. The different effects of convection suppression criterion in stand-alone RegCM3 and corresponding regional air–sea coupled model are also discussed.     

Oceanic climatology in the coupled model FGOALS-g2: Improvements and biases

The present study examines simulated oceanic climatology in the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 (FGOALS-g2) forced by historical external forcing data. The oceanic temperatures and circulations in FGOALS-g2 were found to be comparable to those observed, and substantially improved compared to those simulated by the previous version, FGOALS-g1.0. Compared with simulations by FGOALS-g1.0, the shallow mixed layer depths were better captured in the eastern Atlantic and Pacific Ocean in FGOALS-g2. In the high latitudes of the Northern Hemisphere, the cold biases of SST were about 1°C–5°C smaller in FGOALS-g2. The associated sea ice distributions and their seasonal cycles were more realistic in FGOALS-g2. The pattern of Atlantic Meridional Overturning Circulation (AMOC) was better simulated in FGOALS-g2, although its magnitude was larger than that found in observed data. The simulated Antarctic Circumpolar Current (ACC) transport was about 140 Sv through the Drake Passage, which is close to that observed. Moreover, Antarctic Intermediate Water (AAIW) was better captured in FGOALS-g2. However, large SST cold biases (>3°C) were still found to exist around major western boundary currents and in the Barents Sea, which can be explained by excessively strong oceanic cold advection and unresolved processes owing to the coarse resolution. In the Indo-Pacific warm pool, the cold biases were partly related to the excessive loss of heat from the ocean. Along the eastern coast in the Atlantic and Pacific Oceans, the warm biases were due to overestimation of shortwave radiation. In the Indian Ocean and Southern Ocean, the surface fresh biases were mainly due to the biases of precipitation. In the tropical Pacific Ocean, the surface fresh biases (>2 psu) were mainly caused by excessive precipitation and oceanic advection. In the Indo-Pacific Ocean, fresh biases were also found to dominate in the upper 1000 m, except in the northeastern Indian Ocean. There were warm and salty biases (3°C–4°C and 1–2 psu) from the surface to the bottom in the Labrador Sea, which might be due to large amounts of heat transport and excessive evaporation, respectively. For vertical structures, the maximal biases of temperature and salinity were found to be located at depths of >600 m in the Arctic Ocean, and their values exceeded 4°C and 2 psu, respectively.     

BCC_AGCM2.1对中国东部地区云辐射特征模拟的偏差分析

通过与观测及再分析资料的对比,评估了中国国家气候中心大气环流模式BCC_AGCM 2.1对中国东部地区云辐射特征的模拟性能,并着重分析了模拟偏差的原因.在云辐射特征的基本气候态模拟方面,模式能大致再现中国东部中纬度层状云大值带,以及层状云冷季多、暖季少的季节特征,模拟的短波云辐射强迫也具有与观测相对应的季节变化特征.在云辐射强迫和地面温度相互影响过程的模拟方面,模式也能模拟出与观测相近的相互作用过程,即地面温度降低伴随着层状云云量增多以及负的净云辐射强迫加强,升温时层状云云量减少和净云辐射强迫减弱.但模式模拟的大陆层状云云量系统性偏少(尤其在冷季),使得模式在该处的短波云辐射强迫明显偏弱.初步分析表明,造成层状云模拟差异的主要原因是在中国西南地区对流层低层模式模拟的偏南气流明显偏弱以及陆-气潜热通量偏小.偏南气流偏弱导致低层散度和垂直运动条件不利于中层云的形成.同时偏南气流偏弱也不利于向西南地区的水汽输送,再加上模式模拟地表向上潜热通量偏小,这二者都使得模式模拟中国西南区域对流层低层的水汽含量严重偏少,相对湿度偏低,同样不利于层状云生成和发展.水汽偏少进一步导致在冷异常情况下青藏高原下游云辐射-地表温度反馈模拟偏弱,即呈现冷异常时,水汽条件偏弱限制了云量增加,弱化了进一步降低温度的反馈过程.     

A systematic approach to identify the sources of tropical SST errors in coupled models using the adjustment of initialised experiments

Understanding the sources of systematic errors in climate models is challenging because of coupled feedbacks and errors compensation. The developing seamless approach proposes that the identification and the correction of short term climate model errors have the potential to improve the modeled climate on longer time scales. In previous studies, initialised atmospheric simulations of a few days have been used to compare fast physics processes (convection, cloud processes) among models. The present study explores how initialised seasonal to decadal hindcasts (re-forecasts) relate transient week-to-month errors of the ocean and atmospheric components to the coupled model long-term pervasive SST errors. A protocol is designed to attribute the SST biases to the source processes. It includes five steps: (1) identify and describe biases in a coupled stabilized simulation, (2) determine the time scale of the advent of the bias and its propagation, (3) find the geographical origin of the bias, (4) evaluate the degree of coupling in the development of the bias, (5) find the field responsible for the bias. This strategy has been implemented with a set of experiments based on the initial adjustment of initialised simulations and exploring various degrees of coupling. In particular, hindcasts give the time scale of biases advent, regionally restored experiments show the geographical origin and ocean-only simulations isolate the field responsible for the bias and evaluate the degree of coupling in the bias development. This strategy is applied to four prominent SST biases of the IPSLCM5A-LR coupled model in the tropical Pacific, that are largely shared by other coupled models, including the Southeast Pacific warm bias and the equatorial cold tongue bias. Using the proposed protocol, we demonstrate that the East Pacific warm bias appears in a few months and is caused by a lack of upwelling due to too weak meridional coastal winds off Peru. The cold equatorial bias, which surprisingly takes 30 years to develop, is the result of an equatorward advection of midlatitude cold SST errors. Despite large development efforts, the current generation of coupled models shows only little improvement. The strategy proposed in this study is a further step to move from the current random ad hoc approach, to a bias-targeted, priority setting, systematic model development approach.     

Albedo enhancement of marine clouds to counteract global warming: impacts on the hydrological cycle

Recent studies have shown that changes in solar radiation affect the hydrological cycle more strongly than equivalent CO₂ changes for the same change in global mean surface temperature. Thus, solar radiation management ??geoengineering?? proposals to completely offset global mean temperature increases by reducing the amount of absorbed sunlight might be expected to slow the global water cycle and reduce runoff over land. However, proposed countering of global warming by increasing the albedo of marine clouds would reduce surface solar radiation only over the oceans. Here, for an idealized scenario, we analyze the response of temperature and the hydrological cycle to increased reflection by clouds over the ocean using an atmospheric general circulation model coupled to a mixed layer ocean model. When cloud droplets are reduced in size over all oceans uniformly to offset the temperature increase from a doubling of atmospheric CO₂, the global-mean precipitation and evaporation decreases by about 1.3% but runoff over land increases by 7.5% primarily due to increases over tropical land. In the model, more reflective marine clouds cool the atmospheric column over ocean. The result is a sinking motion over oceans and upward motion over land. We attribute the increased runoff over land to this increased upward motion over land when marine clouds are made more reflective. Our results suggest that, in contrast to other proposals to increase planetary albedo, offsetting mean global warming by reducing marine cloud droplet size does not necessarily lead to a drying, on average, of the continents. However, we note that the changes in precipitation, evaporation and P-E are dominated by small but significant areas, and given the highly idealized nature of this study, a more thorough and broader assessment would be required for proposals of altering marine cloud properties on a large scale.     

赤道太平洋冷舌的春季海表面稳定冷偏差和最小风引起的混合

The authors investigate the relationship between bias in simulated sea surface temperature (SST) in the equatorial eastern Pacific cold tongue during the boreal spring as simulated by an oceanic general circulation model (OGCM) and minimal wind mixing (MWM) at the surface. The cold bias of simulated SST is greatest during the boreal spring, at approximately 3°C. A sensitivity experiment reducing MWM by one order of magnitude greatly alleviates cold biases, especially in March-April. The decrease in bias is primarily due to weakened vertical mixing, which preserves heat in the uppermost layer and results in warmer simulated SST. The reduction in vertical mixing also leads to a weak westward current in the upper layer, which further contributes to warmer SST estimates. These findings imply that there are large uncertainties about simple model parameters such as MWM at the oceanic surface.     

Coupling of a regional atmospheric model (RegCM3) and a regional oceanic model (FVCOM) over the maritime continent

Climatological high resolution coupled climate model simulations for the maritime continent have been carried out using the regional climate model (RegCM) version 3 and the finite volume coastal ocean model (FVCOM) specifically designed to resolve regions characterized by complex geometry and bathymetry. The RegCM3 boundary forcing is provided by the EMCWF-ERA40 re-analysis. FVCOM is embedded in the Global MITgcm which provides boundary forcing. The domain of the coupled regional model covers the entire South China Sea with its through-flow, the entire Indonesian archipelago with the Indonesian through-flow (ITF) and includes a large region in the western Pacific and eastern Indian oceans. The coupled model is able to provide stable and realistic climatological simulations for a specific decade of atmospheric–oceanic variables without flux correction. The major focus of this work is on oceanic properties. First, the coupled simulation is assessed against ocean-only simulations carried out under two different sets of air–sea heat fluxes. The first set, provided by the MITgcm, is proved to be grossly deficient as the heat fluxes are evaluated by a two-dimensional, zonally averaged atmosphere and the simulated SST have anomalous cold biases. Hence the MITgcm fluxes are discarded. The second set, the NCEP re-analysis heat fluxes, produces a climatological evolution of the SST with an average cold bias of ~?0.8 °C. The coupling eliminates the cold bias and the coupled SST evolution is in excellent agreement with the analogous evolution in the SODA re-analysis data. The detailed comparison of oceanic circulation properties with the International Nusantara Stratification and Transport observations shows that the coupled simulation produces the best estimate of the total ITF transport through the Makassar strait while the transports of three ocean-only simulations are all underestimated. The annual cycle of the transport is also very well reproduced. The coupling also considerably improves the vertical thermal structure of the Makassar cross section in the upper layer affected by the heat fluxes. On the other hand, the coupling is relatively ineffective in improving the precipitation fields even though the coupled simulation captures reasonably well the precipitation annual cycle at three land stations in different latitudes.     

Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model

In this study, the impact of the ocean–atmosphere coupling on the atmospheric mean state over the Indian Ocean and the Indian Summer Monsoon (ISM) is examined in the framework of the SINTEX-F2 coupled model through forced and coupled control simulations and several sensitivity coupled experiments. During boreal winter and spring, most of the Indian Ocean biases are common in forced and coupled simulations, suggesting that the errors originate from the atmospheric model, especially a dry islands bias in the Maritime Continent. During boreal summer, the air-sea coupling decreases the ISM rainfall over South India and the monsoon strength to realistic amplitude, but at the expense of important degradations of the rainfall and Sea Surface Temperature (SST) mean states in the Indian Ocean. Strong SST biases of opposite sign are observed over the western (WIO) and eastern (EIO) tropical Indian Ocean. Rainfall amounts over the ocean (land) are systematically higher (lower) in the northern hemisphere and the south equatorial Indian Ocean rainfall band is missing in the control coupled simulation. During boreal fall, positive dipole-like errors emerge in the mean state of the coupled model, with warm and wet (cold and dry) biases in the WIO (EIO), suggesting again a significant impact of the SST errors. The exact contributions and the distinct roles of these SST errors in the seasonal mean atmospheric state of the coupled model have been further assessed with two sensitivity coupled experiments, in which the SST biases are replaced by observed climatology either in the WIO (warm bias) or EIO (cold bias). The correction of the WIO warm bias leads to a global decrease of rainfall in the monsoon region, which confirms that the WIO is an important source of moisture for the ISM. On the other hand, the correction of the EIO cold bias leads to a global improvement of precipitation and circulation mean state during summer and fall. Nevertheless, all these improvements due to SST corrections seem drastically limited by the atmosphere intrinsic biases, including prominently the unimodal oceanic position of the ITCZ (Inter Tropical Convergence Zone) during summer and the enhanced westward wind stress along the equator during fall.