CMIP6全球气候模式对青藏高原中东部地表感热通量模拟能力评估

利用青藏高原（以下简称高原）气象台站常规观测资料、国家青藏高原科学数据中心的青藏高原地气相互作用过程高分辨率（逐小时）综合观测数据集（2005～2016）、国际耦合模式比较计划第六阶段（CMIP6）的历史模拟试验数据和卫星辐射资料,定量评估了12个全球气候模式对1979～2014年高原中东部地表感热通量的模拟能力,并对其模拟偏差进行了成因分析。结果表明,CMIP6模式可较好地重现高原地表感热通量的年循环和季节平均的空间分布型,但数值较计算感热通量偏低,主要表现为对感热通量大值区严重低估。区域平均而言,12个模式模拟的春季高原中东部感热通量的时间演变序列整体较计算感热通量偏低,其中偏差最大的模式为MIROC6,其多年均值仅为计算值的1/3左右。进一步分析发现多模式模拟的春季高原10 m高度处风速和地气温差分别偏强和偏弱,说明CMIP6模拟的春季高原感热通量偏低可主要归因于地气温差的模拟冷偏差。地气温差的模拟冷偏差在高原中东部地区普遍存在,且地表温度和空气温度均存在明显冷偏差,尤其地表温度偏差更大,这很大程度上可能与CMIP6多模式模拟的春季高原降水偏强有关。     

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.     

Vertical Heat Transfer in the Lower Atmosphere over the Arctic Ocean During Clear-sky Periods

A diagnostic study of heat transfer within the lower atmosphere and between the atmosphere and the surface of the Arctic Ocean snow/ice pack during clear-sky conditions is conducted using data from the Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment. Surface heat budgets computed for four cloudy and four clear periods show that, while the net turbulent heat fluxes at the surface are small during the cloudy periods, during the clear-sky periods they are a considerable source of surface heating, balancing significant portions of the conductive heat fluxes from within the snow/ice pack. Analysis of the dynamics and thermodynamics of the lower atmosphere during the clear-sky periods reveals that a considerable portion of the heat lost to the surface by turbulent heat fluxes is balanced by locally strong heating near the atmospheric boundary-layer (ABL) top due to the interaction of subsiding motions with the strong overlying temperature inversions surmounting the ABL. This heat is then entrained into the ABL and transported to the surface by turbulent mixing, maintained by a combination of vertical wind shear and wave-turbulence interactions. The frequency of stable, clear-sky periods, particularly during the winter, combined with these results, suggests that the downward transfer of heat through the lower atmosphere and into the surface represents an important component of the heat budgets of the lower atmosphere and snow/ice pack over the annual cycle     

Simulation of snow processes beneath a boreal scots pine canopy

A physically-based multi-layer snow model Snow-Atmosphere-Soil-Transfer scheme(SAST)and a land surface model Biosphere-Atmosphere Transfer Scheme(BATS)were employed to investigate how boreal forests influence snow accumulation and ablation under the canopy.Mass balance and energetics of snow beneath a Scots pine canopy in Finland at different stages of the 2003-2004 and 2004 2005 snow seasons are analyzed.For the fairly dense Scots pine forest,drop-off of the canopy-intercepted snow contributes,in some cases,twice as much to the underlying snowpack as the direct throughfall of snow.During early winter snow melting,downward turbulent sensible and condensation heat fluxes play a dominant role together with downward net longwave radiation.In the final stage of snow ablation in middle spring,downward net all- wave radiation dominates the snow melting.Although the downward sensible heat flux is comparable to the net solar radiation during this period,evaporative cooling of the melting snow surface makes the turbulent heat flux weaker than net radiation.Sensitivities of snow processes to leaf area index(LAI)indicate that a denser canopy speeds up early winter snowmelt,but also suppresses melting later in the snow season. Higher LAI increases the interception of snowfall,therefore reduces snow accumulation under the canopy during the snow season;this effect and the enhancement of downward longwave radiation by denser foliage outweighs the increased attenuation of solar radiation,resulting in earlier snow ablation under a denser canopy.The difference in sensitivities to LAI in two snow seasons implies that the impact of canopy density on the underlying snowpack is modulated by interannual variations of climate regimes.     

1984-2017年ISCCP-FH辐射资料在青藏高原地区的适用性评估

长序列卫星辐射资料的缺乏一直是制约青藏高原(以下简称高原)辐射长期变化研究的重要原因之一。对国际上最新提供的1984—2017年ISCCP-FH(以下简称FH)长序列卫星辐射资料中的大气顶逸出长波辐射(OLR)、到达地面短波辐射(SWD)、地面向上长波辐射(LWU)、到达地面长波辐射(LWD)进行分析,评估了FH辐射资料在全天气条件下的青藏高原地区的适用性。结果表明:与观测相比,FH资料的4种辐射通量气候平均值误差均小于5%,其中OLR和SWD的偏差较小,LWU的偏差最大。FH资料能正确反映高原各辐射通量的冬季增强趋势,OLR和LWD在各季节的长期变化趋势均与观测一致,LWU则呈现虚假的减弱趋势。总体来说,在高原地区,FH资料的地面短波辐射通量比长波辐射通量适用性好。进一步对长波辐射偏差原因分析显示,气温偏差会增强LWD的气候态和长期趋势,而地温偏差对LWU的作用与之相反。辐射模型、云和水汽的差异导致最终FH资料中的LWD气候态和长期趋势较观测略偏弱,FH资料的计算方案在一定程度上修正了地温偏差造成的LWU偏弱。研究结果将为使用FH辐射资料提供参考依据。     

RegCM4对中国东部区域气候模拟的辐射收支分析

利用卫星和再分析数据,评估了区域气候模式Reg CM4对中国东部地区辐射收支的基本模拟能力,重点关注地表净短波(SNS)、地表净长波(SNL)、大气顶净短波(TNS)、大气顶净长波(TNL)4个辐射分量。结果表明:1)短波辐射的误差值在夏季较大,而长波辐射的误差值在冬季较大。但各辐射分量模拟误差的空间分布在冬、夏季都有较好的一致性。2)对于地表辐射通量,SNS表现为正偏差(向下净短波偏多),在各分量中误差最大,区域平均误差值近50 W/m2;SNL表现为负偏差(向上净长波偏多);对于大气顶辐射通量,TNS和TNL分别表现为"北负南正"的误差分布和整体正偏差。3)利用空间相关和散点线性回归方法对4个辐射分量的模拟误差进行归因分析,发现在云量、地表反照率、地表温度三个直接影响因子中,云量模拟误差的贡献最大,中国东部地区云量模拟显著偏少。     

CMIP6与CMIP5对历史大气层顶和地表辐射收支模拟的时空对比

基于云和地球辐射能量系统观测数据集（CERES),对比分析了耦合模式比较计划第五（CMIP5）和第六阶段（CMIP6）模拟的历史大气层顶和地表辐射收支的年际变化和空间分布,明确了多模式间不确定性大的关键区域。结果表明：在年际尺度上,除地表向上长波辐射外,CMIP6的辐射分量的集合均值较CMIP5更接近于CERES观测值,全球地表向下短波辐射的高估和大气逆辐射的低估在CMIP6中分别降低了1.9 W/m²和3.3 W/m²。除大气逆辐射外,CMIP6的辐射分量在多模式间的一致性较CMIP5提高。在北极,CMIP6对大气层顶反射短波、大气层顶出射长波和地表向下短波辐射的模拟偏差较CMIP5大。在南北纬60°,CMIP6对大气逆辐射的模拟偏差较CMIP5大。其他区域CMIP6的辐射分量更接近CERES观测值。CMIP6模拟的地表向下短波辐射和大气逆辐射的不确定性较大区域面积较CMIP5减小,但不确定性极大区域面积无变化。地表净辐射的不确定性空间分布在两代CMIP间变化甚小。青藏高原、赤道太平洋、热带雨林、阿拉伯半岛和南极洲沿海依然是地球系统模式模拟辐射收支不确定性极大的关键区域。     

Estimations of Land Surface Characteristic Parameters and TurbulentHeat Fluxes over the Tibetan Plateau Based on FY-4A/AGRI Data

正Nan GE1, Lei ZHONG*1,2,3, Yaoming MA4,5,6, Yunfei FU1, Mijun ZOU1,Meilin CHENG1, Xian WANG1, and Ziyu HUANG1     

A dissection of the surface temperature biases in the Community Earth System Model

Based upon the climate feedback-responses analysis method, a quantitative attribution analysis is conducted for the annual-mean surface temperature biases in the Community Earth System Model version 1 (CESM1). Surface temperature biases are decomposed into partial temperature biases associated with model biases in albedo, water vapor, cloud, sensible/latent heat flux, surface dynamics, and atmospheric dynamics. A globally-averaged cold bias of ?1.22 K in CESM1 is largely attributable to albedo bias that accounts for approximately ?0.80 K. Over land, albedo bias contributes ?1.20 K to the averaged cold bias of ?1.45 K. The cold bias over ocean, on the other hand, results from multiple factors including albedo, cloud, oceanic dynamics, and atmospheric dynamics. Bias in the model representation of oceanic dynamics is the primary cause of cold (warm) biases in the Northern (Southern) Hemisphere oceans while surface latent heat flux over oceans always acts to compensate for the overall temperature biases. Albedo bias resulted from the model’s simulation of snow cover and sea ice is the main contributor to temperature biases over high-latitude lands and the Arctic and Antarctic region. Longwave effect of water vapor is responsible for an overall warm (cold) bias in the subtropics (tropics) due to an overestimate (underestimate) of specific humidity in the region. Cloud forcing of temperature biases exhibits large regional variations and the model bias in the simulated ocean mixed layer depth is a key contributor to the partial sea surface temperature biases associated with oceanic dynamics. On a global scale, biases in the model representation of radiative processes account more for surface temperature biases compared to non-radiative, dynamical processes.     

All-Sky Surface Radiation and Clear-Sky Surface Energy Budgets: Summer to Freeze-Up in the Western Maritime Arctic

The 2009 ArcticNet expedition was a field campaign in the Amundsen Gulf–eastern Beaufort Sea region from mid-July to the beginning of November aboard the CCGS Amundsen that provided an opportunity to describe the all-sky surface radiation and the clear-sky surface energy budgets from summer to freeze-up in the data sparse western maritime Arctic. Because the fractional area of open water was generally larger than the fractional area of ice floes, the net radiation at the water surface controlled the radiation budget. Because the water albedo is much less than the albedo of the ice floes, the extent and duration of open water in summer is an important albedo feedback mechanism. From summer to freeze-up, the net all-sky shortwave radiation declined steadily as the solar angle lowered, while coincidently the net all-sky longwave radiation became increasingly negative. The all-sky net surface radiation switched from positive in summer to negative during the freeze-up period. From summer to freeze-up, both upward and downward turbulent heat fluxes occurred. In summer, a positive surface energy budget residual contributed to the melting of ice floes and/or to the warming of the Arctic Ocean's mixed layer. During the freeze-up period, with temperatures below approximately ?5°C, the residuals were mainly negative suggesting that heat loss from the ocean's mixed layer and heat released by the phase change of water were significant components of the energy budget's residual.     

阿尔卑斯山杉林冠层影响辐射传输的个例分析

利用瑞士Alptal观测站杉树林冠层上方、下方的辐射观测资料,分析了冠层对短波辐射的减弱及对长波辐射的增幅作用及其季节变化。结果表明,对比较密集的常绿针叶林,冠层对入射短波辐射的透过率随着太阳高度的降低而减小,春季以后趋于稳定;冠层对长波辐射的增幅作用随天气状况而变化,这种增幅作用在晴空条件下最显著,可达1.5倍。在冬季,因为太阳辐射较弱,冠层对长波辐射的增幅作用超过对短波辐射的减弱从而增加地面净辐射。在其它季节,太阳辐射比较强,冠层对短波辐射的减弱超过对长波辐射的增幅作用而减少地面净辐射。地面净辐射与冠层上方气温的变化趋势虽然在有些时段一致,但在伴随降雪过程的降温时段,地面净辐射与气温的变化趋势近乎反相,在积雪融化时段,地面净辐射的增加比气温升高更显著,尤其是在白天。     

TropFlux: air-sea fluxes for the global tropical oceans—description and evaluation

In this paper, we evaluate several timely, daily air-sea heat flux products (NCEP, NCEP2, ERA-Interim and OAFlux/ISCCP) against observations and present the newly developed TropFlux product. This new product uses bias-corrected ERA-interim and ISCCP data as input parameters to compute air-sea fluxes from the COARE v3.0 algorithm. Wind speed is corrected for mesoscale gustiness. Surface net shortwave radiation is based on corrected ISCCP data. We extend the shortwave radiation time series by using “near real-time” SWR estimated from outgoing longwave radiation. All products reproduce consistent intraseasonal surface net heat flux variations associated with the Madden-Julian Oscillation in the Indian Ocean, but display more disparate interannual heat flux variations associated with El Ni?o in the eastern Pacific. They also exhibit marked differences in mean values and seasonal cycle. Comparison with global tropical moored buoy array data, I-COADS and fully independent mooring data sets shows that the two NCEP products display lowest correlation to mooring turbulent fluxes and significant biases. ERA-interim data captures well temporal variability, but with significant biases. OAFlux and TropFlux perform best. All products have issues in reproducing observed longwave radiation. Shortwave flux is much better captured by ISCCP data than by any of the re-analyses. Our “near real-time” shortwave radiation performs better than most re-analyses, but tends to underestimate variability over the cold tongues of the Atlantic and Pacific. Compared to independent mooring data, NCEP and NCEP2 net heat fluxes display ~0.78 correlation and >65?W?m^?2 rms-difference, ERA-I performs better (~0.86 correlation and ~48?W?m^?2) while OAFlux and TropFlux perform best (~0.9 correlation and ~43?W?m^?2). TropFlux hence provides a useful option for studying flux variability associated with ocean–atmosphere interactions, oceanic heat budgets and climate fluctuations in the tropics.     

华南沿海暖海雾过程中的湍流热量交换特征

湍流交换是海雾中的关键物理过程, 在海雾的热量和水汽平衡过程中起重要作用。本文根据2007年3月24～25日一次海雾的外场观测数据, 分析了海雾过程中近海面湍流热量交换特征; 并在区分风切变机械湍流与雾顶长波辐射冷却热力湍流的基础上, 着重分析了两种不同性质的湍流对海雾发展和维持的作用。结果表明: (1) 本次海雾是在西南低压和变性冷高压的控制下, 来自南海东部暖水区的空气平流在近岸冷海面上形成的暖海雾; 暖海雾中的湍流热量交换过程比冷海雾更为复杂; (2) 在暖海雾的形成和消散阶段, 风切变机械湍流的热量输送起主要作用; 而在发展和维持阶段, 既有风切变机械湍流的热量输送作用, 也有雾顶长波辐射冷却热力湍流的热量输送作用; (3) 风切变机械湍流向冷海面输送热量, 对近海面空气起到降温和增湿作用; 热力湍流同样向冷海面输送热量, 但对雾层起到增温和降湿作用; (4) 暖海雾中的湍流热量交换机制与雾层的非充分混合结构有密切关系。     

Surface mean temperature from the observational stations and multiple reanalyses over the Tibetan Plateau

The Tibetan Plateau (TP), also called the “Third pole”, is sensitive to climate change due to extensive areas at high elevation presently dominated by snow and ice. In this study, observed surface temperature trends at 150 stations over the TP during 1979–2018 are analyzed and compared with surface temperatures from multiple reanalyses (NCEP1, NCEP2, ERA-Interim, MERRA, JRA55). Observed warming at the stations has a mean annual rate of 0.46 °C/decade during 1979–2018. Although all reanalyses underestimate observed temperatures (cold bias), most reproduce much of the inter-decadal variations of surface temperature shown in the observations. Absolute errors of mean surface temperature (reanalysis minus observation) are closely correlated with elevation errors, suggesting that parts of the cold bias can be interpreted by elevation errors of reanalysis. After elevation-temperature correction, about half of the cold bias is typically eliminated, more for both ERA-Interim and JRA55. Compared with the observations, corrected NCEP2 surface temperatures still have larger cold biases, and fail to capture the overall warming over the TP. Since the elevation-temperature correction fails to improve trend magnitudes even when a significant proportion of the bias has been removed, this suggests that a more sophisticated modeling of the lapse rate in each reanalysis is required to realistically model warming trends across complex topography.

     

The Warming of the Tibetan Plateau in Response to Transient and Stabilized 2.0°C/1.5°C Global Warming Targets

As "the third pole", the Tibetan Plateau (TP) is sensitive to climate forcing and has experienced rapid warming in recent decades. This study analyzes annual and seasonal near-surface air temperature changes on the TP in response to transient and stabilized 2.0°C/1.5°C global warming targets based on simulations of the Community Earth System Model (CESM). Elevation-dependent warming (EDW) with faster warming at higher elevations is predicted. A surface energy budget analysis is adopted to uncover the mechanisms responsible for the temperature changes. Our results indicate a clear amplified warming on the TP with positive EDW in 2.0°C/1.5°C warmer futures, especially in the cold season. Mean TP warming relative to the reference period (1961–90) is dominated by an enhanced downward longwave radiation flux, while the variations in surface albedo shape the detailed pattern of EDW. For the same global warming level, the temperature changes under transient scenarios are ~0.2°C higher than those under stabilized scenarios, and the characteristics of EDW are broadly similar for both scenarios. These differences can be primarily attributed to the combined effects of differential downward longwave radiation, cloud radiative forcing, and surface sensible and latent heat fluxes. These findings contribute to a more detailed understanding of regional climate on the TP in response to the long-term climate goals of the Paris Agreement and highlight the differences between transient and stabilized warming scenarios.     

中国西北干旱区戈壁下垫面夏季的热力输送

以敦煌戈壁站2004年6月和2008年8月的常规观测和超声观测为例,分析了西北干旱区戈壁下垫面夏季热力输送的一般过程及特征。首先评价了湍流通量的观测质量以及仪器观测的地表能量通量闭合问题,结果表明敦煌戈壁站的观测在白天总体较好。夏季地表能量通量的平均日变化显示,潜热通量整天都很小,可以忽略,白天到达地表的短波辐射以及地表向上的长波辐射非常强,地表净辐射主要转化为感热输送（敦煌戈壁站在中午时平均分别达380W·m-2以上和250W·m-2以上）;夜间土壤释放热量以平衡地表的辐射冷却,感热通量略低于0。白天时地表大气经常触发自由对流活动,影响动量通量的观测质量,并有效输送地表热力至上层大气中,有助于形成超厚大气边界层。分析了戈壁下垫面的动量粗糙度特征和热力粗糙度特征（敦煌戈壁站动量粗糙度约为0．6mm）,热力粗糙度基本小于动量粗糙度一个量级,这符合目前对干旱区戈壁下垫面热力输送特征的初步认识。     

An evaluation of the surface radiation budget over North America for a suite of regional climate models against surface station observations

Components of the surface radiation budget (SRB) [incoming shortwave radiation (ISR) and downwelling longwave radiation (DLR)] and cloud cover are assessed for three regional climate models (RCM) forced by analysed boundary conditions, over North America. We present a comparison of the mean seasonal and diurnal cycles of surface radiation between the three RCMs, and surface observations. This aids in identifying in what type of sky situation simulated surface radiation budget errors arise. We present results for total-sky conditions as well as overcast and clear-sky conditions separately. Through the analysis of normalised frequency distributions we show the impact of varying cloud cover on the simulated and observed surface radiation budget, from which we derive observed and model estimates of surface cloud radiative forcing. Surface observations are from the NOAA SURFRAD network. For all models DLR all-sky biases are significantly influenced by cloud-free radiation, cloud emissivity and cloud cover errors. Simulated cloud-free DLR exhibits a systematic negative bias during cold, dry conditions, probably due to a combination of omission of trace gas contributions to the DLR and a poor treatment of the water vapor continuum at low water vapor concentrations. Overall, models overestimate ISR all-sky in summer, which is primarily linked to an underestimate of cloud cover. Cloud-free ISR is relatively well simulated by all RCMs. We show that cloud cover and cloud-free ISR biases can often compensate to result in an accurate total-sky ISR, emphasizing the need to evaluate the individual components making up the total simulated SRB.     

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.     

Greenhouse effect and altitude gradients over the Alps – by surface longwave radiation measurements and model calculated LOR

Summary The greenhouse effect has been investigated predominantly with satellite measurements, but more than 90% of the greenhouse radiative flux affecting Earths surface temperature and humidity originates from a 1000 meter layer above the surface. Here we show that substantial improvements on surface longwave radiation measurements and very good agreement with radiative transfer model calculations allow the clear-sky greenhouse effect be determined with measured surface longwave radiation and calculated longwave outgoing radiation at the top of the atmosphere. The cloud radiative forcing is determined by measured net longwave fluxes and added to the clear-sky greenhouse effect to determine the all-sky greenhouse effect. Longwave radiation measurements at different altitudes were used to determine the clear-sky and all-sky annual and seasonal greenhouse effect and altitude gradients over the Alps. Linear altitude gradients are measured for clear-sky situations, whereas the all-sky greenhouse effect is strongly influenced by varying, cloud amounts at different altitudes. Large diurnal and seasonal variations show the importance of surface heating and cooling effects and demonstrate the strong coupling of the greenhouse effect to surface temperature and humidity.     

How well can CMIP5 simulate precipitation and its controlling processes over tropical South America?

Underestimated rainfall over Amazonia was a common problem for the Coupled Model Intercomparison Project phase 3 (CMIP3) models. We investigate whether it still exists in the CMIP phase 5 (CMIP5) models and, if so, what causes these biases? Our evaluation of historical simulations shows that some models still underestimate rainfall over Amazonia. During the dry season, both convective and large-scale precipitation is underestimated in most models. GFDL-ESM2M and IPSL notably show more pentads with no rainfall. During the wet season, large-scale precipitation is still underestimated in most models. In the dry and transition seasons, models with more realistic moisture convergence and surface evapotranspiration generally have more realistic rainfall totals. In some models, overestimates of rainfall are associated with the adjacent tropical and eastern Pacific ITCZs. However, in other models, too much surface net radiation and a resultant high Bowen ratio appears to cause underestimates of rainfall. During the transition season, low pre-seasonal latent heat, high sensible flux, and a weaker influence of cold air incursions contribute to the dry bias. About half the models can capture, but overestimate, the influences of teleconnection. Based on a simple metric, HadGEM2-ES outperforms other models especially for surface conditions and atmospheric circulation. GFDL-ESM2M has the strongest dry bias presumably due to its overestimate of moisture divergence, induced by overestimated ITCZs in adjacent oceans, and reinforced by positive feedbacks between reduced cloudiness, high Bowen ratio and suppression of rainfall during the dry season, and too weak incursions of extratropical disturbances during the transition season.