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We used monthly mean surface wind data from the National Centers for Environmental Prediction/National Centers for Atmospheric Research (NCEP/NCAR) reanalysis dataset during the period 1979-2010 to describe the first two patterns of Arctic surface wind variability by means of the complex vector empirical orthogonal function (CVEOF) analysis. The first two patterns respectively account for 31 and 16% of its total anomalous kinetic energy. The leading pattern consists of the two subpatterns: the northern Laptev Sea (NLS) pattern and the Arctic dipole (AD) pattern. The second pattern contains the northern Kara Sea (NKS) pattern and the central Arctic (CA) pattern. Over the past two decades, the combined dynamical forcing of the first two patterns has contributed to Arctic September sea ice extent (SIE) minima and its declining trend. September SIE minima are mainly associated with the negative phase of the AD pattern and the positive phase of the CA pattern during the summer (July to September) season, and both phases coherently show an anomalous anticyclone over the Arctic Ocean. Wind patterns affect September SIE through their frequency and intensity. The negative trend in September SIE over the past two decades is associated with increased frequency and enhanced intensity of the CA pattern during the melting season from April to September. Thus, it cannot be simply attributed to the AD anomaly characterised by the second empirical orthogonal function mode of sea level pressure north of 708N. The CA pattern exhibited interdecadal variability in the late 1990s, and an anomalous cyclone prevailed before 1997 and was then replaced by an anomalous anticyclone over the Arctic Ocean that is consistent with the rapid decline trend in September SIE. This paper provides an alternative way to identify the dominant patterns of climate variability and investigate their associated Arctic sea ice variability from a dynamical perspective. Indeed, this study investigates only the role of surface wind dynamical forcing in resulting September SIE minima and trend in terms of CVEOF, without even considering contributions from other factors. [ABSTRACT FROM AUTHOR]

The molecular channel of the space-based Doppler lidar ADM-Aeolus relies on a double Fabry–Perot (FP) interferometer. The difference in photon numbers transmitted by the two FPs divided by their sum- the so-called Rayleigh response—is a function of the central frequency of the spectrum of the laser light backscattered by the atmosphere, so that a proper inversion enables the measurement of Doppler shifts and line-of-sight wind velocities. In this paper, it is shown that the relation-ship between the Rayleigh response and the Doppler shift does not depend on the sole characteristics of the instrument, but also on the atmospheric pressure and temperature (through the Rayleigh–Brillouin effect), and the likely presence of a narrow-band radiation due to particle scattering. The impact of these on the precision of inverted Doppler shifts (or line-of-sight winds) is assessed showing that a correction is needed. As they are lacking the appropriate precision, climatology profiles of pressure, temperature or aerosols cannot be used as an input. It is proposed to use data predicted by a numerical weather prediction system instead. A possible correction scheme is proposed. Its implication on the quality of retrieved Rayleigh winds is discussed. [ABSTRACT FROM AUTHOR]

The “Sandström theorem” as interpreted by Jeffreys is that in a flow maintained by a temperature difference, the pathline from the cold region to the warm region must lie below the return path. A formal demonstration of the argument for a rotating fluid requires three assumptions about the relative circulation around a closed material line: (1) the flow is steady, (2) the closed material line is a closed streamline and (3) the work done by friction along the streamline is negative. The argument extends to unsteady flows, thereby relaxing (1–2), if the absolute circulation along the material line is a bounded function of time—a condition that is met for flows with small Rossby number. Its validity for time-periodic two-dimensional flows of horizontal convection is verified numerically. Poincaré sections reveal the presence of chaotic particle transport in these flows, even though the Eulerian velocity fields have a simple time dependence. In spite of chaotic advection, particle motion is in general downwards in the cold region and upwards in the warm region of the fluid, which is consistent with the flow shape envisioned by Jeffreys. This paper gives support to the validity of his argument for the unsteady case and enhances its relevance for the dynamical interpretation of the basic structure of geophysical flows. [ABSTRACT FROM AUTHOR]

Presents a study which investigated the relationship between atmospheric predictability and the Pacific North American (PNA) pattern in a perfect model context using the Canadian Centre for Climate Modelling and Analysis general circulation model (GCM). Description of the GCM model; Relationship between the tropical sea surface temperature anomalies and the PNA pattern; Prediction spread of model experiments for different PNA phases.

The mechanisms underlying the occurrence of temperature extremes in Iberia are analysed considering a Lagrangian perspective of the atmospheric flow, using 6-hourly ERA-Interim reanalysis data for the years 1979-2012. Daily 2-m minimum temperatures below the 1st percentile and 2-m maximum temperatures above the 99th percentile at each grid point over Iberia are selected separately for winter and summer. Four categories of extremes are analysed using 10-d backward trajectories initialized at the extreme temperature grid points close to the surface: winter cold (WCE) and warm extremes (WWE), and summer cold (SCE) and warm extremes (SWE). Air masses leading to temperature extremes are first transported from the North Atlantic towards Europe for all categories. While there is a clear relation to large-scale circulation patterns in winter, the Iberian thermal low is important in summer. Along the trajectories, air mass characteristics are significantly modified through adiabatic warming (air parcel descent), upper-air radiative cooling and near-surface warming (surface heat fluxes and radiation). High residence times over continental areas, such as over northern-central Europe for WCE and, to a lesser extent, over Iberia for SWE, significantly enhance these air mass modifications. Near-surface diabatic warming is particularly striking for SWE. WCE and SWE are responsible for the most extreme conditions in a given year. For WWE and SCE, strong temperature advection associated with important meridional air mass transports are the main driving mechanisms, accompanied by comparatively minor changes in the air mass properties. These results permit a better understanding of mechanisms leading to temperature extremes in Iberia. [ABSTRACT FROM AUTHOR]

High-resolution data are needed in order to assess potential impacts of extreme events on infrastructure in the mid-latitudes. Dynamical downscaling offers one way to obtain this information. However, prior to implementation in any impacts assessment scheme, model output must be validated and determined fitfor- purpose. This study presents the results from two 8-km resolution perfect boundary experiments over Scandinavia. Two different regional climate models were initialised and driven with ERA interim reanalysis from 1990 to 2010. Reference data come from both gridded products and point-based station observations. In addition to the canonical variables of daily precipitation and temperature, winds were also investigated. The models exhibit systematic cold and wet biases on seasonal time scales ( 1K and -50-100%, respectively). However, frequency-based skill scores for daily precipitation and temperature are high, indicating that the distributions of these variables are generally well captured. Wind speeds over the North and Norwegian Seas were simulated more realistically in the models than in the ERA interim reanalysis. However, most importantly, for impacts assessments, the models should be capable of capturing the timing, intensity and location of short-duration extreme events, in particular precipitation. In this respect, both models outperform the reanalysis over the city of Copenhagen, where recent pluvial floods led to costly damages to infrastructure. [ABSTRACT FROM AUTHOR]

The Soil Moisture and Ocean Salinity (SMOS) mission observes brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) with a daily coverage of the polar regions. L-band radiometry has been shown to provide information on the thickness of thin sea ice. Here, we apply a new emission model that has previously been used to investigate the impact of snow on thick Arctic sea ice. The model has not yet been used to retrieve ice thickness. In contrast to previous SMOS ice thickness retrievals, the new model allows us to include a snow layer in the brightness temperature simulations. Using ice thickness estimations from satellite thermal imagery, we simulate brightness temperatures during the ice growth season 2011 in the northern Baltic Sea. In both the simulations and the SMOS observations, brightness temperatures increase by more than 20 K, most likely due to an increase of ice thickness. Only if we include the snow in the model, the absolute values of the simulations and the observations agree well (mean deviations below 3.5 K). In a second comparison, we use high-resolution measurements of total ice thickness (sum of ice and snow thickness) from an electromagnetic (EM) sounding system to simulate brightness temperatures for 12 circular areas. While the SMOS observations and the simulations that use the EM modal ice thickness are highly correlated (r²=0.95), the simulated brightness temperatures are on average 12 K higher than observed by SMOS. This would correspond to an 8-cm overestimation of the modal ice thickness by the SMOS retrieval. In contrast, if the simulations take into account the shape of the EM ice thickness distributions (r²=0.87), the mean deviation between simulated and observed brightness temperatures is below 0.1 K. [ABSTRACT FROM AUTHOR]

The classical non-linear climatic model previously developed by Saltzman with co-authors and Nicolis is analysed in both the deterministic and stochastic cases in a wider domain of system parameters. A detailed analysis of the deterministic model shows a co-existence of a stable cycle and equilibrium phase points of the climate system localisation. A fine structure of attraction basins existing around stable equilibria is studied. The model under consideration possesses the noise-induced transitions between possible system attractors (limit cycle and two equilibria) in the case of stochastic dynamics caused by temperature fluctuations. A new phenomenon of stochastic generation of large amplitude oscillations around two equilibrium points in the absence of a limit cycle is revealed. The co-existence of large-, small- and mixed-mode stochastic transitions between the climate system attractors is found. [ABSTRACT FROM AUTHOR]

Mid-latitudinal cyclones are a key factor for understanding regional anomalies in primary meteorological parameters such as temperature or precipitation. Extreme cyclones can produce notable impacts on human society and economy, for example, by causing enormous economic losses through wind damage. Based on 41 annually initialised (1961-2001) hindcast ensembles, this study evaluates the ability of a single-model decadal forecast system (MPI-ESM-LR) to provide skilful probabilistic three-category forecasts (enhanced, normal or decreased) of winter (ONDJFM) extra-tropical cyclone frequency over the Northern Hemisphere with lead times from 1 yr up to a decade. It is shown that these predictions exhibit some significant skill, mainly for lead times of 2-5 yr, especially over the North Atlantic and Pacific. Skill for intense cyclones is generally higher than for all detected systems. A comparison of decadal hindcasts from two different initialisation techniques indicates that initialising from reanalysis fields yields slightly better results for the first forecast winter (month 10-15), while initialisation based on an assimilation experiment provides better skill for lead times between 2 and 5 yr. The reasons and mechanisms behind this predictive skill are subject to future work. Preliminary analyses suggest a strong relationship of the model's skill over the North Atlantic with the ability to predict upper ocean temperatures modulating lower troposphere baroclinicity for the respective area and time scales. [ABSTRACT FROM AUTHOR]

An adjoint sensitivity-based data assimilation (ASDA) method is proposed and applied to a heavy rainfall case over the Korean Peninsula. The heavy rainfall case, which occurred on 26 July 2006, caused torrential rainfall over the central part of the Korean Peninsula. The mesoscale convective system (MCS) related to the heavy rainfall was classified as training line/adjoining stratiform (TL/AS)-type for the earlier period, and back building (BB)-type for the later period. In the ASDA method, an adjoint model is run backwards with forecasterror gradient as input, and the adjoint sensitivity of the forecast error to the initial condition is scaled by an optimal scaling factor. The optimal scaling factor is determined by minimising the observational cost function of the four-dimensional variational (4D-Var) method, and the scaled sensitivity is added to the original first guess. Finally, the observations at the analysis time are assimilated using a 3D-Var method with the improved first guess. The simulated rainfall distribution is shifted northeastward compared to the observations when no radar data are assimilated or when radar data are assimilated using the 3D-Var method. The rainfall forecasts are improved when radar data are assimilated using the 4D-Var or ASDA method. Simulated atmospheric fields such as horizontal winds, temperature, and water vapour mixing ratio are also improved via the 4D-Var or ASDA method. Due to the improvement in the analysis, subsequent forecasts appropriately simulate the observed features of the TL/AS- and BB-type MCSs and the corresponding heavy rainfall. The computational cost associated with the ASDA method is significantly lower than that of the 4D-Var method. [ABSTRACT FROM AUTHOR]

Nocturnal precipitation cells and lines occur near the coastline in the whole Mediterranean basin in all seasons. The precipitation events are mainly located in areas where coastal mountain ranges and rivers enhance convergence though the interaction of nocturnal mesoscale and local flows (land breeze, katabatic and drainages winds) with prevailing synoptic wind or with other mesoscale and local flows. The methodology used here to study this phenomenon consists of three stages. First, the Tropical Rainfall Measuring Mission (TRMM) radar satellite database is used to detect nocturnal precipitation near the coastline, from 18 to 09 UTC. An event is included in the study if the 3 hours accumulated precipitation detected by TRMM is stationary near the coast, or has moved slightly onshore or offshore, and has lasted no more than six consecutive hours. Second, the NCEP reanalysis database is used to describe the synoptic conditions and to discard precipitation associated with synoptic events (large low pressure areas, dynamic polar fronts, or troughs, for example). In the final step by using the version 3 of the Weather Research Forecast model, we simulate and analyse some of the selected events to determine the role of the land-sea temperature differences, the curvature of the coastline and the sea surface temperature. The simulations confirm that the nocturnal precipitation studied in the Mediterranean basin near the coastline is formed from the interaction between relatively warm and wet sea-air with the cold air mass from drainage winds, as well as from the convergence of several drainage winds offshore. The mechanism is the same that is used to explain nocturnal precipitation in tropical areas. [ABSTRACT FROM AUTHOR]

The impact of anomalous fall Arctic sea ice concentrations (SICs) on atmospheric patterns in the following winter is revisited by analysing results for two time periods: the most recent, satellite-era period (1979-2010) and a longer time-period (1950-2010). On the basis of September SICs for each time-period, an index was constructed which was used to identify anomalous high/low SIC years for both the original, as well as for the linearly detrended sea ice index. Identified years were then used to derive composites for the following winter's monthly atmospheric variables. Mid-troposphere geopotential height composites for winter months are in general reminiscent of the North Atlantic Oscillation pattern with high latitude maximum shifted towards the Barents Sea. Also, lower troposphere temperatures indicate the presence of cooler conditions over the continents during low SIC years. However, differences in the composite patterns are significant only for areas with limited spatial extent. While suggested pathways in previously published studies seem reasonable, our results show that these findings are not yet robust enough from a statistical significance perspective. More data (e.g. provided by longer, climate-quality reanalysis datasets) are needed before conclusions of impacts and feedbacks can be drawn with certainty. [ABSTRACT FROM AUTHOR]

Flow regimes of dry, stratified flow passing over an isolated two-dimensional (2-D) orography mainly concentrate at two stagnation points. One occurs on the upslope of the orography owing to flow blocking; another is related to gravity wave breaking (GWB) over the leeside. Smith (1979) put forward a hypothesis that the occurring of GWB is suppressed when the low-level vertical wind shear (VWS) exceeds some value. In the present study, a theoretical solution in a two-layer linear model of orographic flow with a VWS over a bellshaped 2-D orography is developed to investigate the effect of VWS on GWB's occurring over a range of surface Froude number Fr0=U0/Nh (U0 is surface wind speed, h is orography height and N is stability parameter), over which the GWB occurs first and the upstream flow blocking is excluded. Based on previous simulations and experiments, the range of surface Froude number selected is 0.6≥Fr0≥2.0. Based on this solution, the conditions of surface wind speed (U0) and one-to-one matching critical VWS (Δuc) for GWB's occurring are discussed. Over the selected range of Fr0, GWB's occurring will be suppressed if the VWS (Δu) is larger than Δuc at given U0. Moreover, there is a maximum value of Δuc over the selected range of Fr0, which is labelled as Δumax, and its matching surface wind speed by U0m. Once the Δu is larger than Δumax, the flow will pass over the orography without GWB's occurring. That means, over the selected range of Fr0, the flow regime of 2-D orographic flow related to GWB occurring primarily will be absent when Δu>Δumax, regardless of the value for U0. In addition, the vertical profile of atmospheric stability and height of VWS could result in different features of mountain wave, which leads to different Δuc and Δumax for the GWB's occurring. The possible inaccuracy of estimated Δuc in the present linear model is also discussed. [ABSTRACT FROM AUTHOR]

In Numerical Weather Prediction (NWP), to initialise lake variables for parameterisation of lakes, lake climatology is required. We obtained model lake climatology through offline runs of a lake model FLake (Freshwater Lake model) with different values of lake depth parameter. As a result, a global dataset with the resolution of 18 was developed. To project lake climatology onto a particular NWP model grid, data are extracted from the dataset depending on the lake depth value provided on the target grid. To prevent drifting of the bottom temperature in warm deep lakes, relaxation to the long-term mean air temperature was applied in FLake. Lake model climatology was validated against observations for different types of lakes. We suppose that detected errors for boreal lakes in spring are connected with inaccuracies in forcing data, but further study of errors is needed. [ABSTRACT FROM AUTHOR]

Snow and ice thermodynamics was simulated applying a one-dimensional model for an individual ice season 2008-2009 and for the climatological normal period 1971-2000. Meteorological data were used as the model input. The novel model features were advanced treatment of superimposed ice and turbulent heat fluxes, coupling of snow and ice layers and snow modelled from precipitation. The simulated snow, snow-ice and ice thickness showed good agreement with observations for 2008-2009. Modelled ice climatology was also reasonable, with 0.5 cm d-1 growth in December-March and 2 cm d-1 melting in April. Tuned heat flux from waterto ice was 0.5 W m-2. The diurnal weather cycle gave significant impact on ice thickness in spring. Ice climatology was highly sensitive to snow conditions. Surface temperature showed strong dependency on thickness of thin ice (B0.5 m), supporting the feasibility of thermal remote sensing and showing the importance of lake ice in numerical weather prediction. The lake ice season responded strongly to air temperature: a level increase by 1 or 58C decreased the mean length of the ice season by 13 or 78 d (from 152 d) and the thickness of ice by 6 or 22 cm (from 50 cm), respectively. [ABSTRACT FROM AUTHOR]

In order to improve the quality of the Mediterranean high-impact weather (HIW) numerical predictions, this study proposes to modify the potential vorticity (PV) field of the model initial state, taking advantage of information provided by the water vapour (WV) channel of the METEOSAT-7 satellite. The implemented PV field modifications aim to reduce the mismatch between the upper-level PV features and the WV brightness temperatures guided by the known relation between these two fields (PV-WV technique). The PV-WV technique effectiveness is evaluated on two HIW events, and is also compared with two additional PV modification techniques from an earlier study. The chosen episodes occurred on 9-10 June 2000 and 9-10 October 2002 and produced heavy precipitation over both Spain and France. The main difference between these two episodes is found in the driving mechanism, a mesoscale cyclone for the June 2000 event and a larger low-pressure centre for the October 2002 case. The two additional PV modification techniques introduce perturbations along the zones highlighted by the MM5 adjoint model calculated sensitivity zones (PV-adjoint) and along the three-dimensional PV structure presenting the locally most intense values and gradients of the field (PV-gradient). A close examination of both case studies of the forecast rainfall fields and several objective verification indices show that the PV-WV technique performance exceeds the control (or non-perturbed) forecast skill while remaining inside the distribution obtained by both PV-gradient and PV-adjoint techniques. This PV-WV technique could be used to increase the ensemble spread introducing higher amplitude modifications. Thus, a more skilled ensemble prediction system could be built by taking advantage of the subjectivity inherent to this method (manual perturbations) and also of the uncertainty present in the initial state. [ABSTRACT FROM AUTHOR]

This study investigated the potential impact of soil moisture perturbations on the statistical spread of an ensemble forecast for three different synoptic events during the summer of 2006. Soil moisture was perturbed from a control simulation to generate a 12 member ensemble with six drier and six moister soils. The impacts on the near-surface atmospheric conditions and on precipitation were analysed. It was found, as previous studies have confirmed, that soil moisture can change the spatial and temporal distribution of precipitation and of the overlying circulation. It was found that regardless of the conditions in synoptic forcing, temperature, relative humidity and horizontal wind field exhibited a spatial correlation coefficient (R) close to one with respect to the control simulation. Vertical velocity, however, showed a marked decrease in R down to 0.4 as the precipitation activity increased. For vertical velocity, however, this quantity grew to near 1.0 consistent with R near zero and standard deviations very close to that of the control. These results suggested a more complex picture in which soil moisture perturbations played a major role in modifying precipitation and the near-surface circulation but did not broaden the statistical spread of trajectories in phase space of all variables. [ABSTRACT FROM AUTHOR]

ABSTRACT The snow surface on thick multiyear sea ice in winter is on average colder than the air because of the negative radiation balance. Beneath the snow surface there is a strong temperature gradient in winter with increasing temperatures towards the ice-water interface temperature at the freezing point around -1.8 °C. The sea ice surface temperature and the thermal microwave brightness temperature were simulated using a combination of thermodynamic and microwave emission models. The simulations indicate that the physical snow-ice interface temperature or alternatively the 6 GHz effective temperature have a good correlation with the effective temperature at the temperature sounding channels near 50 GHz. The complete correlation matrix based on the simulations for physical and effective temperatures is given. The physical snow-ice interface temperature is related to the brightness temperature at 6 GHz vertical polarization as expected. However, the emissivity factor normally used when converting brightness temperature to the ice temperature is dependent on the ice temperature. The simulations indicate that a simple model may be used to derive the snow-ice interface temperature from satellite AMSR 6 GHz measurements. [ABSTRACT FROM AUTHOR]

ABSTRACT One key question regarding current climate models is whether the projection of climate extremes converges to a realistic representation as the spatial and temporal resolutions of the model are increased. Ideally the model extreme statistics should approach a fixed distribution once the resolutions are commensurate with the characteristic length and time scales of the processes governing the formation of the extreme phenomena of interest. In this study, a series of AGCM runs with idealized 'aquaplanet-steady-state' boundary conditions have been performed with the Community Atmosphere Model CAM3 to investigate the effect of horizontal resolution on climate extreme simulations. The use of the aquaplanet framework highlights the roles of model physics and dynamics and removes any apparent convergence in extreme statistics due to better resolution of surface boundary conditions and other external inputs. Assessed at a same large spatial scale, the results show that the horizontal resolution and time step have strong effects on the simulations of precipitation extremes. The horizontal resolution has a much stronger impact on precipitation extremes than on mean precipitation. Updrafts are strongly correlated with extreme precipitation at tropics at all the resolutions, while positive low-tropospheric temperature anomalies are associated with extreme precipitation at mid-latitudes. [ABSTRACT FROM AUTHOR]

Detection, attribution and understanding of temperature changes in the high northern latitudes depend on constraining uncertainties and resolving apparent discrepancies in observational data sets. We quantitatively compare four of the most widely used data sets of surface air temperature (SAT), and present a newly produced SAT data set, called NansenSAT. The existing data sets are highly correlated ( r∼ 0.8–0.9), except for some ocean areas. The evolution of SAT anomalies indicates differences reaching 3 °C during the 1920s–1930s warming period for the polar region (60–90°N). Substantial errors in trends also result from spatial sampling limitations, especially during the early–20th-century. Maximum differences between the data sets reaching 0.64 °C/100 yr are found in 1900–1999 linear trends in July and October for 60–90°N. We produced a new SAT data set for the region north of 40°N for the period 1900–2000, using all available data and Objective Analysis methods. The new data set has been compared with existing SAT data. For the polar region, the magnitude of temperature-trend errors caused by sparse data coverage is about 0.5 °C/100 yr. The advantage of the new data set is its enhanced spatial coverage in high latitudes. The NansenSAT data set is available for the research community. [ABSTRACT FROM AUTHOR]

Model differences in projections of global mean and regional climate change due to increasing greenhouse gases are investigated using two atmospheric general circulation models (AGCMs): ECHAM4 (Max Planck Institute, version 4) and CCM3 (National Center for Atmospheric Research Community Climate Model version 3). We replace the ECHAM4 short-wave processes (including routines for short-wave radiation, aerosols, cloud liquid water path and cloud droplet size distribution) with the corresponding parametrizations from CCM3. We also eliminate sea-ice in both models. We find that the resulting ‘hybrid’-ECHAM4 model has the same global mean temperature sensitivity (defined as the difference in temperature between the 2× CO2 and 1× CO2 integrations at equilibrium) and similar regional temperature change patterns as CCM3. The global mean precipitation sensitivity was only slightly affected; indicating different processes control this. Investigation of top of the atmosphere radiative feedbacks in the standard-ECHAM4 and hybrid-ECHAM4 models show that the differences in global mean temperature sensitivity and regional temperature change patterns can be attributed primarily to a stronger, negative, cloud short-wave feedback in the tropics of the hybrid-ECHAM4 model. However, comparison of the hybrid-ECHAM4 model to CCM3 reveals large differences in partitioning of the cloud feedbacks between long-wave and short-wave in the two models. This suggests that the global mean temperature sensitivity and regional temperature change patterns respond primarily to the magnitude and distribution of the top of the atmosphere feedbacks and are relatively insensitive to the partitioning between individual processes. [ABSTRACT FROM AUTHOR]

The statistical properties of temperature maxima are investigated in a very long integration (2 400 000 months) of an intermediate order Quasi-Geostrophic model displaying deterministic chaos. The variations of the moments of the extreme value distributions as a function of the time window, n, are first explored and compared with the behaviours expected from the classical Generalized Extreme Value (GEV) theory. The analysis reveals a very slow convergence (if any) toward the asymptotic GEV distributions. This highlights the difficulty in assessing the parameters of the GEV distribution in the context of deterministic chaotic (bounded) atmospheric flows. The properties of bivariate extremes located at different sites are then explored, with emphasis on their spatial dependences. Several measures are used indicating: (i) a complex dependence of the covariance between the extremes as a function of the time window; (ii) the presence of spatial (non-trivial) teleconnections for low-amplitude extremes and (iii) the progressive decrease of the spatial dependence as a function of the amplitude of the maxima. An interpretation of these different characteristics in terms of the internal dynamics of the model is advanced. [ABSTRACT FROM AUTHOR]

The atmosphere-ocean model ECHO-G, run with solar, volcanic and greenhouse gas forcing for the past millennium, is used to analyse winter and summer temperature variability in Scandinavia. Relationships with atmospheric circulation, North Atlantic SSTs and Northern Hemisphere (NH) temperatures are investigated at timescales longer and shorter than 10 yr. The simulated response to volcanic forcing is also analysed. Realistic relationships with the atmospheric circulation, with some deficiencies in summer, are found. High-frequency co-variations with SSTs and NH temperatures are too weak, but low-frequency co-variations with NH temperatures in winter are apparently too strong. The summer cooling response to volcanic forcing is realistic, but the expected winter warming is absent. The simulated long-term temperature evolution agrees broadly with proxy data. Combinations of several forcing factors can lead to decadal and multidecadal anomalies from the centennial trends. Decreased solar forcing can account for cold intervals in both summer and winter. A systematic negative North Atlantic Oscillation (NAO) phase can explain the coldest winter temperatures during 1590–1650. Several strong volcanic forcing events can have contributed to a simultaneous summer cooling. Proxy data also indicate cold summers and winters, and a negative NAO in winter, in the same period. [ABSTRACT FROM AUTHOR]

How much can we trust model-based projections of future anthropogenic climate change? This review attempts to give an overview of this important but difficult topic by using three main lines of evidence: the skill of models in simulating present-day climate, intermodel agreement on future climate changes, and the ability of models to simulate climate changes that have already occurred. A comparison of simulated and observed present-day climates shows good agreement for many basic variables, particularly at large horizontal scales, and a tendency for biases to vary in sign between different models, but there is a risk that these features might be partly a result of tuning. Overall, the connection between model skill in simulating present-day climate and the skill in simulating future climate changes is poorly known. An intercomparison of future climate changes between models shows a better agreement for changes in temperature than that for precipitation and sea level pressure, but some aspects of change in the latter two variables are also quite consistent between models. A comparison of simulations with observed climate changes is, in principle, a good test for the models, but there are several complications. Nonetheless, models have skilfully simulated many large-scale aspects of observed climate changes, including but not limited to the evolution of the global mean surface air temperature in the 20th century. Furthermore, although there is no detailed agreement between the simulated and observed geographical patterns of change, the grid box scale temperature, precipitation and pressure changes observed during the past half-century generally fall within the range of model results. Considering the difficulties associated with other sources of information, the variation of climate changes between different models is probably the most meaningful measure of uncertainty that is presently available. In general, however, this measure is more likely to underestimate than overestimate the actual uncertainty. [ABSTRACT FROM AUTHOR]

The properties of tropical cyclones in three low-resolution atmospheric general circulation models (AGCMs) in seven ocean basins are discussed. The models are forced by prescribed, observed sea surface temperatures over a period of 40 yr, and their simulations of tropical cyclone activity are compared with observations. The model cyclone characteristics considered include genesis position, number of cyclones per year, seasonality, accumulated cyclone energy, track locations, and number of storm days. Correlations between model and observed interannual variations of these characteristics are evaluated. The models are found able to reproduce the basic features of observed tropical cyclone behavior such as seasonality, general location and interannual variability, but with identifiable biases. A bias correction is applied to the tropical cyclone variables of the three models. The three AGCMs have different levels of realism in simulating different aspects of tropical cyclone activity in different ocean basins. Some strengths and weaknesses in simulating certain tropical cyclone activity variables are common to the three models, while others are unique to each model and/or basin. Although the overall skill of the models in reproducing observed interannual variability of tropical cyclone variables has not surpassed or often even equalled that of statistical models, there exists potential for higher future skills using improved versions of dynamical approaches. [ABSTRACT FROM AUTHOR]

Observational and modelling evidence suggest that poleward ocean heat transport (OHT) can vary in response to both natural climate variability and greenhouse warming. Recent modelling studies have shown that increased OHT warms both the tropical and global mean climates. Using two different coupled climate models with mixed-layer oceans, with and without OHT, along with a coupled model with a fixed-current ocean component in which the currents are uniformly reduced and increased by 50%, an attempt is made to explain why this may happen. OHT warms the global mean climate by 1 to 1.6 K in the atmospheric general circulation (AGCM) ML model and 3.5 K in the AGCM fixed current model. In each model the warming is attributed to an increase in atmospheric greenhouse trapping, primarily clear-sky greenhouse trapping, and a reduction in albedo. This occurs as OHT moistens the atmosphere, particularly at subtropical latitudes. This is not purely a thermodynamic response to the reduction in planetary albedo at these latitudes. It is a change in atmospheric circulation that both redistributes the water vapour and allows for a global atmospheric moistening—a positive ‘dynamical’ water vapour feedback. With increasing OHT the atmospheric water vapour content increases as atmospheric convection spreads out of the deep tropics. The global mean planetary albedo is decreased with increased OHT. This change is explained by a decrease in subtropical and mid-latitude low cloudiness, along with a reduction in high-latitude surface albedo due to decreased sea ice. The climate models with the mixed layer oceans underestimate both the subtropical low cloud cover and the high-latitude sea ice/surface albedo, and consequently have a smaller warming response to OHT. [ABSTRACT FROM AUTHOR]

Recent studies indicate that the atmospheric response to anomalies in the lower boundary conditions, e.g. sea surface temperatures, is strongly dependent on the atmospheric background flow. Since all general circulation models have long-term systematic errors it is therefore possible that the skill in seasonal prediction is improved by reducing the systematic errors of the model. In this study sensitivity experiments along this line are made with an empirically corrected dynamical model for which the systematic errors are reduced substantially and the dynamical variability has become more realistic than for the original model. As a measure of seasonal prediction skill, correlation of temporal anomalies between modelled and observed data has been determined. The corrected model shows improved skill in the Southern Hemisphere in general—on average a 20–30% improvement for the Southern Hemisphere compared with the original model. In the Northern Hemisphere skill is improved in some areas, but in other areas the skill of the original model is better. On average there is no improvement for the Northern Hemisphere. Also, pattern correlations have been determined for the following areas: the Northern Hemisphere, the Southern Hemisphere, the tropics and Europe. The general picture is that the two model versions are very similar in the Northern Hemisphere and in the tropics. For Europe the results of the two models are rather different, but no model can be said to be better than the other. In the Southern Hemisphere it is again seen that the correlations are higher for the corrected model than for the original model. [ABSTRACT FROM AUTHOR]

Aquasi-Newton method developed for adopting a non-diagonal first-guess covariance matrix in nonlinear variational analyses (i.e. variational analyses adopting a non-quadratic cost function) is presented. As an example, we also show the effect of the nonlinear relationship between temperature and sea-surface height in three-dimensional variational ocean analyses. [ABSTRACT FROM AUTHOR]

Predictability of seasonal precipitation in the Nordic countries (Denmark, Finland, Iceland, Norway and Sweden) is investigated using a nine-member ensemble of atmospheric general circulation model simulations with prescribed sea-surface temperature from October 1950 until March 1999. The simulations and corresponding observations from 65 stations in the Nordic countries are used to identify large-scale patterns of seasonal precipitation, the predictability of which is investigated. Subsequently, the identified large-scale patterns are used in a statistical downscaling of the model simulated precipitation. The downscaling, which is of the model output statistics type, yields seasonal predictions for the individual stations. The model simulations of precipitation are compared to predictions of precipitation directly from observed sea-surface temperature using a statistical prediction method and no dynamic model. The two different methods give consistent results. It is demonstrated that seasonal precipitation in the Nordic region contains a weak predictable signal in several seasons. The most skilful predictions can be made in spring, especially in the April-June season when precipitation appears to be influenced both by tropical and North Atlantic sea surface temperature. In particular, the North Atlantic Oscillation in winter appears to influence the North Atlantic sea-surface temperature in spring, which in turn has an effect on precipitation in Scandinavia. [ABSTRACT FROM AUTHOR]