Quantifying uncertainties in projections of extremes��a perturbed land surface parameter experiment

Uncertainties in the climate response to a doubling of atmospheric CO₂ concentrations are quantified in a perturbed land surface parameter experiment. The ensemble of 108 members is constructed by systematically perturbing five poorly constrained land surface parameters of global climate model individually and in all possible combinations. The land surface parameters induce small uncertainties at global scale, substantial uncertainties at regional and seasonal scale and very large uncertainties in the tails of the distribution, the climate extremes. Climate sensitivity varies across the ensemble mainly due to the perturbation of the snow albedo parameterization, which controls the snow albedo feedback strength. The uncertainty range in the global response is small relative to perturbed physics experiments focusing on atmospheric parameters. However, land surface parameters are revealed to control the response not only of the mean but also of the variability of temperature. Major uncertainties are identified in the response of climate extremes to a doubling of CO₂. During winter the response both of temperature mean and daily variability relates to fractional snow cover. Cold extremes over high latitudes warm disproportionately in ensemble members with strong snow albedo feedback and large snow cover reduction. Reduced snow cover leads to more winter warming and stronger variability decrease. As a result uncertainties in mean and variability response line up, with some members showing weak and others very strong warming of the cold tail of the distribution, depending on the snow albedo parametrization. The uncertainty across the ensemble regionally exceeds the CMIP3 multi-model range. Regarding summer hot extremes, the uncertainties are larger than for mean summer warming but smaller than in multi-model experiments. The summer precipitation response to a doubling of CO₂ is not robust over many regions. Land surface parameter perturbations and natural variability alter the sign of the response even over subtropical regions.     

Albedo of coastal landfast sea ice in Prydz Bay,Antarctica: Observations and parameterization

The snow/sea-ice albedo was measured over coastal landfast sea ice in Prydz Bay, East Antarctica(off Zhongshan Station)during the austral spring and summer of 2010 and 2011. The variation of the observed albedo was a combination of a gradual seasonal transition from spring to summer and abrupt changes resulting from synoptic events, including snowfall, blowing snow, and overcast skies. The measured albedo ranged from 0.94 over thick fresh snow to 0.36 over melting sea ice. It was found that snow thickness was the most important factor influencing the albedo variation, while synoptic events and overcast skies could increase the albedo by about 0.18 and 0.06, respectively. The in-situ measured albedo and related physical parameters(e.g., snow thickness, ice thickness, surface temperature, and air temperature) were then used to evaluate four different snow/ice albedo parameterizations used in a variety of climate models. The parameterized albedos showed substantial discrepancies compared to the observed albedo, particularly during the summer melt period, even though more complex parameterizations yielded more realistic variations than simple ones. A modified parameterization was developed,which further considered synoptic events, cloud cover, and the local landfast sea-ice surface characteristics. The resulting parameterized albedo showed very good agreement with the observed albedo.     

Ice-albedo feedback in a CO2-doubling simulation

We estimate the feedback of sea-ice change to the warming from CO₂-doubling according to the simulation of Washington and Meehl (1984). Without ice-snow albedo feedback, their global warming of 3.5 °C would have been 2.2. °C according to our estimate of the ice-snow feedback. About 80% of the albedo change from ice and snow occurred in the Southern Hemisphere. Whether this change was an overestimate will require further study.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

The effect of atmospheric CO2 and ice sheet topography on LGM climate

The role of reduced atmospheric CO₂ concentration and ice sheet topography plus its associated land albedo on the LGM climate is investigated using a coupled atmosphere-ocean-sea ice climate system model. The surface cooling induced by the reduced CO₂ concentration is larger than that by the ice sheet topography plus other factors by about 30% for the surface air temperature and by about 100% for the sea surface temperature. A large inter-hemispheric asymmetry in surface cooling with a larger cooling in the Northern Hemisphere is found for both cases. This asymmetric inter-hemispheric temperature response is consistent in the ice sheet topography case with earlier studies using an atmospheric model coupled with a mixed-layer ocean representation, but contrasts with these results in the reduced CO₂ case. The incorporation of ocean dynamics presumably leads to a larger snow and sea ice feedback as a result of the reduction in northward ocean heat transport, mainly as a consequence of the decrease in the North Atlantic overturning circulation by the substantial freshening of the North Atlantic convection regions. A reversed case is found in the Southern Ocean. Overall, the reduction in atmospheric CO₂ concentration accounts for about 60% of the total LGM climate change.     

极冰气候效应的数值试验

利用一个大气环流模式（ＡＧＣＭ）和一个全球耦合海气模式（ＣＯＡＧＣＭ）,模拟了北极海冰边界范围的变化对月平均气候的影响。结果表明,极冰边缘的异常完全可以改变中高纬度某些地区的局地气候。受冷源的影响,北半球中高纬度冷高压加强,低纬度暖高压减弱。同时利用一个全球三维大气环流模式,作了海冰反照率参数化的数值试验,用两种不同的海冰反照率参数化方案,检验对地表面温度、海平面气压、极地表面对太阳辐射吸收的影响。模拟试验表明了冰雪圈反照率的反馈作用,对气候变化的影响十分重要。     

Climate Change Scenarios for the Hudson Bay Region: An Intermodel Comparison

General circulation models (GCMs) are unanimous in projecting warmer temperatures in an enhanced CO₂ atmosphere, with amplification of this warming in higher latitudes. The Hudson Bay region, which is located in the Arctic and subarctic regions of Canada, should therefore be strongly influenced by global warming. In this study, we compare the response of Hudson Bay to a transient warming scenario provided by six-coupled atmosphere-ocean models. Our analysis focuses on surface temperature, precipitation, sea-ice coverage, and permafrost distribution. The results show that warming is expected to peak in winter over the ocean, because of a northward retreat of the sea-ice cover. Also, a secondary warming peak is observed in summer over land in the Canadian and Australian-coupled GCMs, which is associated with both a reduction in soil moisture conditions and changes in permafrost distribution. In addition, a relationship is identified between the retreat of the sea-ice cover and an enhancement of precipitation over both land and oceanic surfaces. The response of the sea-ice cover and permafrost layer to global warming varies considerably among models and thus large differences are observed in the projected regional increase in temperature and precipitation. In view of the important feedbacks that a retreat of the sea-ice cover and the distribution of permafrost are likely to play in the doubled and tripled CO₂ climates of Hudson Bay, a good representation of these two parameters is necessary to provide realistic climate change scenarios. The use of higher resolution regional climate model is recommended to develop scenarios of climate change for the Hudson Bay region.     

A subgrid parameterization of orographic precipitation

Summary Estimates of the impact of global climate change on land surface hydrology require climate information on spatial scales far smaller than those explicitly resolved by global climate models of today and the foreseeable future. To bridge the gap between what is required and what is resolved, we propose a subgrid-scale parameterization of the influence of topography on clouds, precipitation, and land surface hydrology. The parameterization represents subgrid variations in surface elevation in terms of probability distributions of discrete elevation classes. Separate cloud, radiative, and surface processes are calculated for each elevation class. Rainshadow effects are not treated by the parameterization; they have to be explicitly resolved by the host model. The simulated surface temperature, precipitation, and snow cover for each elevation class are distributed to different geographical locations according to the spatial distribution of surface elevation within each grid cell.The subgrid parameterization has been implemented in the Pacific Northwest Laboratory's climate version of the Penn State/NCAR Mesoscale Model. The scheme is evaluated by driving the regional climate model with observed lateral boundary conditions for the Pacific Northwest and comparing simulated fields with surface observations. The method yields more realistic spatial distributions of precipitation and snow cover in mountainous areas and is considerably more computationally efficient than achieving high resolution by the use of nesting in the regional climate model.With 17 Figures     

On the role of high latitude ice,snow, and vegetation feedbacks in the climatic response to external forcing changes

A seasonal energy balance climate model containing a detailed treatment of surface and planetary albedo, and in which seasonally varying land snow and sea ice amounts are simulated in terms of a number of explicit physical processes, is used to investigate the role of high latitude ice, snow, and vegetation feedback processes. Feedback processes are quantified by computing changes in radiative forcing and feedback factors associated with individual processes. Global sea ice albedo feedback is 5–8 times stronger than global land snowcover albedo feedback for a 2% solar constant increase or decrease, with Southern Hemisphere cryosphere feedback being 2–5 times stronger than Northern Hemisphere cryosphere feedback.In the absence of changes in ice extent, changes in ice thickness in response to an increase in solar constant are associated with an increase in summer surface melting which is exactly balanced by increased basal winter freezing, and a reduction in the upward ocean-air flux in summer which is exactly balanced by an increased flux in winter, with no change in the annual mean ocean-air flux. Changes in the mean annual ocean-air heat flux require changes in mean annual ice extent, and are constrained to equal the change in meridional oceanic heat flux convergence in equilibrium. Feedback between ice extent and the meridional oceanic heat flux obtained by scaling the oceanic heat diffusion coefficient by the ice-free fraction regulates the feedback between ice extent and mean annual air-sea heat fluxes in polar regions, and has a modest effect on model-simulated high latitude temperature change.Accounting for the partial masking effect of vegetation on snow-covered land reduces the Northern Hemisphere mean temperature response to a 2% solar constant decrease or increase by 20% and 10%, respectively, even though the radiative forcing change caused by land snowcover changes is about 3 times larger in the absence of vegetational masking. Two parameterizations of the tundra fraction are tested: one based on mean annual land air temperature, and the other based on July land air temperature. The enhancement of the mean Northern Hemisphere temperature response to solar constant changes when the forest-tundra ecotone is allowed to shift with climate is only 1/3 to 1/2 that obtained by Otterman et al. (1984) when the mean annual parameterization is used here, and only 1/4 to 1/3 as large using the July parameterization.The parameterized temperature dependence of ice and snow albedo is found to enhance the global mean temperature response to a 2% solar constant increase by only 0.04 °C, in sharp contrast to the results of Washington and Meehl (1986) obtained with a mean annual model. However, there are significant differences in the method used here and in Washington and Meehl to estimate the importance of this feedback process. When their approach is used in a mean annual version of the present model, closer agreement to their results is obtained.     

Sensitivity experiments performed with an energy balance atmosphere model coupled to an advection-diffusion ocean model

Summary In this paper a simple climate model is presented which is used to perform some sensitivity experiments. The atmospheric part is represented by a vertically and zonally averaged layer in which the surface air temperature, radiative fluxes at the surface and at the top of the atmosphere, the turbulent fluxes between atmosphere and surface and the snow cover are calculated. This atmospheric layer is coupled to a two-dimensional advection-diffusion ocean model in which the zonal overturning pattern is prescribed. The ocean model evaluates the temperature distribution, the amount of sea-ice and the meridional and vertical heat fluxes. The present-day climate simulated by the model compares reasonably well with observations of the seasonal and latitudinal distribution of temperature, radiation, surface alebdo, sea-ice and snow cover and meridional energy fluxes. Then, the sensitivity of the model-simulated present-day climate to perturbations in the incident solar radiation at the top of the atmosphere is investigated. The temperature response displays large latitudinal and seasonal variations, which is in qualitative agreement with results obtained with other climate models. It is found that the seasonal variation of sea-ice cover (and hence, the effective oceanic heat capacity) is one of the most important elements determining seasonal variations in climate sensitivity. Differences in sensitivity between the seasonal and annual mean version of the model are discussed. Finally, the equilibrium response to perturbations in some selected model variables is presented; these variables include meridional diffusion coefficients, drag coefficient, sea-ice thickness, atmospheric CO₂-concentration and cloud optical thickness.With 13 Figures     

Climate sensitivity due to increased CO2: experiments with a coupled atmosphere and ocean general circulation model

A version of the National Center for Atmospheric Research community climate model — a global, spectral (R15) general circulation model — is coupled to a coarse-grid (5° latitude-] longitude, four-layer) ocean general circulation model to study the response of the climate system to increases of atmospheric carbon dioxide (CO₂). Three simulations are run: one with an instantaneous doubling of atmospheric CO₂ (from 330 to 660 ppm), another with the CO₂ concentration starting at 330 ppm and increasing linearly at a rate of 1% per year, and a third with CO₂ held constant at 330 pm. Results at the end of 30 years of simulation indicate a globally averaged surface air temperature increase of 1.6° C for the instantaneous doubling case and 0.7°C for the transient forcing case. Inherent characteristics of the coarse-grid ocean model flow sea-surface temperatures (SSTs) in the tropics and higher-than-observed SSTs and reduced sea-ice extent at higher latitudes] produce lower sensitivity in this model after 30 years than in earlier simulations with the same atmosphere coupled to a 50-m, slab-ocean mixed layer. Within the limitations of the simulated meridional overturning, the thermohaline circulation weakens in the coupled model with doubled CO₂ as the high-latitude ocean-surface layer warms and freshens and westerly wind stress is decreased. In the transient forcing case with slowly increasing CO₂ (30% increase after 30 years), the zonal mean warming of the ocean is most evident in the surface layer near 30°–50° S. Geographical plots of surface air temperature change in the transient case show patterns of regional climate anomalies that differ from those in the instantaneous CO₂ doubling case, particularly in the North Atlantic and northern European regions. This suggests that differences in CO₂ forcing in the climate system are important in CO₂ response in regard to time-dependent climate anomaly regimes. This confirms earlier studies with simple climate models that instantaneous CO₂ doubling simulations may not be analogous in all respects to simulations with slowly increasing CO₂.A portion of this study is supported by the US Department of Energy as part of its Carbon Dioxide Research Program     

General circulation model CO2 sensitivity experiments: Snow-sea ice albedo parameterizations and globally averaged surface air temperature

Two experiments are performed with the NCAR Community Climate Model (CCM) coupled to a swamp ocean with annually averaged solar forcing. A swamp ocean model is one in which the ocean temperature is computed from a surface energy balance. Both experiments are run with present (1 × CO₂) and doubled (2 × CO₂) amounts of atmospheric carbon dioxide (CO₂). The first tests the sensitivity of the model to a snow and sea-ice-albedo formulation which facilitates relatively greater ice melt. The second assesses the model response when the basic state of the model in the control run is colder due to a 2% decrease in solar constant. Both are compared to a previous experiment with the same model using a different snow and sea-ice-albedo formulation and the present value of the solar constant. It is found that the globally averaged surface air temperature increase due to a doubling of CO₂ is highly dependent on (1) the type of snow-sea-ice-albedo formulation used such that the parameterization which better facilitates relatively greater ice melt exhibits a greater sensitivity to increased CO₂, and (2) the basic state of the control run such that the colder the basic state, the greater the warming due to increased CO₂.A portion of this study is supported by 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     

A parameterization of radiative fluxes suitable for use in a statistical-dynamical model

Summary A parameterization of shortwave and longwave radiation fluxes derived from detailed radiative transfer models is included in a global primitive equation statistical-dynamical model (SDM) with two bulk atmospheric layers. The model is validated comparing the model simulations with the observed mean annual and seasonal zonally averaged climate. The results show that the simulation of the shortwave and longwave radiation fluxes matches well with the observations. The SDM variables such as surface and 500 hPa temperatures, zonal winds at 250 hPa and 750 hPa, vertical velocity at 500 hPa and precipitation are also in good agreement with the observations. A comparison between the results obtained with the present SDM and those with the previous version of the model indicates that the model results improved when the parameterization of the radiative fluxes based on detailed radiative transfer models are included into the SDM.The SDM is used to investigate its response to the greenhouse effect. Sensitivity experiments regarding the doubling of CO₂ and the changing of the cloud amount and height are performed. In the case 2×CO₂ the model results are consistent with those obtained from GCMs, showing a warming of the climate system. An enhancement of the greenhouse effect is also noted when the cloud layer is higher. However, an increase of the cloud amount in all the latitude belts provokes an increase of the surface temperature near poles and a decrease in all the other regions. This suggests that the greenhouse effect overcomes the albedo effect in the polar latitudes and the opposite occurs in other regions. In all the experiments the changes in the surface temperature are larger near poles, mainly in the Southern Hemisphere.With 8 Figures     

Regional climate changes as simulated in time-slice experiments

Three 30 year long simulations have been performed with a T42 atmosphere model, in which the sea-surface temperature (SST) and sea-ice distribution have been taken from a transient climate change experiment with a T21 global coupled ocean-atmosphere model. In this so-called time-slice experiment, the SST values (and the greenhouse gas concentration) were taken at present time CO₂ level, at the time of CO₂ doubling and tripling.The annual cycle of temperature and precipitation has been studied over the IPCC regions and has been compared with observations. Additionally the combination of temperature and precipitation change has been analysed. Further parameters investigated include the difference between daily minimum and maximum temperature, the rainfall intensity and the length of droughts.While the regional simulation of the annual cycle of the near surface temperature is quite realistic with deviations rarely exceeding 3 K, the precipitation is reproduced to a much smaller degree of accuracy.The changes in temperature at the time of CO₂ doubling amount to only 30–40% of those at the 3 * CO₂ level and show hardly any seasonal variation, contrary to the 3 * CO₂ experiment. The comparatively small response to the CO₂ doubling can be attributed to the cold-start of the simulation, from which the SST has been extracted. The strong change in the seasonality cannot be explained by internal fluctuations and cold start alone, but has to be caused by feedback mechanisms. Due to the delay in warming caused by the transient experiment, from which the SST has been derived, the 3 * CO₂ experiment can be compared to the CO₂ doubling studies performed with mixed-layer models.The precipitation change does not display a clear signal. However, an increase of the rain intensity and of longer dry periods is simulated in many regions of the globe.The changes in these parameters as well as the combination of temperature- and precipitation change and the changes in the daily temperature range give valuable hints, in which regions observational studies should be intensified and under which aspects the observational data should be evaluated.     

Asymmetries in tropical rainfall and circulation patterns in idealised CO2 removal experiments

Atmospheric CO₂ removal is currently receiving serious consideration as a supplement or even alternative to emissions reduction. However the possible consequences of such a strategy for the climate system, and particularly for regional changes to the hydrological cycle, are not well understood. Two idealised general circulation model experiments are described, where CO₂ concentrations are steadily increased, then decreased along the same path. Global mean precipitation continues to increase for several decades after CO₂ begins to decrease. The mean tropical circulation shows associated changes due to the constraint on the global circulation imposed by precipitation and water vapour. The patterns of precipitation and circulation change also exhibit asymmetries with regard to changes in both CO₂ and global mean temperature, but while the lag in global precipitation can be ascribed to different levels of CO₂ at the same temperature state, the regional changes cannot. Instead, ocean memory and heat transfer are important here. In particular the equatorial East Pacific continues to warm relative to the West Pacific during CO₂ ramp-down, producing an anomalously large equatorial Pacific sea surface temperature gradient and associated rainfall anomalies. The mechanism is likely to be a lag in response to atmospheric forcing between mixed-layer water in the east Pacific and the sub-thermocline water below, due to transport through the ocean circulation. The implication of this study is that a CO₂ pathway of increasing then decreasing atmospheric CO₂ concentrations may lead us to climate states during CO₂ decrease that have not been experienced during the increase.     

Why radiative forcing might fail as a predictor of climate change

Radiative forcing has been widely used as a metric of climate change, i.e. as a measure by which various contributors to a net surface temperature change can be quantitatively compared. The extent to which this concept is valid for spatially inhomogeneous perturbations to the climate system is tested. A series of climate model simulations involving ozone changes of different spatial structure reveals that the climate sensitivity parameter is highly variable: for an ozone increase in the northern hemisphere lower stratosphere, it is more than twice as large as for a homogeneous CO₂ perturbation. A global ozone perturbation in the upper troposphere, however, causes a significantly smaller surface temperature response than CO₂. The variability of the climate sensitivity parameter is shown to be mostly due to the varying strength of the stratospheric water vapour feedback. The variability of the sea-ice albedo feedback modifies climate sensitivity of perturbations with the same vertical structure but a different horizontal structure. This feedback is also the origin of the comparatively larger climate sensitivity to perturbations restricted to the northern hemisphere extratropics. As cloud feedback does not operate independently from the other feedbacks, quantifying its effect is rather difficult. However, its effect on the variability of for horizontally and vertically inhomogeneous perturbations within one model framework seems to be comparatively small.This revised version was published online March 2005 with corrections to table 5.     

CLIMATE CHANGE DUE TO GREENHOUSE EFFECTS IN CHINA AS SIMULATED BY A REGIONAL CLIMATE MODEL-PART I:EVALUATION OF THE MODEL SIMULATIONS*

Impacts of greenhouse effects(2×CO₂) on climate change over China as simulated by a regional climate model have been investigated.The model was based on RegCM2 and is nested in one-way mode within a global coupled atmosphere-ocean model(CSIRO R₂₁L₉ AOGCM).Two multi-year simulations,the control run with normal CO₂ concentration and the sensitivity run with doubled CO₂ concentration are conducted. As Part I of the publications,results of control run of the CSIRO,i.e.its simulation of present climate in China,are analyzed briefly.It shows that the model can basically reproduce the surface air temperature and precipitation pattern over China.Therefore,its outputs can be used to drive the regional model. Analysis of control run of RegCM shows that with a high resolution,the model improves the simulations of surface air temperature and precipitation in China as compared to the CSIRO model, especially for the precipitation.The spatial correlation coefficient between simulated and observed annual temperature increased from 0.83 in the CSIRO to 0.92 in the RegCM and for annual precipitation from 0.48 in the CSIRO to 0.65 in the RegCM.A similar improvement in the RegCM compared to the CSIRO was found in all simulated months.The main improvement for surface temperature is that RegCM can simulate the fine scale structure of temperature caused by topography.RegCM greatly improved the spatial distribution of precipitation by eliminating the virtual precipitation center in central China,which was simulated by many other GCMs.The precipitation simulated by RegCM in North and Northwest China is smaller than that by CSIRO, which makes it closer to the observation.     

Climate change impact on snow and soil temperature in boreal Scots pine stands

Scenarios indicate that the air temperature will increase in high latitude regions in coming decades, causing the snow covered period to shorten, the growing season to lengthen and soil temperatures to change during the winter, spring and early summer. To evaluate how a warmer climate is likely to alter the snow cover and soil temperature in Scots pine stands of varying ages in northern Sweden, climate scenarios from the Swedish regional climate modelling programme SWECLIM were used to drive a Soil-Vegetation-Atmosphere Transfer (SVAT)-model (COUP). Using the two CO₂ emission scenarios A and B in the Hadley centres global climate model, HadleyA and HadleyB, SWECLIM predicts that the annual mean air temperature and precipitation will increase at most 4.8°C and 315 mm, respectively, within a century in the study region. The results of this analysis indicate that a warmer climate will shorten the period of persistent snow pack by 73–93 days, increase the average soil temperature by 0.9–1.5°C at 10 cm depth, advance soil warming by 15–19 days in spring and cause more soil freeze–thaw cycles by 31–38%. The results also predict that the large current variations in snow cover due to variations in tree interception and topography will be enhanced in the coming century, resulting in increased spatial variability in soil temperatures.     

Sensitivity to prescribed changes in sea surface temperature and sea ice in doubled carbon dioxide experiments

Time sclice experiments are performed with the atmospheric GCM ARPEGE, developed at Météo-France, to study the impact to increases in the atmospheric carbon dioxide. This spectral model runs at T42 horizontal resolution with 30 vertical layers including a comprehensive tropospheric and stratospheric resolution and a prognostic parameterization of the ozone mixing ratio. The model is forced in a 5-year control run by climatological SSTs and sea-ice extents in order to obtain an accurate simulation of the present-day climate. Two perturbed runs are performed using SSTs and sea-ice extents for doubled CO₂ concentration, obtained from transient runs performed by two coupled atmospheric-oceanic models run at the Max Planck Institute (MPI) in Hamburg and the Hadley Centre (HC). A global surface temperature warming of 1.6 K is obtained with the MPI SST anomalies and 1.9 K with the HC SST anomalies. The precipitation rate increases by 4.2% (and 4.7%). The features obtained in the stratosphere (a cooling increasing with the altitude and an increase in the ozone mixing ratio) are not sensitive to the oceanic forcing. On the contrary, the anomalies in the troposphere such as a warming increasing with altitude, an acceleration of westerly jets and a raised cloud height, depend on the oceanic forcing imposed in the two perturbed runs. Special attention is given to continental areas where the impact of the oceanic forcing is studied over eight regions around the globe. Regions sensitive to oceanic forcing such as Europe are identified in contrast with areas where the patterns are driven by land-surface physical processes, such as over continental Asia. Finally, the Köppen classification is applied to the climate simulated in the three experiments. Both doubled CO₂ runs show the same predominance of global warming over precipitation changes in the Kbppen analyses.     

Climate feedback efficiency and synergy

Earth’s climate sensitivity to radiative forcing induced by a doubling of the atmospheric CO₂ is determined by feedback mechanisms, including changes in atmospheric water vapor, clouds and surface albedo, that act to either amplify or dampen the response. The climate system is frequently interpreted in terms of a simple energy balance model, in which it is assumed that individual feedback mechanisms are additive and act independently. Here we test these assumptions by systematically controlling, or locking, the radiative feedbacks in a state-of-the-art climate model. The method is shown to yield a near-perfect decomposition of change into partial temperature contributions pertaining to forcing and each of the feedbacks. In the studied model water vapor feedback stands for about half the temperature change, CO₂-forcing about one third, while cloud and surface albedo feedback contributions are relatively small. We find a close correspondence between forcing, feedback and partial surface temperature response for the water vapor and surface albedo feedbacks, while the cloud feedback is inefficient in inducing surface temperature change. Analysis suggests that cloud-induced warming in the upper tropical troposphere, consistent with rising convective cloud anvils in a warming climate enhances the negative lapse-rate feedback, thereby offsetting some of the warming that would otherwise be attributable to this positive cloud feedback. By subsequently combining feedback mechanisms we find a positive synergy acting between the water vapor feedback and the cloud feedback; that is, the combined cloud and water vapor feedback is greater than the sum of its parts. Negative synergies surround the surface albedo feedback, as associated cloud and water vapor changes dampen the anticipated climate change induced by retreating snow and ice. Our results highlight the importance of treating the coupling between clouds, water vapor and temperature in a deepening troposphere.     

Projections of Climate Change Effects on Water Temperature Characteristics of Small Lakes in the Contiguous U.S.

To simulate effects of projected climate change on water temperature characteristics of small lakes in the contiguous U.S., a deterministic, one-dimensional year-round water temperature model is applied. In cold regions the model simulates ice and snow cover on a lake. The lake parameters required as model input are surface area, maximum depth, and Secchi depth as a measure of radiation attenuation and trophic state. The model is driven by daily weather data. Weather records from 209 stations in the contiguous U.S. for the period 1961–1979 were used to represent present climate conditions. The projected climate change owing to a doubling of atmospheric CO₂ was obtained from the output of the Canadian Climate Center General Circulation Model. The simulated water temperature and ice characteristics are related to the geometric and trophic state lake characteristics and to geographic location. By interpolation, the sensitivity of lake water temperature characteristics to latitude, longitude, lake geometry and trophic status can therefore be quantified for small lakes in the contiguous U.S. The 2× CO₂ climate scenario is projected to increase maximum and minimum lake surface temperatures by up to 5.2°C. (Maximum surface water temperatures in lakes near the northern and the southern border of the contiguous U.S. currently differ by up to 13°C.) Maximum temperature differences between lake surface and lake bottom are projected to increase in average by only 1 to 2°C after climate warming. The duration of seasonal summer stratification is projected to be up to 66 days longer under a 2×CO₂ climate scenario. Water temperatures of less than 8°C are projected to occur on lake bottoms during a period which is on the order of 50 days shorter under a 2×CO₂ climate scenario. With water temperature change projected to be as high as 5.2°C, ecological impacts such as shifts in species distributions and in fish habitat are most likely. Ice covers on lakes of northern regions would also be changed strongly.