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Climate models project an intensification of the wintertime North Atlantic Ocean storm track, over its downstream region, by the end of this century. Previous studies have suggested that ocean–atmosphere coupling plays a key role in this intensification, but the precise role of the different components of the coupling has not been explored and quantified. In this paper, using a hierarchy of ocean coupling experiments, we isolate and quantify the respective roles of thermodynamic (changes in surface heat fluxes) and dynamic (changes in ocean heat flux convergence) ocean coupling in the projected intensification of North Atlantic transient eddy kinetic energy (TEKE). We show that dynamic coupling accounts for nearly all of the future TEKE strengthening as it overcomes the much smaller effect of surface heat flux changes to weaken the TEKE. We further show that by reducing the Arctic amplification in the North Atlantic, ocean heat flux convergence increases the meridional temperature gradient aloft, causing a larger eddy growth rate and resulting in the strengthening of North Atlantic TEKE. Our results stress the importance of better monitoring and investigating the changes in ocean heat transport, for improving climate change adaptation strategies. Significance Statement: By the end of this century, the North Atlantic Ocean storm track is projected to intensify on its eastward flank. Such intensification will have large societal impacts, mostly over western Europe. Thus, it is critical to better understand the mechanism underlying the intensification of the storm track. Here we investigate the role of ocean coupling in the future intensification of the North Atlantic storm track and find that ocean heat transport processes are responsible for the strengthening of the storm track. Our results suggest that better monitoring the changes in ocean heat transport will hopefully improve climate change adaption strategies. [ABSTRACT FROM AUTHOR]

This paper generalizes and applies recently developed blocking diagnostics in a two-dimensional (2D) latitude-longitude context, which takes into consideration both mid- and high-latitude blocking. These diagnostics identify characteristics of the associated wave breaking as seen in the potential temperature θ on the dynamical tropopause, particularly the cyclonic or anticyclonic direction of wave breaking ('DB index') and the relative intensity ('RI index') of the air masses that contribute to blocking formation. The methodology is extended to a 2D domain and a cluster technique is deployed to classify mid- and high-latitude blocking according to the wave-breaking characteristics. Midlatitude blocking is observed over Europe and Asia, where the meridional gradient of θ is generally weak, whereas high-latitude blocking is mainly present over the oceans, to the north of the jet stream, where the meridional gradient of θ is much stronger. They occur on the equatorward and poleward flank of the jet stream, respectively, where the horizontal shear ∂ u/∂ y is positive in the first case and negative in the second case. A regional analysis is also conducted. Warm-cyclonic blocking over the Pacific and cold-anticyclonic blocking over Europe are identified as the most persistent types and are associated with large amplitude anomalies in temperature and precipitation. Finally, the high-latitude cyclonic events seem to correlate well with low-frequency modes of variability over the Pacific and Atlantic Oceans. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal method for estimating time-dependent climate change signals from general circulation models. The basic idea is to identify vectors that maximize the mean-square detection statistic derived from optimal fingerprinting techniques. The method also provides an objective and systematic procedure for identifying the limit to which a signal can be restricted in space and time without losing detectability. As an illustration, the method is applied to the Coupled Model Intercomparison Project, phase 3 multimodel dataset to determine the continental seasonal-mean anomaly in surface air temperature and precipitation that is most detectable, on average, in these models. Anomalies in seasonal-mean surface air temperature are detectable in all seasons by almost all models on all continents but Europe; seasonal-mean anomalies over Europe are undetectable for some models, though this does not preclude other expressions of the signal, such as those that include longer time averages or time-lag information, from being detectable. Detectability in seasonal-mean temperature is found not only for multidecadal warming trends but also for cooling after major volcanic eruptions. In contrast, seasonal-mean precipitation anomalies are detectable in only a few models for averages over 5 yr or more, suggesting that the signal should include more spatiotemporal detail to be detectable across more models. Nevertheless, of the precipitation anomalies that are detectable, the signal appears to be of two characters: a systematic trend and enhanced frequency of extreme values. These results derived from twentieth-century simulations appear to be consistent with previous studies based on twenty-first-century simulations with larger signal-to-noise ratios. [ABSTRACT FROM AUTHOR]

Perturbed physics ensembles (PPEs) have been widely used to assess climate model uncertainties and have provided new estimates of climate sensitivity and parametric uncertainty in state-of-the-art climate models. So far, mainly global climate models were used to generate PPEs, and little work has been conducted with regional climate models. This paper discusses the parameter uncertainty in two PPEs of a regional climate model driven by reanalysis data for the present climate over Europe. The uncertainty is evaluated for the variables of 2-m temperature, precipitation, and total cloud cover, with a focus on the annual cycle, interannual variability, and selected extremes. The authors show that the simulated spread of the PPEs encompasses the observations at a regional scale in terms of the annual cycle and the interannual variability, provided observational uncertainty is taken into account. To rank the PPEs a new skill metric is proposed, which takes into account observational uncertainty and natural variability. The metric is a generalization of the climate prediction index (CPI) and is compared to metrics used in other studies. The consideration of observational uncertainty is particularly important for total cloud cover and reveals that current observations do not allow for a systematic evaluation of high precipitation intensities over the entire European domain. The skill framework is additionally used to identify important model parameters, which are of interest for an objective model calibration. [ABSTRACT FROM AUTHOR]

The idea of using large-scale information to predict local climate variability is widely exploited in climate change impact studies as an alternative to computationally expensive high-resolution models. This approach implies the hypothesis that the statistical relationship between large-scale climate states and local variables defined for the present-day climate remains valid in the altered climate. In this paper, the concept of weather regimes is used to deduce a relationship between large-scale circulation and European winter temperature. The change in temperature with increased greenhouse gases is, however, not homogeneous among the individual regimes. As a result, the impact of the weather regimes on local temperature changes varies in the future, limiting its usefulness for refining temperature changes to the small scale. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the precipitation climate signal in Europe emerging from a simulation of heterogeneous regional climate models (RCMs) using five observational datasets as the reference for present day climate conditions. Current climate simulations, as well as those from the A2 family of scenarios from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES-A2), from eight RCMs involved in the Prediction of Regional Scenarios and Uncertainties for Defining European Climate Change Risks and Effects (PRUDENCE) project have been cross-compared with data from the Climate Research Unit (CRU), the Global Precipitation Climatology Project (GPCP), the Global Precipitation Climatology Centre (GPCC), the Climate Prediction Center (CPC), and the CPC Merged Analysis of Precipitation (CMAP) databases for Europe. The RCMs used are HIRHAM, the Climate High Resolution Model (CHRM), the Rossby Centre Atmosphere–Ocean (RCAO) model, the GKSS Climate Version of the Local Model (CLM), the Hadley Center RCM (HadRM3H), the Atmospheric Hydrostatic Regional Model (REMO), the Prognostic Model at the Mesoscale (PROMES), and the regional coupled ocean–atmosphere–ice model (RACMO). The comparison shows that the climate signal has to be interpreted depending on the reference data used. Although each validation dataset has its own relative merits and shortcomings, it is known that all of the datasets present variable uncertainties and error sources, which impedes consideration of a single dataset as the only valid representation of actual precipitation. Hence, it is suggested that a robust joint estimate of changes in future precipitation might include the uncertainties of both the RCMs and those of the observational datasets. After accounting for the difference between observed and simulated precipitation in the present climate, the analysis of such joint estimates reveals significant agreement in the climate signal for most of Europe. This lends confidence to the idea that the RCMs are able to correctly simulate future changes in precipitation. [ABSTRACT FROM AUTHOR]

Drought in spring and early summer has been shown to precede anomalous hot summer temperature. In particular, drought in the Mediterranean region has been recently shown to precede and to contribute to the development of extreme heat in continental Europe. In this paper, this mechanism is investigated by performing integrations of a regional mesoscale model at the scale of the European continent in order to reproduce hot summer inception, starting with different initial values of soil moisture south of 46°N. The mesoscale model is driven by the large-scale atmospheric conditions corresponding to the 10 hottest summers on record from the European Climate Assessment dataset. A northward progression of heat and drought from late spring to summer is observed from the Mediterranean regions, which leads to a further increase of temperature during summer in temperate continental Europe. Dry air formed over dry soils in the Mediterranean region induces less convection and diminished cloudiness, which gets transported northward by occasional southerly wind, increasing northward temperature and vegetation evaporative demand. Later in the season, drier soils have been established in western and central Europe where they further amplify the warming through two main feedback mechanisms: 1) higher sensible heat emissions and 2) favored upper-air anticyclonic circulation. Drier soils in southern Europe accelerate the northward propagation of heat and drying, increasing the probability of strong heat wave episodes in the middle or the end of the summer. [ABSTRACT FROM AUTHOR]

The evaluation of the diurnal cycle of cloud amount (CA) and cloud condensed water path (CWP) as predicted by climate models receives relatively little attention, mostly because of the lack of observational data capturing the diurnal cycle of such quantities. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary Meteosat-8 satellite is the first instrument able to provide accurate information on diurnal cycles during daylight hours of cloud properties over land and ocean surfaces. This paper evaluates the daylight cycle of CA and CWP as predicted by the Regional Atmospheric Climate Model version 2 (RACMO2), using corresponding SEVIRI retrievals. The study is done for Europe using hourly cloud properties retrievals from SEVIRI during the summer months from May to September 2004. The results of this study show that SEVIRI-retrieved daylight cycles of CA and CWP provide a powerful tool for identifying climate model deficiencies. Over Europe the SEVIRI retrievals of cloud condensed water paths comprise about 80% liquid water and about 20% ice water. The daylight cycles of CA and CWP from SEVIRI show large spatial variations in their mean values and time of daily maximum and daytime-normalized amplitude. In general, RACMO2 overestimates CWP by about 30% and underestimates CA by about 20% as compared to SEVIRI. The largest amplitudes are observed in the Mediterranean and northern Africa. For the greater part of the ocean and coastal areas the time of daily maximum CWP is found during morning, whereas over land this maximum is found after local solar noon. These features are reasonably well captured by RACMO2. In the Mediterranean and continental Europe RACMO2 tends to predict maximum CWP associated with convection to occur about two hours earlier than SEVIRI indicates. [ABSTRACT FROM AUTHOR]

This paper analyzes the changes in the precipitation climatologies of Europe for the periods 1960–90 and 2070–2100 using a heterogeneous set of regional climate models (RCMs). The authors used the Climatic Research Unit (CRU) database to define a precipitation climatology for current climate conditions (1960–90), then compare the estimates with the RCMs’ simulations for the same period using spectral analysis. After the authors evaluated the performance of the models compared with validation data for current climate, they calculated the future climate spectra (2070–2100). Changes in the future climate have been evaluated in terms of differences in the phase and amplitude of the annual cycle with respect to present conditions. The results show that models provide consistent results and that under the A2 scenario (increased greenhouse gases conditions) precipitation climatologies in Europe are expected to suffer noticeable changes, the most important being a strengthening of the annual cycle in most of the Atlantic coastal areas of the continent. While total amounts of rainfall might undergo little change, the consequences of changes in the seasonal distribution of precipitation will strongly affect both ecosystems and human activities. Differences were also found in the probability distribution function (pdf) of precipitation, indicating an overall increase in the frequency of precipitation-related hazards in Europe. [ABSTRACT FROM AUTHOR]

ABSTRACT The European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA) results for July 1987 are compared with stratocumulus observations for the same period made during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE). The FIRE I experiment, conducted off the coast of California, provided a comprehensive observational set of data on marine stratocumulus during July 1987. The observations reported in this paper and used as a basis for comparison with the ERA results include the mean diurnal variation of cloud cover, liquid water path, cloud-base and cloud-top height, incoming short-wave and long-wave radiation at the surface, and monthly mean vertical profiles of (potential) temperature and specific humidity. It is concluded that the ERA thermal structure in the boundary layer is quite realistic and the ERA data reveal some diurnal variability. However, in ERA the cloud thickness is overestimated and cloud cover and liquid water path are strongly underestimated as compared with the FIRE I observations. As a result the ERA downwelling short-wave radiation at the surface is much larger than observed in FIRE I. It is argued that the large difference between the ERA downwelling shortwave radiation at the surface and that observed in FIRE I can lead to large biases in the sea surface temperature in a coupled ocean-atmosphere model. [ABSTRACT FROM AUTHOR]

Results are presented from the project Clear-sky Longwave from ERA (CLERA), in which simulations were performed of clear-sky longwave fluxes and heating rates for the period 1979-93, based on data from the European Centre for Medium-Range Weather Forecasts Re-Analysis project (ERA). This paper presents selected results from CLERA and compares the clear-sky outgoing longwave radiation (OLR) with data from the Earth Radiation Budget Experiment (ERBE). Over much of the globe, especially over the oceans, the clear-sky OLR from CLERA is within the expected uncertainty in the ERBE data of 65 W m 22 . Elsewhere, there are larger differences and to study these the ERA data are compared with independent sources of information: surface synoptic observations of screen-level temperatures and retrievals of the total column moisture and upper-tro-pospheric humidity from satellite data. Over land, the largest clear-sky OLR differences occur at high latitudes in winter and these can be explained by the fact that the ERA surface temperatures are too low in these regions. However, for many other regions over land there was no obvious explanation for the clear-sky OLR differences. Over the oceans, the clear-sky OLR differences in the Tropics are consistent with known systematic biases in ERBE, the most important consequence of which is that the ERBE clear-sky OLR is too high in convective regions such as the ITCZ. [ABSTRACT FROM AUTHOR]