On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles

Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO₂ doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%.     

Radiative forcing and response of a GCM to ice age boundary conditions: cloud feedback and climate sensitivity

 A general circulation model is used to examine the effects of reduced atmospheric CO₂, insolation changes and an updated reconstruction of the continental ice sheets at the Last Glacial Maximum (LGM). A set of experiments is performed to estimate the radiative forcing from each of the boundary conditions. These calculations are used to estimate a total radiative forcing for the climate of the LGM. The response of the general circulation model to the forcing from each of the changed boundary conditions is then investigated. About two-thirds of the simulated glacial cooling is due to the presence of the continental ice sheets. The effect of the cloud feedback is substantially modified where there are large changes to surface albedo. Finally, the climate sensitivity is estimated based on the global mean LGM radiative forcing and temperature response, and is compared to the climate sensitivity calculated from equilibrium experiments with atmospheric CO₂ doubled from present day concentration. The calculations here using the model and palaeodata support a climate sensitivity of about 1 Wm^-2 K^-1 which is within the conventional range. Received: 8 February 1997 / Accepted: 4 June 1997     

GCM simulations of the Last Glacial Maximum surface climate of Greenland and Antarctica

 The LMDz variable grid GCM was used to simulate the Last Glacial Maximum (LGM, 21 ky Bp.) climate of Greenland and Antarctica at a spatial resolution of about 100 km.The high spatial resolution allows to investigate the spatial variability of surface climate change signals, and thus to address the question whether the sparse ice core data can be viewed as representative for the regional scale climate change. This study addresses primarily surface climate parameters because these can be checked against the, limited, ice core record. The changes are generally stronger for Greenland than for Antarctica, as the imposed changes of the forcing boundary conditions (e.g., sea surface temperatures) are more important in the vicinity of Greenland. Over Greenland, and to a limited extent also in Antarctica, the climate shows stronger changes in winter than in summer. The model suggests that the linear relationship between the surface temperature and inversion strength is modified during the LGM. The temperature dependency of the moisture holding capacity of the atmosphere alone cannot explain the strong reduction in snowfall over central Greenland; atmospheric circulation changes also play a crucial role. Changes in the high frequency variability of snowfall, atmospheric pressure and temperature are investigated and possible consequences for the interpretation of ice core records are discussed. Using an objective cyclone tracking scheme, the importance of changes of the atmospheric dynamics off the coasts of the ice sheets, especially for the high frequency variability of surface climate parameters, is illustrated. The importance of the choice of the LGM ice sheet topography is illustrated for Greenland, where two different topographies have been used, yielding results that differ quite strongly in certain nontrivial respects. This means that the paleo-topography is a significant source of uncertainty for the modelled paleoclimate. The sensitivity of the Greenland LGM climate to the prescribed sea surface conditions is examined by using two different LGM North Atlantic data sets. Received: 23 October 1997 / Accepted: 17 March 1998     

Climate sensitivity and cloud feedback processes imposed by two different external forcings in an aquaplanet GCM

The sensitivity of climate to an increase in sea surface temperature (SST) and CO₂, as well as cloud feedback processes, is analyzed through a series of aquaplanet experiments listed in the Coupled Model Intercomparison Project. Rainfall is strengthened in a +4K anomaly SST experiment due to the enhanced surface evaporation; while in a quadruple CO₂ experiment, precipitation and total cloud cover are appreciably weakened. In both the +4K and quadruple CO₂ (4xCO₂) experiments, the Hadley cell is impaired, with an increase in moderate subsidence and a decrease in the frequency of strong convective activity. Regarding cloud radiation forcing (CRF), the analysis technique of Bony et al. (Climate Dynamics, 22:71–86, 2004) is used to sort cloud variables by dynamic regimes using the 500-hPa vertical velocity in tropical areas (30°S–30°N). Results show that the tropically averaged CRF change is negative and is dominated mainly by the thermodynamic component. Within convective regimes, the behavior of longwave CRF is different in the +4K and 4xCO₂ experiments, with positive and negative changes, respectively. The globally averaged CRF also reveals a negative change in both aquaplanet and Earthlike experiments, implying that clouds may play a role in decelerating global warming. The calculated climate sensitivity demonstrates that our results are close to those obtained from other models, with 0.384 and 0.584?Km²?W^?1 for aquaplanet and Earthlike experiments, respectively.     

The impact of new land surface physics on the GCM simulation of climate and climate sensitivity

 Recent improvements to the Hadley Centre climate model include the introduction of a new land surface scheme called “MOSES” (Met Office Surface Exchange Scheme). MOSES is built on the previous scheme, but incorporates in addition an interactive plant photosynthesis and conductance module, and a new soil thermodynamics scheme which simulates the freezing and melting of soil water, and takes account of the dependence of soil thermal characteristics on the frozen and unfrozen components. The impact of these new features is demonstrated by comparing 1×CO₂ and 2×CO₂ climate simulations carried out using the old (UKMO) and new (MOSES) land surface schemes. MOSES is found to improve the simulation of current climate. Soil water freezing tends to warm the high-latitude land in the northern Hemisphere during autumn and winter, whilst the increased soil water availability in MOSES alleviates a spurious summer drying in the mid-latitudes. The interactive canopy conductance responds directly to CO₂, supressing transpiration as the concentration increases and producing a significant enhancement of the warming due to the radiative effects of CO₂ alone. Received: 16 March 1998 / Accepted: 4 August 1998     

Origins of differences in climate sensitivity, forcing and feedback in climate models

We diagnose climate feedback parameters and CO₂ forcing including rapid adjustment in twelve atmosphere/mixed-layer-ocean (“slab”) climate models from the CMIP3/CFMIP-1 project (the AR4 ensemble) and fifteen parameter-perturbed versions of the HadSM3 slab model (the PPE). In both ensembles, differences in climate feedbacks can account for approximately twice as much of the range in climate sensitivity as differences in CO₂ forcing. In the AR4 ensemble, cloud effects can explain the full range of climate sensitivities, and cloud feedback components contribute four times as much as cloud components of CO₂ forcing to the range. Non-cloud feedbacks are required to fully account for the high sensitivities of some models however. The largest contribution to the high sensitivity of HadGEM1 is from a high latitude clear-sky shortwave feedback, and clear-sky longwave feedbacks contribute substantially to the highest sensitivity members of the PPE. Differences in low latitude ocean regions (30°N/S) contribute more to the range than those in mid-latitude oceans (30–55°N/S), low/mid latitude land (55°N/S) or high latitude ocean/land (55–90°N/S), but contributions from these other regions are required to account fully for the higher model sensitivities, for example from land areas in IPSL CM4. Net cloud feedback components over the low latitude oceans sorted into percentile ranges of lower tropospheric stability (LTS) show largest differences among models in stable regions, mainly due to their shortwave components, most of which are positive in spite of increasing LTS. Differences in the mid-stability range are smaller, but cover a larger area, contributing a comparable amount to the range in climate sensitivity. These are strongly anti-correlated with changes in subsidence. Cloud components of CO₂ forcing also show the largest differences in stable regions, and are strongly anticorrelated with changes in estimated inversion strength (EIS). This is qualitatively consistent with what would be expected from observed relationships between EIS and low-level cloud fraction. We identify a number of cases where individual models show unusually strong forcings and feedbacks compared to other members of the ensemble. We encourage modelling groups to investigate unusual model behaviours further with sensitivity experiments. Most of the models fail to correctly reproduce the observed relationships between stability and cloud radiative effect in the subtropics, indicating that there remains considerable room for model improvements in the future.     

Objective comparison of patterns of CO2 induced climate change in coupled GCM experiments

 Four transient GCM experiments simulating the climatic response to gradually increasing CO₂, and two equilibrium doubled CO₂ experiments are compared. The zonally symmetric and asymmetric features of climate are both examined. Surface air temperature, sea level pressure, the 500 mb height and the relative topography between 500 and 1000 mb are analyzed. In the control simulations, the broad aspects of the present climate are in most cases well reproduced, although the stationary eddies tend to be less reliably simulated than the zonal means. However, the agreement between the four transient experiments on the geographical patterns of climate change is less impressive. While some zonally symmetric features, in particular the meridional distribution of surface air warming in the boreal winter, are rather similar in all models, the intermodel cross correlations for the zonally asymmetric changes are low. The agreement is largely restricted to some very general features such as more warming over the continents than over the oceans. The largest discrepancies between the two equilibrium-doubled CO₂ experiments and the transient experiments are found at the high southern latitudes, in particular in the austral winter. To identify the most robust geographical patterns of change in the transient experiments, the standard t test is used to determine if the four-model mean change is significantly above or below the global mean. Received: 18 January 1996 / Accepted: 5 July 1996     

Climate sensitivity estimated from ensemble simulations of glacial climate

The concentration of greenhouse gases (GHGs) in the atmosphere continues to rise, hence estimating the climate system’s sensitivity to changes in GHG concentration is of vital importance. Uncertainty in climate sensitivity is a main source of uncertainty in projections of future climate change. Here we present a new approach for constraining this key uncertainty by combining ensemble simulations of the last glacial maximum (LGM) with paleo-data. For this purpose we used a climate model of intermediate complexity to perform a large set of equilibrium runs for (1) pre-industrial boundary conditions, (2) doubled CO₂ concentrations, and (3) a complete set of glacial forcings (including dust and vegetation changes). Using proxy-data from the LGM at low and high latitudes we constrain the set of realistic model versions and thus climate sensitivity. We show that irrespective of uncertainties in model parameters and feedback strengths, in our model a close link exists between the simulated warming due to a doubling of CO₂, and the cooling obtained for the LGM. Our results agree with recent studies that annual mean data-constraints from present day climate prove to not rule out climate sensitivities above the widely assumed sensitivity range of 1.5–4.5°C (Houghton et al. 2001). Based on our inferred close relationship between past and future temperature evolution, our study suggests that paleo-climatic data can help to reduce uncertainty in future climate projections. Our inferred uncertainty range for climate sensitivity, constrained by paleo-data, is 1.2–4.3°C and thus almost identical to the IPCC estimate. When additionally accounting for potential structural uncertainties inferred from other models the upper limit increases by about 1°C.     

Interannual variability and predictability in an ensemble of AMIP climate simulations conducted with the CCC GCM2

This study considers an ensemble of six 10-year climate simulations conducted with the Canadian Climate Centre 2nd generation General Circulation Model (CCC GCM2). Each simulation was forced according to the Atmospheric Model Intercomparison Project (AMIP) experimental protocol using monthly mean sea surface temperatures and sea-ice extents based on observations for January, 1979 to December 1988. One simulation, conducted on a CRAY computer, was initiated from analysed 1 January 1979 conditions while the remaining 5 simulations, conducted on a NEC computer, were initiated from previously simulated model states obtained from a long control integration. The interannual variability and potential predictability of simulated and observed 500 hPa geopotential, 850 hPa temperature and 300 hPa stream function are examined and inter-compared using statistical analysis of variance techniques to partition variance into a number of components. The boundary conditions specified by AMIP are found to induce statistically significant amounts of predictable variance on the interannual time scale in the tropics and, to a lesser extent, at extratropical latitudes. In addition, local interactions between the atmosphere and the land surface apparently induce significant amounts of potentially predictable interannual variance in the tropical lower atmosphere and also at some locations in the temperate lower atmosphere. No evidence was found that the atmosphere's internal dynamics on their own generate potentially predictable variations on the interannual time scale. The sensitivity of the statistical methods used is demonstrated by the fact that we are able to detect differences between the climates simulated on the two computers used. The causes of these physically insignificant changes are traced. The statistical procedures are checked by confirming that the choice of initial conditions does not lead to significant inter-simulation variation. The simulations are also interpreted as an ensemble of climate forecasts that rely only on the specified boundary conditions for their predictive skill. The forecasts are verified against observations and against themselves. In agreement with other studies it was found that the forecasts have very high skill in the tropics and moderate skill in the extratropics. Received: 18 December 1995 / Accepted: 4 April 1996     

Empirical Estimates of Global Climate Sensitivity： An Assessment of Strategies Using a Coupled GCM

A control integration with the normal solar constant and one with it increased by 2.5% in the National Center for Atmospheric Research （NCAR） coupled atmosphere-ocean Climate System Model were conducted to see how well the actual realized global warming could be predicted just by analysis of the control results. This is a test, within a model context, of proposals that have been advanced to use knowledge of the present day climate to make ＂empirical＂ estimates of global climate sensitivity. The scaling of the top-of-the-atmosphere infrared flux and the planetary albedo as functions of surface temperature was inferred by examining four different temporal and geographical variations of the control simulations. Each of these inferences greatly overestimates the climate sensitivity of the model, largely because of the behavior of the cloud albedo. In each inference the control results suggest that cloudiness and albedo decrease with increasing surface temperature. However, the experiment with the increased solar constant actually has higher albedo and more cloudiness at most latitudes. The increased albedo is a strong negative feedback, and this helps account for the rather weak sensitivity of the climate in the NCAR model. To the extent that these model results apply to the real world, they suggest empirical evaluation of the scaling of global-mean radiative properties with surface temperature in the present day climate provides little useful guidance for estimates of the actual climate sensitivity to global changes.     

Circulation patterns, daily precipitation in Portugal and implications for climate change simulated by the second Hadley Centre GCM

Based on principal component analysis (PCA) and a k-means clustering algorithm, daily mean sea level pressure (MSLP) fields over the northeastern Atlantic and Western Europe, simulated by the Hadley Centre's second generation coupled ocean-atmosphere GCM (HADCM2) control run (HADCM2CON), are validated by comparison with the observed daily MSLP fields. It is clear that HADCM2 reproduces daily MSLP fields and its seasonal variability over the region very well, despite suffering from some deficiencies, such as the systematic displacement of the atmospheric centres of action. Four daily circulation patterns, previously identified from the observed daily MSLP fields over the area and well related to daily precipitation in Portugal, were also well classified from the daily MSLP fields simulated by HADCM2. The model can also simulate rather successfully the relationships between the four daily circulation patterns and daily precipitation in southern Portugal. However, compared with observations, daily precipitation intensities simulated by the model are too weak in southern Portugal. Nevertheless, HADCM2 represents a considerable improvement relative to the UKTR experiment. The results described here imply that it is doubtful whether regional precipitation scenarios provided by HADCM2 can be directly applied in impact studies and that a downscaling technique, based on daily circulation patterns, might be successful in reproducing local and regional precipitation characteristics. Moreover, the four circulation patterns can also be clearly identified in the two perturbed experiments, one under greenhouse gases forcing only (HADCM2GHG) and the other under additional forcing of sulphate aerosol (HADCM2SUL), although changes in the frequencies of occurrence of certain circulation patterns are found. Nevertheless, the observed links between regional precipitation in southern Portugal and large-scale atmospheric circulation seem likely to hold in the model's perturbed climate. It is therefore credible to use those links to downscale large-scale atmospheric circulation from GCM simulations to obtain future precipitation scenarios in southern Portugal. Received: 21 August 1998 / Accepted: 28 May 1999     

Regional climate change patterns identified by cluster analysis

Climate change caused by anthropogenic greenhouse emissions leads to impacts on a global and a regional scale. A quantitative picture of the projected changes on a regional scale can help to decide on appropriate mitigation and adaptation measures. In the past, regional climate change results have often been presented on rectangular areas. But climate is not bound to a rectangular shape and each climate variable shows a distinct pattern of change. Therefore, the regions over which the simulated climate change results are aggregated should be based on the variable(s) of interest, on current mean climate as well as on the projected future changes. A cluster analysis algorithm is used here to define regions encompassing a similar mean climate and similar projected changes. The number and the size of the regions depend on the variable(s) of interest, the local climate pattern and on the uncertainty introduced by model disagreement. The new regions defined by the cluster analysis algorithm include information about regional climatic features which can be of a rather small scale. Comparing the regions used so far for large scale regional climate change studies and the new regions it can be shown that the spacial uncertainty of the projected changes of different climate variables is reduced significantly, i.e. both the mean climate and the expected changes are more consistent within one region and therefore more representative for local impacts.     

Statistical analysis of tropical climate anomaly simulations

The statistical analysis of two atmospheric general circulation simulations using the ECHAM3 GCM in permanent January conditions are presented. The two simulations utilize different oceanic surface temperatures in the Atlantic as boundary conditions: the cold simulation has SST representing the anomalous cold conditions during the decade 1904-13 while the warm simulation has SST representative for the decade 1951-60 where anomalous warm conditions have been observed. The analysis concentrates on the simulated differences between both experiments within the tropical belt to test the working hypothesis whether changes in the deep tropical heating initiated by the anomalous SST are responsible for the anomalies in the flow and mass field. We present a method which extracts the significant and dynamically consistent signal of the total difference using a multivariate statistical test based on the amplitudes of an a-priori specified mode expansion. These expansion modes are defined from a variant of the Matsuno-Gill linearized reduced gravity model for the tropical atmosphere. The application of the method shows a clear and well defined tropical signal in the flow and mass field which can be understood as the reponse of the ECHAM3 model to a deep heating anomaly not in the vicinity of the anomalous SST but on the neighboring continents especially South America and with opposite sign in remote areas between Indonesia and the dateline. The signal can be summarized as an enhancement of the GCM's tropical East-West circulation with the ascending branch over South America in the warm simulation compared to the cold run.     

Teleconnection Paterns in the Northern Hemisphere Simulated by IAP GCM

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Skill and reproducibility of seasonal rainfall patterns in the tropics in ECHAM-4 GCM simulations with prescribed SST

 The ECHAM4 atmospheric general circulation model (GCM) has been integrated at T30 resolution through the period 1960–1994 forced with the observed sea-surface temperatures (SSTs) as compiled at the Hadley Centre (GISST2.2). Three experiments were made starting from different initial conditions. The large-scale tropical precipitation patterns simulated by the model have been studied, focusing on the skill (i.e. the capability to simulate the observed anomaly over land areas) and reproducibility (i.e. the GCM’s interannual rainfall variance that is independent from the initial conditions). Analysis of variance is used to estimate the reproducibility amongst ensemble members at each grid-box, but most emphasis is placed on large-scale patterns, as revealed by various singular value decomposition analyses (SVDAs), between observed and model fields (OM analyses) and amongst the different model runs (MM analyses). Generally, it is found that the first model mode in the MM analysis is very similar to that in the OM analysis, suggesting the model mode with strongest reproducibility is also the mode which tallies best with observations. For the global tropics, the first MM mode is highly reproducible (external variance above 90%) and the first OM couplet is very skillful (correlation between observed and model SVDA time series is over 0.84). The extent to which skill and reproducibility is related to El Nino/Southern Oscillation (ENSO) has been investigated by comparing the OM and MM time series with the Southern Oscillation Index (SOI). For the global tropics, most of the OM and MM variance is common with the SOI, though in boreal summer, the first modes do also have some clear independence from the SOI. The analyses were repeated at the regional scale for Oceania, tropical America, tropical Africa and tropical Southeast Asia. A highly reproducible mode is found in all cases except October-December in Africa. Skill, while always positive, is more variable, strongest for Oceania and tropical America and weakest for Africa. Comparisons with the SOI suggest skill in tropical America and tropical Africa has substantial components that are independent of the SOI, especially in boreal spring and summer when the tropical Atlantic SSTs are strongly related to the leading OM and MM time series. Received: 1 January 1997 / Accepted: 28 July 1997     

The sensitivity of climate simulations to the specification of mixed phase clouds

In the prognostic stratiform cloud scheme used in the UK Meteorological Office Unified Model, mixed phase clouds are assumed to exist between 0 and –15 °C. Recent observations of such clouds, carried out using the C-130 aircraft of the Meteorological Research Flight, suggest that a smaller range of 0 to –9°C may be more appropriate. The sensitivity of cloud and radiation fields as simulated by a 5 × 7.5° latitude-longitude version of the Unified Model to such a reduction in the temperature range of mixed phase clouds is considered. Using a smaller temperature range systematic errors in the radiation budget of the model are reduced in mid-latitudes, bringing the model into closer agreement with ERBE data. The sensitivity of model albedo to an increase in the temperature range over which mixed phase clouds are assumed to exist, suggested by previous observational studies, is also considered together with the impact of removing the mixed phase part of the precipitation parametrization altogether.     

CO2 climate sensitivity and snow-sea-ice albedo parameterization in an atmospheric GCM coupled to a mixed-layer ocean model

The snow-sea-ice albedo parameterization in an atmospheric general circulation model (GCM), coupled to a simple mixed-layer ocean and run with an annual cycle of solar forcing, is altered from a version of the same model described by Washington and Meehl (1984). The model with the revised formulation is run to equilibrium for 1 × CO₂ and 2 × CO₂ experiments. The 1 ×CO₂ (control) simulation produces a global mean climate about 1° warmer than the original version, and sea-ice extent is reduced. The model with the altered parameterization displays heightened sensitivity in the global means, but the geographical patterns of climate change due to increased carbon dioxide (CO₂) are qualitatively similar. The magnitude of the climate change is affected, not only in areas directly influenced by snow and ice changes but also in other regions of the globe, including the tropics where sea-surface temperature, evaporation, and precipitation over the oceans are greater. With the less-sensitive formulation, the global mean surface air temperature increase is 3.5 °C, and the increase of global mean precipitation is 7.12%. The revised formulation produces a globally averaged surface air temperature increase of 4.04 °C and a precipitation increase of 7.25%, as well as greater warming of the upper tropical troposphere. Sensitivity of surface hydrology is qualitatively similar between the two cases with the larger-magnitude changes in the revised snow and ice-albedo scheme experiment. Variability of surface air temperature in the model is comparable to observations in most areas except at high latitudes during winter. In those regions, temporal variation of the sea-ice margin and fluctuations of snow cover dependent on the snow-ice-albedo formulation contribute to larger-than-observed temperature variability. This study highlights an uncertainty associated with results from current climate GCMs that use highly parameterized snow-sea-ice albedo schemes with simple mixed-layer ocean models.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

On the linear response of tropical African climate to SST changes deduced from regional climate model simulations

Summary Previous studies have highlighted the crucial role of sea surface temperature (SST) anomalies in the tropical Atlantic region in forcing the summer monsoon rainfall over subsaharan West Africa. Understanding the physical processes, relating SST variations to changes in the amount and distribution of African rainfall, is a key factor in improving weather and climate forecasts in this highly vulnerable region. Here, we present sensitivity experiments from a regional climate model with prescribed warmer tropical SSTs, according to enhanced greenhouse conditions at the end of the 21st century. This dynamical downscaling approach provides information about the nonlinear response of the atmosphere to oceanic heating. It has been suggested that the response is at least partly accounted for by the linear theory of tropical dynamics, involving a Kelvin and Rossby wave response to a tropical heat source. We compute the major modes of the linear Matsuno-Gill model for geopotential height and horizontal wind components and project the simulated response patterns onto these linear modes, in order to evaluate to which extent the simple linear theory may explain the SST-induced climate anomalies over Africa. A multivariate Hotelling T² test is used to evaluate whether these anomalies are statistically significant. Forcing the regional climate model by warmer SSTs leads to substantial climate anomalies over tropical Africa: Rainfall is increases over the Guinea Coast region (GCR) and tropical East Africa, but decreases over the Congo Basin and the Sahel Zone (SHZ). At the 850 hPa level, a trough develops over southern West Africa and the Gulf of Guinea, and is associated with stronger surface wind convergence over the GCR. These changes in the atmospheric dynamics strongly project onto the leading modes of the linear Matsuno-Gill model at various zonal wave numbers. The corresponding atmospheric heating pattern is highly reminiscent of the simulated nonlinear model reponse. The T² test statistics reveal that the SST forcing induces a statistically significant climate anomaly over tropical Africa if the climate state vector is reduced by projecting the simulated data onto the leading 10 linear modes. It is also shown that the linear response prevails in a long-term simulation with more realistic lower and lateral boundary conditions. Thus, linear tropical dynamics are assumed to be a major physical process on the ground of the prominent SST-African rainfall relationship.     

Non-linear climate feedback analysis in an atmospheric general circulation model

 A method is described for evaluating the ‘partial derivatives’ of globally averaged top-of-atmosphere (TOA) radiation changes with respect to basic climate model physical parameters. This method is used to analyse feedbacks in the Australian Bureau of Meteorology Research Centre general circulation model. The parameters considered are surface temperature, water vapour, lapse rate and cloud cover. The climate forcing which produces the changes is a globally uniform sea surface temperature (SST) perturbation. The first and second order differentials of model parameters with respect to the forcing (i.e. SST changes) are estimated from quadratic least square fitting. Except for total cloud cover, variables are found to be strong functions of global SST. Strongly non-linear variations of lapse rate and high cloud amount and height appear to relate to the non-linear response in penetrative convection. Globally averaged TOA radiation differentials with respect to model parameters are also evaluated. With the exception of total cloud contributions, a high correlation is generally found to exist, on the global mean level, between TOA radiation and the respective parameter perturbations. The largest non-linear terms contributing to radiative changes are those due to lapse rate and high cloud. The contributions of linear and non-linear terms to the overall radiative response from a 4 K SST perturbation are assessed. Significant non-linear responses are found to be associated with lapse rate, water vapour and cloud changes. Although the exact magnitude of these responses is likely to be a function of the particular model as well as the imposed SST perturbation pattern, the present experiments flag these as processes which cannot properly be understood from linear theory in the evaluation of climate change sensitivity. Received: 16 January 1997/Accepted: 9 May 1997