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Climate change has been and will be accompanied by widespread changes in surface temperature. It is clear that these changes include global-wide increases in mean surface temperature and changes in temperature variance that are more regionally-dependent.sup.1-3. It is less clear whether they also include changes in the persistence of surface temperature. This is important as the effects of weather events on ecosystems and society depend critically on the length of the event. Here we provide an extensive survey of the response of surface temperature persistence to climate change over the twenty-first century from the output of 150 simulations run on four different Earth system models, and from simulations run on simplified models with varying representations of radiative processes and large-scale dynamics. Together, the results indicate that climate change simulations are marked by widespread changes in surface temperature persistence that are generally most robust over ocean areas and arise due to a seemingly broad range of physical processes. The findings point to both the robustness of widespread changes in persistence under climate change, and the critical need to better understand, simulate and constrain such changes. A survey of climate change simulations from different models indicates widespread changes in surface temperature persistence under global warming that may be attributable to a broad range of physical processes., Author(s): Jingyuan Li [sup.1] , David W. J. Thompson [sup.1] [sup.2] Author Affiliations: (1) Department of Atmospheric Science, Colorado State University, Fort Collins, USA (2) School of Environmental Sciences, University [...]

Snowfall is an important element of the climate system, and one that is expected to change in a warming climate (1-4). Both mean snowfall and the intensity distribution of snowfall are important, with heavy snowfall events having particularly large economic and human impacts (5-7). Simulations with climate models indicate that annual mean snowfall declines with warming in most regions but increases in regions with very low surface temperatures (3,4). The response of heavy snowfall events to a changing climate, however, is unclear. Here I show that in simulations with climate models under a scenario of high emissions of greenhouse gases, by the late twenty-first century there are smaller fractional changes in the intensities of daily snowfall extremes than in mean snowfall over many Northern Hemisphere land regions. For example, for monthly climatological temperatures just below freezing and surface elevations below 1,000 metres, the 99.99th percentile of daily snowfall decreases by 8% in the multimodel median, compared to a 65% reduction in mean snowfall. Both mean and extreme snowfall must decrease for a sufficiently large warming, but the climatological temperature above which snowfall extremes decrease with warming in the simulations is as high as -9°C, compared to -14°C for mean snowfall. These results are supported by a physically based theory that is consistent with the observed rain-snow transition. According to the theory, snowfall extremes occur near an optimal temperature that is insensitive to climate warming, and this results in smaller fractional changes for higher percentiles of daily snowfall. The simulated changes in snowfall that I find would influence surface snow and its hazards; these changes also suggest that it may be difficult to detect a regional climate-change signal in snowfall extremes., Extremes of daily precipitation (including liquid and solid precipitation) are found to increase in intensity with climate warming in observations and simulations (8-10), and this is physically consistent with greater [...]

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1523-1739.2007.00814.x Byline: LETICIA GOMEZ-MENDOZA (*), LAURA ARRIAGA ([dagger][double dagger]) Keywords: climate-change scenarios; GARP; HadCM2; models; Pinus; Quercus; species distribution; temperate forests Abstract: Abstract: We examined the vulnerability of 34 species of oaks (Quercus) and pines (Pinus) to the effects of global climate change in Mexico. We regionalized the HadCM2 model of climate change with local climatic data (mean annual temperature and rainfall) and downscaled the model with the inverse distance-weighted method. Databases of herbaria specimens, genetic algorithms (GARP), and digital covers of biophysical variables that affect oaks and pines were used to project geographic distributions of the species under a severe and conservative scenario of climate change for the year 2050. Starting with the current average temperature of 20.2 [degrees]C and average precipitation of 793 mm, under the severe warming scenario mean temperature and precipitation changed to 22.7 [degrees]C and 660 mm, respectively, in 2050. For the conservative warming scenario, these variables shifted to 21.8 [degrees]C and 721 mm. Responses to the different scenarios of climate change were predicted to be species-specific and related to each species climate affinity. The current geographic distribution of oaks and pines decreased 7-48% and 0.2-64%, respectively. The more vulnerable pines were Pinus rudis, P. chihuahuana, P. oocarpa, and P. culminicola, and the most vulnerable oaks were Quercus crispipilis, Q. peduncularis, Q. acutifolia, and Q. sideroxyla. In addition to habitat conservation, we think sensitive pine and oak species should be looked at more closely to define ex situ strategies (i.e., seed preservation in germplasm banks) for their long-term conservation. Modeling climatic-change scenarios is important to the development of conservation strategies. Abstract (Spanish): Modelando el Efecto del Cambio Climatico sobre la Distribucion de Especies de Encino y Pino de Mexico Resumen: Examinamos la vulnerabilidad de 34 especies de encinos (Quercus) y pinos (Pinus) a los efectos del cambio climatico global en Mexico. Regionalizamos el modelo de cambio climatico HadCM2 con datos climaticos locales (temperatura y precipitacion media anual) y redujimos la escala del modelo con el metodo de distancia inversa. Utilizamos bases de datos de especimenes de herbario, algoritmos geneticos (GARP) y coberturas digitales de variables biofisicas que afectan a pinos y encinos para proyectar distribuciones geograficas de las especies bajo un escenario de cambio climatico severo al ano 2050 y uno conservador. Partiendo de la temperatura promedio actual de 22.2 [degrees]C y la precipitacion promedio de 793 mm, la temperatura y la precipitacion cambiaron a 22.7 [degrees]C y 660 mm, respectivamente, en 2050 en el escenario severo. En el escenario conservador, estas variables cambiaron a 21.8 [degrees]C y 721 mm. Se predijo que las respuestas a los diferentes escenarios de cambio climatico serian especificas por especie y relacionadas con la afinidad climatica de cada especie. La distribucion geografica actual de encinos y pinos decrecio 7-48% y 0.2-64% respectivamente. Las especies mas vulnerables de pino fueron Pinus rudis, P. chihuahuana, P. oocarpa y P. culminicola, y las especies mas vulnerables de encino fueron Quercus crispipilis, Q. peduncularis, Q. acutifolia y Q. sideroxyla. Adicionalmente a la conservacion del habitat, pensamos que las especies sensibles de pino y encino deberian ser vistas mas de cerca para definir estrategias ex situ (i.e., preservacion de semillas en bancos de germoplasma) para su conservacion a largo plazo. El modelado de escenarios de cambio climatico es importante para el desarrollo de estrategias de conservacion. Author Affiliation: (*)Instituto de Geografia, Universidad Nacional Autonoma de Mexico, Circuito Exterior, Ciudad Universitaria, Mexico, D.F. C.P. 14510, Mexico ([dagger])Centro de Investigaciones Biologicas del Noroeste, S.C. Mar Bermejo 195, Col. Playa Palo de Santa Rita, La Paz 23090, Baja California Sur, Mexico Article History: Paper submitted July 25, 2006; revised manuscript accepted June 11, 2007. Article note: ([double dagger]) Address correspondence to L. Arriaga, email larriaga04@cibnor.mx

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jenvman.2005.01.008 Byline: Peter Romilly Abstract: Climate change has important implications for business and economic activity. Effective management of climate change impacts will depend on the availability of accurate and cost-effective forecasts. This paper uses univariate time series techniques to model the properties of a global mean temperature dataset in order to develop a parsimonious forecasting model for managerial decision-making over the short-term horizon. Although the model is estimated on global temperature data, the methodology could also be applied to temperature data at more localised levels. The statistical techniques include seasonal and non-seasonal unit root testing with and without structural breaks, as well as ARIMA and GARCH modelling. A forecasting evaluation shows that the chosen model performs well against rival models. The estimation results confirm the findings of a number of previous studies, namely that global mean temperatures increased significantly throughout the 20th century. The use of GARCH modelling also shows the presence of volatility clustering in the temperature data, and a positive association between volatility and global mean temperature. Author Affiliation: Economics, Finance and Statistics Division, Dundee Business School, University of Abertay Dundee, Bell Street, Dundee DD1 1HG, Scotland

A study of the question of accounting for the anthropogenic contribution of different countries or groups of countries to the increase of global temperature, instead of being restricted to their carbon emissions as adopted in the Kyoto protocol on sharing of responsibility are discussed. A discussion on the methodology and scientific aspects of the Brazilian Proposal (BP) by SBSTA/UNFCCC and results of energy sector and land use change contributions to the climate response by different countries is also presented.

One of the sustainable development challenges to the globe, is climate disruption resulting from greenhouse emissions. Emissions are calculated as, the difference between a project emission and its baseline.

A new model is presented describing aboveground net primary production in arid ecosystems, which includes the separation of functional types. The model is applied to Patagonia's Occidental District, and distinguishes between climatic variables from precipitation and from precipitation and temperature.

Research into the response of several climate models to a rise in greenhouse-gas concentrations indicates that interannual variability of Northern Hemisphere wintertime sea-level pressure is dominated by an almost axisymmetric spatial pattern centred over the Arctic. This trend is reproduced only by models that resolve stratospheric dynamics. Models with no dynamical stratosphere do not simulate the observed trend in the Arctic Oscillation. It appears that the stratosphere influences climate at the surface by modulating energy propagation out of the troposphere.

The Intergovernmental Panel on Climate Change's 1995 report includes several CO2 emission models that would allow stabilization of atmospheric CO2 at levels between 350-1,000 ppm. However, the illustrations do not take into account the changing ability over time of the land and ocean to act as a sink for anthropogenic CO2. A new simulation of global warming focuses on the ocean carbon sink covering the period from 1765-2065. Details of the study are presented.

The world's climate systems and terrestrial ecosystems are interrelated, particularly the exchange of carbon between the atmosphere, vegetation and soils. A new model, focused on the terrestrial carbon sink, shows that the terrestrial ecosystem carbon fluxes strongly influence and respond to climate change and atmospheric CO2 increase.

Increasing greenhouse gases could cause serious ozone depletion over the Arctic, as well as making the severity and duration of the Antarctic ozone hole worse, according to research into the links between projected future emissions of greenhouse gases and levels of ozone-depleting halogen species. It has been established that Arctic ozone loss is very sensitive to a fall in the frequency of sudden stratospheric warmings. This is in alignment with earlier research showing that the presence or absence of mid-winter sudden stratospheric warming is a key element in determining whether an Arctic ozone hole will arise under doubled-carbon dioxide conditions.

It has been possible to develop two basic models that reproduce quite well the succession of glacial-interglacial cycles over the late Pleistocene. The first model has three separate states: interglacial, mild glacial and full glacial. The second model is an extension of the first. The three state-model was found to be quite resilient to changes in its parameters. It is clear that the geological record can easily be explained in the framework of the classical astronomical theory.

To help transform our understanding of the biosphere, ecologists -- like climate scientists -- should simulate whole ecosystems, argue Drew Purves and colleagues., Author(s): Drew Purves [sup.1] , Jörn P. W. Scharlemann [sup.2] , Mike Harfoot [sup.3] , Tim Newbold [sup.4] , Derek P. Tittensor [sup.5] , Jon Hutton [sup.6] , Stephen Emmott [...]

It has been shown to be possible to use a basic coupled atmosphere-ocean climate model to indicate that the Atlantic thermohaline circulation depends on the rate of change of the carbon dioxide (CO2) concentration in the atmosphere. A rise in atmospheric CO2 concentration in this climate model causes temporary changes which are very similar to those in three-dimensional coupled atmosphere-ocean models. It was concluded that the atmosphere-ocean system involves critical levels of atmospheric CO2 beyond which permanent changes of the Atlantic thermohaline circulation will probably occur.

The impact on a doubled-carbon dioxide climate of structural vegetation and physiological feedbacks is calculated using an equilibrium vegetation model coupled to a general circulation model. Physiological vegetation-climate feedbacks are partly offset by vegetation structure changes in the long term, although important regional-scale effects are yielded from vegetation feedbacks. Climatic change induced by a CO2-enriched atmosphere could change vegetation cover density to ultimately produce a further climate feedback.

A model using grey programming (GP) is applicable to risk assessment procedures based on climate change uncertainties, which cannot be analyzed through stochastic or fuzzy quantification. The GP model allows comparison of the importance of climatic uncertainty with other uncertainties involved. The model decreases the computational requirements, and does away with the need for distribution information for model parameters, thus making the technique more practical. A hop, skip, and jump formulation of GP is used to analyze the expansion of forestry and agriculture in the Mackenzie River Basin.

Bayesian methods used for analyzing climate change uncertainties and their effects on water resource systems are more practical and easier to understand as compared to alternative paradigms for analyzing uncertainty. Bayesian analysis is capable of yielding inferences and recommendations for decisions which conform to these inferences. The methods have a comprehensive and coherent framework based on normatively appealing theoretical assumptions. The methods are capable of including different sources of information, such as subjective opinions, historical observations, and model outputs.

Dempster-Shafer theory for representing climate change uncertainties allows for more flexibility than the Bayesian approach when quantifying weak information. The approach also reveals the results of decision analysis more accurately. This is achieved by using probabilities which are assigned to intervals of values that can have chosen interval size for all inputs, whether overlapping or not. However, both the approaches yield the same results when the uncertainties are less acute.

Future changes in climate and atmospheric C[O.sub.2] concentration will change the hydrologic cycle, affecting important soil-plant-water interactions, which in turn affect soil erosion rates. Climate and C[O.sub.2] changes can be [...]

Integrated assessment models of global climate change suffer from inadequate representations of impact valuation, adaptive response, formation and effects of policies and the determinants of emissions trends. Integrated assessment models may be improved with other forms of integration, integration by formal modeling and representation of the decisions of other parties through dialogue. Suggestions on how to achieve consensus on best practices for integrated assessment models are presented.

Climate change policymakers are constrained by uncertainties regarding the avoided costs of climate change and the costs of greenhouse gas emission abatement. These uncertainties may be mitigated by using a sequential approach. The no-regret policy and the innovation process exploitation policy minimize learning time when inertia constraints in the decision process are taken care of.

Technical innovation in energy technologies and systems are induced by need but are restrained by potentially large transitional costs. Nevertheless, it is evident that energy systems accommodate external pressures by adapting slowly over time. A simple integrated model of optimal greenhouse gas abatement over time which incorporates fixed and transitional elements was developed to show that induced technical change and other adaptive responses in energy systems affect climate change assessments and are thus important for abatement policies.

Climate change policymakers have been criticized for creating bias against future generations by ignoring future costs and benefits in the formulation of climate change policies. To answer these criticisms, cost-benefit analysis was used to include intergenerational equity and discounting in climate change policy. The results show that the cost-benefit criterion obscures basic problems and thus cannot be a definitive basis for committing to long-term climate change policies. These problems include drastic, disastrous changes in the world's climate and the economic consequences of these changes.

The Asian Pacific Integrated Model (AIM) was developed to generate scenarios of future greenhouse gas emissions and the impact of these emissions on global warming in the Asia-Pacific region. The AIM emission module and the AIM impact module are linked by global greenhouse gas cycle amd climate change models. The primary impact of climate change on the region's water resources and natural vegetation was assessed using scenarios built with the AIM.

The Evaluation Strategies to address Climate change by Adapting to and Preventing Emissions (ESCAPE) is an integrated assessment model of climate change developed in Europe to generate scenarios of greenhouse gas emissions and their impact on the sea level and the global climate. To solve certain limitations of ESCAPE, its global climate module and regional climate scenario-generating module were improved. The model with the enhanced modules is called Model for the Assessment of Greenhouse gas Induced Climate Change.

The CETA is an integrated assessment model of climate change that considers energy consumption, energy technology choice, worldwide economic growth, global warming and global warming costs. The CETA was used to examine three alternative regimes for international control of carbon dioxide emissions between two regions, only one of which is able to optimally control its CO2 emissions. The results show that the regime in which region one and region two jointly control CO2 emissions and region one pays region two to participate is the best alternative for international control of CO2 emissions.

An overview of integrated assessment models of climate change for use in policymaking is presented. Various integrated assessment models have been used in the past for studies of the weather and acid rain. Such models should satisfy certain criteria before they can be used in studies of climate change. The integrated assessment of climate change at Carnegie Mellon University is presented as an example of policy-motivated integrated assessment.

A climate-ocean model based on data since 1856 shows that changes in the amount of solar radiation reaching the Earth helped to raise global temperatures since that time but that the increase in greenhouse gases (GHGs) was the more important factor. The model compared data on GHG levels, recurring fluctuations in solar irradiance and atmospheric temperature. The impressive but circumstantial evidence for the Sun's role in global warming must be taken into account when considering the effects of GHG concentrations.

Too little is known about the hydrological cycle and current climatic models contain too many discrepancies for the long-range impact of rising greenhouse gas levels to be properly evaluated. The hydrological cycle determines how much water is available for economically important needs such as farming, forests and rivers. A comparison of climatic models shows that they are too rife with uncertainties to gauge how greenhouse warming might change the hydrological cycle. Greatly increased international research on the hydrological cycle and more cooperation among climate modellers are needed.

The first paleoecological analysis of a complete sedimentary record spanning the period from the late Pleistocene to the present from lowland Panama, documents changes in lowland vegetation communities through major climatic change and the onset of human disturbance. Past sympatry is found among presently allopatric species, suggesting that tropical forest communities are not species-stable through time. Late Pleistocene floras at Lake La Yeguada (elevation 650 m), Panama, had high relative abundance of montane forest elements, e.g., Quercus and Magnolia, existing some 900 m below their present range, suggesting a climatic cooling of [is nearly equal] 5 [degrees] C below present. This descent of montane forest taxa onto lowland hilltops denied the ground to postulated lowland rain forest refugia. The late Pleistocene (14 350-11 050 yr BP) was not uniformly cool and was interrupted by brief phases of near present-day warming. The onset of the Holocene was abrupt, taking < 100 yr, and was almost coincidental with the start of human forest disturbance. Changes in climate at La Yeguada were found to be largely synchronous with those documented at Lake Valencia, Venezuela, but no fine-scale climatic synchrony was apparent with South American or European sites, and significant departures from the predictions of published climatic circulation models are found.

Climatic response to changes in solar insolation usually lags by several thousand years, but a core from the Indian Ocean suggests that monsoonal changes over the last 24,000 years often take 300 years or fewer. Rather than a gradual change there appear to have been several distinct, relatively brief steps during the transition from a glacial to a post-glacial climate. The rapid response may be due to albedo changes from snow cover in Asia.

A new climatic model based on data from 1765 to 1985 showed that variations in the solar cycle contributed to the rise in global temperatures during that period but not enough to oust human-produced greenhouse gases as the dominant cause. The upwelling-diffusion energy-balance model compared the likely climatic effects of the solar cycle and the greenhouse gases both by themselves and together. Global warming was found to result chiefly from the gases' rising concentrations rather than from variations in solar activity.

The Rossby Centre regional climate model (RCA2) is integrated over the Arctic Ocean as part of the international Arctic Regional Climate Model Intercomparison Project (2) (ARCMIP). The sea-ice processes, atmospheric stable boundary layers, ice-cloud processes and radiative transfer in a clean, cold and dry atmosphere particularly over the Arctic Ocean are all crucial to the model.

A summary of the hydrological studies of climate changes carried out within Swedish Regional Climate Modeling Programme (SWECLIM) is presented. It is concluded that a projected hydrological change is just as dependent on the choice of the global climate model boundary conditions as the choice of anthropogenic emissions scenario.

The atmospheric component of Rossby Centre Atmospheric regional Climate Model (RCA2) is described. The quality of near-surface parameters is investigated, particularly in case of temperature, precipitation, the surface energy budget and cloud cover.

A review of the Swedish Regional Climate Modeling Programme, SWECLIM activities on development of regional dmodeling, Nordic climate change projections, hydrological impact studies and a set of targeted process and data studies are presented. Further some recommendations are made for future activities.

It is hard to imagine beaches in northern Greenland or driftwood washing up on islands of Canada's Arctic archipelago, but both were a reality some 6,000 years ago. 'At least [...]

Aerosols such as black carbon and dust particles seem to have a greater effect on the Tibetan Plateau's snow than does anthropogenic climate change. Yun Qian of the Pacific Northwest [...]

Arctic Ocean surface temperatures recorded between 1950 and 1990 failed to detect the warming trend that would confirm the greenhouse-related rise in atmospheric temperature required by widely-accepted global climate models. In fact, Arctic Ocean temperatures went down during this period rather than up. However, these Arctic temperatures should be interpreted cautiously since they do not include data from marginal ice zones where the effects of global warming would be more apparent.

The world's most sophisticated climate models fail to adequately replicate climate at high latitudes and over continents' interiors during ancient periods of greenhouse-gas-induced warming: the wintertime predictions are consistently too [...]

Research describing international aspects of climate change mitigation is presented. In particular the efficiency of international cooperation is analysed by linking individual national programmes in a mathematical model.