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Ensemble forecasts aim to improve decision-making by predicting a set of possible outcomes. Ideally, these would provide probabilities which are both sharp and reliable. In practice, the models, data assimilation and ensemble perturbation systems are all imperfect, leading to deficiencies in the predicted probabilities. This paper presents an ensemble post-processing scheme which directly targets local reliability, calibrating both climatology and ensemble dispersion in one coherent operation. It makes minimal assumptions about the underlying statistical distributions, aiming to extract as much information as possible from the original dynamic forecasts and support statistically awkward variables such as precipitation. The output is a set of ensemble members preserving the spatial, temporal and inter-variable structure from the raw forecasts, which should be beneficial to downstream applications such as hydrological models. The calibration is tested on three leading 15-d ensemble systems, and their aggregation into a simple multimodel ensemble. Results are presented for 12 h, 1° scale over Europe for a range of surface variables, including precipitation. The scheme is very effective at removing unreliability from the raw forecasts, whilst generally preserving or improving statistical resolution. In most cases, these benefits extend to the rarest events at each location within the 2-yr verification period. The reliability and resolution are generally equivalent or superior to those achieved using a Local Quantile-Quantile Transform, an established calibration method which generalises bias correction. The value of preserving spatial structure is demonstrated by the fact that 3x3 averages derived from grid-scale precipitation calibration perform almost as well as direct calibration at 3x3 scale, and much better than a similar test neglecting the spatial relationships. Some remaining issues are discussed regarding the finite size of the output ensemble, variables such as sea-level pressure which are very reliable to start with, and the best way to handle derived variables such as dewpoint depression. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper focuses on the application of a simple analytical parameterization to the filling of the Ultraviolet Index (UVI) data gaps, and the reconstruction of past UVI values at Badajoz and Caceres (Southwestern Spain). The empirical model involves three independent variables: the solar zenith angle, the total ozone column and the clearness index. Regarding the first application, daily UVI was estimated for more than 30 days when UV measurements were not available in 2007. For these cases, the missing UVI data were replaced by estimated values, thus affecting the UVI annual mean and median. Regarding the second application, the reconstruction of past UVI time-series (1950-2000) is performed only for clear-sky cases (cloud and aerosol free conditions) using the COST 726 total ozone climatology. The linear UVI trends for two periods (1957-1978 and 1979-2000) are calculated for summer months using linear least squares fits. Both locations show statistically significant UVI trends for the most recent period 1979-2000, with values of +4.4 ± 1.6% per decade for Badajoz, and +4.9 ± 1.8% per decade for Caceres. This result is mainly driven by the ozone decline at northern mid-latitudes during this period. No significant trend is found for the other analysed period. [ABSTRACT FROM AUTHOR]

BSTRACT In order to assess the potential of regional climate models to be used to project future weather events, a first step is to study the regional model forced by actual weather, or more precisely by reanalysis of weather data. In this paper we investigate how well the Norwegian regional model HIRHAM, forced by ERA-40 reanalysis data, compares to observed precipitation data from the Norwegian Meteorological Institute over Norwegian mainland. This paper aims to show how standard methods of statistical testing may be used to assess dynamic downscaling. Methods considered are the Kolmogorov-Smirnov two-sample test, a Fisher exact test for equality of quantiles, an Extreme Value Theory test, where equality of the 1-yr return levels are tested, and equality of wet-day frequency. All tests are performed seasonally. The regional model is skillful in describing the lower quartile of the precipitation distribution, but underestimates higher levels of precipitation. Our results indicate that the regional model has too many but too small rain events for all seasons. [ABSTRACT FROM AUTHOR]

This paper constitutes the author's continuing effort in the construction of a minimal theory of the earth's climate. In an earlier paper published in the Journal of Climate in 2001, this author has derived the global-mean fields of an aquatic planet forced by the solar insolation, which provide the necessary constraints for the present derivation of the meridional thermal field. The model closure invokes maximized entropy production (MEP), a thermodynamic principle widely used in turbulence and climate studies. Based on differing convective regimes of the ocean and atmosphere, both fluids are first reduced two thermal masses with aligned fronts, consistent with a minimal description of the observed field. Subjected to natural bounds, a robust solution is then found, characterized by an ice-free ocean, near-freezing cold fluid masses, mid-latitude fronts, and comparable ocean and atmosphere heat transports. The presence of polar continents, however, sharply reduces the ocean heat transport outside the tropics, but leaves the thermal field largely unchanged. Given the limitation of an extremely crude model, the deduced thermal field nonetheless seems sensible, suggesting that the model has captured the physics for a minimal account of the observed field. Together with the above-mentioned paper, the model reinforces the pre-eminent role of the triple point of water in stabilizing the surface temperature – against changing external condition. Such internal control is made possible by the turbulent nature of the climate fluids, which necessitates a selection rule based on extremization. [ABSTRACT FROM AUTHOR]

In this paper, a multi-model ensemble approach with statistical correction for seasonal precipitation forecasts using a coupled DEMETER model data set is presented. Despite the continuous improvement of coupled models, they have serious systematic errors in terms of the mean, the annual cycle and the interannual variability; consequently, the predictive skill of extended forecasts remains quite low. One of the approaches to the improvement of seasonal prediction is the empirical weighted multi-model ensemble, or superensemble, combination. In the superensemble approach, the different model forecasts are statistically combined during the training phase using multiple linear regression, with the skill of each ensemble member implicitly factored into the superensemble forecast. The skill of a superensemble relies strongly on the past performance of the individual member models used in its construction. The algorithm proposed here involves empirical orthogonal function (EOF) filtering of the actual data set prior to the construction of a multi-model ensemble or superensemble as an alternative solution for seasonal prediction. This algorithm generates a new data set from the input multi-model data set by finding a consistent spatial pattern between the observed analysis and the individual model forecast. This procedure is a multiple linear regression problem in the EOF space. The newly generated EOF-filtered data set is then used as an input data set for the construction of a multi-model ensemble and superensemble. The skill of forecast anomalies is assessed using statistics of categorical forecast, spatial anomaly correlation and root mean square (RMS) errors. The various verifications show that the unbiased multi-model ensemble of DEMETER forecasts improves the prediction of spatial patterns (i.e. the anomaly correlation), but it shows poor skill in categorical forecast. Due to the removal of seasonal mean biases of the different models, the forecast errors of the bias-corrected multi-model ensemble and superensemble are already quite small. Based on the anomaly correlation and RMS measures, the forecasts produced by the proposed method slightly outperform the other conventional forecasts. [ABSTRACT FROM AUTHOR]

This paper describes the third full release of the Rossby Centre Regional Climate model (RCA3), with an emphasis on changes compared to earlier versions, in particular the introduction of a new tiled land-surface scheme. The model performance over Europe when driven at the boundaries by ERA40 reanalysis is discussed and systematic biases identified. This discussion is performed for key near-surface variables, such as temperature, precipitation, wind speed and snow amounts at both seasonal and daily timescales. An analysis of simulated clouds and surface turbulent and radiation fluxes is also made, to understand the causes of the identified biases. RCA3 shows equally good, or better, correspondence to observations than previous model versions at both analysed timescales. The primary model bias relates to an underestimate of the diurnal surface temperature range over Northern Europe, which maximizes in summer. This error is mainly linked to an overestimate of soil heat flux. It is shown that the introduction of an organic soil component reduces the error significantly. During the summer season, precipitation and surface evaporation are both overestimated over Northern Europe, whereas for most other regions and seasons precipitation and surface turbulent fluxes are well simulated. [ABSTRACT FROM AUTHOR]

This paper describes the potential effects of present-day aerosol pollution from North America (USA, Canada) on the climate of the North Atlantic region. The study has been performed by applying the comprehensive atmospheric general circulation model ECHAM5-HAM, which is coupled to a mixed-layer ocean with an embedded thermodynamic sea ice module. The model includes a microphysical aerosol model (HAM), which allows for the assessment of aerosol impacts on climate. Sulphate, black and organic carbon, sea salt and mineral dust are considered as aerosol species. Two equilibrium simulations with two different aerosol pollutant scenarios are compared for each season. We investigate the effect on radiation, temperature, hydrological quantities and dynamics, when human-induced aerosol emissions from North America were omitted. The decrease of both direct and indirect aerosol effects induces a positive change in top of the atmosphere (TOA) radiative fluxes resulting in an overall warming in the whole region. Our results demonstrate the vulnerability especially of the Arctic to the reduction in aerosol load. For fall we find an increase in precipitation over the North Atlantic, associated with a tendency to a larger number of cyclones with high-pressure gradients and a higher frequency in storm days. [ABSTRACT FROM AUTHOR]

Observations suggest that the large-scale tropical atmospheric circulations, associated with intraseasonal variabilties, are dominated more by the vorticity than the divergence. The present paper examines the consistency of the above observations with linear equatorial wave theories. Both free and forced linear waves are considered. The free equatorial waves are classified into two major categories: (1) the Rossby waves, strongly dominated by vorticity and (2) the inertial-gravity waves, relatively dominated by the divergence. Both the Kelvin and the mixed-Rossby gravity waves are intermediate of these two major categories. In the forced case, the wave response is predominantly inertial-gravity wave-like for periods less than 5 d, thus predominantly divergent. On the other hand, for forcing with the longer periods, the wave response closely following free Rossby-wave structures, asymptotically approaches to a non-divergent state. The asymptotic tendency for non-divergence is found to be much stronger than observed. The difference is so stark that, notably, the tropical intraseasonal variability cannot be consistent with linear equatorial waves theories. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) anomalies associated with El Niño/Southern Oscillation (ENSO) constitute a major source of predictability in the tropics. We evaluate the ability of a regional climate model (the Rossby Centre Atmospheric Model; RCA) to downscale SST and large-scale atmospheric anomalies associated with ENSO. RCA is configured over the tropical east Pacific and tropical Americas and runs for the period 1979–2005, using European Centre for Medium-Range Weather Forecasts (ECMWF) lateral and surface boundary conditions. We study the ability of RCA to represent regional patterns of precipitation, with respect to both the climatology and interannual variability associated with ENSO. The latter is achieved by grouping the simulations into El Niño and La Niña composites and studying the delayed response of precipitation to SST forcing in four regions of Central and South America. In this paper, we concentrate on seasonal mean timescales. We find that RCA accurately simulates the main features of the precipitation climatology over the four regions and also reproduces the majority of the documented regional responses to ENSO forcing. Furthermore, the model captures the variability in precipitation anomalies between different ENSO events. The model exhibits a wet bias over the northern Amazon and slightly overestimates the magnitude of ENSO anomalies over Central America. [ABSTRACT FROM AUTHOR]

We analyse the lifetimes (persistence) of circulation types using 23 classifications (of which 18 are objective and 5 subjective) in the period 1957–2002 over Europe and its subregions. The objective catalogues are developed on the same gridded climatic data (ECMWF ERA-40 reanalysis) but differ in the classification method used and in the number of synoptic types. Significant seasonal trends in the lifetime (both positive and negative) are fairly scarce and are present in all seasons in the manual catalogues only. In the subjective Hess–Brezowsky catalogue, there is an abrupt shift toward higher persistence in 1986, whereas in the Hungarian manual catalogue, a smaller but significant negative shift took place in the same year. These statistical inconsistencies probably result from inhomogeneities in the subjective catalogues. Our results suggest that the increase in the persistence of circulation types reported recently in several papers for the Hess–Brezowsky catalogue is an artefact rather than a real feature. [ABSTRACT FROM AUTHOR]

Although the large-scale tropical atmospheric circulations are often considered as primarily divergent, a simple scale analysis, originally presented by Charney (1963) , suggests otherwise—a dominance of vorticity over divergence. The present paper quantitatively documents the asymptotic non-divergence of the large-scale tropical atmosphere, in association with Madden–Julian oscillations, with use of the Tropical Ocean Global Atmosphere—Coupled Ocean Atmosphere Response Experiment, Large-Scale Array (TOGA–COARE LSA) data set. The vorticity is larger than the divergence at the majority (70%–80%) of points at any instant for the levels between 850 and 250 hPa, and the vorticity is more than 10 times stronger than the divergence both at 850 and 500 hPa more than half of the time. The root mean square (rms) ratio between the transient components of divergence and vorticity, which is defined as the deviation from the mean for the whole data period, decreases substantially with increasing horizontal scales from 100 to 2000 km, over an intraseasonal timescale (20–100 d). The analysis suggests that the Madden–Julian oscillations are dominated more by vorticity than divergence and more so than at the smaller scales. The analysis as a whole suggests the feasibility of constructing an asymptotically non-divergent theory for large-scale tropical circulations. A brief sketch of the formulation is presented. [ABSTRACT FROM AUTHOR]

Response function models are often used to represent the behaviour of complex, high order global carbon cycle (GCC) and climate models in applications which require short model run times. Although apparently black-box, these response function models need not necessarily be entirely opaque, but instead may also convey useful insights into the properties of the parent model or process. By exploiting a transfer function (TF) framework to analyse the Lenton GCC model, this paper attempts to demonstrate that response function representations of GCC models can sometimes also provide structural information on the parent model from which they are identified and calibrated. We take a fifth-order TF identified from the impulse response of the Lenton model atmospheric burden, and decompose this to show how it can be re-expresses in a generic five-box form in sympathy with the structure of the parent model. [ABSTRACT FROM AUTHOR]

The complexity of the laws of dynamics governing 3-D atmospheric flows associated with incomplete and noisy observations make the recovery of atmospheric dynamics from satellite image sequences very difficult. In this paper, we address the challenging problem of estimating physical sound and time-consistent horizontal motion fields at various atmospheric depths for a whole image sequence. Based on a vertical decomposition of the atmosphere, we propose a dynamically consistent atmospheric motion estimator relying on a multilayer dynamic model. This estimator is based on a weak constraint variational data assimilation scheme and is applied on noisy and incomplete pressure difference observations derived from satellite images. The dynamic model is a simplified vorticity-divergence form of a multilayer shallow-water model. Average horizontal motion fields are estimated for each layer. The performance of the proposed technique is assessed using synthetic examples and using real world meteorological satellite image sequences. In particular, it is shown that the estimator enables exploiting fine spatio-temporal image structures and succeeds in characterizing motion at small spatial scales. [ABSTRACT FROM AUTHOR]

Regional climate models (RCMs) are dynamical downscaling tools aimed to improve the modelling of local physical processes. Ensembles of RCMs are widely used to improve the coarse-grain estimates of global climate models (GCMs) since the use of several RCMs helps to palliate uncertainties arising from different dynamical cores and numerical schemes methods. In this paper, we analyse the differences and similarities in the climate change response for an ensemble of heterogeneous RCMs forced by one GCM (HadAM3H), and one emissions scenario (IPCC's SRES-A2 scenario). As a difference with previous approaches using PRUDENCE database, the statistical description of climate characteristics is made through the spatial and temporal aggregation of the RCMs outputs into probability distribution functions (PDF) of monthly values. This procedure is a complementary approach to conventional seasonal analyses. Our results provide new, stronger evidence on expected marked regional differences in Europe in the A2 scenario in terms of precipitation and temperature changes. While we found an overall increase in the mean temperature and extreme values, we also found mixed regional differences for precipitation. [ABSTRACT FROM AUTHOR]

This paper presents climatological properties of Northern Hemisphere summer extratropical storm tracks using data extracted from an existing, relative-vorticity-based storm database. This database was constructed using the NCEP-NCAR ‘Reanalysis I’ data set from 1948 to 2002. Results contrasting summer and winter patterns for several storm parameters indicated general similarity at the largest scales, including the prominent track corridors of the middle latitude ocean regions and the mid-continental and east coast genesis zones. Variations between seasons generally consisted of differences in the strength and position of these major features. Several results underscored by this study are: summer storms have longer life-spans than their winter counterparts; the Atlantic track corridor in summer is more tightly confined over northern Europe, whereas in winter it is more diffuse; summertime Atlantic storms are found to be slightly weaker but more numerous than their Pacific counterparts; Pacific storm counts exhibit a large drop from winter to summer that is not observed in the Atlantic; and summer storms appear to be related to the summer NAM, PDO and NAO. [ABSTRACT FROM AUTHOR]

Baroclinic waves give major contributions to the climatology and variability of key climate variables in mid- and high-latitudes. An important aspect of cyclone variability is the seriality (succession of cyclone occurrence). Serial cyclones are clustered in time and are associated with large economic losses in Europe. Cyclone variability and seriality are intimately linked to the low frequency variability. To have a realistic representation of high and mid-latitude regional climate in general circulation models (GCM), it is of vital importance that the described phenomena are realistically represented. In the present paper we evaluate the ability of the atmospheric GCM ARPEGE to represent various storm track parameters, both with respect to climatology and variability. Cyclone tracks are identified for the Northern Hemisphere during 55 extended winters (1950/51–2004/05) using the NCEP reanalyses by means of an objective tracking method. A corresponding cyclone track data set is derived from a simulation with ARPEGE, forced with observed monthly SSTs from 1950 to 2004. The comparison of the two data sets shows that ARPEGE reproduces the main features of the observed cyclone track fields. The mid-latitude corridors of cyclones and cyclone variability are well reproduced. The model, however, underestimates the mean number of cyclone occurrence and its variance. In the eastern North Atlantic and Nordic Seas the model simulates 70 and 90% of the observed mean cyclone occurrence and its variance, respectively. ARPEGE also substantially underestimates the clustering of cyclones in the eastern North Atlantic (jet exit region). In addition, the model also fails to simulate the relationship between clustering and low-frequency flow patterns at the exit of the North Atlantic storm track. [ABSTRACT FROM AUTHOR]

As a logical progression of a deductive climate theory, this paper addresses three interconnected climatic features: the humidity profile, the atmospheric water transport and the ocean stratification—taking as given the thermal field previously determined. The theory invokes the maximization of the entropy production, which propels the tropospheric temperature and specific humidity to their updraft values, yielding moist-adiabatic lapse rate and bi-modal relative humidity in the vertical. With the humidity profile known, the atmospheric water transport at mid-latitudes can be linked to the thermal field, which then determines the ocean salinity range. The deduced density ratio across the thermocline however is quite larger than unity, suggesting considerable static stability. The model deductions, while crude, are consistent with observations, which underscore the internal control of the hydrological cycle and ocean stratification by energy balances, with significant implications on climate changes. Doubling the atmospheric CO2, for example, only slightly perturbs the energy balance and with it the global precipitation and the high relative humidity near the surface. The warming would however more strongly enhance the atmospheric water transport to accentuate the zonal-mean E-P pattern and ocean salinity contrast. [ABSTRACT FROM AUTHOR]

Low-resolution global ocean models display hysteresis behaviour when forced with an anomalous freshwater input into the northern North Atlantic. Of central importance in this hysteresis behaviour is the existence of so-called saddle-node bifurcations. In this paper, focus is on the physical characterization of the multiple equilibrium regime using a fully implicit global ocean model for which bifurcation diagrams can be explicitly computed. The physics of the position of the relevant saddle-node bifurcation in parameter space is clarified and a modification of an earlier suggested diagnostic of the presence of the multiple equilibrium regime is proposed. The relevance of this indicator for coupled climate models is shown by studying the sensitivity of the multiple equilibria regime to changes in the horizontal and vertical diffusivities of the model. [ABSTRACT FROM AUTHOR]

Extending the meteorological record back in time can offer critical data for assessing tropical cyclone-climate links. While paleotempestology, the study of ancient storms, can provide a more realistic view of past ‘worst case scenarios’, future environmental conditions may have no analogues in the paleoclimate record. The primary value in paleotempestology proxy records arises from their ability to quantify climate–tropical cyclone interactions by sampling tropical cyclone activity during pre-historic periods with a wider range of different climates. New paleotempestology proxies are just beginning to be applied, encouraging new collaboration between the paleo and tropical cyclone dynamics communities. The aim of this paper is to point out some paths toward closer coordination by outlining target needs of the tropical cyclone theory and modelling community and potential contributions of the paleotempestology community. We review recent advances in paleotempestology, summarize the range of types and quality of paleodata generation, and identify future research opportunities for paleotempestology, tropical cyclone dynamics and climate change impacts and attribution communities. [ABSTRACT FROM AUTHOR]

This paper documents the diverse role of land-use/land-cover change on precipitation. Since land conversion continues at a rapid pace, this type of human disturbance of the climate system will continue and become even more significant in the coming decades. [ABSTRACT FROM AUTHOR]

This paper examines the implications of uncertainty in the carbon cycle for the cost of stabilizing carbon dioxide concentrations. Using a state of the art integrated assessment model, we find that uncertainty in our understanding of the carbon cycle has significant implications for the costs of a climate stabilization policy, with cost differences denominated in trillions of dollars. Uncertainty in the carbon cycle is equivalent to a change in concentration target of up to 100 ppmv. The impact of carbon cycle uncertainties are smaller than those for climate sensitivity, and broadly comparable to the effect of uncertainty in technology availability. [ABSTRACT FROM AUTHOR]

This paper describes a numerical study of the role of zonally symmetric normal modes in the dynamics of the Arctic Oscillation (AO) or Northern Hemisphere Annular Mode (NAM) with seasonally varying climatological fields. A general theory of the mechanism for normal mode selection involving a fully developed non-linear interaction between different modes is proposed, and this explains not only the prominence of the AO/NAM in the Northern Hemisphere, but also the existence of the Antarctic Oscillation (AAO) in the Southern Hemisphere. Following this normal mode selection mechanism, zonally symmetric normal mode with spatial structures resembling those of the AO and AAO is extracted by use of ECMWF data and the linear operator of a two-dimensional model with a seasonally varying basic state. The interannual variability of this mode is also investigated in the light of this theory. [ABSTRACT FROM AUTHOR]

Sulfate aerosols (of both biogenic and anthropogenic origin) play a key role in the Earth's radiation balance both directly through scattering and absorption of solar and terrestrial radiation, and indirectly by modifying cloud microphysical properties. However, the uncertainties associated with radiative forcing of climate due to aerosols substantially exceed those associated with the greenhouse gases. The major source of sulfate aerosols in the remote marine atmosphere is the biogenic compound dimethylsulfide (DMS), which is ubiquitous in the world's oceans and is synthesized by plankton. Climate models point to significant future changes in sea-ice cover in the Arctic Ocean due to warming. This will have consequences for primary production and the sea-to-air flux of a number of biogenic compounds, including DMS. In this paper we discuss the impact of warming on the future production of DMS in the Arctic Ocean. A DMS production model has been calibrated to current climate conditions with satellite ocean colour data (SeaWiFS) using a genetic algorithm, an efficient non-derivative based optimization technique. We use the CSIRO Mk 2 climate model to force the DMS model under enhanced greenhouse climate conditions. We discuss the simulated change in DMS flux and its consequences for future aerosol production and the radiative budget of the Arctic. Significant decreases in sea-ice cover (by 18.5% annually and 61% in summer–autumn), increases in mean annual sea surface temperature of 1°C, and a decrease of mixed layer depth by 13% annually are predicted to result in annual DMS flux increases of over 80% by the time of equivalent CO2 tripling (2080). Estimates of the impact of this increase in DMS emissions suggest significant changes to summer aerosol concentrations and the radiative balance in the Arctic region. [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) is a dominant pattern of large-scale variability in the Northern Hemisphere, with important regional effects on the winter climate of Europe. Nested regional climate models (RCMs) can be useful tools for studying the regional signal of the NAO. Therefore, it is important to assess whether they can reproduce the observed NAO signal over Europe when driven by lateral boundary conditions from global climate models. In this paper we investigate the NAO-related winter variability over Europe in a RCM simulation driven by large-scale fields from an atmospheric global model simulation forced with historic sea surface temperature and sea ice distribution for the period 1961–1990. We show that (1) the NAO-related winter variability signal over the European region shows substantial topographically induced fine-scale features, both for temperature and precipitation, and (2) the model is capable of reproducing many aspects of this fine-scale regional signal and, in particular, the topographically forced regional response of precipitation to NAO-type circulations. We conclude that nested regional climate models can be used to study the fine-scale regional signature of the NAO under different climatic conditions. [ABSTRACT FROM AUTHOR]

In this paper we present a unified conceptual framework for the creation of calibrated probability forecasts of observable variables based on information from ensembles of weather/climate model predictions. For the same reasons that data assimilation is required to feed observed information into numerical prediction models, an analogous process of forecast assimilation is required to convert model predictions into well-calibrated forecasts of observable variables. Forecast assimilation includes and generalizes previous calibration methods such as model output statistics and statistical downscaling. To illustrate the approach, we present a flexible variational form of forecast assimilation based on a Bayesian multivariate normal model capable of assimilating multi-model predictions of gridded fields. This method is then successfully applied to equatorial Pacific sea surface temperature grid point predictions produced by seven coupled models in the DEMETER project. The results show improved forecast skill compared to individual model forecasts and multi-model mean forecasts. [ABSTRACT FROM AUTHOR]

We discuss a novel three-tier hierarchical approach to the validation of an end-to-end seasonal climate forecast system. We present a malaria transmission simulation model (MTSM) driven with output from the DEMETER multi-model seasonal climate predictions, to produce probabilistic hindcasts of malaria prevalence. These prevalence hindcasts are second-tier validated against estimates from the MTSM driven with ERA-40 gridded analyses. The DEMETER–MTSM prevalence hindcasts are shown to be (tier-2) skilful for the one-month lead seasonal predictions as well as for the period covering the seasonal malaria peak with a 4–6 month forecast window for the event prevalence above the median. Interestingly, the tier-2 Brier skill score for the forecast window of the hindcasts starting in February, for the event prevalence above the median, is higher than for either the tier-1 precipitation or temperature forecasts, which were the MTSM driving variables. [ABSTRACT FROM AUTHOR]

Coupled climate and carbon cycle modelling studies have shown that the feedback between global warming and the carbon cycle, in particular the terrestrial carbon cycle, could accelerate climate change and result in greater warming. In this paper we investigate the sensitivity of this feedback for year 2100 global warming in the range of 0 to 8 K. Differing climate sensitivities to increased CO2 content are imposed on the carbon cycle models for the same emissions. Emissions from the SRES A2 scenario are used. We use a fully coupled climate and carbon cycle model, the INtegrated Climate and CArbon model (INCCA), the NCAR/DOE Parallel Climate Model coupled to the IBIS terrestrial biosphere model and a modified OCMIP ocean biogeochemistry model. In our integrated model, for scenarios with year 2100 global warming increasing from 0 to 8 K, land uptake decreases from 47% to 29% of total CO2 emissions. Due to competing effects, ocean uptake (16%) shows almost no change at all. Atmospheric CO2 concentration increases are 48% higher in the run with 8 K global climate warming than in the case with no warming. Our results indicate that carbon cycle amplification of climate warming will be greater if there is higher climate sensitivity to increased atmospheric CO2 content; the carbon cycle feedback factor increases from 1.13 to 1.48 when global warming increases from 3.2 to 8 K. [ABSTRACT FROM AUTHOR]

Reanalysis data obtained from data assimilation are increasingly used for diagnostic studies of the general circulation of the atmosphere, for the validation of modelling experiments and for estimating energy and water fluxes between the Earth surface and the atmosphere. Because fluxes are not specifically observed, but determined by the data assimilation system, they are not only influenced by the utilized observations but also by model physics and dynamics and by the assimilation method. In order to better understand the relative importance of humidity observations for the determination of the hydrological cycle, in this paper we describe an assimilation experiment using the ERA40 reanalysis system where all humidity data have been excluded from the observational data base. The surprising result is that the model, driven by the time evolution of wind, temperature and surface pressure, is able to almost completely reconstitute the large-scale hydrological cycle of the control assimilation without the use of any humidity data. In addition, analysis of the individual weather systems in the extratropics and tropics using an objective feature tracking analysis indicates that the humidity data have very little impact on these systems. We include a discussion of these results and possible consequences for the way moisture information is assimilated, as well as the potential consequences for the design of observing systems for climate monitoring. It is further suggested, with support from a simple assimilation study with another model, that model physics and dynamics play a decisive role for the hydrological cycle, stressing the need to better understand these aspects of model parametrization. [ABSTRACT FROM AUTHOR]

ABSTRACT This study focuses on the atmospheric temperature response to dust deduced from a new source of data–the European Reanalysis (ERA) increments. These increments are the systematic errors of global climate models, generated in the reanalysis procedure. The model errors result not only from the lack of desert dust but also from a complex combination of many kinds of model errors. Over the Sahara desert the lack of dust radiative effect is believed to be a predominant model defect which should significantly affect the increments. This dust effect was examined by considering correlation between the increments and remotely sensed dust. Comparisons were made between April temporal variations of the ERA analysis increments and the variations of the Total Ozone Mapping Spectrometer aerosol index (AI) between 1979 and 1993. The distinctive structure was identified in the distribution of correlation composed of three nested areas with high positive correlation (>0.5), low correlation and high negative correlation (< -0.5). The innermost positive correlation area (PCA) is a large area near the center of the Sahara desert. For some local maxima inside this area the correlation even exceeds 0.8. The outermost negative correlation area (NCA) is not uniform. It consists of some areas over the eastern and western parts of North Africa with a relatively small amount of dust. Inside those areas both positive and negative high correlations exist at pressure levels ranging from 850 to 700 hPa, with the peak values near 775 hPa. Dust-forced heating (cooling) inside the PCA (NCA) is accompanied by changes in the static instability of the atmosphere above the dust layer. The reanalysis data of the European Center for Medium Range Weather Forecast (ECMWF) suggest that the PCA (NCA) corresponds mainly to anticyclonic (cyclonic) flow, negative (positive) vorticity and downward (upward) airflow. These findings are associated with the interaction between dust-forced heating/cooling and atmospheric circulation. This paper contributes to a better understanding of dust radiative processes missed in the model. [ABSTRACT FROM AUTHOR]

An introduction to articles published within the issue is presented, including a biographical sketch describing oceanographer J. W. Sandström's meteorological and oceanographical research and another on the dynamical properties of climate models as well as on their representation of some key physical processes going beyond the typical time-mean diagnostics.

The study evaluates the performance of the dimension-reduced projection four-dimensional variational data assimilation (DRP-4-DVar) with the Lorenz-96 model. Idealized experiments over a period of 200 days have been conducted. The results show that the DRP-4-DVar works well. It generates an analysis equivalent to that of the Ensemble Kalman Filter (EnKF) if the synchronous observations are assimilated at the analysis time, while it produces more accurate analysis than the EnKF does when assimilating observations in an 18-h assimilation window. The experiments also reveal that the impact of the tangent linear assumption for the Lorenz-96 model in the DRP-4-DVar over a 24-h or shorter assimilation window is negligible. Furthermore, with a background error covariance matrix (-matrix) that has a non-singular projection onto the ensemble space or is explicitly flow-dependent, the DRP-4-DVar performs even better than with a -matrix that has a singular projection or is not explicitly flow-dependent. [ABSTRACT FROM AUTHOR]

ENSEMBLES stream 2 single-model and multimodel ensemble seasonal precipitation forecasts are evaluated over the African continent with respect to Global Precipitation Climatology Centre (GPCC) precipitation data for the 1960-2005 time period using deterministic and probabilistic skill scores. Focus is set on three regions of Africa during main precipitation seasons: West Africa during boreal summer, southern Africa during austral summer and the Greater Horn of Africa during the 'long rains' and 'short rains' transition seasons. The 45-member multimodel improves the ensemble spread-skill ratio over all regions, which translates into enhanced skill in terms of anomaly correlation and ranked probability skill scores for climatological precipitation deciles over West Africa and southern Africa. Results are contrasted depending on the region and probabilistic formulations of the ensemble predictions after a quantile-quantile calibration give valuable information essentially over areas where deterministic skill is found. Probabilistic skill scores illustrate the range of possibilities for more user-related applications of ensemble seasonal forecasts. A simple illustration using a cost-loss model shows that model potential economic values can reach over 10% depending on the regions and occurrences studied. [ABSTRACT FROM AUTHOR]

The ice cover of the Arctic peripheral seas bordering the Northern North Atlantic is examined for 1992–2008 using the ARTIST Sea Ice (ASI) algorithm applied to derive the sea ice concentration from 85 GHz SSM/I measurements. Our analysis reveals a 2 months longer ice-free season in the Irminger Sea (IS), and reductions in ice area and extent between 1992–1999 and 2000–2008 by 10–20% during winter and 30–55% in summer. Barents Sea (BS) ice-cover anomalies (ICA) persist twice as long as ICA in the other regions. Early winter ICA in region IS are correlated to late summer/fall Greenland Sea (GS) ICA. Summertime GS and wintertime IS ICA are correlated to winter Fram Strait ice-area flux anomalies. The wintertime GS ice-cover decrease is associated with less Is Odden events. Our analysis suggests a large-scale, interregional ocean–ice–atmosphere feedback mechanism involving regions BS, Kara (KS) and White/Pechora Sea (WPS). To understand this mechanism the current and preceding general atmospheric circulation, associated variations in Arctic Ocean ice export and oceanic heat advection are needed. However, our results suggest (1) BS ICA could play a key role to predict subsequent KS ICA and (2) anomalous Arctic Ocean ice export into BS could trigger long-lasting BS ICA. [ABSTRACT FROM AUTHOR]

Reports on a workshop held during the Climate Conference in August 2001 at Utrecht University in the Netherlands regarding the katabatic flows over glaciers and ice sheets. Effects of turbulence on the glacier surface and atmosphere; Reasons behind the existence of katabatic flows; Discussion on the spatial scale of glaciers.

abstract The quantitative formulation of the fertilization effect of CO2 enrichment on net primary production (NPP) introduced by Keeling and Bacastow in 1970s (known as Keeling's formula) has been recognized as a summary of experimental data and has been used in various assessments of the industrial impact on atmospheric chemistry. Nevertheless, the magnitude of the formula's key coefficient, the so-called growth factor, has remained open to question. Some of the global carbon cycle modelers avoid this question by tuning growth factor and choosing the value that fits the observed course of atmospheric CO2 changes. However, for mapping terrestrial sinks induced by the CO2 fertilization effect one needs a geographical pattern of the growth factor rather than its globally averaged value. The earlier approach to this problem involved formulating the climate dependence of the growth factor and the derivation of its global pattern from climatic variables (whose geographical distribution is known). We use a process-based model (TsuBiMo) for this purpose and derive the values of growth factor for major biomes for comparison our approach with the earlier studies. Contrary to the earlier prevailing opinion, TsuBiMo predicts that these values decrease with mean annual temperature (excluding biomes of limited water supply). We attribute this result to the effect of light limitation caused by mutual shading inside a canopy, which was considered earlier as unimportant, and conclude that current hypotheses about CO2 fertilization effect (and thus projections of the related carbon sink) are very sensitive to the choice of driving forces taken into account. [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.

Discusses research arising from the project DEMETER or Development of a Multi-model Ensemble System for Seasonal to International Climate Prediction funded by the European Union Vth Framework Programme. Origins of DEMETER; Basis of the usefulness of seasonal climate predictions; Legacy left by DEMETER.

An evaporation duct climatology is constructed for the Gulf of Aden using a 31-year high-resolution data set from the climate reanalysis product National Centers for Environmental Prediction Climate Forecast System Reanalysis. The climatology reveals spatio-temporal heterogeneity in the evaporation duct height (EDH) regulated by the strong interplay between the seasonal monsoon reversals and the related atmospheric and oceanic responses. It also reveals that the Gulf of Aden exhibits a special EDH distribution that is distinct from the adjacent Arabian Sea when the south-west monsoon dominates the gulf. Under these conditions, the EDH of the entire gulf is significantly higher than that of the adjoining Arabian Sea. A cliff-style EDH drop (referred to as the EDH cliff) forms at the mouth of the Gulf of Aden. Furthermore, the influence of the EDH cliff on marine radar was investigated using a ray-optics method. Based on the analysis, it was found that the local EDH significantly affects the radar detection ability beneath the evaporation duct for ships sailing in the Gulf of Aden. [ABSTRACT FROM AUTHOR]

In this study, reanalysis and regional atmospheric modelling was used to resolve the climatology and mesoscale structure, spatial variability and temporal characteristics of the Oman coastal low-level jet (CLLJ). The limited area model COAMPS® was used at a 6-km horizontal resolution for a 5-month period (May–September) during 2009. Analysis of high-resolution model fields reveals the mesoscale structure of the Oman CLLJ, clearly distinguishing it from the large-scale South Asia monsoon circulation farther offshore, and from the previously identified Findlater (or Somali) jet, which occurs at a higher altitude. The Oman CLLJ is closer to the coast and spreads northeastward along the coast of Oman, clearly interacting with the coastal topography and headlands. It has a very strong annual cycle, related to the South Asia monsoon, with July exhibiting the highest CLLJ frequency of occurrence (around 80%) and highest wind speeds (around 27 ms−1), and May and September being the transition months. The southerly location of the Oman CLLJ, along with the very strong inland summer heating in the Arabian Peninsula, affects its diurnal cycle, with highest number of occurrences early in the morning, whereas the highest wind speeds occur during late afternoon, setting this CLLJ apart from other coastal jets in mid-latitude areas along eastern boundary currents. [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]

ABSTRACT The Adélie Land coastal region of Antarctica is one of the most prominent cyclogenesis regions in the Southern Hemisphere, and is adjacent to the continent's most intense katabatic wind regime. However, the physical mechanisms responsible for cyclogenesis are not known. A manual analysis of cyclogenesis for the 2003-2005 period using output from the Antarctic Mesoscale Prediction System (AMPS) identifies two primary patterns of cyclogenesis near the Adélie Land coast. For 'secondary development' cyclones, enhanced low-level cyclonic vorticity and baroclinicity result from the combination of an existing synoptic-scale cyclone to the west, coastal barrier winds and katabatic winds. 'Lee cyclogenesis' occurs near 152°E on the cyclonic-shear side of the Adélie Land katabatic jet, where a low-level warm potential temperature anomaly sets up a lee trough that becomes mobile with the arrival of upper-level synoptic-scale forcing. The representation of both 'secondary development' and 'lee cyclogenesis' cyclones in an automated cyclone-tracking scheme is explored, where it is found that the automated scheme overestimates cyclogenesis for this region. The location of the Antarctic coastal cyclogenesis maximum near Adélie Land is due to the unique juxtaposition of the extraordinary katabatic wind regime and dissipating synoptic-scale cyclones to the west. [ABSTRACT FROM AUTHOR]

BSTRACT A new and consistent convection scheme, providing continuous treatment of this atmospheric process, is described. The main concept ensuring the consistency of the whole system is buoyancy, a key element of any convective vertical motion. The buoyancy constitutes the forcing term of the convective vertical velocity, which is then used to define the triggering condition, the mass flux and the rates of entrainment-detrainment. The buoyancy is also used in its vertically integrated form to express the closure condition as a CAPE relaxation. The continuous treatment of convection from dry thermals to deep precipitating cumulus is made possible through the use of a continuous formulation of the entrainment-detrainment rates and CAPE relaxation time, together with an embedded precipitation scheme. This convection scheme is first evaluated with the help of single-column model simulations of specific case studies encompassing a variety of convective situations. Second, a coupled general-circulation model multiyear simulation is provided as a means to assess the model climate with respect to observations. [ABSTRACT FROM AUTHOR]

BSTRACT Reproduction of daily maximum and minimum temperatures, including tails of their distributions and links to large-scale circulation, is evaluated in an ensemble of high-resolution regional climate model (RCM) simulations over the Czech Republic. RCM data for recent climate (1961-1990) are validated against observed data gridded from a high-density station network. We find large biases in mean monthly temperatures and in seasonal extremes, which are significant in most RCMs throughout the year. The results suggest that an RCM's formulation plays a much more important role in summer, whereas in winter RCM performance is closely linked to the driving GCM. Biases are usually larger for extremes than central parts of temperature distributions, and RCMs tend to underestimate the severity of extremes in both seasons. Substantial underestimation of diurnal temperature range throughout the year in all RCMs and a shift of maximum in its annual cycle suggest general errors in simulating climate processes affecting the difference between daytime and nighttime temperatures. Some features of the temperature biases in RCMs are related to deficiencies in the simulation of atmospheric circulation, particularly too strong advection and overestimation of westerly flow at the expense of easterly flow in most RCMs. The general biases in simulating anticyclonic, cyclonic and straight flow also contribute to the underestimated diurnal temperature range. [ABSTRACT FROM AUTHOR]

BSTRACT The operational performance and usefulness of regional climate models at seasonal time scales are assessed by downscaling an ensemble of global seasonal forecasts. The Rossby Centre RCA regional model was applied to downscale a five-member ensemble from the ECMWF System3 global model in the European Atlantic domain for the period 1981-2001. One month lead time global and regional precipitation predictions were compared over Europe-and particularly over Spain-focusing the study in SON (autumn) dry events. A robust tercile-based probabilistic validation approach was applied to compare the forecasts from global and regional models, obtaining significant skill in both cases, but over a wider area for the later. Finally, we also analyse the performance of a mixed ensemble combining both forecasts. [ABSTRACT FROM AUTHOR]

BSTRACT The trends of terrestrial carbon exchange and their mechanistic drivers are key components in understanding how carbon reservoirs will respond to climate change. Here we show trends in seasonal non-fossil land-atmosphere carbon exchange from 1980 to 2008 using atmospheric CO [ABSTRACT FROM AUTHOR]

Clouds play a crucial role in the Arctic climate system. Therefore, it is essential to accurately and reliably quantify and understand cloud properties over the Arctic. It is also important to monitor and attribute changes in Arctic clouds. Here, we exploit the capability of the CALIPSO-CALIOP instrument and provide comprehensive statistics of tropospheric thin clouds, otherwise extremely difficult to monitor from passive satellite sensors. We use 4 yr of data (June 2006-May 2010) over the circumpolar Arctic, here defined as 67-82°N, and characterize probability density functions of cloud base and top heights, geometrical thickness and zonal distribution of such cloud layers, separately for water and ice phases, and discuss seasonal variability of these properties. When computed for the entire study area, probability density functions of cloud base and top heights and geometrical thickness peak at 200-400, 1000-2000 and 400-800 m, respectively, for thin water clouds, while for ice clouds they peak at 6-8, 7-9 and 400-1000 m, respectively. In general, liquid clouds were often identified below 2 km during all seasons, whereas ice clouds were sensed throughout the majority of the upper troposphere and also, but to a smaller extent, below 2 km for all seasons. [ABSTRACT FROM AUTHOR]

Regional climate models (RCMs) primarily represent physical components of the climate system, omitting vegetation dynamics, ecosystem biogeochemistry and their associated feedbacks. To account for such feedbacks, we implemented a novel plant individual-based vegetation dynamics-ecosystem biogeochemistry scheme within the RCA3 RCM. Variations in leaf area index (LAI) of seven plant functional type (PFTs) in response to physical forcing and evolving vegetation state feed back to climate via adjustments in surface energy fluxes and surface properties. In an ERA-40-driven simulation over Europe, the model reproduces the recent past climate with comparable accuracy to the standard RCM. Large-scale patterns of LAI, net primary production and vegetation composition were comparable with observations, although winter LAI was systematically overestimated compared to satellite estimates. Analysis of the ERA-40 simulation and an A1B climate-change simulation revealed considerable covariation among dynamic variables of the physical climate and vegetation. At a Mediterranean site, periodic soil water limitation led to fluctuations in leaf cover and a likely positive feedback to near-surface temperature. At an alpine site, rising temperatures led to forest advance onto tundra areas, reducing albedo and effecting a likely positive feedback on temperature. Climate-vegetation coupling was less pronounced but still apparent at intermediate temperate and boreal sites. [ABSTRACT FROM AUTHOR]

ABSTRACT We assess the impact of two sources of uncertainties in a limited area model (LAM) on the representation of intense precipitation: the size of the domain of integration and the use of the spectral nudging technique (driving of the large-scale within the domain of integration). We work in a perfect-model approach where the LAM is driven by a general circulation model (GCM) run at the same resolution and sharing the same physics and dynamics as the LAM. A set of three 50 km resolution simulations run over Western Europe with the LAM ALADIN-Climate and the GCM ARPEGE-Climate are performed to address this issue. Results are consistent with previous studies regarding the seasonal-mean fields. Furthermore, they show that neither the use of the spectral nudging nor the choice of a small domain are detrimental to the modelling of heavy precipitation in the present experiment. [ABSTRACT FROM AUTHOR]

Several 1000 yr runs of the University of Victoria Earth System Climate Model (UVic ESCM) with a hydraulically controlled overflow in the Denmark Strait are used to analyse the effects of NAO-like variations of the wind stress localized in the subpolar North Atlantic. The focus is laid on improving the representation of the Atlantic meridional overturning circulation (AMOC), the sea surface temperatures in the Nordic Seas and the sea ice coverage without increasing the resolution of the global model. We show that by implementing hydraulic control in the Denmark Strait Overflow the AMOC can be enhanced at depths between 1000 and 3000 m by up to 7 Sverdrup (Sv) towards more realistic values. The stability of the Deep Western Boundary Current is considerably enhanced. The expansion of sea ice into the Nordic Seas in the standard run is pushed back from about N to N when hydraulic parametrization is switched on. In this case sea ice variations at N and Northern Europe air temperatures exhibit a lag of 9 yr to variations in the wind stress curl. [ABSTRACT FROM AUTHOR]