Numerical Simulation of Global Temperature Change during the 20th Century with the IAP／LASG GOALS Model

The IAP/LASG GOALS coupled model is used to simulate the climate change during the 20th century using historical greenhouse gases concentrations, the mass mixing ratio of sulfate aerosols simulated by a CTM model, and reconstruction of solar variability spanning the period 1900 to 1997. Four simulations, including a control simulation and three forcing simulations, are conducted. Comparison with the observational record for the period indicates that the three forcing experiments simulate reasonable temporal and spatial distributions of the temperature change. The global warming during the 20th century is caused mainly by increasing greenhouse gas concentration especially since the late 1980s; sulfate aerosols offset a portion of the global warming and the reduction of global temperature is up to about 0.11℃ over the century; additionally, the effect of solar variability is not negligible in the simulation of climate change over the 20th century.     

A transient climate change simulation with greenhouse gas and aerosol forcing: experimental design and comparison with the instrumental record for the twentieth century

 The Canadian Centre for Climate Modelling and Analysis (CCCma) global coupled model is used to investigate the potential climate effects of increasing greenhouse gas (GHG) concentrations and changes in sulfate aerosol loadings. The forcing scenario adopted closely resembles that of Mitchell et al. for both the greenhouse gas and aerosol components. Its implementation in the model and the resulting changes in forcing are described. Five simulations of 200 years in length, nominally for the years 1900 to 2100, are available for analysis. They consist of a control simulation without change in forcing, three independent simulations with the same greenhouse gas and aerosol changes, and a single simulation with greenhouse gas only forcing. Simulations of the evolution of temperature and precipitation from 1900 to the present are compared with available observations. Temperature and precipitation are primary climate variables with reasonable temporal and spatial coverage in the observational record for the period. The simulation of potential climate change from the present to the end of the twenty-first century, based on projected GHG and aerosol forcing changes, is discussed in a companion paper. For the historical period dealt with here, the GHG and aerosol forcing has changed relatively little compared to the forcing changes projected to the end of the twenty-first century. Nevertheless, the forced climate signal for temperature in the model is reasonably consistent with the observed global mean temperature from the instrumental record. This is true also for the trend in zonally averaged temperature as a function of latitude and for some aspects of the geographical and regional distributions of temperature. Despite the modest change in overall forcing, the difference between GHG+aerosol and GHG-only forcing is discernible in the temperature response for this period. Changes in precipitation, on the other hand, are much less evident in both the instrumental and simulated record. There is an apparent increasing trend in average precipitation in both the observations and the model results over that part of the land for which observations are available. Regional and geographical changes and trends (which are less affected by sampling considerations), if they exist, are masked by the large natural variability of precipitation in both model and observations. Received: 24 September 1998 / Accepted: 8 October 1999     

European temperature records of the past five centuries based on documentary/instrumental information compared to climate simulations

Two European temperature reconstructions for the past half-millennium, January-to-April air temperature for Stockholm (Sweden) and seasonal temperature for a Central European region, both derived from the analysis of documentary sources and long instrumental records, are compared with the output of climate simulations with the model ECHO-G. The analysis is complemented by comparisons with the long (early)-instrumental record of Central England Temperature (CET). Both approaches to study past climates (simulations and reconstructions) are burdened with uncertainties. The main objective of this comparative analysis is to identify robust features and weaknesses in each method which may help to improve models and reconstruction methods. The results indicate a general agreement between simulations obtained with temporally changing external forcings and the reconstructed Stockholm and CET records for the multi-centennial temperature trend over the recent centuries, which is not reproduced in a control simulation. This trend is likely due to the long-term change in external forcing. Additionally, the Stockholm reconstruction and the CET record also show a clear multi-decadal warm episode peaking around AD 1730, which is absent in the simulations. Neither the reconstruction uncertainties nor the model internal climate variability can easily explain this difference. Regarding the interannual variability, the Stockholm series displays, in some periods, higher amplitudes than the simulations but these differences are within the statistical uncertainty and further decrease if output from a regional model driven by the global model is used. The long-term trend of the CET series agrees less well with the simulations. The reconstructed temperature displays, for all seasons, a smaller difference between the present climate and past centuries than is seen in the simulations. Possible reasons for these differences may be related to a limitation of the traditional ‘indexing’ technique for converting documentary evidence to temperature values to capture long-term climate changes, because the documents often reflect temperatures relative to the contemporary authors’ own perception of what constituted ‘normal’ conditions. By contrast, the amplitude of the simulated and reconstructed inter-annual variability agrees rather well.     

Multi-fingerprint detection and attribution analysis of greenhouse gas, greenhouse gas-plus-aerosol and solar forced climate change

 A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single fingerprint is optimal for the detection of climate change, further tests of the statistical consistency of the detected climate change signal with model predictions for different candidate forcing mechanisms require the simultaneous application of several fingerprints. Model-predicted climate change signals are derived from three anthropogenic global warming simulations for the period 1880 to 2049 and two simulations forced by estimated changes in solar radiation from 1700 to 1992. In the first global warming simulation, the forcing is by greenhouse gas only, while in the remaining two simulations the direct influence of sulfate aerosols is also included. From the climate change signals of the greenhouse gas only and the average of the two greenhouse gas-plus-aerosol simulations, two optimized fingerprint patterns are derived by weighting the model-predicted climate change patterns towards low-noise directions. The optimized fingerprint patterns are then applied as a filter to the observed near-surface temperature trend patterns, yielding several detection variables. The space-time structure of natural climate variability needed to determine the optimal fingerprint pattern and the resultant signal-to-noise ratio of the detection variable is estimated from several multi-century control simulations with different CGCMs and from instrumental data over the last 136 y. Applying the combined greenhouse gas-plus-aerosol fingerprint in the same way as the greenhouse gas only fingerprint in a previous work, the recent 30-y trends (1966–1995) of annual mean near surface temperature are again found to represent a significant climate change at the 97.5% confidence level. However, using both the greenhouse gas and the combined forcing fingerprints in a two-pattern analysis, a substantially better agreement between observations and the climate model prediction is found for the combined forcing simulation. Anticipating that the influence of the aerosol forcing is strongest for longer term temperature trends in summer, application of the detection and attribution test to the latest observed 50-y trend pattern of summer temperature yielded statistical consistency with the greenhouse gas-plus-aerosol simulation with respect to both the pattern and amplitude of the signal. In contrast, the observations are inconsistent with the greenhouse-gas only climate change signal at a 95% confidence level for all estimates of climate variability. The observed trend 1943–1992 is furthermore inconsistent with a hypothesized solar radiation change alone at an estimated 90% confidence level. Thus, in contrast to the single pattern analysis, the two pattern analysis is able to discriminate between different forcing hypotheses in the observed climate change signal. The results are subject to uncertainties associated with the forcing history, which is poorly known for the solar and aerosol forcing, the possible omission of other important forcings, and inevitable model errors in the computation of the response to the forcing. Further uncertainties in the estimated significance levels arise from the use of model internal variability simulations and relatively short instrumental observations (after subtraction of an estimated greenhouse gas signal) to estimate the natural climate variability. The resulting confidence limits accordingly vary for different estimates using different variability data. Despite these uncertainties, however, we consider our results sufficiently robust to have some confidence in our finding that the observed climate change is consistent with a combined greenhouse gas and aerosol forcing, but inconsistent with greenhouse gas or solar forcing alone. Received: 28 April 1996 / Accepted: 27 January 1997     

The absence of memory in the climatic forcing of glaciers

Glaciers respond to both long-term, persistent climate changes as well as the year-to-year variability that is inherent to a constant climate. Distinguishing between these two causes of length change is important for identifying the true climatic cause of past glacier fluctuations. A key step in addressing this is to determine the relative importance of year-to-year variability in climate relative to more persistent climate fluctuations. We address this question for European climate using several long-term observational records: a century-long, Europe-wide atmospheric gridded dataset; longer-term instrumental measurements of summertime temperature where available (up to 250 years); and seasonal and annual records of glacier mass balance (between 30 and 50 years). After linear detrending of the datasets, we find that throughout Europe persistence in both melt-season temperature and annual accumulation is generally indistinguishable from zero. The main exception is in Southern Europe where a degree of interannual persistence can be identified in summertime temperatures. On the basis of this analysis, we conclude that year-to-year variability dominates the natural climate forcing of glacier fluctuations on timescales up to a few centuries.     

A European pattern climatology 1766–2000

Using monthly independently reconstructed gridded European fields for the 500 hPa geopotential height, temperature, and precipitation covering the last 235 years we investigate the temporal and spatial evolution of these key climate variables and assess the leading combined patterns of climate variability. Seasonal European temperatures show a positive trend mainly over the last 40 years with absolute highest values since 1766. Precipitation indicates no clear trend. Spatial correlation technique reveals that winter, spring, and autumn covariability between European temperature and precipitation is mainly influenced by advective processes, whereas during summer convection plays the dominant role. Empirical Orthogonal Function analysis is applied to the combined fields of pressure, temperature, and precipitation. The dominant patterns of climate variability for winter, spring, and autumn resemble the North Atlantic Oscillation and show a distinct positive trend during the past 40 years for winter and spring. A positive trend is also detected for summer pattern 2, which reflects an increased influence of the Azores High towards central Europe and the Mediterranean coinciding with warm and dry conditions. The question to which extent these recent trends in European climate patterns can be explained by internal variability or are a result of radiative forcing is answered using cross wavelets on an annual basis. Natural radiative forcing (solar and volcanic) has no imprint on annual European climate patterns. Connections to CO₂ forcing are only detected at the margins of the wavelets where edge effects are apparent and hence one has to be cautious in a further interpretation. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Mean, interannual variability and trends in a regional climate change experiment over Europe. I. Present-day climate (1961–1990)

We present an analysis of a multidecadal simulation of present-day climate (1961–1990) over Europe with the regional climate model RegCM nested within the global atmospheric model HadAMH. Climatic means, interannual variability and trends are examined, with focus on surface air temperature and precipitation. The RegCM driven by HadAMH fields is able to reproduce the basic features of the observed mean surface climate over Europe, its seasonal evolution and the regional detail due to topographic forcing. Surface air temperature biases are mostly less than 1–2 °C and precipitation biases mostly within 10–20%. The RegCM has more intense vertical transport of temperature and water vapor than HadAMH, which results in lower surface air temperatures and greater precipitation than found in the HadAMH simulation. In some cases this is in the direction of greater agreement with observations, while in others it is in the opposite direction. The simulation shows a tendency to overestimate interannual variability of temperature and precipitation compared to observations, particularly during summer and over the Mediterranean regions. It is shown that in DJF, MAM and SON the RegCM interannual variability is primarily determined by the boundary forcing from HadAMH, while in JJA the internal model physics and resolution effects dominate over many subregions of the domain, and the RegCM has higher interannual variability than HadAMH. The precipitation trends simulated by the nested modeling system for the period 1961–1990 capture some features of the observed trends, in particular the cold season drying over the Mediterranean regions. Ensembles of simulations are, however, needed for a more robust assessment of the models capability to simulate climatic trends. Overall, this simulation is of good quality compared with previous nested RegCM experiments and will constitute the basis for the generation of climate change scenarios over the European region to be reported in future work.     

RegCM3 regional climatologies for South America using reanalysis and ECHAM global model driving fields

To enable downscaling of seasonal prediction and climate change scenarios, long-term baseline regional climatologies which employ global model forcing are needed for South America. As a first step in this process, this work examines climatological integrations with a regional climate model using a continental scale domain nested in both reanalysis data and multiple realizations of an atmospheric general circulation model (GCM). The analysis presents an evaluation of the nested model simulated large scale circulation, mean annual cycle and interannual variability which is compared against observational estimates and also with the driving GCM for the Northeast, Amazon, Monsoon and Southeast regions of South America. Results indicate that the regional climate model simulates the annual cycle of precipitation well in the Northeast region and Monsoon regions; it exhibits a dry bias during winter (July–September) in the Southeast, and simulates a semi-annual cycle with a dry bias in summer (December–February) in the Amazon region. There is little difference in the annual cycle between the GCM and renalyses driven simulations, however, substantial differences are seen in the interannual variability. Despite the biases in the annual cycle, the regional model captures much of the interannual variability observed in the Northeast, Southeast and Amazon regions. In the Monsoon region, where remote influences are weak, the regional model improves upon the GCM, though neither show substantial predictability. We conclude that in regions where remote influences are strong and the global model performs well it is difficult for the regional model to improve the large scale climatological features, indeed the regional model may degrade the simulation. Where remote forcing is weak and local processes dominate, there is some potential for the regional model to add value. This, however, will require improvments in physical parameterizations for high resolution tropical simulations.     

Climate Variability-Observations, Reconstructions, and Model Simulations for the Atlantic-European and Alpine Region from 1500-2100 AD

A detailed analysis is undertaken of the Atlantic-European climate using data from 500-year-long proxy-based climate reconstructions, a long climate simulation with perpetual 1990 forcing, as well as two global and one regional climate change scenarios. The observed and simulated interannual variability and teleconnectivity are compared and interpreted in order to improve the understanding of natural climate variability on interannual to decadal time scales for the late Holocene. The focus is set on the Atlantic-European and Alpine regions during the winter and summer seasons, using temperature, precipitation, and 500 hPa geopotential height fields. The climate reconstruction shows pronounced interdecadal variations that appear to “lock” the atmospheric circulation in quasi-steady long-term patterns over multi-decadal periods controlling at least part of the temperature and precipitation variability. Different circulation patterns are persistent over several decades for the period 1500 to 1900. The 500-year-long simulation with perpetual 1990 forcing shows some substantial differences, with a more unsteady teleconnectivity behaviour. Two global scenario simulations indicate a transition towards more stable teleconnectivity for the next 100 years. Time series of reconstructed and simulated temperature and precipitation over the Alpine region show comparatively small changes in interannual variability within the time frame considered, with the exception of the summer season, where a substantial increase in interannual variability is simulated by regional climate models.     

Modelled and observed variability in atmospheric vertical temperature structure

Realistic simulation of the internal variability of the climate system is important both for climate change detection and as an indicator of whether the physics of the climate system is well-represented in a climate model. In this work zonal mean atmospheric temperatures from a control run of the second Hadley Centre coupled GCM are compared with gridded radiosonde observations for the past 38 years to examine how well modelled and observed variability agree. On time scales of between six months and twenty years, simulated and observed variability of global mean temperatures agree well for the troposphere, but in the equatorial stratosphere variability is lower in the model than in the observations, particularly at periods of two years and seven to twenty years. We find good agreement between modelled and observed variability in the mass-weighted amplitude of a forcing-response pattern, as used for climate change detection, but variability in a signal-to-noise optimised fingerprint pattern is significantly greater in the observations than in a model control run. This discrepancy is marginally consistent with anthropogenic forcing, but more clearly explained by a combination of solar and volcanic forcing, suggesting these should be considered in future `vertical detection' studies. When the relationship between tropical lapse rate and mean temperature was examined, it was found that these quantities are unrealistically coherent in the model at periods above three years. However, there is a clear negative lapse rate feedback in both model and observations: as the tropical troposphere warms, the mid-tropospheric lapse rate decreases on all the time scales considered. Received: 11 August 1998 / Accepted: 20 July 1999     

Signal analysis of the atmospheric mean 500/1000 hPa temperature north of 55°N between 1949 and 1994

 The lower tropospheric mean temperature 500/1000 hPa is examined in the Northern Hemisphere high-latitude region north of 55°N with regard to a climate change signal due to anthropogenic climate forcing as a supplement to previous studies which concentrated on near surface temperatures. An observational data set of the German Weather Service is compared with several model simulations including different scenarios of greenhouse gas and sulfate aerosol forcing derived from the two recent versions of the coupled climate model in Hamburg, ECHAM-3/LSG and ECHAM-4/OPYC. The signal analysis is based on the optimal fingerprint method, which supplies a detection variable with optimal signal-to-noise ratio. The natural variability measures are derived from the corresponding long-term control experiments. From 1970 onward, we find high trend pattern analogies between the observational data and the greenhouse-gas induced model simulations. The fingerprint of this common temperature signal consists of a predominate warming with maximum over Siberia and a weak cooling over the North Atlantic reaching an estimated significance level of about 1%. A non-optimized approach has also been examined, leading to even closer trend pattern correlations. The additional forcing by sulfate aerosols decreases the correlation of this climate change simulation with the observations. The natural variability constitutes about 50% of the conforming trend patterns. The signal-to-noise ratio is best over the oceans while the tropospheric temperatures over the land masses are contaminated by strong noise. The trend pattern correlations look the same for both model versions and several ensemble members with different noise realizations. Received: 4 January 1999 / Accepted: 11 April 2001     

Regional climate change experiments over southern South America. I: present climate

We present an analysis of a regional simulation of present-day climate (1981–1990) over southern South America. The regional model MM5 was nested within time-slice global atmospheric model experiments conducted by the HadAM3H model. We evaluate the capability of the model in simulating the observed climate with emphasis on low-level circulation patterns and surface variables, such as precipitation and surface air mean, maximum and minimum temperatures. The regional model performance was evaluated in terms of seasonal means, seasonal cycles, interannual variability and extreme events. Overall, the regional model is able to capture the main features of the observed mean surface climate over South America, its seasonal evolution and the regional detail due to topographic forcing. The observed regional patterns of surface air temperatures (mean, maxima and minima) are well reproduced. Biases are mostly within 3°C, temperature being overestimated over central Argentina and underestimated in mountainous regions during all seasons. Biases in northeastern Argentina and southeastern Brazil are positive during austral spring season and negative in other seasons. In general, maximum temperatures are better represented than minimum temperatures. Warm bias is larger during austral summer for maximum temperature and during austral winter for minimum temperature, mainly over central Argentina. The broad spatial pattern of precipitation and its seasonal evolution are well captured; however, the regional model overestimates the precipitation over the Andes region in all seasons and in southern Brazil during summer. Precipitation amounts are underestimated over the La Plata basin from fall to spring. Extremes of precipitation are better reproduced by the regional model compared with the driving model. Interannual variability is well reproduced too, but strongly regulated by boundary conditions, particularly during summer months. Overall, taking into account the quality of the simulation, we can conclude that the regional model is capable in reproducing the main regional patterns and seasonal cycle of surface variables. The present reference simulation constitutes the basis to examine the climate change simulations resulting from the A2 and B2 forcing scenarios which are being reported in a separate study.     

A transient climate change simulation with greenhouse gas and aerosol forcing: projected climate to the twenty-first century

 The potential climatic consequences of increasing atmospheric greenhouse gas (GHG) concentration and sulfate aerosol loading are investigated for the years 1900 to 2100 based on five simulations with the CCCma coupled climate model. The five simulations comprise a control experiment without change in GHG or aerosol amount, three independent simulations with increasing GHG and aerosol forcing, and a simulation with increasing GHG forcing only. Climate warming accelerates from the present with global mean temperatures simulated to increase by 1.7 °C to the year 2050 and by a further 2.7 °C by the year 2100. The warming is non-uniform as to hemisphere, season, and underlying surface. Changes in interannual variability of temperature show considerable structure and seasonal dependence. The effect of the comparatively localized negative radiative forcing associated with the aerosol is to retard and reduce the warming by about 0.9 °C at 2050 and 1.2 °C at 2100. Its primary effect on temperature is to counteract the global pattern of GHG-induced warming and only secondarily to affect local temperatures suggesting that the first order transient climate response of the system is determined by feedback processes and only secondarily by the local pattern of radiative forcing. The warming is accompanied by a more active hydrological cycle with increases in precipitation and evaporation rates that are delayed by comparison with temperature increases. There is an “El Nino-like” shift in precipitation and an overall increase in the interannual variability of precipitation. The effect of the aerosol forcing is again primarily to delay and counteract the GHG-induced increase. Decreases in soil moisture are common but regionally dependent and interannual variability changes show considerable structure. Snow cover and sea-ice retreat. A PNA-like anomaly in mean sea-level pressure with an enhanced Aleutian low in northern winter is associated with the tropical shift in precipitation regime. The interannual variability of mean sea-level pressure generally decreases with largest decreases in the tropical Indian ocean region. Changes to the ocean thermal structure are associated with a spin-down of the Atlantic thermohaline circulation together with a decrease in its variability. The effect of aerosol forcing, although modest, differs from that for most other quantities in that it does not act primarily to counteract the GHG forcing effect. The barotropic stream function in the ocean exhibits modest change in the north Pacific but accelerating changes in much of the Southern Ocean and particularly in the north Atlantic where the gyre spins down in conjunction with the decrease in the thermohaline circulation. The results differ in non-trivial ways from earlier equilibrium 2 × CO₂ results with the CCCma model as a consequence of the coupling to a fully three-dimensional ocean model and the evolving nature of the forcing. Received: 24 September 1998 / Accepted: 8 October 1999     

Variation of surface temperature during the last millennium in a simulation with the FGOALS-gl climate system model

A reasonable past millennial climate simulation relies heavily on the specified external forcings, including both natural and anthropogenic forcing agents. In this paper, we examine the surface temperature responses to specified external forcing agents in a millennium-scale transient climate simulation with the fast version of LASG IAP Flexible Global Ocean-Atmosphere-Land System model (FGOALS-gl) developed in the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP). The model presents a reasonable performance in comparison with reconstructions of surface temperature. Differentiated from significant changes in the 20th century at the global scale, changes during the natural-forcing-dominant period are mainly manifested in the Northern Hemisphere. Seasonally, modeled significant changes are more pronounced during the wintertime at higher latitudes. This may be a manifestation of polar amplification associated with sea-ice-temperature positive feedback. The climate responses to total external forcings can explain about half of the climate variance during the whole millennium period, especially at decadal timescales. Surface temperature in the Antarctic shows heterogeneous and insignificant changes during the preindustrial period and the climate response to external forcings is undetectable due to the strong internal variability. The model response to specified external forcings is modulated by cloud radiative forcing (CRF). The CRF acts against the fluctuations of external forcings. Effects of clouds are manifested in shortwave radiation by changes in cloud water during the natural-forcing-dominant period, but mainly in longwave radiation by a decrease in cloud amount in the anthropogenic-forcing-dominant period.     

从全球到区域气候变化

尽管气候变化是全球性的现象,但其表现和结果随区域不同而不同,因此区域气候信息对于气候变化的作用和风险评估很重要。基于此,IPCC第六次评估报告（AR6）第一工作组（WGI）报告第十章对如何从全球链接到区域气候变化方面进行了评估。区域气候变化是对自然强迫和人类活动的区域响应、对大尺度气候系统内部变率的响应和区域气候本身反馈过程的相互作用结果。因此,本章重点关注如何从多套观测资料,不同模式的集合,物理过程的理解、专家判断和本地信息等多元信息中有效提炼出区域信息的方法。通过提炼方法指出人类活动是许多次大陆尺度上1950年代以来区域平均温度变化的主要驱动力,但参考时段和阈值的选择对人类活动信号是否出现和出现的早晚有影响。人类活动对一些区域的多年代际降水变化有一定贡献,但其不确定性相对全球平均而言更大。气候系统内部变率可以在很大程度上延迟和阻碍人类活动信号在区域气候变化中的出现。区域气候变化的评估给决策者提供了更多有用的信息,增加了评估报告的适用性。     

On long range dependence in global surface temperature series

Long Range Dependence (LRD) scaling behavior has been argued to characterize long-term surface temperature time series. LRD is typically measured by the so-called “Hurst” coefficient, “H”. Using synthetic temperature time series generated by a simple climate model with known physics, I demonstrate that the values of H obtained for observational temperature time series can be understood in terms of the linear response to past estimated natural and anthropogenic external radiative forcing combined with the effects of random white noise weather forcing. The precise value of H is seen to depend on the particular noise realization. The overall distribution obtained over an ensemble of noise realizations is seen to be a function of the relative amplitude of external forcing and internal stochastic variability and additionally in climate “proxy” records, the amount of non-climatic noise present. There is no obvious reason to appeal to more exotic physics for an explanation of the apparent scaling behavior in observed temperature data.     

Observed dependence of the water vapor and clear-sky greenhouse effect on sea surface temperature: comparison with climate warming experiments

This study presents a comparison of the water vapor and clear-sky greenhouse effect dependence on sea surface temperature for climate variations of different types. Firstly, coincident satellite observations and meteorological analyses are used to examine seasonal and interannual variations and to evaluate the performance of a general circulation model. Then, this model is used to compare the results inferred from the analysis of observed climate variability with those derived from global climate warming experiments. One part of the coupling between the surface temperature, the water vapor and the clear-sky greenhouse effect is explained by the dependence of the saturation water vapor pressure on the atmospheric temperature. However, the analysis of observed and simulated fields shows that the coupling is very different according to the type of region under consideration and the type of climate forcing that is applied to the Earth-atmosphere system. This difference, due to the variability of the vertical structure of the atmosphere, is analyzed in detail by considering the temperature lapse rate and the vertical profile of relative humidity. Our results suggest that extrapolating the feedbacks inferred from seasonal and short-term interannual climate variability to longer-term climate changes requires great caution. It is argued that our confidence in climate models' predictions would be increased significantly if the basic physical processes that govern the variability of the vertical structure of the atmosphere, and its relation to the large-scale circulation, were better understood and simulated. For this purpose, combined observational and numerical studies focusing on physical processes are needed.     

The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate

 A global, three-dimensional climate model, developed by coupling the CCCma second-generation atmospheric general circulation model (GCM2) to a version of the GFDL modular ocean model (MOM1), forms the basis for extended simulations of past, current and projected future climate. The spin-up and coupling procedures are described, as is the resulting climate based on a 200 year model simulation with constant atmospheric composition and external forcing. The simulated climate is systematically compared to available observations in terms of mean climate quantities and their spatial patterns, temporal variability, and regional behavior. Such comparison demonstrates a generally successful reproduction of the broad features of mean climate quantities, albeit with local discrepancies. Variability is generally well-simulated over land, but somewhat underestimated in the tropical ocean and the extratropical storm-track regions. The modelled climate state shows only small trends, indicating a reasonable level of balance at the surface, which is achieved in part by the use of heat and freshwater flux adjustments. The control simulation provides a basis against which to compare simulated climate change due to historical and projected greenhouse gas and aerosol forcing as described in companion publications. Received: 24 September 1998 / Accepted: 8 October 1999     

An assessment of European synoptic variability in Hadley Centre Global Environmental models based on an objective classification of weather regimes

The frequency of occurrence of persistent synoptic-scale weather patterns over the European and North-East Atlantic regions is examined in a hierarchy of climate model simulations and compared to observational re-analysed data. A new objective method, employing pattern correlation techniques, has been constructed for classifying daily-mean mean-sea-level pressure and 500 hPa geopotential height fields with respect to a set of 29 European weather regime types, based on the widely known subjective Grosswetterlagen (GWL) system of the German Weather Service. The objective method is described and applied initially to ERA40 and NCEP re-analysis data. While the resulting daily Objective-GWL catalogue shows some systematic differences with respect to the subjectively-derived original GWL series, the method is shown to be sufficiently robust for application to climate model output. Ensemble runs from the most recent development of the Hadley Centre’s Global Environmental model, HadGEM1, in atmosphere-only, coupled and climate change scenario modes are analysed with regards to European synoptic variability. All simulations successfully exhibit a wide spread of GWL occurrences across all regime types, but some systematic differences in mean GWL frequencies are seen in spite of significant levels of interdecadal variability. These differences provide a basis for estimating local anomalies of surface temperature and precipitation over Europe, which would result from circulation changes alone, in each climate simulation. Comparison to observational re-analyses shows a clear and significant improvement in the simulation of realistic European synoptic variability with the development and resolution of the atmosphere-only models.     

Quantifying the contributions of anthropogenic and natural forcings to climate changes over arid-semiarid areas during 1946–2005

In this study, the contributions from changes in man-made greenhouse gases (GHG), anthropogenic aerosols (AA), and land use (LU), as well as natural solar and volcanic (NAT) forcing changes, to observed changes in surface air temperature (T) and precipitation (P) over global land, especially over arid-semiarid areas, during 1946–2005 are quantified using observations and climate model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Results show that the anthropogenic (ANT) forcings dominate the ubiquitous surface warming seen in observations and lead to slight increases in precipitation over most land areas, while the NAT forcing leads to small cooling over land. GHG increases are the primary factor responsible for the anthropogenic climate change, while the AA forcing offsets a large part of the GHG-induced warming and P changes. The LU forcing generally contributes little to the T and P changes from 1946 to 2005 over most land areas. Unlike the consistent temperature changes among most model simulations, precipitation changes display a large spread among the models and are incomparable with the observations in spatial distributions and magnitude, mainly due to its large internal variability that varies among individual model runs. Using an optimal fingerprinting method, we find that the observed warming over land during 1946–2005 can be largely attributed to the ANT forcings, and the combination of the ANT and NAT forcings can explain about 85~95% of the observed warming trend over global land as well as over most arid-semiarid regions such as Northern China. However, the anthropogenic influences on precipitation over the past 60 years are generally undetectable over most land areas, including most arid-semiarid regions. This indicates that internal variability is still larger than the forced change for land precipitation.