Impact of global warming on the geobotanic zones: an experiment with a statistical�Cdynamical climate model

In this study, a zonally-averaged statistical climate model (SDM) is used to investigate the impact of global warming on the distribution of the geobotanic zones over the globe. The model includes a parameterization of the biogeophysical feedback mechanism that links the state of surface to the atmosphere (a bidirectional interaction between vegetation and climate). In the control experiment (simulation of the present-day climate) the geobotanic state is well simulated by the model, so that the distribution of the geobotanic zones over the globe shows a very good agreement with the observed ones. The impact of global warming on the distribution of the geobotanic zones is investigated considering the increase of CO₂ concentration for the B1, A2 and A1FI scenarios. The results showed that the geobotanic zones over the entire earth can be modified in future due to global warming. Expansion of subtropical desert and semi-desert zones in the Northern and Southern Hemispheres, retreat of glaciers and sea-ice, with the Arctic region being particularly affected and a reduction of the tropical rainforest and boreal forest can occur due to the increase of the greenhouse gases concentration. The effects were more pronounced in the A1FI and A2 scenarios compared with the B1 scenario. The SDM results confirm IPCC AR4 projections of future climate and are consistent with simulations of more complex GCMs, reinforcing the necessity of the mitigation of climate change associated to global warming.     

Sensitivity of Hudson Bay Sea ice and ocean climate to atmospheric temperature forcing

A regional sea-ice?Cocean model was used to investigate the response of sea ice and oceanic heat storage in the Hudson Bay system to a climate-warming scenario. Projections of air temperature (for the years 2041?C2070; effective CO₂ concentration of 707?C950?ppmv) obtained from the Canadian Regional Climate Model (CRCM 4.2.3), driven by the third-generation coupled global climate model (CGCM 3) for lateral atmospheric and land and ocean surface boundaries, were used to drive a single sensitivity experiment with the delta-change approach. The projected change in air temperature varies from 0.8°C (summer) to 10°C (winter), with a mean warming of 3.9°C. The hydrologic forcing in the warmer climate scenario was identical to the one used for the present climate simulation. Under this warmer climate scenario, the sea-ice season is reduced by 7?C9?weeks. The highest change in summer sea-surface temperature, up to 5°C, is found in southeastern Hudson Bay, along the Nunavik coast and in James Bay. In central Hudson Bay, sea-surface temperature increases by over 3°C. Analysis of the heat content stored in the water column revealed an accumulation of additional heat, exceeding 3?MJ?m^?3, trapped along the eastern shore of James and Hudson bays during winter. Despite the stratification due to meltwater and river runoff during summer, the shallow coastal regions demonstrate a higher capacity of heat storage. The maximum volume of dense water produced at the end of winter was halved under the climate-warming perturbation. The maximum volume of sea ice is reduced by 31% (592?km3) while the difference in the maximum cover is only 2.6% (32,350?km²). Overall, the depletion of sea-ice thickness in Hudson Bay follows a southeast?Cnorthwest gradient. Sea-ice thickness in Hudson Strait and Ungava Bay is 50% thinner than in present climate conditions during wintertime. The model indicates that the greatest changes in both sea-ice climate and heat content would occur in southeastern Hudson Bay, James Bay, and Hudson Strait.     

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.     

The Influences of NAO and the Hudson Bay sea-ice on the climate of eastern Canada

Sea-ice cover over the Hudson Bay (HB) exhibits large variability in the freeze-up season normally starting in November. Its influence on the climate over eastern Canada has been studied with the Canadian Regional Climate Model (CRCM) in three steps. First, a 30-year continuous simulation from 1970 to 1999 was performed as a control run to evaluate the simulated climate variability over eastern Canada, in particularly variability associated with the North Atlantic oscillation (NAO). Then, 50 additional 1 month experiments were performed with modified sea-surface conditions prescribed over the HB. These integrations allowed us to quantify the contribution of HB sea-ice anomalies versus large scale NAO atmospheric variability (as defined by prescribed lateral boundary conditions) in inducing climate variability over eastern Canada. Results show that the NAO is the dominant factor controlling climate variability over eastern Canada. The contribution of HB sea-ice anomalies is significant only in the immediate coastal region. Under the influence of different phases of NAO, HB sea-ice anomalies do co-vary with temperature and precipitation anomalies downstream of the HB over eastern Canada. The ultimate cause of this co-variability is NAO variability which forces variability in both HB sea-ice cover as well as temperature/precipitation over eastern Canada.     

The impact of dynamic sea-ice on the climatology and climate sensitivity of a GCM: a study of past, present, and future climates

 We assess two parametrisations of sea-ice in a coupled atmosphere–mixed layer ocean–sea-ice model. One parametrisation represents the thermodynamic properties of sea-ice formation alone (THERM), while the other also includes advection of the ice (DYN). The inclusion of some sea-ice dynamics improves the model's simulation of the present day sea-ice cover when compared to observations. Two climate change scenarios are used to investigate the effect of these different parametrisations on the model's climate sensitivity. The scenarios are the equilibrium response to a doubling of atmospheric CO₂ and the response to imposed glacial boundary conditions. DYN produces a smaller temperature response to a doubling of CO₂ than THERM. The temperature response of THERM is more similar to DYN in the glacial case than in the 2×CO₂ case which implies that the climate sensitivity of THERM and DYN varies with the nature of the forcing. The different responses can largely be explained by the different distribution of Southern Hemisphere sea-ice cover in the control simulations, with the inclusion of ice dynamics playing an important part in producing the differences. This emphasises the importance of realistically simulating the reference climatic state when attempting to simulate a climate change to a prescribed forcing. The simulated glacial sea-ice cover is consistent with the limited palaeodata in both THERM and DYN, but DYN simulates a more realistic present day sea-ice cover. We conclude that the inclusion of simple ice dynamics in our model increases our confidence in the simulation of the anomaly climate. Received: 24 May 2000 / Accepted: 25 October 2000     

Use of general circulation model output in the creation of climate change scenarios for impact analysis

Many scientific studies warn of a rapid global climate change during the next century. These changes are understood with much less certainty on a regional scale than on a global scale, but effects on ecosystems and society will occur at local and regional scales. Consequently, in order to study the true impacts of climate change, regional scenarios of future climate are needed. One of the most important sources of information for creating scenarios is the output from general circulation models (GCMs) of the climate system. However, current state-of-the-art GCMs are unable to simulate accurately even the current seasonal cycle of climate on a regional basis. Thus the simple technique of adding the difference between 2 × CO₂ and 1 × CO₂ GCM simulations to current climatic time series cannot produce scenarios with appropriate spatial and temporal details without corrections for model deficiencies. In this study a technique is developed to allow the information from GCM simulations to be used, while accommodating for the deficiencies. GCM output is combined with knowledge of the regional climate to produce scenarios of the equilibrium climate response to a doubling of the atmospheric CO₂ concentration for three case study regions, China, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general climate change calculated with several GCMs with the observed patterns of interannual climate variability, reasonable scenarios of temperature and precipitation variations can be created. Generalizations of this procedure to other regions of the world are discussed.     

Climate simulations of major estuarine watersheds in the Mid-Atlantic region of the US

To better understand the implications of anthropogenic climate change for three major Mid-Atlantic estuaries (the Chesapeake Bay, the Delaware Bay, and the Hudson River Estuary), we analyzed the regional output of seven global climate models. The simulation given by the average of the models was generally superior to individual models, which differed dramatically in their ability to simulate twentieth-century climate. The model average had little bias in its mean temperature and precipitation and, except in the Lower Chesapeake Watershed, was able to capture the twentieth-century temperature trend. Weaknesses in the model average were too much seasonality in temperature and precipitation, a shift in precipitation’s summer maximum to spring and winter minimum to fall, interannual variability that was too high in temperature and too low in precipitation, and inability to capture the twentieth-century precipitation increase. There is some evidence that model deficiencies are related to land surface parameterizations. All models warmed over the twenty-first century under the six greenhouse gas scenarios considered, with an increase of 4.7 ± 2.0°C (model mean ± 1 standard deviation) for the A2 scenario (a medium-high emission scenario) over the Chesapeake Bay Watershed by 2070–2099. Precipitation projections had much weaker consensus, with a corresponding increase of 3 ± 12% for the A2 scenario, but in winter there was a more consistent increase of 8 ± 7%. The projected climate averaged over the four best-performing models was significantly cooler and wetter than the projected seven-model-average climate. Precipitation projections were within the range of interannual variability but temperature projections were not. The implied research needs are for improvements in precipitation projections and a better understanding of the impacts of warming on streamflow and estuarine ecology and biogeochemistry.     

Precipitation Change: Model Simulations and Paleoreconstructions

Zonal-scale patterns of precipitation change, as reconstructed for the Mid-Pliocene and the two Pleistocene optima, are compared with those generated in standard 2 × CO₂–1 × CO₂ equilibrium experiments by two high-resolution GCMs of equal sensitivities of global precipitation and temperature to CO₂ doubling. We find that the three warm paleoclimates, despite differences in boundary conditions/forcings, exhibit a similarity in zonal-scale patterns of change for precipitation over land in the Northern Hemisphere (NH); the between-epoch pattern correlation is 0.9 on the average. The two models give marked differences in zonal distribution of precipitation anomalies at mid-latitudes; the between-model pattern correlation for changes of precipitation over NH land is 0.4. The response of precipitation over the NH land area to the NH warming is about 10%/°C in the paleodata compared to 3%/°C in the models. The largest model/paleodata descrepancy refers to the present-day desert belt, where a large precipitation anomaly persists in all epochs. North of 50 N, the absolute values of the zonally-averaged precipitation anomalies simulated by both models fall in the range implied by the three warm paleoclimates, but they are systematically lower than the anomalies of the Mid-Pliocene. If our reconsructions are valid and if climate changes in the Mid-Pliocene were driven solely by CO₂ changes, then our results suggest that models are underestimating the magnitude of the precipitation response, especially in the regions of subtropical deserts; the magnitude of the simulated temperature response at high latitudes is also underestimated. At least part of the reported model/paleodata discordance appears to be due to lack of interactive land surface package in the models examined.     

PROJECTIONS OF CLIMATE CHANGE FOR THE CZECH REPUBLIC

The paper deals with a selection of the climatological baseline, GCM validity and construction of the climate change scenarios for an impact assessment in the Czech territory. The period of 1961–1990 has been selected as the climatological baseline. The corresponding database includes more than 50 monthly mean temperature and precipitation series, and 16 time series of daily meteorological data that contain also the solar radiation data. The 1× CO₂ outputs produced by four GCMs, provided by the CSMT (GISS, GFD30, GFD01, and CCCM), were compared with observed temperature and precipitation conditions in western and central Europe with a particular attention devoted to the Czech territory. The GCM ability to simulate annual cycles of temperature, precipitation and radiation was thoroughly examined. The GISS and CCCM were selected as a basis for constructing climate change scenarios as they simulated reasonably the observed patterns. According to the GISS variant, 2× CO₂ climate assumes a higher winter and lower summer warming, and an increase in annual precipitation amounts. A dangerous combination of the summer temperature increase and declining precipitation amounts is a specific feature of the CCCM scenario. An incremental scenario for temperature and precipitation is based on the combination of prescribed changes in both annual means and annual courses.     

Implications of CO2 global warming on great lakes ice cover

Statistical ice cover models were used to project daily mean basin ice cover and annual ice cover duration for Lakes Superior and Erie. Models were applied to a 1951–80 base period and to three 30-year steady double carbon dioxide (2 × CO₂) scenarios produced by the Geophysical Fluid Dynamics Laboratory (GFDL), the Goddard Institute of Space Studies (GISS), and the Oregon State University (OSU) general circulation models. Ice cover estimates were made for the West, Central, and East Basins of Lake Erie and for the West, East, and Whitefish Bay Basins of Lake Superior. Average ice cover duration for the 1951– 80 base period ranged from 13 to 16 weeks for individual lake basins. Reductions in average ice cover duration under the three 2 × CO₂ scenarios for individual lake basins ranged from 5 to 12 weeks for the OSU scenario, 8 to 13 weeks for the GISS scenario, and 11 to 13 weeks for GFDL scenario. Winters without ice formation become common for Lake Superior under the GFDL scenario and under all three 2 × CO₂ scenarios for the Central and East Basins of Lake Erie. During an average 2 × CO₂ winter, ice cover would be limited to the shallow areas of Lakes Erie and Superior. Because of uncertainties in the ice cover models, the results given here represent only a first approximation and are likely to represent an upper limit of the extent and duration of ice cover under the climate change projected by the three 2 × CO₂scenarios. Notwithstanding these limitations, ice cover projected by the 2 × CO₂ scenarios provides a preliminary assessment of the potential sensitivity of the Great Lakes ice cover to global warming. Potential environmental and socioeconomic impacts of a 2 × CO₂ warming include year-round navigation, change in abundance of some fish species in the Great Lakes, discontinuation or reduction of winter recreational activities, and an increase in winter lake evaporation.     

Climatic changes associated with a global “2°C-stabilization” scenario simulated by the ECHAM5/MPI-OM coupled climate model

In this study, concentrations of the well-mixed greenhouse gases as well as the anthropogenic sulphate aerosol load and stratospheric ozone concentrations are prescribed to the ECHAM5/MPI-OM coupled climate model so that the simulated global warming does not exceed 2°C relative to pre-industrial times. The climatic changes associated with this so-called “2°C-stabilization” scenario are assessed in further detail, considering a variety of meteorological and oceanic variables. The climatic changes associated with such a relatively weak climate forcing supplement the recently published fourth assessment report by the IPCC in that such a stabilization scenario can only be achieved by mitigation initiatives. Also, the impact of the anthropogenic sulphate aerosol load and stratospheric ozone concentrations on the simulated climatic changes is investigated. For this particular climate model, the 2°C-stabilization scenario is characterized by the following atmospheric concentrations of the well-mixed greenhouse gases: 418 ppm (CO₂), 2,026 ppb (CH₄), and 331 ppb (N₂O), 786 ppt (CFC-11) and 486 ppt (CFC-12), respectively. These greenhouse gas concentrations correspond to those for 2020 according to the SRES A1B scenario. At the same time, the anthropogenic sulphate aerosol load and stratospheric ozone concentrations are changed to the level in 2100 (again, according to the SRES A1B scenario), with a global anthropogenic sulphur dioxide emission of 28 TgS/year leading to a global anthropogenic sulphate aerosol load of 0.23 TgS. The future changes in climate associated with the 2°C-stabilization scenario show many of the typical features of other climate change scenarios, including those associated with stronger climatic forcings. That are a pronounced warming, particularly at high latitudes accompanied by a marked reduction of the sea-ice cover, a substantial increase in precipitation in the tropics as well as at mid- and high latitudes in both hemispheres but a marked reduction in the subtropics, a significant strengthening of the meridional temperature gradient between the tropical upper troposphere and the lower stratosphere in the extratropics accompanied by a pronounced intensification of the westerly winds in the lower stratosphere, and a strengthening of the westerly winds in the Southern Hemisphere extratropics throughout the troposphere. The magnitudes of these changes, however, are somewhat weaker than for the scenarios associated with stronger global warming due to stronger climatic forcings, such as the SRES A1B scenario. Some of the climatic changes associated with the 2°C-stabilization are relatively strong with respect to the magnitude of the simulated global warming, i.e., the pronounced warming and sea-ice reduction in the Arctic region, the strengthening of the meridional temperature gradient at the northern high latitudes and the general increase in precipitation. Other climatic changes, i.e., the El Niño like warming pattern in the tropical Pacific Ocean and the corresponding changes in the distribution of precipitation in the tropics and in the Southern Oscillation, are not as markedly pronounced as for the scenarios with a stronger global warming. A higher anthropogenic sulphate aerosol load (for 2030 as compared to the level in 2100 according to the SRES A1B scenario) generally weakens the future changes in climate, particularly for precipitation. The most pronounced effects occur in the Northern Hemisphere and in the tropics, where also the main sources of anthropogenic sulphate aerosols are located.     

The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming

Summary A suite of simulations with the HadCM3LC coupled climate-carbon cycle model is used to examine the various forcings and feedbacks involved in the simulated precipitation decrease and forest dieback. Rising atmospheric CO₂ is found to contribute 20% to the precipitation reduction through the physiological forcing of stomatal closure, with 80% of the reduction being seen when stomatal closure was excluded and only radiative forcing by CO₂ was included. The forest dieback exerts two positive feedbacks on the precipitation reduction; a biogeophysical feedback through reduced forest cover suppressing local evaporative water recycling, and a biogeochemical feedback through the release of CO₂ contributing to an accelerated global warming. The precipitation reduction is enhanced by 20% by the biogeophysical feedback, and 5% by the carbon cycle feedback from the forest dieback. This analysis helps to explain why the Amazonian precipitation reduction simulated by HadCM3LC is more extreme than that simulated in other GCMs; in the fully-coupled, climate-carbon cycle simulation, approximately half of the precipitation reduction in Amazonia is attributable to a combination of physiological forcing and biogeophysical and global carbon cycle feedbacks, which are generally not included in other GCM simulations of future climate change. The analysis also demonstrates the potential contribution of regional-scale climate and ecosystem change to uncertainties in global CO₂ and climate change projections. Moreover, the importance of feedbacks suggests that a human-induced increase in forest vulnerability to climate change may have implications for regional and global scale climate sensitivity.     

Changes in temperature and precipitation extremes in the CMIP5 ensemble

Twenty-year temperature and precipitation extremes and their projected future changes are evaluated in an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), updating a similar study based on the CMIP3 ensemble. The projected changes are documented for three radiative forcing scenarios. The performance of the CMIP5 models in simulating 20-year temperature and precipitation extremes is comparable to that of the CMIP3 ensemble. The models simulate late 20th century warm extremes reasonably well, compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes. Simulated late 20th century precipitation extremes are plausible in the extratropics but uncertainty in extreme precipitation in the tropics and subtropics remains very large, both in the models and the observationally-constrained datasets. Consistent with CMIP3 results, CMIP5 cold extremes generally warm faster than warm extremes, mainly in regions where snow and sea-ice retreat with global warming. There are tropical and subtropical regions where warming rates of warm extremes exceed those of cold extremes. Relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation. The corresponding waiting times for late 20th century extreme precipitation events are reduced almost everywhere, except for a few subtropical regions. The CMIP5 planetary sensitivity in extreme precipitation is about 6 %/°C, with generally lower values over extratropical land.     

High resolution regional climate model simulations for Germany: Part II—projected climate changes

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.     

REGIONAL CLIMATE CHANGE SCENARIOS FOR VULNERABILITY AND ADAPTATION ASSESSMENTS

This paper describes the regional climate change scenarios that are recommended for use in the U.S. Country Studies Program (CSP) and evaluates how well four general circulation models (GCMs) simulate current climate over Europe. Under the umbrella of the CSP, 50 countries with varying skills and experience in developing climate change scenarios are assessing vulnerability and adaptation. We considered the use of general circulation models, analogue warm periods, and incremental scenarios as the basis for creating climate change scenarios. We recommended that participants in the CSP use a combination of GCM based scenarios and incremental scenarios. The GCMs, in spite of their many deficiencies, are the best source of information about regional climate change. Incremental scenarios help identify sensitivities to changes in a particular meteorological variable and ensure that a wide range of regional climate change scenarios are considered. We recommend using the period 1951–1980 as baseline climate because it was a relatively stable climate period globally. Average monthly changes from the GCMs and the incremental changes in climate variables are combined with the historical record to produce scenarios. The scenarios do not consider changes in interannual, daily, or subgrid scale variability. Countries participating in the Country Studies Program were encouraged to compare the GCMs' estimates of current climate with actual long-term climate means. In this paper, we compare output of four GCMs (CCCM, GFDL, UKMO, and GISS) with observed climate over Europe by performing a spatial correlation analysis for temperature and precipitation, by statistically comparing spatial patterns averaged climate estimates from the GCMs with observed climate, and by examining how well the models estimate seasonal patterns of temperature and precipitation. In Europe, the GISS and CCCM models best simulate current temperature, whereas the GISS and UK89 models, and the CCCM model, best simulate precipitation in defined northern and southern regions, respectively.     

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.     

Modelling climate change effects on the spatial distribution of mountain permafrost at three sites in northwest Canada

Spatial models of present-day mountain permafrost probability were perturbed to examine potential climate change impacts. Mean annual air temperature (MAAT) changes were simulated by adjusting elevation in the models, and cloud cover changes were examined by altering the partitioning of direct beam and diffuse radiation within the calculation for potential incoming solar radiation (PISR). The effects of changes in MAAT on equilibrium permafrost distribution proved to be more important than those due to cloud cover. Under a ?2 K scenario (approximating Little Ice Age conditions), permafrost expanded into an additional 22?C43% of the study areas as zonal boundaries descended by 155?C290 m K^???1. Under warming scenarios, permafrost probabilities progressively declined and zonal boundaries rose in elevation. A MAAT change of +5 K, caused two of the areas to become essentially permafrost-free. The absolute values of these predictions were affected up to ±10% when lapse rates were altered by ±1.5 K km^???1 but patterns and trends were maintained. A higher proportion of diffuse radiation (greater cloud cover) produced increases in permafrost extent of only 2?C4% while decreases in the diffuse radiation fraction had an equal but opposite effect. Notwithstanding the small change in overall extent, permafrost probabilities on steep south-facing slopes were significantly impacted by the altered partitioning. Combined temperature and PISR partitioning scenarios produced essentially additive results, but the impact of changes in the latter declined as MAAT increased. The modelling illustrated that mountain permafrost in the discontinuous zone is sensitive spatially to long-term climate change and identified those areas where changes may already be underway following recent atmospheric warming.     

Polar amplification of climate change in coupled models

The Northern Hemisphere polar amplification of climate change is documented in models taking part in the Coupled Model Intercomparison Project and in the new version of the Community Climate System Model. In particular, the magnitude, spatial distribution, and seasonality of the surface warming in the Arctic is examined and compared among the models. The range of simulated polar warming in the Arctic is from 1.5 to 4.5 times the global mean warming. While ice-albedo feedback is likely to account for much of the polar amplification, the strength of the feedback depends on numerous physical processes and parametrizations which differ considerably among the models. Nonetheless, the mean sea-ice state in the control (or present) climate is found to influence both the magnitude and spatial distribution of the high-latitude warming in the models. In particular, the latitude of the maximum warming is correlated inversely and significantly with sea-ice extent in the control climate. Additionally, models with relatively thin Arctic ice cover in the control climate tend to have higher polar amplification. An intercomparison of model results also shows that increases in poleward ocean heat transport at high latitudes and increases in polar cloud cover are significantly correlated to amplified Arctic warming. This suggests that these changes in the climate state may modify polar amplification. No significant correlation is found between polar amplification and the control climate continental ice and snow cover.     

Sea-ice and its response to CO2 forcing as simulated by global climate models

The simulation of sea-ice in global climate models participating in the Coupled Model Intercomparison Project (CMIP1 and CMIP2) is analyzed. CMIP1 simulations are of the unpertubed control climate whereas in CMIP2, all models have been forced with the same 1% yr^–1 increase in CO₂ concentration, starting from a near equilibrium initial condition. These simulations are not intended as forecasts of climate change, but rather provide a means of evaluating the response of current climate models to the same forcing. The difference in modeled response therefore indicates the range (or uncertainty) in model sensitivity to greenhouse gas and other climatic perturbations. The results illustrate a wide range in the ability of climate models to reproduce contemporary sea-ice extent and thickness; however, the errors are not obviously related to the manner in which sea-ice processes are represented in the models (e.g. the inclusion or neglect of sea-ice motion). The implication is that errors in the ocean and atmosphere components of the climate model are at least as important. There is also a large range in the simulated sea-ice response to CO₂ change, again with no obvious stratification in terms of model attributes. In contrast to results obtained earlier with a particular model, the CMIP ensemble yields rather mixed results in terms of the dependence of high-latitude warming on sea-ice initial conditions. There is an indication that, in the Arctic, models that produce thick ice in their control integration exhibit less warming than those with thin ice. The opposite tendency appears in the Antarctic (albeit with low statistical significance). There is a tendency for models with more extensive ice coverage in the Southern Hemisphere to exhibit greater Antarctic warming. Results for the Arctic indicate the opposite tendency (though with low statistical significance).A list of the CMIP modeling groups is included in the Acknowledgements section.