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The Earth's climate is regulated by the energy absorbed from the Sun and the loss of energy to space through both the reflection of the solar radiation itself and the [...]

Stratospheric variability is examined in a vertically extended version of the Met Office global climate model. Equatorial variability includes the simulation of an internally generated quasi-biennial oscillation (QBO) and semiannual oscillation (SAO). Polar variability includes an examination of the frequency of sudden stratospheric warmings (SSW) and annular mode variability. Results from two different horizontal resolutions are also compared. Changes in gravity wave filtering at the higher resolution result in a slightly longer QBO that extends deeper into the lower stratosphere. At the higher resolution there is also a reduction in the occurrence rate of sudden stratospheric warmings, in better agreement with observations. This is linked with reduced levels of resolved waves entering the high-latitude stratosphere. Covariability of the tropical and extratropical stratosphere is seen, linking the phase of the QBO with disturbed NH winters, although this linkage is sporadic, in agreement with observations. Finally, tropospheric persistence time scales and seasonal variability for the northern and southern annular modes are significantly improved at the higher resolution, consistent with findings from other studies. DOI: 10.1175/2010JAS3338.1

Current estimates of the European windstorm climate and their associated losses are often hampered by either relatively short, coarse resolution or inhomogeneous datasets. This study tries to overcome some of these shortcomings by estimating the European windstorm climate using dynamical seasonal-to-decadal (s2d) climate forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF). The current s2d models have limited predictive skill of European storminess, making the ensemble forecasts ergodic samples on which to build pseudoclimates of 310-396 yr in length. Extended winter (October-April) windstorm climatologies are created using scalar extreme wind indices considering only data above a high threshold. The method identifies up to 2363 windstorms in s2d data and up to 380 windstorms in the 40-yr ECMWF Re-Analysis (ERA-40). Classical extreme value analysis (EVA) techniques are used to determine the windstorm climatologies. Differences between the ERA-40 and s2d windstorm climatologies require the application of calibration techniques to result in meaningful comparisons. Using a combined dynamical-statistical sampling technique, the largest influence on ERA-40 return period (RP) uncertainties is the sampling variability associated with only 45 seasons of storms. However, both maximum likelihood (ML) and L-moments (LM) methods of fitting a generalized Pareto distribution result in biased parameters and biased RP at sample sizes typically obtained from 45 seasons of reanalysis data. The authors correct the bias in the ML and LM methods and find that the ML-based ERA-40 climatology overestimates the RP of windstorms with RPs between 10 and 300 yr and underestimates the RP of windstorms with RPs greater than 300 yr. A 50-yr event in ERA-40 is approximately a 40-yr event after bias correction. Biases in the LM method result in higher RPs after bias correction although they are small when compared with those of the ML method. The climatologies are linked to the Swiss Reinsurance Company (Swiss Re) European windstorm loss model. New estimates of the risk of loss are compared with those from historical and stochastically generated windstorm fields used by Swiss Re. The resulting loss-frequency relationship matches well with the two independently modeled estimates and clearly demonstrates the added value by using alternative data and methods, as proposed in this study, to estimate the RP of high RP losses. DOI: 10.1175/2010JAMC2133.1

Byline: Eric P. Salathe (1), L. Ruby Leung (2), Yun Qian (2), Yongxin Zhang (3) Abstract: Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional climate of the State of Washington. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year regional climate simulations using the Weather Research and Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970--1999) to the mid twenty-first century (2030--2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations. Author Affiliation: (1) JISAO/CSES Climate Impacts Group, University of Washington, Seattle, WA, USA (2) Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, WA, USA (3) Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, USA Article History: Registration Date: 24/03/2010 Received Date: 04/06/2009 Accepted Date: 23/03/2010 Online Date: 05/05/2010

An ice nucleation parameterization based on classical nucleation theory, with aerosol-specific parameters derived from experiments, has been implemented into a global climate model--the Community Atmosphere Model (CAM)-Oslo. The parameterization treats immersion, contact, and deposition nucleation by mineral dust, soot, bacteria, fungal spores, and pollen in mixed-phase clouds at temperatures between 0[degrees] and -38[degrees]C. Immersion freezing is considered for insoluble particles that are activated to cloud droplets, and deposition and contact nucleation are only allowed for uncoated, unactivated aerosols. Immersion freezing by mineral dust is found to be the dominant ice formation process, followed by immersion and contact freezing by soot. The simulated biological aerosol contribution to global atmospheric ice formation is marginal, even with high estimates of their ice nucleation activity, because the number concentration of ice nucleation active biological particles in the atmosphere is low compared to other ice nucleating aerosols. Because of the dominance of mineral dust, the simulated ice nuclei concentrations at temperatures below -20[degrees]C are found to correlate with coarse-mode aerosol particle concentrations. The ice nuclei (IN) concentrations in the model agree well overall with in situ continuous flow diffusion chamber measurements. At individual locations, the model exhibits a stronger temperature dependence on IN concentrations than what is observed. The simulated IN composition (77% mineral dust, 23% soot, and [10.sup.-5]% biological particles) lies in the range of observed ice nuclei and ice crystal residue compositions. DOI: 10.1175/2010JAS3425.1

Accurately accounting for radiative energy balance between the incoming solar and the outgoing infrared radiative fluxes is very important in modeling the Earth's climate. Water vapor absorption plays a critical role in the radiative heating rate profile in the midtroposphere by strongly absorbing both infrared and solar radiation in several absorption bands throughout the electromagnetic spectrum. One of the most important of these absorption bands is in the far-infrared portion of the spectrum, where the far-infrared is defined here to be wavelengths longer than 15 microns. A large fraction (~40%) of the outgoing infrared flux is emitted by water vapor in the far-infrared. Errors in the radiative transfer models associated with the far-infrared and other strong water vapor absorption bands will therefore affect the calculation of the planet's total outgoing radiative flux and its vertical distribution of the radiant energy; these errors may result in inaccurate modeling of the general circulation of the planet. A set of field experiments, called the Radiative Heating in Underexplored Bands Campaigns (RHUBC), has been conducted as part of the Atmospheric Radiation Measurement (ARM) program. The RHUBC campaigns deployed spectrally resolved far-infrared spectrometers alongside other ARM observations in extremely dry environments to provide a robust and complete dataset that allows radiative transfer models to be evaluated in the far-infrared and other spectral regions where water vapor absorbs strongly. RHUBC I was conducted in February-March 2007 in Barrow, Alaska, and RHUBC II was conducted in August-October 2009 in the Atacama Desert region of Chile at an altitude of 5.3 kin. The motivation for and initial results from these experiments are described, as well as the implications for global climate models. DOI: 10.1175/2010BAMS2904.1

The climatology of a stratosphere-resolving version of the Met Office's climate model is studied and validated against ECMWF reanalysis data. Ensemble integrations are carried out at two different horizontal resolutions. Along with a realistic climatology and annual cycle in zonal mean zonal wind and temperature, several physical effects are noted in the model. The time of final warming of the winter polar vortex is found to descend monotonically in the Southern Hemisphere, as would be expected for purely radiative forcing. In the Northern Hemisphere, however, the time of final warming is driven largely by dynamical effects in the lower stratosphere and radiative effects in the upper stratosphere, leading to the earliest transition to westward winds being seen in the midstratosphere. A realistic annual cycle in stratospheric water vapor concentrations--the tropical 'tape recorder'--is captured. Tropical variability in the zonal mean zonal wind is found to be in better agreement with the reanalysis for the model run at higher horizontal resolution because the simulated quasibiennial oscillation has a more realistic amplitude. Unexpectedly, variability in the extratropics becomes less realistic under increased resolution because of reduced resolved wave drag and increased orographic gravity wave drag. Overall, the differences in climatology between the simulations at high and moderate horizontal resolution are found to be small. DOI: 10.1175/2009JAS3337.1

Despite considerable technological advances, aviation impacts on global climate are significant and may constitute a future constraint on the continued growth of air travel. The most important but least understood component in aviation climate impact assessments are contrails, which form as line-shaped ice clouds (linear contrails) and transform into irregularly shaped ice clouds (contrail cirrus) in favorable meteorological conditions. No reliable best estimate of the contribution of contrail cirrus to climate change exists, but statistical evidence from cirrus trend analyses suggests a potentially large contribution. This article reviews the scientific knowledge and key problems regarding the modeling of the life cycle of contrail cirrus (including linear contrails), their global climate impact, and the validation of model simulations with suitable observational datasets. The prerequisites for global modeling of contrail cirrus, such as the representation of ice supersaturation and the processes governing contrail cirrus evolution as well as improvements in the cloud schemes regarding cirrus, are discussed. Recommendations are given for avenues of research to ensure that future decisions aimed at mitigating the climate impact of contrails and contrail cirrus are based on increasingly sound scientific knowledge. DOI: 10.1175/2009BAMS2656.1

This study quantifies the ranges of climate model biases in surface air temperature for July and August (summer temperature) and daily total insolation for May-October (warm-season insolation) that can give simulated regional paddy rice yields with a bias within [+ or -]2.5% of the 20-yr mean observed regional yield. The following four sets of three meteorological elements (daily maximum and minimum temperatures and daily total insolation) from daily climate model outputs were used as meteorological inputs for a large-scale crop model for irrigated paddy rice: 1) raw climate model outputs of all meteorological elements, 2) bias-corrected temperatures and raw climate model outputs of insolation, 3) bias-corrected insolation and raw climate model outputs of temperatures, and 4) bias-corrected climate model outputs of all meteorological elements. These meteorological inputs were sourced from seven coupled general circulation models, one regional climate model, and one reanalysis dataset. Crop model simulations with artificially biased meteorological inputs were also used. By using the approximation formula derived from these crop model simulation results and the Monte Carlo simulation technique, it was found that climate model outputs with biases within [+ or -]0.6[degrees]C and [+ or -]3% for summer temperature and warm-season insolation, respectively, could result in a simulated regional paddy rice yield with a bias within [+ or -]2.5% of the 20-yr mean observed regional yield. The simulated regional yield was less biased not only when the biases of two meteorological inputs were small but also when the cold or warm bias of summer temperature and the overestimation of warm-season insolation were balanced through the crop model processes. The methodology presented here will lead to a better and more comprehensive understanding of the nature of error propagation from a climate model to an application model and will facilitate the selection of climate models suitable for specific applications. DOI: 10.1175/2009JAMC2225.1

Snow albedo plays an important role in land models for weather, climate, and hydrometeorological studies, but its treatment in various land models still contains significant deficiencies. Complementary to previous studies that evaluated the snow albedo as part of an overall land model study, the snow albedo formulations as used in four major weather forecasting and climate models [European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP) 'Noah' land model, National Center for Atmospheric Research (NCAR) Community Land Model (CLM3), and NCEP global model] were directly evaluated here using multiyear Boreal Ecosystem--Atmosphere Study (BOREAS) in situ data over grass and forest sites. First, four idealized cases over grass and forest sites were designed to understand better the different albedo formulations in these models. Then the BOREAS data were used to evaluate snow albedo and relevant formulations and to identify deficiencies of each model. Based on these analyses, suggestions that involve only minor changes in parameters or formulations were made to significantly reduce these deficiencies of each model. For the ECMWF land model, using the square root of snow water equivalent (SWE), rather than SWE itself, in the computation of snow fraction would significantly reduce the underestimation of albedo over grass. For the NCEP Noah land model, reducing (increasing) the critical SWE for full snow cover over short (tall) vegetation would reduce the underestimate (overestimate) of snow albedo over the grass (forest) site. For the NCAR CLM3, revising the coefficient used in the ground snow-fraction computation would substantially reduce the albedo underestimation over grass. For the albedo formulations in the NCEP global model, replacing the globally constant fresh snow albedo by the vegetation-type-dependent Moderate-Resolution Imaging Spectroradiometer (MODIS) maximum snow albedo would significantly improve the overestimation of model albedo over forest. DOI: 10.1175/2009JAMC2134.1

Byline: Anabela Carvalho (1), Mike D. Flannigan (2), Kim A. Logan (2), Lynn M. Gowman (2), Ana Isabel Miranda (1), Carlos Borrego (1) Abstract: In this study, we investigated the impact of future climate change on fire activity in 12 districts across Portugal. Using historical relationships and the HIRHAM (High Resolution Hamburg Model) 12 and 25 km climate simulations, we assessed the fire weather and subsequent fire activity under a 2 x CO.sub.2 scenario. We found that the fire activity prediction was not affected by the spatial resolution of the climate model used (12 vs. 25 km). Future area burned is predicted to increase 478% for Portugal as a whole, which equates to an increase from 1.4% to 7.8% of the available burnable area burning annually. Fire occurrence will also see a dramatic increase (279%) for all of Portugal. There is significant spatial variation within these results the north and central districts of the country generally will see larger increases in fire activity. Author Affiliation: (1) CESAM & Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal (2) Canadian Forest Service, Great Lakes Forestry Centre, Sault Ste Marie, ON, P6A 2E5, Canada Article History: Registration Date: 31/07/2009 Received Date: 23/03/2007 Accepted Date: 27/05/2009 Online Date: 12/09/2009

This note examines the sensitivity of simulated U.S. warm-season precipitation in the Weather Research and Forecasting model (WRF), used as a nested regional climate model, to variations in model setup. Numerous options have been tested and a few of the more interesting and unexpected sensitivities are documented here. Specifically, the impacts of changes in convective and land surface parameterizations, nest feedbacks, sea surface temperature, and WRF version on mean precipitation are evaluated in 4-month-long simulations. Running the model over an entire season has brought to light some issues that are not otherwise apparent in shorter, weather forecast type simulations, emphasizing the need for careful scrutiny of output from any model simulation. After substantial testing, a reasonable model setup was found that produced a definite improvement in the climatological characteristics of precipitation over that from the National Centers for Environmental Prediction-National Center for Atmospheric Research global reanalysis, the dataset used for WRF initial and boundary conditions in this analysis. DOI: 10.1175/2009JAMC2186.1

Since the early 1990s, Meteo-France has used an automatic system combining three numerical models to simulate meteorological parameters, snow cover stratification, and avalanche risk at various altitudes, aspects, and slopes for a number of mountainous regions in France. Given the lack of sufficient directly observed long-term snow data, this 'SAFRAN'-Crocus-'MEPRA' (SCM) model chain, usually applied to operational avalanche forecasting, has been used to carry out and validate retrospective snow and weather climate analyses for the 1958-2002 period. The SAFRAN 2-m air temperature and precipitation climatology shows that the climate of the French Alps is temperate and is mainly determined by atmospheric westerly flow conditions. Vertical profiles of temperature and precipitation averaged over the whole period for altitudes up to 3000 m MSL show a relatively linear variation with altitude for different mountain areas with no constraint of that kind imposed by the analysis scheme itself. Over the observation period 1958-2002, the overall trend corresponds to an increase in the annual near-surface air temperature of about 1[degrees]C. However, variations are large at different altitudes and for different seasons and regions. This significantly positive trend is most obvious in the 1500-2000-m MSL altitude range, especially in the northwest regions, and exhibits a significant relationship with the North Atlantic Oscillation index over long periods. Precipitation data are diverse, making it hard to identify clear trends within the high year-to-year variability.

Projections of polar bear (Ursus maritimus) sea ice habitat distribution in the polar basin during the 21st century were developed to understand the consequences of anticipated sea ice reductions on polar bear populations. We used location data from satellite-collared polar bears and environmental data (e.g., bathymetry, distance to coastlines, and sea ice) collected from 1985 to 1995 to build resource selection functions (RSFs). RSFs described habitats that polar bears preferred in summer, autumn, winter, and spring. When applied to independent data from 1996 to 2006, the RSFs consistently identified habitats most frequently used by polar bears. We applied the RSFs to monthly maps of 21st-century sea ice concentration projected by 10 general circulation models (GCMs) used in the Intergovernmental Panel of Climate Change Fourth Assessment Report, under the A1B greenhouse gas forcing scenario. Despite variation in their projections, all GCMs indicated habitat losses in the polar basin during the 21st century. Losses in the highest-valued RSF habitat (optimal habitat) were greatest in the southern seas of the polar basin, especially the Chukchi and Barents seas, and least along the Arctic Ocean shores of Banks Island to northern Greenland. Mean loss of optimal polar bear habitat was greatest during summer; from an observed 1.0 million [km.sup.2] in 1985-1995 (baseline) to a projected multi-model mean of 0.32 million [km.sup.2] in 2090-2099 (-68% change). Projected winter losses of polar bear habitat were less: from 1.7 million [km.sup.2] in 1985 1995 to 1.4 million [km.sup.2] in 2090-2099 (-17% change). Habitat losses based on GCM multi-model means may be conservative; simulated rates of habitat loss during 1985-2006 from many GCMs were less than the actual observed rates of loss. Although a reduction in the total amount of optimal habitat will likely reduce polar bear populations, exact relationships between habitat losses and population demographics remain unknown. Density and energetic effects may become important as polar bears make long-distance annual migrations from traditional winter ranges to remnant high-latitude summer sea ice. These impacts will likely affect specific sex and age groups differently and may ultimately preclude bears from seasonally returning to their traditional ranges. Key words: climate change; general circulation model; IPCC; passive microwave; polar basin; polar bear; radio telemetry; resource selection function; sea ice; SMMR; SSM/I; Ursus maritimus.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.earscirev.2008.12.002 Byline: Charles Harris (a), Lukas U. Arenson (b), Hanne H. Christiansen (c), Bernd Etzelmuller (d), Regula Frauenfelder (d), Stephan Gruber (e), Wilfried Haeberli (e), Christian Hauck (f), Martin Holzle (e), Ole Humlum (d), Ketil Isaksen (g), Andreas Kaab (d), Martina A. Kern-Lutschg (a), Michael Lehning (h), Norikazu Matsuoka (i), Julian B. Murton (j), Jeanette Notzli (e), Marcia Phillips (h), Neil Ross (k), Matti Seppala (l), Sarah M. Springman (m), Daniel Vonder Muhll (n) Keywords: European permafrost; climate change; geothermal monitoring; geothermal modelling; geophysics; slope stability; permafost hazards; permafrost engineering Abstract: We present a review of the changing state of European permafrost within a spatial zone that includes the continuous high latitude arctic permafrost of Svalbard and the discontinuous high altitude mountain permafrost of Iceland, Fennoscandia and the Alps. The paper focuses on methodological developments and data collection over the last decade or so, including research associated with the continent-scale network of instrumented permafrost boreholes established between 1998 and 2001 under the European Union PACE project. Data indicate recent warming trends, with greatest warming at higher latitudes. Equally important are the impacts of shorter-term extreme climatic events, most immediately reflected in changes in active layer thickness. A large number of complex variables, including altitude, topography, insolation and snow distribution, determine permafrost temperatures. The development of regionally calibrated empirical-statistical models, and physically based process-oriented models, is described, and it is shown that, though more complex and data dependent, process-oriented approaches are better suited to estimating transient effects of climate change in complex mountain topography. Mapping and characterisation of permafrost depth and distribution requires integrated multiple geophysical approaches and recent advances are discussed. We report on recent research into ground ice formation, including ice segregation within bedrock and vein ice formation within ice wedge systems. The potential impacts of climate change on rock weathering, permafrost creep, landslides, rock falls, debris flows and slow mass movements are also discussed. Recent engineering responses to the potentially damaging effects of climate warming are outlined, and risk assessment strategies to minimise geological hazards are described. We conclude that forecasting changes in hazard occurrence, magnitude and frequency is likely to depend on process-based modelling, demanding improved understanding of geomorphological process-response systems and their impacts on human activity. Author Affiliation: (a) School of Earth and Ocean Sciences, Cardiff University, CF10 3YE, UK (b) Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada T6G 2W2 (c) Department of Geology, The University Centre in Svalbard, 9171 Longyearbyen, Norway (d) Department of Geosciences, University of Oslo, Blindern, NO-0316 Oslo, Norway (e) Department of Geography, University of Zurich, CH-8057 Zurich, Switzerland (f) Institute for Meteorology and Climate Reasearch, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany (g) The Norwegian Meteorological Institute, Blindern, 0313 Oslo, Norway (h) WSL,Swiss Federal Institute for Snow and Avalanche Research, SLF Davos, CH-7260 Davos Dorf, Switzerland (i) Graduate School of Life and Environmental Sciences, University of Tsukuba, Ibaraki 305-8572, Japan (j) Department of Geography, University of Sussex, Brighton, BN1 9SJ, UK (k) School of Geosciences, University of Edinburgh, West Mains Road, Edinburgh EH9 3JW, UK (l) Department of Geography, University of Helsinki, Helsinki, FIN-00014, Finland (m) Geotechnical Institute, ETH Zurich, CH-8093 Zurich, Switzerland (n) The Swiss Initiative in Systems Biology, ETH-Zurich, CH-8092 Zurich, Switzerland Article History: Received 13 July 2007; Accepted 5 December 2008

This paper presents a novel method based on the application of interpolation techniques to the multicomponent aerosol-cloud parameterization for global climate modeling. Quantifying the aerosol indirect effect still remains a difficult task, and thus developing parameterizations for general circulation models (GCMs) of the microphysics of clouds and their interactions with aerosols is a major challenge for climate modelers. Three aerosol species are considered in this paper--namely sulfate, sea salt, and biomass smoke--and a detailed microphysical chemical parcel model is used to obtain a dataset of points relating the cloud droplet number concentration (CDNC) to the three aerosol input masses. The resulting variation of CDNC with the aerosol mass has some nonlinear features that require a complex but efficient parameterization to be easily incorporated into GCMs. In bicomponent systems, simple interpolation techniques may be sufficient to relate the CDNC to the aerosol mass, but with increasing components, simple methods fail. The parameterization technique proposed in this study employs either the modified Shepard interpolation method or the Hardy multiquadrics interpolation method, and the numerical results obtained show that both methods provide realistic results for a wide range of aerosol mass loadings. This is the first application of these two interpolation techniques to aerosol-cloud interaction studies.

The diurnal cycle of outgoing longwave radiation (OLR) computed by a climate model provides a powerful test of the numerical description of various physical processes. Diurnal cycles of OLR computed by version 3 of the Hadley Centre Atmospheric Model (HadAM3) are compared with those observed by the Earth Radiation Budget Satellite (ERBS) for the boreal summer season (June-August). The ERBS observations cover the domain from 55[degrees]S to 55[degrees]N. To compare the observed and modeled diurnal cycles, the principal component (PC) analysis method is used over this domain. The analysis is performed separately for the land and ocean regions. For land over this domain, the diurnal cycle computed by the model has a root-mean-square (RMS) of 11.4 W [m.sup.-2], as compared with 13.3 W [m.sup.-2] for ERBS. PC-1 for ERBS observations and for the model are similar, but the ERBS result has a peak near 1230 LST and decreases very slightly during night, whereas the peak of the model result is an hour later and at night the OLR decreases by 7 W [m.sup.-2] between 2000 and 0600 LST. Some of the difference between the ERBS and model results is due to the computation of convection too early in the afternoon by the model. PC-2 describes effects of morning/afternoon cloudiness on OLR, depending on the sign. Over ocean in the ERBS domain, the model RMS of the OLR diurnal cycle is 2.8 W [m.sup.-2], as compared with 5.9 W [m.sup.-2] for ERBS. Also, for the model, PC-1 accounts for 66% of the variance, while for ERBS, PC-1 accounts for only 16% of the variance. Thus, over ocean, the ERBS results show a greater variety of OLR diurnal cycles than the model does.

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1365-2745.2008.01422.x Byline: Jens-Christian Svenning (1), Signe Normand (1), Masa Kageyama (2) Keywords: climate change; cryptic refugia; hind-casting; ice age refugia; Last Glacial Maximum; maximum entropy species distribution modelling; Pleistocene; pleniglacial vegetation; range dynamics; tree species distributions Abstract: Summary The Pleistocene is an important period for assessing the impact of climate change on biodiversity. During the Last Glacial Maximum (LGM; 21 000 years ago), large glaciers and permafrost reached far south in Europe. Trees are traditionally thought to have survived only in scattered Mediterranean refugia (southern refugia hypothesis), but a recent proposal suggests that trees may have been much more widely and northerly distributed (northern refugia hypothesis). In this study, the southern vs. northern refugia hypotheses were investigated by estimating the potential LGM distributions of 7 boreal and 15 nemoral widespread European tree species using species distribution modelling. The models were calibrated using data for modern species distributions and climate and projected onto two LGM climate simulations for Europe. Five modelling variants were implemented. Models with moderate to good predictive ability for current species range limits and species richness patterns were developed. Broadly consistent results were obtained irrespective of the climate simulation and modelling variant used. Our results indicate that LGM climatic conditions suitable for boreal species existed across Central and Eastern Europe and into the Russian Plain. In contrast, suitable climatic conditions for nemoral tree species were largely restricted to the Mediterranean and Black Sea regions. Large proportions of these northern and southern regions would have been suitable for a number of boreal or boreal plus nemoral tree species, respectively. These findings are consistent with recent palaeoecological and phylogeographic data regarding LGM distributions of trees and other boreal and nemoral taxa. Synthesis. It is clear that the view of the LGM landscape in Europe as largely treeless, especially north of the Alps, needs to be revised. Trees were probably much more widespread during the LGM than hitherto thought, although patchily distributed at low densities due to low atmospheric CO.sub.2 concentrations and high wind-speeds. The findings presented here help explain the occurrence of mammal assemblages with mixtures of forest, tundra and steppe species at many localities in southern Central and Eastern Europe during the LGM, as well as the phylogeographic evidence for the extra-Mediterranean persistence of many boreal species. Author Affiliation: (1)University of Aarhus, Department of Biological Sciences, Ny Munkegade, building 1540, DK-8000 Aarhus C, Denmark; and (2)Laboratoire des sciences du climat et de l'environnement/IPSL, UMR CEA-CNRS-UVSQ 1572, CE Saclay, l'Orme des Merisiers, Batiment 701, 91191 Gif-sur-Yvette cedex, France Article History: Received 21 December 2007; accepted 23 June 2008 Handling Editor: Richard Bradshaw Article note: (*) Correspondence author. E-mail: svenning@biology.au.dk

Downwelling radiation in six regional models from the Arctic Regional Climate Model Intercomparison (ARCMIP) project is systematically biased negative in comparison with observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment, although the correlations with observations are relatively good. In this paper, links between model errors and the representation of clouds in these models are investigated. Although some modeled cloud properties, such as the cloud water paths, are reasonable in a climatological sense, the temporal correlation of model cloud properties with observations is poor. The vertical distribution of cloud water is distinctly different among the different models; some common features also appear. Most models underestimate the presence of high clouds, and, although the observed preference for low clouds in the Arctic is present in most of the models, the modeled low clouds are too thin and are displaced downward. Practically all models show a preference to locate the lowest cloud base at the lowest model grid point. In some models this happens also to be where the observations show the highest occurrence of the lowest cloud base; it is not possible to determine if this result is just a coincidence. Different factors contribute to model surface radiation errors. For longwave radiation in summer, a negative bias is present both for cloudy and clear conditions, and intermodel differences are smaller when clouds are present. There is a clear relationship between errors in cloud-base temperature and radiation errors. In winter, in contrast, clear-sky cases are modeled reasonably well, but cloudy cases show a very large intermodel scatter with a significant bias in all models. This bias likely results from a complete failure in all of the models to retain liquid water in cold winter clouds. All models overestimate the cloud attenuation of summer solar radiation for thin and intermediate clouds, and some models maintain this behavior also for thick clouds.

The tropospheric response to midlatitude SST anomalies has been investigated through a series of aquaplaner simulations using a high-resolution version of the Hadley Centre atmosphere model (HadAM3) under perpetual equinox conditions. Model integrations show that increases in the midlatitude SST gradient generally lead to stronger storm tracks that are shifted slightly poleward, consistent with changes in the lower-tropospheric baroclinicity. The large-scale atmospheric response is, however, highly sensitive to the position of the SST gradient anomaly relative to that of the subtropical jet in the unperturbed atmosphere. In particular, when SST gradients are increased very close to the subtropical jet, then the Hadley cell and subtropical jet is strengthened while the storm track and eddy-driven jet are shifted equatorward. Conversely, if the subtropical SST gradients are reduced and the midlatitude gradients increased, then the storm track shows a strong poleward shift and a well-separated eddy-driven jet is produced. The sign of the SST anomaly is shown to play a secondary role in determining the overall tropospheric response. These findings are used to provide a new and consistent interpretation of some previous GCM studies concerning the atmospheric response to midlatitude SST anomalies.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.dsr.2008.02.010 Byline: N. Steiner (a), K. Denman (a)(b) Abstract: We have developed a marine DMS (dimethylsulfide) module and implemented it in a 1-D coupled atmosphere-ocean-biogeochemical model. In developing the marine sulphur model we have found that several parameters used in the model are not known to even an order of magnitude. Our approach is used to test the model's sensitivity to these parameters. A parameter change of [+ or -]25% is applied to test the respective range of changes in the DMS fluxes. The model is run for a 3-year time period as well as for the time period of the Subarctic Ecosystem Response to Iron Enrichment Study (SERIES) in July 2002. The simulated seasonal cycle is in agreement with available observations: Near surface DMS concentrations vary from 1.5nmolL.sup.-1 in winter to 13.5nmolL.sup.-1 in summer. Simulated DMS production is found to be most sensitive to variations of the S:N ratio and the bacterial consumption rate of DMS. Implementing light or UV limited bacterial activity shows a negligible effect in winter and increases DMS concentrations by 0.2-0.6nmolL.sup.-1 in summer. Similarly a yield increase under UV stress increases summer values by 1-2nmolL.sup.-1. The simulated diel cycle in surface DMS concentration is no more than 2.5nmolL.sup.-1, even when light-dependent changes in bacterial activity are considered. Simulating the DMS response to iron fertilization with the standard run leads to overestimation during an initial bloom of small phytoplankton. While implementing light-dependent bacterial activity has a minor effect, the implementation of yields that depend on nutrient availability significantly improves the results. The model confirms earlier results showing the importance of including atmospheric DMS concentrations in gas flux calculations when there are high surface concentrations and small atmospheric boundary layer heights. Simulated summer concentrations in the upper layer can be underestimated by 2nmolL.sup.-1 or more if the atmospheric concentration is set to zero. Our study shows that inclusion of mechanistic DMS modules in comprehensive climate models requires better knowledge of the variation of key parameters in the marine sulphur cycle. Even though there are still open questions, the model reasonably reproduces the mean annual cycle; and including variable DMS yield improves the simulation of the DMS response to iron fertilization during SERIES. Author Affiliation: (a) Environment Canada, Canadian Centre for Climate Modelling and Analysis, University of Victoria, P.O. Box 1700, Victoria, BC, Canada V8W 2Y2 (b) Fisheries and Oceans Canada, Institute of Ocean Sciences, Sidney, BC, Canada Article History: Received 1 August 2007; Revised 18 January 2008; Accepted 30 March 2008

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1365-2745.2008.01369.x Byline: Xavier Morin (1), David Viner (2), Isabelle Chuine (1) Keywords: biodiversity; biogeography; climate change; extinction; migration; nonlinearity; North American trees; phenology; process-based model; species' distribution Abstract: Summary Climate change has already caused distribution shifts in many species, and climate predictions strongly suggest that these will accelerate in the future. Obtaining reliable predictions of species range shifts under climate change is thus currently one of the most crucial challenges for both ecologists and stakeholders. Here we simulate the distributions of 16 North American tree species at a continental scale for the 21st century according to two IPCC storylines, using a process-based species distribution model that for the first time allows identification of the possible causes of distribution change. Our projections show local extinctions in the south of species ranges (21% of the present distribution, on average), and colonizations of new habitats in the north, though these are limited by dispersal ability for most species. Areas undergoing local extinctions are slightly larger under climate scenario A2 (+3.2 C, +22% on average) than B2 (+1.0 C, +19% on average). This small difference is caused by nonlinear responses of processes (leaves and flowers phenological processes in particular) to temperature. We also show that local extinction may proceed at a slower rate than forecasted so far. Although predicted distribution shifts are very species-specific, we show that the loss of habitats southward will be mostly due to increased drought mortality and decreased reproductive success, while northward colonizations will be primarily promoted by increased probability of fruit ripening and flower frost survival. Synthesis. Our results show that different species will not face the same risks due to climate change, because their responses to climate differ as well as their dispersal rate. Focusing on processes, our study therefore tempers the alarming conclusions of widely used niche-based models about biodiversity loss, mainly because our predictions take into account the local adaptation and trait plasticity to climate of the species. Author Affiliation: (1)Centre d'Ecologie Fonctionnelle et Evolutive, Equipe BIOFLUX, CNRS, 1919 route de Mende, 34293 Montpellier cedex 5, France; and (2)Natural England, Science and Evidence, 60 Bracondale, Norwich NR1 2BE, UK Article History: Received 24 October 2007; accepted 14 February 2008Handling Editor: Jonathan Newman Article note: (*) Correspondence author. Department of Biology, Stewart Biology Building, W6/15, McGill University, 1205 Dr Penfield Avenue, Montreal, Quebec, Canada H3A 1B1. E-mail: xavier.morin@mail.mcgill.ca

The objective of this study is to investigate the effects of urban land on the climate in Europe on local and regional scales. Effects of urban land cover on the climate are isolated using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) Mesoscale Model (MM5) with a modified land surface scheme based on the Town Energy Budget model. Two model scenarios represent responses of climate to different states of urbanization in Europe: 1) no urban areas and 2) urban land in the actual state in the beginning of the twenty-first century. By comparing the simulations of these contrasting scenarios, spatial differences in near-surface temperature and precipitation are quantified. Simulated near-surface temperatures and an urban heat island for January and July over a period of 6 yr (2000-05) agree well with corresponding measurements at selected urban areas. The conversion of rural to urban land results in statistically significant changes to precipitation and near-surface temperature over areas of the land cover perturbations. The diurnal temperature range in urbanized regions was reduced on average by 1.26[degrees] [+ or -] 0.71[degrees]C in summer and by 0.73[degrees] [+ or -] 00.54[degrees]C in winter. Inclusion of urban areas results in an increase of urban precipitation in winter (0.09 [+ or -] 00.16 mm [day.sup.-1]) and a precipitation reduction in summer (-0.05 [+ or -] 0.22 mm [day.sup.-1]).

Byline: M. Rivington (1), D. Miller (1), K. B. Matthews (1), G. Russell (2), G. Bellocchi (3), K. Buchan (1) Abstract: This paper compares precipitation, maximum and minimum air temperature and solar radiation estimates from the Hadley Centre's HadRM3 regional climate model (RCM), (50x50 km grid cells), with observed data from 15 meteorological station in the UK, for the period 1960--90. The aim was to investigate how well the HadRM3 is able to represent weather characteristics for a historical period (hindcast) for which validation data exist. The rationale was to determine if the HadRM3 data contain systematic errors and to investigate how suitable the data are for use in climate change impact studies at particular locations. Comparing modelled and observed data helps assess and quantify the uncertainty introduced to climate impact studies. The results show that the model performs very well for some locations and weather variable combinations, but poorly for others. Maximum temperature estimations are generally good, but minimum temperature is overestimated and extreme cold events are not represented well. For precipitation, the model produces too many small events leading to a serious under estimation of the number of dry days (zero precipitation), whilst also over- or underestimating the mean annual total. Estimates represent well the temporal distribution of precipitation events. The model systematically over-estimates solar radiation, but does produce good quality estimates at some locations. It is concluded that the HadRM3 data are unsuitable for detailed (i.e. daily time step simulation model based) site-specific impacts studies in their current form. However, the close similarity between modelled and observed data for the historical case raises the potential for using simple adjustment methods and applying these to future projection data. Author Affiliation: (1) Macaulay Institute, Craigiebuckler, Aberdeen, AB15 8QH, UK (2) School of Geosciences, The Crew Building, University of Edinburgh, West Mains Road, Edinburgh, EH9 3JN, UK (3) Agrichiana Farming, Montepulciano, Siena, Italy Article History: Registration Date: 27/11/2007 Received Date: 27/06/2006 Accepted Date: 06/11/2007 Online Date: 19/02/2008

Information about climate and how it responds to increased greenhouse gas concentrations depends heavily on insight gained from numerical simulations by coupled climate models. The confidence placed in quantitative estimates of the rate and magnitude of future climate change is therefore strongly related to the quality of these models. In this study, we test the realism of several generations of coupled climate models, including those used for the 1995, 2001, and 2007 reports of the Intergovernmental Panel on Climate Change (IPCC). By validating against observations of present climate, we show that the coupled models have been steadily improving over time and that the best models are converging toward a level of accuracy that is similar to observation-based analyses of the atmosphere.

Byline: Kirsti Jylha (1), Stefan Fronzek (2), Heikki Tuomenvirta (1), Timothy R. Carter (2), Kimmo Ruosteenoja (1) Abstract: Changes in indices related to frost and snow in Europe by the end of the twenty-first century were analyzed based on experiments performed with seven regional climate models (RCMs). All the RCMs regionalized information from the same general circulation model (GCM), applying the IPCC-SRES A2 radiative forcing scenario. In addition, some simulations used SRES B2 radiative forcing and/or boundary conditions provided by an alternative GCM. Ice cover over the Baltic Sea was examined using a statistical model that related the annual maximum extent of ice to wintertime coastal temperatures. Fewer days with frost and snow, shorter frost seasons, a smaller liquid water equivalent of snow, and milder sea ice conditions were produced by all model simulations, irrespective of the forcing scenario and the driving GCM. The projected changes have implications across a diverse range of human activities. Details of the projections were subject to differences in RCM design, deviations between the boundary conditions of the driving GCMs, uncertainties in future emissions and random effects due to internal climate variability. A larger number of GCMs as drivers of the RCMs would most likely have resulted in somewhat wider ranges in the frost, snow and sea ice estimates than those presented in this paper. Author Affiliation: (1) Finnish Meteorological Institute, P.O. Box 503, 00101, Helsinki, Finland (2) Finnish Environment Institute, P.O. Box 140, 00251, Helsinki, Finland Article History: Registration Date: 04/07/2007 Received Date: 15/02/2005 Accepted Date: 10/05/2007 Online Date: 05/09/2007

This paper first reviews the current status, issues, and limitations of the parameterizations of atmospheric large-scale and convective moist processes that are used in numerical weather prediction and climate general circulation models. Both large-scale (resolved) and convective (subgrid scale) moist processes are dealt with. Then, the general question of the inclusion of diabatic processes in variational data assimilation systems is addressed. The focus is put on linearity and resolution issues, the specification of model and observation error statistics, the formulation of the control vector, and the problems specific to the assimilation of observations directly affected by clouds and precipitation.

Byline: Caspar M. Ammann (1), Eugene R. Wahl (2) Abstract: A portion of the debate about climate reconstructions of the past millennium, and in particular about the well-known Mann-Bradley-Hughes ('MBH' 1998, 1999) reconstructions, has become disconnected from the goal of understanding natural climate variability. Here, we reflect on what can be learned from recent scientific exchanges and identify important challenges that remain to be addressed openly and productively by the community. One challenge arises from the real, underlying trend in temperatures during the instrumental period. This trend can affect regression-based reconstruction performance in cases where the calibration period does not appropriately cover the range of conditions encountered during the reconstruction. However, because it is tied to a unique spatial pattern driven by change in radiative balance, the trend cannot simply be removed in the method of climate field reconstruction used by MBH on the statistical argument of preserving degrees of freedom. More appropriately, the influence from the trend can be taken into account in some methods of significance testing. We illustrate these considerations as they apply to the MBH reconstruction and show that it remains robust back to AD 1450, and given other empirical information also back to AD 1000. However, there is now a need to move beyond hemispheric average temperatures and to focus instead on resolving climate variability at the socially more relevant regional scale. Author Affiliation: (1) Climate and Global Dynamics Division, National Center for Atmospheric Research, 1850 Table Mesa Drive, Boulder, CO, 80305, USA (2) Environmental Studies and Geology Division, Alfred University, One Saxon Drive, Alfred, NY, 14802, USA Article History: Registration Date: 19/06/2007 Received Date: 22/08/2000 Accepted Date: 13/06/2007 Online Date: 24/08/2007

Byline: Eugene R. Wahl (1), Caspar M. Ammann (2) Abstract: The Mann et al. (1998) Northern Hemisphere annual temperature reconstruction over 1400--1980 is examined in light of recent criticisms concerning the nature and processing of included climate proxy data. A systematic sequence of analyses is presented that examine issues concerning the proxy evidence, utilizing both indirect analyses via exclusion of proxies and processing steps subject to criticism, and direct analyses of principal component (PC) processing methods in question. Altogether new reconstructions over 1400--1980 are developed in both the indirect and direct analyses, which demonstrate that the Mann et al. reconstruction is robust against the proxy-based criticisms addressed. In particular, reconstructed hemispheric temperatures are demonstrated to be largely unaffected by the use or non-use of PCs to summarize proxy evidence from the data-rich North American region. When proxy PCs are employed, neither the time period used to 'center' the data before PC calculation nor the way the PC calculations are performed significantly affects the results, as long as the full extent of the climate information actually in the proxy data is represented by the PC time series. Clear convergence of the resulting climate reconstructions is a strong indicator for achieving this criterion. Also, recent 'corrections' to the Mann et al. reconstruction that suggest 15th century temperatures could have been as high as those of the late-20th century are shown to be without statistical and climatological merit. Our examination does suggest that a slight modification to the original Mann et al. reconstruction is justifiable for the first half of the 15th century ([proportional to]+0.05.sup.a), which leaves entirely unaltered the primary conclusion of Mann et al. (as well as many other reconstructions) that both the 20th century upward trend and high late-20th century hemispheric surface temperatures are anomalous over at least the last 600 years. Our results are also used to evaluate the separate criticism of reduced amplitude in the Mann et al. reconstructions over significant portions of 1400--1900, in relation to some other climate reconstructions and model-based examinations. We find that, from the perspective of the proxy data themselves, such losses probably exist, but they may be smaller than those reported in other recent work. Author Affiliation: (1) Environmental Studies and Geology Division, Alfred University, One Saxon Dr., Alfred, NY, 14802, USA (2) Climate and Global Dynamics Division, National Center for Atmospheric Research Boulder, Boulder, Colorado, U.S.A. Article History: Registration Date: 15/03/2006 Accepted Date: 01/03/2006 Online Date: 31/08/2007 Article note: The National Center for Atmospheric Research is sponsored by the National Science Foundation, USA. The authors contributed equally to the development of the research presented.

Regional climate models are important research tools available to scientists around the world, including in economically developing nations (EDNs). The Earth Systems Physics (ESP) group of the Abdus Salam International Centre for Theoretical Physics (ICTP) maintains and distributes a state-of-the-science regional climate model called the ICTP Regional Climate Model version 3 (RegCM3), which is currently being used by a large research community for a diverse range of climate-related studies. The RegCM3 is the central, but not only, tool of the ICTP-maintained Regional Climate Research Network (RegCNET) aimed at creating south-south and north-south scientific interactions on the topic of climate and associated impacts research and modeling. In this paper, RegCNET, RegCM3, and illustrative results from RegCM3 benchmark simulations applied over south Asia, Africa, and South America are presented. It is shown that RegCM3 performs reasonably well over these regions and is therefore useful for climate studies in EDNs.

Byline: Heiko Paeth (1), Hans-Peter Thamm (2) Abstract: Previous studies have highlighted the crucial role of land degradation in tropical African climate. This effect urgently has to be taken into account when predicting future African climate under enhanced greenhouse conditions. Here, we present time slice experiments of African climate until 2025, using a high-resolution regional climate model. A supposable scenario of future land use changes, involving vegetation loss and soil degradation, is prescribed simultaneously with increasing greenhouse-gas concentrations in order to detect, where the different forcings counterbalance or reinforce each other. This proceeding allows us to define the regions of highest vulnerability with respect to future freshwater availability and food security in tropical and subtropical Africa and may provide a decision basis for political measures. The model simulates a considerable reduction in precipitation amount until 2025 over most of tropical Africa, amounting to partly more than 500 mm (20--40% of the annual sum), particularly in the Congo Basin and the Sahel Zone. The change is strongest in boreal summer and basically reflects the pattern of maximum vegetation cover during the seasonal cycle. The related change in the surface energy fluxes induces a substantial near-surface warming by up to 7degC. According to the modified temperature gradients over tropical Africa, the summer monsoon circulation intensifies and transports more humid air masses into the southern part of West Africa. This humidifying effect is overcompensated by a remarkable decrease in surface evaporation, leading to the overall drying tendency over most of Africa. Extreme daily rainfall events become stronger in autumn but less intense in spring. Summer and autumn appear to be characterized by more severe heat waves over Subsaharan West Africa. In addition, the Tropical Easterly Jet is weakening, leading to enhanced drought conditions in the Sahel Zone. All these results suggest that the local impact of land degradation and reduction of vegetation cover may be more important in tropical Africa than the global radiative heating, at least until 2025. This implies that vegetation protection measures at a national scale may directly lead to a mitigation of the expected negative implications of future climate change in tropical Africa. Author Affiliation: (1) Geographical Institute, University of Wurzburg, Am Hubland, 97074, Wurzburg, Germany (2) Geographical Institute, University of Bonn, Bonn, Germany Article History: Registration Date: 28/12/2006 Received Date: 17/11/2004 Accepted Date: 15/11/2006 Online Date: 08/02/2007

Byline: Mark A. Snyder (1), Bruno Sanso (2), Lisa C. Sloan (1) Abstract: The growing interest in and emphasis on high spatial resolution estimates of future climate has demonstrated the need to apply regional climate models (RCMs) to that problem. As a consequence, the need for validation of these models, an assessment of how well an RCM reproduces a known climate, has also grown. Validation is often performed by comparing RCM output to gridded climate datasets and/or station data. The primary disadvantage of using gridded climate datasets is that the spatial resolution is almost always different and generally coarser than climate model output. We have used a Bayesian statistical model derived from observational data to validate RCM output. We used surface air temperature (SAT) data from 109 observational stations in California, all with records of approximately 50 years in length, and created a statistical model based on this data. The statistical model takes into account the elevation of the station, distance from coastline, and the NOAA climate region in which the station resides. Analysis indicates that the statistical model provides reliable estimates of the mean monthly SAT at any given station. In our method, the uncertainty in the estimates produced by the statistical model are directly determined by obtaining probability density functions for predicted SATs. This statistical model is then used to estimate average SATs corresponding to each of the climate model grid cells. These estimates are compared to the output of the RCM to assess how well the RCM matches the observed climate as defined by the statistical model. Overall, the match between the RCM output and the statistical model is good, with some deficiencies likely due in part to the representation of topography in the RCM. Author Affiliation: (1) Climate Change and Impacts Laboratory, Department of Earth Sciences, University of California Santa Cruz, Santa Cruz, CA, USA (2) Department of Applied Mathematics and Statistics, University of California Santa Cruz, Santa Cruz, CA, USA Article History: Registration Date: 12/04/2007 Received Date: 25/08/2005 Accepted Date: 13/03/2007 Online Date: 23/05/2007

The Atmospheric Radiation Measurement (ARM) Program maintains a suite of instruments in various locations to provide continuous monitoring of atmospheric parameters. Temperature and humidity retrievals are two of the key parameters used by the climate-modeling community. Accuracy in the spectroscopy adopted by the various radiative transfer models is crucial for obtaining accurate retrievals. While the accuracy of the spectroscopic parameters used for water-vapor retrievals is satisfactory, temperature retrievals continue to be affected by uncertainties in oxygen line parameters leading to discrepancies between the modeled and observed brightness temperatures. In this paper, we compare the model calculations in the oxygen-band channels with the measurements collected by the ARM-operated 12-channel Microwave Radiometer Profiler (MWRP). The dataset used spans a wide range of atmospheric temperature conditions, with ground temperatures varying between -40 [degrees]C and +20 [degrees]C. Model calculations are performed by using line parameters from the high-resolution transmission molecular-absorption (HITRAN) database and from a set of newly published parameters. Our comparison shows that the newly published parameters agree more closely with the MWRP measurements and confirms the need to update the HITRAN database for the oxygen lines. We show the effect of line parameters on the retrievals of temperature, water vapor, and liquid water, and show that improved oxygen absorption is essential to reduce the clear-sky bias in the liquid-water path retrievals. Index Terms--Microwave radiometry, oxygen absorption, temperature retrieval, water-vapor retrieval.

Simulation models integrate our knowledge of soil organic C (SOC) dynamics and are useful tools for evaluating impacts of crop management on soil C sequestration; yet, they require local calibration. Our objectives were to calibrate the Environmental Policy Integrated Climate (EPIC) model, and evaluate its performance for simulating SOC fractions as affected by soil landscape and management. An automated parameter optimization procedure was used to calibrate the model for a site-specific experiment in the Coastal Plain of central Alabama. The ability of EPIC to predict corn (Zea mays L.) and cotton (Gossypium hirsutum L.) yields and SOC dynamics on different soil landscape positions (summit, sideslope, and drainageway) during the initial period of conservation tillage adoption (5 yr) was evaluated using regression and mean squared deviations. Simulated yield explained 88% of measured yield variation, with the greatest disagreement on the sideslope position and the greatest agreement in the drainageway. Simulations explained approximately 1, 34, and 40% of the total variation in microbial biomass C (MBC), particulate organic C (POC), and total organic C (TOC), respectively. The lowest errors in TOC simulations (0-20 cm) were found on the sideslope and summit. We conclude that the automated parameterization was generally successful, although further work is needed to refine the MBC and POC fractions, and to improve EPIC predictions of SOC dynamics with depth. Overall, EPIC was sensitive to spatial differences in C fractions that resulted from differing soil landscape positions. The model needs additional refinement for accurate simulations of field-scale SOC dynamics affected by short-term management decisions. Abbreviations: CT, conventional tillage; CTm, conventional tillage plus manure; EPIC, Environmental Policy Integrated Climate; FHP, fraction of humus in the passive pool; HI, harvest index; MBC, microbial biomass carbon; MSD, mean squared deviation; NT, no-till; NTm, no-till plus manure; PARM 20, microbial decay rate; PARM 51, microbial activity in the top layer; POC, particulate organic carbon; SOC, soil organic carbon; SOM, soil organic matter; TOC, total organic carbon; WA, biomass/energy ratio.

Observations show both a pronounced increase in ocean heat content (OHC) over the second half of the 20th century and substantial OHC variability on interannual-to-decadal time scales. Although climate models are able to simulate overall changes in OHC, they are generally thought to underestimate the amplitude of OHC variability. Using simulations of 20th century climate performed with 13 numerical models, we demonstrate that the apparent discrepancy between modeled and observed variability is largely explained by accounting for changes in observational coverage and instrumentation and by including the effects of volcanic eruptions. Our work does not support the recent claim that the 0- to 700-m layer of the global ocean experienced a substantial OHC decrease over the 2003 to 2005 time period. We show that the 2003-2005 cooling is largely an artifact of a systematic change in the observing system, with the deployment of Argo floats reducing a warm bias in the original observing system. climate | models | observations | ocean heat content

Byline: Martin Beniston (1), David B. Stephenson (2), Ole B. Christensen (3), Christopher A. T. Ferro (2), Christoph Frei (4), Stephane Goyette (1), Kirsten Halsnaes (5), Tom Holt (6), Kirsti Jylha (7), Brigitte Koffi (8), Jean Palutikof (6), Regina Scholl (4), Tido Semmler (9), Katja Woth (10) Abstract: This paper presents an overview of changes in the extreme events that are most likely to affect Europe in forthcoming decades. A variety of diagnostic methods are used to determine how heat waves, heavy precipitation, drought, wind storms, and storm surges change between present (1961--90) and future (2071--2100) climate on the basis of regional climate model simulations produced by the PRUDENCE project. A summary of the main results follows. Heat waves -- Regional surface warming causes the frequency, intensity and duration of heat waves to increase over Europe. By the end of the twenty first century, countries in central Europe will experience the same number of hot days as are currently experienced in southern Europe. The intensity of extreme temperatures increases more rapidly than the intensity of more moderate temperatures over the continental interior due to increases in temperature variability. Precipitation -- Heavy winter precipitation increases in central and northern Europe and decreases in the south heavy summer precipitation increases in north-eastern Europe and decreases in the south. Mediterranean droughts start earlier in the year and last longer. Winter storms -- Extreme wind speeds increase between 45degN and 55degN, except over and south of the Alps, and become more north-westerly than cuurently. These changes are associated with reductions in mean sea-level pressure, leading to more North Sea storms and a corresponding increase in storm surges along coastal regions of Holland, Germany and Denmark, in particular. These results are found to depend to different degrees on model formulation. While the responses of heat waves are robust to model formulation, the magnitudes of changes in precipitation and wind speed are sensitive to the choice of regional model, and the detailed patterns of these changes are sensitive to the choice of the driving global model. In the case of precipitation, variation between models can exceed both internal variability and variability between different emissions scenarios. Author Affiliation: (1) Climate Research, University of Geneva, Geneva, Switzerland (2) Department of Meteorology, University of Reading, Reading, UK (3) Danish Meteorological Institute, Copenhagen, Denmark (4) Swiss Federal Institute of Technology (ETH), Zurich, Switzerland (5) Risoe National Laboratory, Roskilde, Denmark (6) Climatic Research Unit, University of East Anglia, Norwich, United Kingdom (7) Finnish Meteorological Institute, Helsinki, Finland (8) University of Fribourg, Fribourg, Switzerland (9) Met Eireann, Dublin, Ireland (10) GKSS Research Center, Geesthacht, Germany Article History: Registration Date: 23/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 22/03/2007

Byline: C. E. Hanson (1), J. P. Palutikof (2), M. T. J. Livermore (1), L. Barring (3), M. Bindi (4), J. Corte-Real (5), R. Durao (5), C. Giannakopoulos (6), P. Good (6), T. Holt (1), Z. Kundzewicz (7,8), G. C. Leckebusch (9), M. Moriondo (4), M. Radziejewski (7,10), J. Santos (11,12), P. Schlyter (13), M. Schwarb (14), I. Stjernquist (13), U. Ulbrich (9) Abstract: This paper provides an overview of the aims, objectives, research activities undertaken, and a selection of results generated in the European Commission-funded project entitled 'Modelling the Impact of Climate Extremes' (MICE) -- a pan-European end-to-end assessment, from climate model to impact model, of the potential impacts of climate change on a range of economic sectors important to the region. MICE focussed on changes in temperature, precipitation and wind extremes. The research programme had three main themes -- the evaluation of climate model performance, an assessment of the potential future changes in the occurrence of extremes, and an examination of the impacts of changes in extremes on six activity sectors using a blend of quantitative modelling and expert judgement techniques. MICE culminated in a large stakeholder-orientated workshop, the aim of which was not only to disseminate project results but also to develop new stakeholder networks, whose expertise can be drawn on in future projects such as ENSEMBLES. MICE is part of a cluster of three projects, all related to European climate change and its impacts. The other projects in the cluster are PRUDENCE (Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects) and STARDEX (Statistical and Regional Dynamical Downscaling of Extremes for European Regions). Author Affiliation: (1) Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK (2) Hadley Centre, Met Office, Fitzroy Road, Exeter, EX1 3PB, UK (3) Department of Physical Geography and Ecosystems Analysis, Geobiosphere Science Centre, Lund University, Solvegatan 12, 223 62, Lund, Sweden (4) Department of Agronomy and Land Management, University of Florence, Piazale delle Cascine 18, 50144, Florence, Italy (5) Instituto de Cienca Aplicada e Tecnologia, Faculdade de Ciencas, Universidade Lisboa, Campo Grande, 1749-016, Lisbon, Portugal (6) National Observatory of Athens, Institute of Environmental Research & Sustainable Development, 15236, P. Penteli, Athens, Greece (7) Research Centre for Agricultural and Forest Environment, Polish Academy of Sciences, Bukowska 19, 60809, Poznan, Poland (8) Potsdam Institute for Climate Impact Research, Telegrafenberg, 14412, Potsdam, Germany (9) Institute for Meteorology, Freie Universitat Berlin, Carl-Heinrich-Becker-Weg 6-10, 12165, Berlin, Germany (10) Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Umultowska 87, 61-614, Poznan, Poland (11) Departamento de Fisica, Centro de Geofisica, Colegio Luis Antonio Verney, Universidade de Evora, R. Romao Ramalho 59, 7000, Evora, Portugal (12) Departamento de Fisica, Universidade de Tras-os-Montes e Alto Douro, Quinta dos Prados, Apartado 1013, 5000-911, Vila Real, Portugal (13) Department of Physical Geography and Quaternary Geology, Stockholm University, 106 91, Stockholm, Sweden (14) Institute of Geography, University of Bern, Hallerstr. 12, 3012, Bern, Switzerland Article History: Registration Date: 05/12/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 23/03/2007

Byline: Maria Ines Minguez (1), Margarita Ruiz-Ramos (1), Carlos H. Diaz-Ambrona (1), Miguel Quemada (1), Federico Sau (2) Abstract: The first-order or initial agricultural impacts of climate change in the Iberian Peninsula were evaluated by linking crop simulation models to several high-resolution climate models (RCMs). The RCMs provided the daily weather data for control, and the A2 and B2 IPCC scenarios. All RCMs used boundary conditions from the atmospheric general circulation model (AGCM) HadAM3 while two were also bounded to two other AGCMs. The analyses were standardised to control the sources of variation and uncertainties that were added in the process. Climatic impacts on wheat and maize of climate were derived from the A2 scenario generated by RCMs bounded to HadAM3. Some results derived from B2 scenarios are included for comparisons together with impacts derived from RCMs using different boundary conditions. Crop models were used as impact models and yield was used as an indicator that summarised the effects of climate to quantify initial impacts and differentiate among regions. Comparison among RCMs was made through the choice of different crop management options. All RCM-crop model combinations detected crop failures for winter wheat in the South under control and future scenarios, and projected yield increases for spring wheat in northern and high altitude areas. Although projected impacts differed among RCMs, similar trends emerged for relative yields for some regions. RCM-crop model outputs compared favourably to others using European Re-Analysis data (ERA-15), establishing the feasibility of using direct daily outputs from RCM for impact analysis. Uncertainties were quantified as the standard deviation of the mean obtained for all RCMs in each location and differed greatly between winter (wheat) and summer (maize) seasons, being smaller in the latter. Author Affiliation: (1) Depto de Produccion Vegetal: Fitotecnia, E.T.S. Ingenieros Agronomos, Universidad Politecnica de Madrid, Ciudad Universitaria, 28040, Madrid, Spain (2) Depto de Produccion Vegetal, Depto Produccion Vegetal, Universidad de Santiago de Compostela EPS-USC, 27002, Lugo, Spain Article History: Registration Date: 23/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 20/03/2007

Byline: Burkhardt Rockel (1), Katja Woth (1) Abstract: In this study, we analyse the uncertainty of the effect of enhanced greenhouse gas conditions on windiness projected by an ensemble of regional model simulations driven by the same global control and climate change simulations. These global conditions, representative for 1961--1990 and 2071--2100, were prepared by the Hadley Centre based on the IPCC SRES/A2 scenario. The basic data sets consist of simulated daily maximum and daily mean wind speed fields (over land) from the PRUDENCE data archive at the Danish Meteorological Institute. The main focus is on the results from the standard 50 km-resolution runs of eight regional models. The best parameter for determining possible future changes in extreme wind speeds and possible change in the number of storm events is maximum daily wind speed. It turned out during this study that the method for calculating maximum daily wind speed differs among the regional models. A comparison of simulated winds with observations for the control period shows that models without gust parameterisation are not able to realistically capture high wind speeds. The two models with gust parametrization estimate an increase of up to 20% of the number of storm peak (defined as gustsaY=8 Bft in this paper) events over Central Europe in the future. In order to use a larger ensemble of models than just the two with gust parameterisation, we also look at the 99th percentile of daily mean wind speed. We divide Europe into eight sub-regions (e.g., British Isles, Iberian Peninsula, NE Europe) and investigate the inter-monthly variation of wind over these regions as well as differences between today's climate and a possible future climate. Results show differences and similarities between the sub-regions in magnitude, spread, and seasonal tendencies. The model ensemble indicates a possible increase in future mean daily wind speed during winter months, and a decrease during autumn in areas influenced by North Atlantic extra-tropical cyclones. Author Affiliation: (1) GKSS Research Centre, Geesthacht, Germany Article History: Registration Date: 30/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 20/03/2007

Byline: M. Deque (1), D. P. Rowell (2), D. Luthi (3), F. Giorgi (4), J. H. Christensen (5), B. Rockel (6), D. Jacob (7), E. Kjellstrom (8), M. Castro (9), B. Hurk (10) Abstract: Ten regional climate models (RCM) have been integrated with the standard forcings of the PRUDENCE experiment: IPCC-SRES A2 radiative forcing and Hadley Centre boundary conditions. The response over Europe, calculated as the difference between the 2071--2100 and the 1961--1990 means can be viewed as an expected value about which various uncertainties exist. Uncertainties are measured here by variance in eight sub-European boxes. Four sources of uncertainty can be evaluated with the material provided by the PRUDENCE project. Sampling uncertainty is due to the fact that the model climate is estimated as an average over a finite number of years (30). Model uncertainty is due to the fact that the models use different techniques to discretize the equations and to represent sub-grid effects. Radiative uncertainty is due to the fact that IPCC-SRES A2 is merely one hypothesis. Some RCMs have been run with another scenario of greenhouse gas concentration (IPCC-SRES B2). Boundary uncertainty is due to the fact that the regional models have been run under the constraint of the same global model. Some RCMs have been run with other boundary forcings. The contribution of the different sources varies according to the field, the region and the season, but the role of boundary forcing is generally greater than the role of the RCM, in particular for temperature. Maps of minimum expected 2m temperature and precipitation responses for the IPCC-A2 scenario show that, despite the above mentioned uncertainties, the signal from the PRUDENCE ensemble is significant. Author Affiliation: (1) Meteo-France, Centre National de Recherches Meteorologiques, 42 Avenue Coriolis, 31057, Toulouse Cedex 01, France (2) Met Office, Hadley Centre for Climate Prediction and Research, FitzRoy Road, Exeter, Devon, EX1 3PB, UK (3) Swiss Federal Institute of Technology, Institute for Atmospheric and Climate Science, ETH, Winterthurerstrasse 190, 8057, Zurich, Switzerland (4) Abdus Salam International Centre for Theoretical Physics, Trieste, Italy (5) Danish Meteorological Institute, Lyngbyvej 100, 2100, Copenhagen A, Denmark (6) GKSS Forschungszentrum Geesthacht GmbH, Institute of Coastal Research, Max Planck Strasse, 21502, Geesthacht, Germany (7) Max-Planck-Institut fur Meteorologie, Bundesstrasse 55, 20146, Hamburg, Germany (8) Swedish Meteorological and Hydrological Institute, Folkborgsvagen 1, 60176, Norrkoping, Sweden (9) Dept. de Ciencias Ambientales, Universidad de Castilla La Mancha, Campus Tecnologico, 45071, Toledo, Spain (10) KNMI, Postbus 201, 3730 AE, De Bilt, The Netherlands Article History: Registration Date: 30/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 20/03/2007

Byline: Stefan Hagemann (1), Daniela Jacob (1) Abstract: In order to perform hydrological studies on the PRUDENCE regional climate model (RCM) simulations, a special focus was put on the discharge from large river catchments located in northern and central Europe. The discharge was simulated with a simplified land surface (SL) scheme and the Hydrological Discharge (HD) model. The daily fields of precipitation, 2 m temperature and evapotranspiration from the RCM simulations were used as forcing. Therefore the total catchment water balances are constrained by the hydrological cycle of the different RCMs. The validation of the simulated hydrological cycle from the control simulations shows that the multi-model ensemble mean is closer to the observations than each of the models, especially if different catchments and hydrological variables are considered. Therefore, the multi-model ensemble mean can be used to largely reduce the uncertainty that is introduced by a single RCM. This also provides more confidence in the future projections for the multi-model ensemble means. The scenario simulations predict a gradient in the climate change signal over Northern and Central Europe. Common features are the overall warming and the general increase of evapotranspiration. But while in the northern parts the warming will enhance the hydrological cycle leading to an increased discharge, the large warming, especially in the summer, will slow down the hydrological cycle caused by a drying in the central parts of Europe which is accompanied by a reduction of discharge. The comparison of the changes predicted by the multi-model ensemble mean to the changes predicted by the driving GCM indicates that the RCMs can compensate problems that a driving GCM may have with local scale processes or parameterizations. Author Affiliation: (1) Max Planck Institute for Meteorology, Bundesstr. 53, 20146, Hamburg, Germany Article History: Registration Date: 23/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 20/03/2007

Byline: M. Castro (1), C. Gallardo (1), K. Jylha (2), H. Tuomenvirta (2) Abstract: Making use of the Koppen--Trewartha (K--T) climate classification, we have found that a set of nine high-resolution regional climate models (RCM) are fairly capable of reproducing the current climate in Europe. The percentage of grid-point to grid-point coincidences between climate subtypes based on the control simulations and those of the Climate Research Unit (CRU) climatology varied between 73 and 82%. The best agreement with the CRU climatology corresponds to the RCM 'ensemble mean'. The K--T classification was then used to elucidate scenarios of climate change for 2071--2100 under the SRES A2 emission scenario. The percentage of land grid-points with unchanged K--T subtypes ranged from 41 to 49%, while those with a shift from the current climate subtypes towards warmer or drier ones ranged from 51 to 59%. As a first approximation, one may assume that in regions with a shift of two or more climate subtypes, ecosystems might be at risk. Excluding northern Scandinavia, such regions were projected to cover about 12% of the European land area. Author Affiliation: (1) ICAM-Universidad de Castilla-La Mancha, 45071, Toledo, Spain (2) Finnish Meteorological Institute, 00101, Helsinki, Finland Article History: Registration Date: 23/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 21/03/2007

Byline: Stefan Fronzek (1), Timothy R. Carter (1) Abstract: An analysis is presented of the estimated impacts of climate change on resource potential in Europe under a wide range of model-based climate scenarios. Simple models and indices were used to assess impacts on the growing season, potential biomass, thermal suitability for the cultivation of crops, and potential energy demand for indoor cooling. Impacts were estimated for climate during the 1961--1990 baseline period (both observed and modelled) and projected during 2071--2100 based on outputs from a range of regional climate models (RCMs) driven by general circulation models (GCMs) assuming forcing by SRES emission scenarios A2 and B2, and from six atmosphere--ocean GCMs forced by a wider range of emission scenarios. Uncertainties in the projected impacts of climate change are assessed with respect to: (1) the direct climate model output vs. delta change approach, (2) differences in the driving GCMs and the RCM runs, (3) differences across a range of emission scenarios, (4) changes in long-term mean climate, and (5) changes in inter-annual climate variability. Future simulations show substantial changes in all analysed impact sectors, but with a relatively large spread of results attributable to uncertainties in future climate expressed by the different scenarios. Results included shifts of the northern limits of areas thermally suitable for the cultivation of soya bean and grain maize by several hundred kilometres, lengthening of the thermal growing season by 3--12 weeks, strong increases of potential biomass in northern Europe and slight decreases in southern Europe, and increased energy demand for cooling throughout Europe. Our results hint at systematic differences between RCM and GCM projections of temperature, though not precipitation, over Europe. The results also highlight the importance of accounting for inter-annual variability in estimating future impacts, through its affect on levels of risk. However, the results caution against the use of direct RCM outputs in impact models, due to biases in the representation of present-day climate. The delta change approach still appears to be the preferred option for most applications. Author Affiliation: (1) Finnish Environment Institute, Box 140, FIN-00251, Helsinki, Finland Article History: Registration Date: 20/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 17/03/2007

Byline: L. Phil Graham (1), Johan Andreasson (1), Bengt Carlsson (1) Abstract: This paper investigates how using different regional climate model (RCM) simulations affects climate change impacts on hydrology in northern Europe using an offline hydrological model. Climate change scenarios from an ensemble of seven RCMs, two global climate models (GCMs), two global emissions scenarios and two RCMs of varying resolution were used. A total of 15 climate change simulations were included in studies on the Lule River basin in Northern Sweden. Two different approaches to transfer climate change from the RCMs to hydrological models were tested. A rudimentary estimate of change in hydropower potential on the Lule River due to climate change was also made. The results indicate an overall increase in river flow, earlier spring peak flows and an increase in hydropower potential. The two approaches for transferring the signal of climate change to the hydrological impacts model gave similar mean results, but considerably different seasonal dynamics, a result that is highly relevant for other types of climate change impacts studies. Author Affiliation: (1) Swedish Meteorological and Hydrological Institute, SE-60176, Norrkoping, Sweden Article History: Registration Date: 20/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 17/03/2007

Byline: L. Phil Graham (1), Stefan Hagemann (2), Simon Jaun (3), Martin Beniston (4) Abstract: Although representation of hydrology is included in all regional climate models (RCMs), the utility of hydrological results from RCMs varies considerably from model to model. Studies to evaluate and compare the hydrological components of a suite of RCMs and their use in assessing hydrological impacts from future climate change were carried out over Europe. This included using different methods to transfer RCM runoff directly to river discharge and coupling different RCMs to offline hydrological models using different methods to transfer the climate change signal between models. The work focused on drainage areas to the Baltic Basin, the Bothnian Bay Basin and the Rhine Basin. A total of 20 anthropogenic climate change scenario simulations from 11 different RCMs were used. One conclusion is that choice of GCM (global climate model) has a larger impact on projected hydrological change than either selection of emissions scenario or RCM used for downscaling. Author Affiliation: (1) Swedish Meteorological and Hydrological Institute, 60176, Norrkoping, Sweden (2) Max-Planck-Institute for Meteorology, Bundesstrasse 55, 20146, Hamburg, Germany (3) Swiss Federal Institute of Technology, Institute for Atmospheric and Climate Science ETH, Winterthurerstrasse 190, 8057, Zurich, Switzerland (4) University of Geneva, Chair for Climate Research, Site de Battelle / D, 7, chemin de Drize, 1227, Geneva, Switzerland Article History: Registration Date: 20/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 23/03/2007

Byline: Daniela Jacob (1), Lars Barring (5), Ole Bossing Christensen (2), Jens Hesselbjerg Christensen (2), Manuel Castro (11), Michel Deque (8), Filippo Giorgi (10), Stefan Hagemann (1), Martin Hirschi (3), Richard Jones (9), Erik Kjellstrom (5), Geert Lenderink (6), Burkhardt Rockel (7), Enrique Sanchez (11), Christoph Schar (3), Sonia I. Seneviratne (4), Samuel Somot (8), Aad Ulden (6), Bart Hurk (6) Abstract: The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation. Author Affiliation: (1) Max Planck Institute for Meteorology, Bundesstr.53, 20146, Hamburg, Germany (2) Danish Meteorological Institute, Lyngbyvej 100, 2100, Copenhagen, Denmark (3) Institut for Atmospheric and Climate Science ETH, 8057, Zurich, Switzerland (4) Global Modeling and Assimilation Office NASA, Goddard Space Flight Center, Greenbelt, MD, USA (5) Rossby Centre, SMHI, 60176, Norrkoping, Sweden (6) Royal Netherlands Meteorological Institute, 3730 AE, de Bilt, The Netherlands (7) GKSS Forschungszentrum Geesthacht, Max-Planck-Strasse, 21502, Geesthacht, Germany (8) Meteo-France CNRM, 42 av. Gaspard Coriolis, 31057, Toulouse Cedex, France (9) Met Office Hadley Centre (Reading Unit), Meteorology Building, University of Reading, Reading, RG6 6BB, UK (10) The Abdus Salam International Centre for Theoretical Physics, P. O. BOX 586, 34100, Trieste, Italy (11) Facultad de Ciencias del Medio Ambiente, Universidad de Castilla-La Mancha, Avda. Carlos III s/n, 45071, Toledo, Spain Article History: Registration Date: 17/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 17/03/2007

Byline: Jens Hesselbjerg Christensen (1), Ole Bossing Christensen (1) Abstract: An overview of the PRUDENCE fine resolution climate model experiments for Europe is presented in terms of their climate change signals, in particular 2-meter temperature and precipitation. A comparison is made with regard to the seasonal variation in climate change response of the different models participating in the project. In particular, it will be possible to check how representative a particular PRUDENCE regional experiment is of the overall set in terms of seasonal values of temperature and precipitation. This is of relevance for such further studies and impact models that for practical reasons cannot use all the PRUDENCE regional experiments. This paper also provides some guidelines for how to select subsets of the PRUDENCE regional experiments according to such main sources of uncertainty in regional climate simulations as the choice of the emission scenario and of the driving global climate model. Author Affiliation: (1) Danish Meteorological Institute, Lyngbyvej 100, DK-2100, Copenhagen A, Denmark Article History: Registration Date: 17/11/2006 Received Date: 07/12/2005 Accepted Date: 18/05/2006 Online Date: 17/03/2007

Byline: Jens H. Christensen (1), Timothy R. Carter (2), Markku Rummukainen (3), Georgios Amanatidis (4) Abstract: This special issue of Climatic Change contains a series of research articles documenting co-ordinated work carried out within a 3-year European Union project 'Prediction of Regional scenarios and Uncertainties for Defining European Climate change risks and Effects' (PRUDENCE). The main objective of the PRUDENCE project was to provide high resolution climate change scenarios for Europe at the end of the twenty-first century by means of dynamical downscaling (regional climate modelling) of global climate simulations. The first part of the issue comprises seven overarching PRUDENCE papers on: (1) the design of the model simulations and analyses of climate model performance, (2 and 3) evaluation and intercomparison of simulated climate changes, (4 and 5) specialised analyses of impacts on water resources and on other sectors including agriculture, ecosystems, energy, and transport, (6) investigation of extreme weather events and (7) implications of the results for policy. A paper summarising the related MICE (Modelling the Impact of Climate Extremes) project is also included. The second part of the issue contains 12 articles that focus in more detail on some of the themes summarised in the overarching papers. The PRUDENCE results represent the first comprehensive, continental-scale intercomparison and evaluation of high resolution climate models and their applications, bringing together climate modelling, impact research and social sciences expertise on climate change. Author Affiliation: (1) Danish Meteorological Institute, Lyngbyvej 100, 2100, Copenhagen A, Denmark (2) Finnish Environment Institute (SYKE), Box 140, 00251, Helsinki, Finland (3) Rossby Centre, SMHI, 60176, Norrkoping, Sweden (4) European Commision, CDMA 3/128, B-1049, Brussels, Belgium Article History: Registration Date: 17/11/2006 Received Date: 15/02/2005 Accepted Date: 17/10/2006 Online Date: 17/03/2007

Byline: Michelle L. Bell (1), Richard Goldberg (2), Christian Hogrefe (3), Patrick L. Kinney (4), Kim Knowlton (4), Barry Lynn (5), Joyce Rosenthal (4), Cynthia Rosenzweig (5), Jonathan A. Patz (6) Abstract: We investigated how climate change could affect ambient ozone concentrations and the subsequent human health impacts. Hourly concentrations were estimated for 50 eastern US cities for five representative summers each in the 1990s and 2050s, reflecting current and projected future climates, respectively. Estimates of future concentrations were based on the IPCC A2 scenario using global climate, regional climate, and regional air quality models. This work does not explore the effects of future changes in anthropogenic emissions, but isolates the impact of altered climate on ozone and health. The cities' ozone levels are estimated to increase under predicted future climatic conditions, with the largest increases in cities with present-day high pollution. On average across the 50 cities, the summertime daily 1-h maximum increased 4.8 ppb, with the largest increase at 9.6 ppb. The average number of days/summer exceeding the 8-h regulatory standard increased 68%. Elevated ozone levels correspond to approximately a 0.11% to 0.27% increase in daily total mortality. While actual future ozone concentrations depend on climate and other influences such as changes in emissions of anthropogenic precursors, the results presented here indicate that with other factors constant, climate change could detrimentally affect air quality and thereby harm human health. Author Affiliation: (1) School of Forestry and Environmental Studies, Yale University, 205 Prospect St., New Haven, CT, 06511, USA (2) Center for Climate Systems Research, Columbia University, New York, NY, USA (3) Atmospheric Sciences Research Center, State University of New York at Albany, Albany, NY, USA (4) Mailman School of Public Health, Columbia University, New York, NY, USA (5) National Aeronautic and Space Administration (NASA) Goddard Institute for Space Studies, New York, NY, USA (6) Nelson Institute for Environmental Studies, University of Wisconsin at Madison, Madison, WI, USA Article History: Registration Date: 28/06/2006 Received Date: 30/06/2005 Accepted Date: 23/05/2006 Online Date: 06/01/2007