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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