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Currently, major efforts are under way to refine the horizontal resolution of weather and climate models to kilometer-scale grid spacing (Dx). Besides refining the representation of the atmospheric dynamics and enabling the use of explicit convection, this will also provide higher resolution in the representation of orography. This study investigates the influence of these resolution increments on the simulation of orographic moist convection. Nine days of fair-weather thermally driven flow over the Alps are analyzed. Two sets of simulations with the COSMO model are compared, each consisting of three runs at Dx of 4.4, 2.2, and 1.1 km: one set using a fixed representation of orography at a resolution of 8.8 km, and one with varying representation at the resolution of the computational mesh. The spatial distribution of precipitation during daytime is only marginally affected by the orographic details, but nighttime convection to the south of the Alps-triggered by cold-air outflow from the valleys-is very sensitive to orography and precipitation is enhanced if more detailed orography is provided. During daytime, the onset of precipitation is delayed. The amplitude of the diurnal cycle of precipitation is reduced, even though more moisture converges toward the Alpine region during the afternoon. The hereby accumulated moisture sustains precipitation during the evening and nighttime over the surrounding plains. For these differences, the effects of changes in orographic detail are more important than changes in grid spacing. In addition, the individual convective cells are weaker, but their number increases with higher resolved orography. © 2020 American Meteorological Society ISSN:1520-0493 ISSN:0027-0644

Over the past few decades the horizontal resolution of regional climate models (RCMs) has steadily increased, leading to a better representation of small-scale topographic features and more details in simulating dynamical aspects, especially in coastal regions and over complex terrain. Due to its complex terrain, the broader Adriatic region represents a major challenge to state-of-the- art RCMs in simulating local wind systems realistically. The objective of this study is to identify the added value in near-surface wind due to the refined grid spacing of RCMs. For this purpose, we use a multi-model ensemble composed of CORDEX regional climate simulations at 0.11° and 0.44° grid spacing, forced by the ERA-Interim reanalysis, a COSMO convection- parameterizing simulation at 0.11° and a COSMO convection-resolving simulation at 0.02° grid spacing. Surface station observations from this region and satellite QuikSCAT data over the Adriatic Sea have been compared against daily output obtained from the available simulations. Both day-to-day wind and its frequency distribution are examined. The results indicate that the 0.44° RCMs rarely outperform ERA- Interim reanalysis, while the performance of the high- resolution simulations surpasses that of ERA- Interim. We also disclose that refining the grid spacing to a few km is needed to properly capture the small-scale wind systems. Finally, we show that the simulations frequently yield the accurate angle of local wind regimes, such as for the Bora flow, but overestimate the associated wind magnitude. Finally, spectral analysis shows good agreement between measurements and simulations, indicating the correct temporal variability of the wind speed.

The Global Energy Balance Archive (GEBA) is a database for the central storage of the worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 dataset, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and contains in its 2017 version around 500 000 monthly mean entries of various surface energy balance components measured at 2500 locations. The database contains observations from 15 surface energy flux components, with the most widely measured quantity available in GEBA being the shortwave radiation incident at the Earth's surface (global radiation). Many of the historic records extend over several decades. GEBA contains monthly data from a variety of sources, namely from the World Radiation Data Centre (WRDC) in St. Petersburg, from national weather services, from different research networks (BSRN, ARM, SURFRAD), from peer-reviewed publications, project and data reports, and from personal communications. Quality checks are applied to test for gross errors in the dataset. GEBA has played a key role in various research applications, such as in the quantification of the global energy balance, in the discussion of the anomalous atmospheric shortwave absorption, and in the detection of multi-decadal variations in global radiation, known as global dimming and brightening. GEBA is further extensively used for the evaluation of climate models and satellite-derived surface flux products. On a more applied level, GEBA provides the basis for engineering applications in the context of solar power generation, water management, agricultural production and tourism. GEBA is publicly accessible through the internet via http://www.geba.ethz.ch. Supplementary data are available at https://doi.org/10.1594/PANGAEA.873078.

Convection-resolving models allow to explicitly resolve deep convection at horizontal grid spacings of O(1 km). On current supercomputers, refining the grid spacing to the kilometer scale is computationally still extremely demanding, and therefore climate simulations at this resolution have so far largely been limited to sub-continental computational domains. However, new supercomputers that mix conventional multi-core CPUs and accelerators possess properties beneficial for climate codes. Exploiting these capabilities allows expansion of the size of the computational domains to continental scales. Here we present such a convection-resolving climate simulation, using a version of the COSMO model, capable of exploiting GPU accelerators. The simulation has a grid spacing of 2.2 km, 1536×1536×60 grid points, covers the period 1999-2008, and is driven by the ERA-Interim reanalysis. An assessment of the 10-year-long simulation is conducted using a wide range of data sets, including several rain-gauge networks, energy balance stations, and a remotely-sensed lightning data set. Substantial improvements are found for the 2 km simulation in terms of the diurnal cycles of precipitation. This confirms results found in studies using smaller computational domains. However, the continental-scale simulations also reveal deficiencies such as substantial performance differences between regions with and without strong orographic forcing. Analysis of the statistical distribution of updrafts and downdrafts shows an increase of the amplitude in seasons with convection, and a pronounced asymmetry between updrafts and downdrafts. Furthermore, the analysis of lightning data shows that the convection-resolving simulation is able to reproduce important features of the annual cycle of deep convection in Europe.

Potential vorticity is among the most important scalar quantities in atmospheric dynamics. For instance, potential vorticity plays a key role in particularly strong wind peaks in extratropical cyclones and it is able to explain the occurrence of frontal rain bands. Potential vorticity combines the key quantities of atmospheric dynamics, namely rotation and stratification. Under suitable wind conditions elongated banners of potential vorticity appear in the lee of mountains. Their role in atmospheric dynamics has recently raised considerable interest in the meteorological community for instance due to their influence in aviation wind hazards and maritime transport. In order to support meteorologists and climatologists in the analysis of these structures, we developed an extraction algorithm and a visual exploration framework consisting of multiple linked views. For the extraction we apply a predictor-corrector algorithm that follows streamlines and realigns them with extremal lines of potential vorticity. Using the agglomerative hierarchical clustering algorithm, we group banners from different sources based on their proximity. To visually analyze the time-dependent banner geometry, we provide interactive overviews and enable the query for detail on demand, including the analysis of different time steps, potentially correlated scalar quantities, and the wind vector field. In particular, we study the relationship between relative humidity and the banners for their potential in indicating the development of precipitation. Working with our method, the collaborating meteorologists gained a deeper understanding of the three-dimensional processes, which may spur follow-up research in the future.

This review paper explores the field of mesoscale to microscale modeling over complex terrain as it traverses multiple so-called gray zones. In an attempt to bridge the gap between previous large-scale and small-scale modeling efforts, atmospheric simulations are being run at an unprecedented range of resolutions. The gray zone is the range of grid resolutions where particular features are neither subgrid nor fully resolved, but rather are partially resolved. The definition of a gray zone depends strongly on the feature being represented and its relationship to the model resolution. This paper explores three gray zones relevant to simulations over complex terrain: turbulence, convection, and topography. Taken together, these may be referred to as the gray continuum. The focus is on horizontal grid resolutions from ∼10 km to ∼10 m. In each case, the challenges are presented together with recent progress in the literature. A common theme is to address cross-scale interaction and scale-awareness in parameterization schemes. How numerical models are designed to cross these gray zones is critical to complex terrain applications in numerical weather prediction, wind resource forecasting, and regional climate modeling, among others., Atmosphere, 10 (5), ISSN:2073-4433

In the framework of the global energy balance, the radiative energy exchanges between Sun, Earth and space are now accurately quantified from new satellite missions. Much less is known about the magnitude of the energy flows within the climate system and at the Earth surface, which cannot be directly measured by satellites. In addition to satellite observations, here we make extensive use of the growing number of surface observations to constrain the global energy balance not only from space, but also from the surface. We combine these observations with the latest modeling efforts performed for the 5th IPCC assessment report to infer best estimates for the global mean surface radiative components. Our analyses favor global mean downward surface solar and thermal radiation values near 185 and 342 Wm−2, respectively, which are most compatible with surface observations. Combined with an estimated surface absorbed solar radiation and thermal emission of 161 and 397 Wm−2, respectively, this leaves 106 Wm−2 of surface net radiation available globally for distribution amongst the non-radiative surface energy balance components. The climate models overestimate the downward solar and underestimate the downward thermal radiation, thereby simulating nevertheless an adequate global mean surface net radiation by error compensation. This also suggests that, globally, the simulated surface sensible and latent heat fluxes, around 20 and 85 Wm−2 on average, state realistic values. The findings of this study are compiled into a new global energy balance diagram, which may be able to reconcile currently disputed inconsistencies between energy and water cycle estimates., Climate Dynamics, 40, ISSN:0930-7575, ISSN:1432-0894

Climatic Change, 101 (3-4), ISSN:0165-0009, ISSN:1573-1480

Climate impact studies constitute the basis for the formulation of adaptation strategies. Usually such assessments apply statistically postprocessed output of climate model projections to force impact models. Increasingly, time series with daily resolution are used, which require high consistency, for instance with respect to transition probabilities (TPs) between wet and dry days and spell durations. However, both climate models and commonly applied statistical tools have considerable uncertainties and drawbacks. This paper compares the ability of 1) raw regional climate model (RCM) output, 2) bias-corrected RCM output, and 3) a conventional weather generator (WG) that has been calibrated to match observed TPs to simulate the sequence of dry, wet, and very wet days at a set of long-term weather stations across Switzerland. The study finds systematic biases in TPs and spell lengths for raw RCM output, but a substantial improvement after bias correction using the deterministic quantile mapping technique. For the region considered, bias-corrected climate model output agrees well with observations in terms of TPs as well as dry and wet spell durations. For the majority of cases (models and stations) bias-corrected climate model output is similar in skill to a simple Markov chain stochastic weather generator. There is strong evidence that bias-corrected climate model simulations capture the atmospheric event sequence more realistically than a simple WG.

A Bayesian hierarchical model for heterogeneous multimodel ensembles of global and regional climate models is presented. By applying the methodology herein to regional and seasonal temperature averages from the ENSEMBLES project, probabilistic projections of future climate are derived. Intermodel correlations that are particularly strong between regional climate models and their driving global climate models are explicitly accounted for. Instead of working with time slices, a data archive is investigated in a transient setting. This enables a coherent treatment of internal variability on multidecadal time scales. Results are presented for four European regions to highlight the feasibility of the approach. In particular, the methodology is able to objectively identify patterns of variability changes, in ways that previously required subjective expert knowledge. Furthermore, this study underlines that assumptions about bias changes have an effect on the projected warming. It is also shown that validating the out-of-sample predictive performance is possible on short-term prediction horizons and that the hierarchical model herein is competitive. Additionally, the findings indicate that instead of running a large suite of regional climate models all forced by the same driver, priority should be given to a rich diversity of global climate models that force a number of regional climate models in the experimental design of future multimodel ensembles.

How clouds respond to warming remains the greatest source of uncertainty in climate projections. Improved computational and observational tools can reduce this uncertainty. Here we discuss the need for research focusing on high-resolution atmosphere models and the representation of clouds and turbulence within them.

Ship tracks provide an ideal test bed for studying aerosol–cloud interactions (ACIs) and for evaluating their representation in model parameterisations. Regional modelling can be of particular use for this task, as this approach provides sufficient resolution to resolve the structure of the produced track including their meteorological environment whilst relying on the same formulations of parameterisations as many general circulation models. In this work we simulate a particular case of ship tracks embedded in an optically thin stratus cloud sheet which was observed by a polar orbiting satellite at 12:00 UTC on 26 January 2003 around the Bay of Biscay. The simulations, which include moving ship emissions, show that the model is indeed able to capture the structure of the track at a horizontal grid spacing of 2 km and to qualitatively capture the observed cloud response in all simulations performed. At least a doubling of the cloud optical thickness was simulated in all simulations together with an increase in cloud droplet number concentration by about 40 cm−3 (300%) and decrease in effective radius by about 5 μm (40%). Furthermore, the ship emissions lead to an increase in liquid water path in at least 25% of the track regions. We are confident in the model's ability to capture key processes of ship track formation. However, it was found that realistic ship emissions lead to unrealistic aerosol perturbations near the source regions within the simulated tracks due to grid-scale dilution and homogeneity. Combining the regional-modelling approach with comprehensive field studies could likely improve our understanding of the sensitivities and biases in ACI parameterisations, and could therefore help to constrain global ACI estimates, which strongly rely on these parameterisations.

The Global Energy Balance Archive (GEBA) is a database for the worldwide measured energy fluxes at the Earth’s surface. GEBA is maintained at ETH Zurich (Switzerland) and has been founded in the 1980s by Prof. Atsumu Ohmura. It has continuously been updated and currently contains around 2500 stations with 500‘000 monthly mean entries of various surface energy balance components. Many of the records extend over several decades. The most widely measured quantity available in GEBA is the solar radiation incident at the Earth’s surface (“global radiation”). The data sources include, in addition to the World Radiation Data Centre (WRDC) in St. Petersburg, data reports from National Weather Services, data from different research networks (BSRN, ARM, SURFRAD), data published in peer-reviewed publications and data obtained through personal communications. Different quality checks are applied to check for gross errors in the dataset. GEBA is used in various research applications, such as for the quantification of ...

In previous studies1, 2 we derived new estimates for the magnitude of the components of the global mean energy budget using to the extent possible the information contained in direct observations from surface and space. Here we establish complementary estimates for the global mean energy budget specifically under cloud-free conditions. The energy fluxes under cloud-free conditions at the Top of Atmosphere (TOA) can be determined with high accuracy from satellite measurements (CERES-EBAF). For the estimation of their counterparts at the Earth’s surface we follow the approach presented in our recent studies, based on an analysis of 39 state of the art global climate models from CMIP5 and their bias structure compared to a comprehensive set of high quality surface observations from the Baseline Surface Radiation Network (BSRN). Thereby we infer a best estimate of 249 Wm−2 for the global mean clear-sky downward shortwave radiation at the surface, and a corresponding clear-sky surface shortwave absorption of 2...

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.

The explicit treatment of moist convection in cloud-resolving models with kilometer-scale horizontal resolution is increasingly used for atmospheric research and numerical weather prediction purposes. However, several previous studies have implicitly questioned the physical validity of this approach, as the accurate representation of the structure and evolution of moist convective phenomena requires considerably higher resolution. Unlike these studies, which focused on single convective systems, here the convergence of bulk properties of an ensemble of moist convective cells in kilometer-scale simulations is considered. To address the convergence, the authors focus on the bulk net heating and moistening in a large control volume, the associated vertical fluxes, and the diurnal evolution of regionally averaged precipitation. Besides numerical convergence, “physical” convergence (Reynolds number increases with resolution) is addressed for two conceptually different subgrid-mixing approaches (1D mesoscale and 3D LES). Simulations are conducted for a 9-day period of diurnal summer convection over the Alps, using a large computational domain with grid spacings of 4.4, 2.2, 1.1, and 0.55 km and grid-independent topography. Results show that for the model and episode considered, the simulated bulk properties and vertical fluxes converge numerically toward the 0.55-km solution. In terms of bulk effects, differences between the simulations are surprisingly small, even within the physical convergence framework that exhibits a sensitivity of the small-scale dynamics and ensuing convective structures to the horizontal resolution. Despite some sensitivities related to the applied turbulence closure, the results support the feasibility of kilometer-scale models to appropriately represent the bulk feedbacks between moist convection and the larger-scale flow.

Increasing the aerosol number in warm-phase clouds is thought to decrease the rain formation rate, whereas the physical processes taking place in mixed-phase clouds are more uncertain. Increasing number concentrations of soluble aerosols may reduce the riming efficiency and therefore also decrease precipitation. On the other hand, the glaciation of a cloud by heterogeneous freezing of cloud droplets may enhance the formation of graupel and snow. Using a numerical weather prediction model with coupled aerosol microphysics, it is found, in a statistical framework with 270 clean and polluted 2D simulations of mixed-phase precipitation over an Alpine transect, that the presence of the ice phase determines the magnitude and the sign of the effect of an increasing aerosol number concentration on orographic precipitation. Immersion/condensation freezing is the only ice-nucleating process considered here. It is shown that this indirect aerosol effect is much less pronounced in cold simulations compared to a warmer subset and that cloud glaciation tends to compensate the loss of rain in polluted situations. Comparing the clean and polluted cases, a reduction of rain by 52%, on average (std dev = 25%), over the transect in the polluted cases is found. For frozen precipitation a much broader range of differences is found (mean = +4%, std dev = 60%). Furthermore, this study shows that in comparison with the clean cases more precipitation spills over to the leeward side of the major ridge in the polluted cases (median = +14.6%).

This paper introduces an idealized cloud-resolving modeling (CRM) framework for the study of midlatitude diurnal convection over land. The framework is used to study the feedbacks among soil, boundary layer, and diurnal convection. It includes a setup with explicit convection and a full set of parameterizations. Predicted variables are constantly relaxed toward prescribed atmospheric profiles and soil conditions. The relaxation is weak in the lower troposphere and upper soil to allow the development of a realistic diurnal planetary boundary layer. The model is run to its own equilibrium (30 days). The framework is able to produce a realistic timing of the diurnal cycle of convection. It also confirms the development of deeper convection in a more unstably stratified atmosphere. With this relaxation method, the simulated “diurnal equilibrium convection” determines the humidity profile of the lower atmosphere, and the simulation becomes insensitive to the reference humidity profile. However, if a faster relaxation time is used in the lower troposphere, the convection and rainfall become much more sensitive to the reference humidity, consistent with previous studies.

Most atmospheric models use terrain-following coordinates, and it is well known that the associated deformation of the computational mesh leads to numerical inaccuracies. In a previous study, the authors proposed a new terrain-following coordinate formulation [the smooth level vertical (SLEVE) coordinate], which yields smooth vertical coordinate levels at mid and upper levels and thereby considerably reduces numerical errors in the simulation of flow past complex topography. In the current paper, a generalization of the SLEVE coordinate is presented by using a modified vertical decay of the topographic signature with height. The new formulation enables an almost uniform thickness of the lowermost computational layers, while preserving the fast transition to smooth levels in the mid and upper atmosphere. This allows for a more consistent and more stable coupling with planetary boundary layer schemes, while retaining the advantages over classic sigma coordinates at upper levels. The generalized SLEVE coordinate is implemented and successfully tested in real-case simulations using an operational nonhydrostatic atmospheric model.

A new snow scheme for the European Centre for Medium-Range Weather Forecasts (ECMWF) land surface model has been tested and validated. The scheme includes a new parameterization of snow density, incorporating a liquid water reservoir, and revised formulations for the subgrid snow cover fraction and snow albedo. Offline validation (covering a wide range of spatial and temporal scales) includes simulations for several observation sites from the Snow Models Intercomparison Project-2 (SnowMIP2) and global simulations driven by the meteorological forcing from the Global Soil Wetness Project-2 (GSWP2) and by ECMWF Re-Analysis ERA-Interim. The new scheme reduces the end of season ablation biases from 10 to 2 days in open areas and from 21 to 13 days in forest areas. Global GSWP2 results are compared against basin-scale runoff and terrestrial water storage. The new snow density parameterization increases the snow thermal insulation, reducing soil freezing and leading to an improved hydrological cycle. Simulated snow cover fraction is compared against NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) with a reduction of the negative bias of snow-covered area of the original snow scheme. The original snow scheme had a systematic negative bias in surface albedo when compared against Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data. The new scheme reduces the albedo bias, consequently reducing the spatial- and time-averaged surface net shortwave radiation bias by 5.2 W m−2 in 14% of the Northern Hemisphere land. The new snow scheme described in this paper was introduced in the ECMWF operational forecast system in September 2009 (cycle 35R3).

Rain gauges and weather radars both constitute important devices for operational precipitation monitoring. Gauges provide accurate yet spotty precipitation estimates, while radars offer high temporal and spatial resolution yet at a limited absolute accuracy. We propose a simple methodology to combine radar and daily rain-gauge data to build up a precipitation dataset with hourly resolution covering a climatological time period. The methodology starts from a daily precipitation analysis, derived from a dense rain-gauge network. A sequence of hourly radar analyses is then used to disaggregate the daily analyses. The disaggregation is applied such as to retain the daily precipitation totals of the rain-gauge analysis, in order to reduce the impact of quantitative radar biases. Hence, only the radar's advantage in terms of temporal resolution is exploited. In this article the disaggregation method is applied to derive a 15-year gridded precipitation dataset at hourly resolution for Switzerland at a spatial resolution of 2 km. Validation of this dataset indicates that errors in hourly intensity and frequency are lower than 25% on average over the Swiss Plateau. In Alpine valleys, however, errors are typically larger due to shielding effects of the radar and the corresponding underestimation of precipitation periods by the disaggregation. For the flatland areas of the Swiss Plateau, the new dataset offers an interesting quantitative description of high-frequency precipitation variations suitable for climatological analyses of heavy events, the evaluation of numerical weather forecasting models and the calibration/operation of hydrological runoff models.

This study explores the potential added-value of applying cloud-resolving resolution to climate simulations. A month-long (July 2006) integration is performed with the CCLM on a convection-resolving grid of 2.2-km (0.02°) mesh size spanning the whole Alpine region. The initial and lateral boundary conditions stem from a coarser-resolution 25-km (0.22°) CCLM integration. Comparison to observations indicates that the cloud-resolving simulation is able to capture the overall precipitation distribution and evolution. With respect to its driving lower-resolution integration, the cloud-resolving resolution yields a more accurate spatial localization of the precipitation maxima, reduces the cold bias, and especially reproduces a better timing of the convective diurnal cycle. The explicit resolution delays the onset of convective precipitation by about 2 h, shifts the time of peak precipitation by a similar period, and slows down the decay of convective activity in the afternoon. In return, the integration shows a tendency to underestimate the afternoon convective rainfalls, particularly under weak synoptic and/or orographic forcing. This latter effect might be improved by modifying the treatment of subgrid-scale clouds in the model.

In this study we explore the potential benefits of applying a cloud-resolving ensemble prediction system (EPS; 2.2 km grid spacing) over its driving synoptic-scale limited-area EPS (COSMO-LEPS, 10 km grid spacing, driven by the ECMWF EPS) for a case of heavy precipitation over the Alpine region. The selected event is the devastating August 2005 flood that affected the northern Alpine slopes. The cloud-resolving EPS includes an explicit treatment of deep convection and dynamically downscales the COSMO-LEPS information. Results are compared against rain-gauge and radar data. Furthermore, the sensitivity of the results to initial versus lateral boundary uncertainties are analyzed using a series of additional simulations. Comparison of the cloud-resolving and its driving limited-area EPS pinpoints the high skill of both ensembles in simulating the major phase of heavy precipitation. The high-resolution EPS yields more realistic rain amounts, in particular in areas of active convection, but in general the resolution-induced differences tend to be smaller than typical member-to-member variability. The differences between the two ensembles can be tied to the synoptic situation (stratiform or convective precipitation, location of the cyclone), to the mesoscale interaction of the flow with the topography (flow over the Alpine ridge), and to the experimental set-up (lead time and computational domain). For the considered event and set-up, the growth of initial perturbations dominates over lateral boundary uncertainties during the first ∼12 integration hours. Afterwards, the ensemble spread is controlled by large-scale error growth advected from the lateral boundaries into the domain. Copyright © 2008 Royal Meteorological Society

Appropriate precautions in the case of flood occurrence often require long lead times (several days) in hydrological forecasting. This in turn implies large uncertainties that are mainly inherited from the meteorological precipitation forecast. Here we present a case study of the extreme flood event of August 2005 in the Swiss part of the Rhine catchment (total area 34 550 km2). This event caused tremendous damage and was associated with precipitation amounts and flood peaks with return periods beyond 10 to 100 years. To deal with the underlying intrinsic predictability limitations, a probabilistic forecasting system is tested, which is based on a hydrological-meteorological ensemble prediction system. The meteorological component of the system is the operational limited-area COSMO-LEPS that downscales the ECMWF ensemble prediction system to a horizontal resolution of 10 km, while the hydrological component is based on the semi-distributed hydrological model PREVAH with a spatial resolution of 500 m. We document the setup of the coupled system and assess its performance for the flood event under consideration. We show that the probabilistic meteorological-hydrological ensemble prediction chain is quite effective and provides additional guidance for extreme event forecasting, in comparison to a purely deterministic forecasting system. For the case studied, it is also shown that most of the benefits of the probabilistic approach may be realized with a comparatively small ensemble size of 10 members.

While the benefits of ensemble techniques over deterministic numerical weather predictions (NWP) are now widely recognized, the prospects of ensemble prediction systems (EPS) at high computational resolution are still largely unclear. Difficulties arise due to the poor knowledge of the mechanisms promoting rapid perturbation growth and propagation, as well as the role of nonlinearities. In this study, the dynamics associated with the growth and propagation of initial uncertainties is investigated by means of real-case high-resolution (cloud resolving) NWP integrations. The considered case is taken from the Mesoscale Alpine Programme intensive observing period 3 (MAP IOP3) and involves convection of intermediate intensity. To assess the underlying mechanisms and the degree of linearity upon the predictability of the flow, vastly different initial perturbation methodologies are compared, while all simulations use identical lateral boundary conditions to mimic a perfectly predictable synoptic-scale flow. Comparison of the perturbation methodologies indicates that the ensuing patterns of ensemble spread converge within 11 h, irrespective of the initial perturbations employed. All methodologies pinpoint the same meso-beta-scale regions of the flow as suffering from predictability limitations. This result reveals the important role of nonlinearities. Analysis also shows that hot spots of error growth can quickly (1–2 h after initialization) develop far away from the initial perturbations. This rapid radiation of the initial uncertainties throughout the computational domain is due to both sound and gravity waves, followed by the triggering and/or growth of perturbations over regions of convective instability. The growth of the uncertainties is then limited by saturation effects, which in turn are controlled by the larger-scale atmospheric environment. From a practical point of view, it is suggested that the combined effects of rapid propagation, sizeable amplification, and inherent nonlinearities may pose severe difficulties for the design of EPS or data assimilation techniques related to high-resolution quantitative precipitation forecasting.

The limited atmospheric predictability has been addressed by the development of ensemble prediction systems (EPS) that are now routinely applied for medium-range synoptic-scale numerical weather prediction (NWP). With the increase of computational power, interest is growing in the design of high-resolution (cloud resolving) NWP models and their associated short-range EPS. This development raises a series of fundamental questions, especially concerning the type of error growth and the validity of the tangent-linear approximation. To address these issues, a comparison between perturbed medium-range (10 day) synoptic-scale integrations (taken from the operational ECMWF EPS with a horizontal resolution of about 80 km) and short-range (1 day) high-resolution simulations (based on the Lokal Modell of the Consortium for Small-Scale Modeling with a grid spacing of 2.2 km) is conducted. The differences between the two systems are interpreted in a nondimensional sense and illustrated with the help of the Lorenz att...

Shallow orographic convection embedded in an unstable cap cloud can organize into convective bands. Previous research has highlighted the important role of small-amplitude topographic variations in triggering and organizing banded convection. Here, the underlying dynamical mechanisms are systematically investigated by conducting three-dimensional simulations of moist flows past a two-dimensional mountain ridge using a cloud-resolving numerical model. Most simulations address a sheared environment to account for the observed wind profiles. Results confirm that small-amplitude topographic variations can enhance the development of embedded convection and anchor quasi-stationary convective bands to a fixed location in space. The resulting precipitation patterns exhibit tremendous spatial variability, since regions receiving heavy rainfall can be only kilometers away from regions receiving little or no rain. In addition, the presence of banded convection has important repercussions on the area-mean precipitation amounts. For the experimental setup here, the gravity wave response to small-amplitude topographic variations close to the upstream edge of the cap cloud (which is forced by the larger-scale topography) is found to be the dominant triggering mechanism. Small-scale variations in the underlying topography are found to force the location and spacing of convective bands over a wide range of scales. Further, a self-sufficient mode of unsteady banded convection is investigated that does not dependent on external perturbations and is able to propagate against the mean flow. Finally, the sensitivity of model simulations of banded convection with respect to horizontal computational resolution is investigated. Consistent with predictions from a linear stability analysis, convective bands of increasingly smaller scales are favored as the horizontal resolution is increased. However, small-amplitude topographic roughness is found to trigger banded convection and to control the spacing and location of the resulting bands. Thereby, the robustness of numerical simulations with respect to an increase in horizontal resolution is increased in the presence of topographic variations.

A high-resolution atmospheric ensemble forecasting system is coupled to a hydrologic model to investigate probabilistic runoff forecasts for the alpine tributaries of the Rhine River basin (34 550 km2). Five-day ensemble forecasts consisting of 51 members, generated with the global ensemble prediction system (EPS) of the European Centre for Medium-Range Weather Forecasts (ECMWF), are downscaled with the limited-area model Lokal Modell (LM). The resulting limited-area ensemble prediction system (LEPS) uses a horizontal grid spacing of 10 km and provides one-hourly output for driving the distributed hydrologic model Precipitation–Runoff–Evapotranspiration–Hydrotope (PREVAH) hydrologic response unit (HRU) with a resolution of 500 × 500 m2 and a time step of 1 h. The hydrologic model component is calibrated for the river catchments considered, which are characterized by highly complex topography, for the period 1997–98 using surface observations, and validated for 1999–2002. This study explores the feasibility of atmospheric ensemble predictions for runoff forecasting, in comparison with deterministic atmospheric forcing. Detailed analysis is presented for two case studies: the spring 1999 flood event affecting central Europe due to a combination of snowmelt and heavy precipitation, and the November 2002 flood in the Alpine Rhine catchment. For both cases, the deterministic simulations yield forecast failures, while the coupled atmospheric–hydrologic EPS provides appropriate probabilistic forecast guidance with early indications for extreme floods. It is further shown that probabilistic runoff forecasts using a subsample of EPS members, selected by a cluster analysis, properly represent the forecasts using all 51 EPS members, while forecasts from randomly chosen subsamples reveal a reduced spread compared to the representative members. Additional analyses show that the representation of horizontal advection of precipitation in the atmospheric model may be crucial for flood forecasts in alpine catchments.

The rapid amplification of small-amplitude perturbations by the chaotic nature of the atmospheric dynamics intrinsically limits the skill of deterministic weather forecasts. In this study, limited-area cloud-resolving numerical weather prediction (NWP) experiments are conducted to investigate the role of mesoscale processes in determining predictability. The focus is set on domain-internal error growth by integrating an ensemble of simulations using slightly modified initial conditions but identical lateral boundary conditions. It is found that the predictability of the three investigated cases taken from the Mesoscale Alpine Programme (MAP) differs tremendously. In terms of normalized precipitation spread, values between 0.05 (highly predictable) and 1 (virtually unpredictable) are obtained. Analysis of the derived ensemble spread demonstrates that the diabatic forcing associated with moist dynamics is the prime source of rapid error growth. However, in agreement with an earlier study it is found that the differentiation between convective and stratiform rain is unable to account for the distinctive precipitation spreads of the three cases. In particular, instability indices are demonstrated to be poor predictors of the predictability level. An alternate hypothesis is proposed and tested. It is inspired by the dynamical instability theory and states that significant loss of predictability only occurs over moist convectively unstable regions that are able to sustain propagation of energy against the mean flow. Using a linear analysis of gravity wave propagation, this hypothesis is shown to provide successful estimates of the predictability level for the three cases under consideration.

Marginally unstable air masses impinging upon a mountain ridge may lead to the development of a nominally stratiform orographic cloud with shallow embedded convection. Rainfall amounts and distribution are then strongly influenced by the convective dynamics. In this study, the transition from purely stratiform orographic precipitation to flow regimes with embedded convection is systematically investigated. To this end, idealized cloud-resolving numerical simulations of moist flow past a two-dimensional mountain ridge are performed in a three-dimensional domain. A series of simulations with increasing upstream potential instability shows that the convective dynamics may significantly increase precipitation amounts, intensity, and efficiency, to an extent that cannot be replicated by two-dimensional simulations. Under conditions of uniform upstream flow, the embedded convection is of the cellular type. It is demonstrated that simple stability measures of the upstream profile are poor predictors for the occurrence and depth of embedded convection. A linear stability analysis is performed to understand the linear growth of the developing convective instabilities. Embedded convection results if the growth rates of convective instabilities are compatible with the advective time scale (the time an air parcel spends inside the orographic cloud) and the microphysical time scale (time for rain production and fallout). Individual convective updrafts are anchored to the mean flow. Additional simulations serve to demonstrate that the development of embedded convection and associated precipitation may strongly depend on small-amplitude upstream perturbations. Such perturbations enhance the efficacy of the convective circulations and lead to overall stronger precipitation. The potential implications of this result for the predictability of quantitative precipitation are also discussed.

The North Atlantic Oscillation (NAO) is a major winter climate mode, describing one-third of the inter-annual variability of the upper-level flow in the Atlantic European mid-latitudes. It provides a statistically well-defined pattern to study the predictability of the European winter climate. In this paper, the predictability of the NAO and the associated surface temperature variations are considered using a dynamical prediction approach. Two state-of-the-art coupled atmosphere–ocean ensemble forecast systems are used, namely the seasonal forecast system 2 from the European Centre for Medium Range Weather Forecast (ECMWF) and the multi-model system developed within the joint European project DEMETER (Development of a European Multi-Model Ensemble Prediction System for Seasonal to Inter-annual Prediction). The predictability is defined in probabilistic space using the debiased ranked probability skill score with adapted discretization (RPSSD). The potential predictability of the NAO and its impact are also investigated in a perfect model approach, where each ensemble member is used once as “observation”. This approach assumes that the climate system is fully represented by the model physics.

The dynamics and structure of the lee-side flow over the Po valley during a northerly föhn event, which occurred in the framework of the Mesoscale Alpine Programme Special Observation Period (on 8 November 1999 during Intensive Observation Period 15), has been investigated using aircraft data and high-resolution numerical simulations. Numerical simulations were performed with the mesoscale non-hydrostatic model Meso-NH, using three nested domains (with horizontal resolutions 32, 8 and 2 km), the 2 km resolution domain being centred on the Po valley. The basic data–model comparison, and back-trajectory and tracer release analyses, provided evidence that the jet/wake structure of the flow above the Po valley could be reasonably identified with the mountain pass/peak distributions. Measurements from three aircraft flying below the Alps crestline (at 2700, 1500 and 600 m above sea level) along two 350 km east–west legs, designed to be approximately perpendicular to the northerly synoptic flow, were used to compute the potential vorticity (PV) experimentally assuming the lee-side flow to be two-dimensional. (The simplified form of the PV under these assumptions is hereafter referred to as SPV). Due to increasing lee-side flow curvature with decreasing altitude (caused by flow splitting at the scale of the Alps), the experimentally derived SPV was compared to its simulated counterpart. In situ measurements showed that coherent secondary PV banners (PVB2s) do exist downstream of the complex Alpine terrain, as observations show oscillations between positive and negative values of SPV as expected from the simulations. The details of the structure of the SPV field simulated with Meso-NH were found to be different from the observations (i.e. the location of observed maxima and minima of SPV did not match their simulated counterparts at particular points). This is because the correspondence between observed and modelled velocity and potential temperature fields was not good enough to expect good correspondence between differentiated quantities such as vorticity and potential temperature gradient (since less-reliable shorter-scale features are thereby accentuated). Parametrized processes such as surface drag and internal diffusion, and ‘numerical’ processes, such as model filters, to which PV production mechanisms are sensitive and whose role is difficult to assess, also contribute to the poor agreement between observed and modelled SPV fluctuations. Finally, simulations suggest that lowlevel gravity-wave breaking was the main mechanism responsible for the formation of the elongated PVB2 modelled/observed over the Po valley.

Predictability limitations in quantitative precipitation forecasting arising from small-scale uncertainties in the initial conditions are investigated for Alpine river catchments, with particular consideration of their implications on hydrological runoff forecasting. To this end, convection-resolving ensembles of limited-area simulations are performed using a nonhydrostatic numerical weather prediction (NWP) model, and results are analysed in terms of catchment-averaged precipitation. The applied ensemble strategy uses slightly modified initial conditions representing observational uncertainties, but identical lateral boundary conditions representing a perfectly predictable synoptic-scale forcing. A total of four case studies is carried out for different synoptic conditions leading to heavy precipitation. Ensemble integrations of 12 members are analysed for 24-h forecasting periods, with particular attention paid to precipitation in the Po basin and in its sub-catchments in the Lago Maggiore area. The simulations exhibit a large variability in the predictability of precipitation amounts, both from case to case and from catchment to catchment. It is demonstrated for an episode of thermal convection, that the predictability may be very low even in large-scale catchments of ∼50,000 km2. In more synoptically dominated cases, predictability limitations appear to be restricted to catchments smaller than ∼10,000 km2, while in one case predictability is found to be high in catchments as small as 200 km2. Overall, the simulations show that precipitation forecasts for alpine river catchments may on occasions be critically affected by predictability limitations, even though the NWP model and the synoptic-scale forcing are assumed to be prefect. It is demonstrated that a substantial fraction of the predictability limitations is due to the scattered and unpredictable occurrence of convective cells, but the presence of convective precipitation alone does not necessarily limit predictability. It is also shown that the predictability is systematically higher in mountainous catchments.

An ensemble methodology is developed and tested to objectively isolate and quantify meso-β-scale predictability limitations in numerical weather prediction (NWP). The methodology involves conducting an ensemble of limited-area simulations with slightly modified initial conditions (representing small-scale observational uncertainties) and identical lateral-boundary conditions (representing perfect synoptic-scale predictability). The methodology is applied using a nonhydrostatic NWP model with a convection-resolving mesh size of 3 km, using a setup covering the entire European Alps. The initial perturbations of the ensemble members have a small-scale structure with predominant scales between 10 and 100 km. Ensembles for four case studies representing different weather conditions are analyzed for 24-h forecasting periods, with particular attention paid to quantitative precipitation forecasting. The simulations show that the predictability of precipitation amounts differs strongly depending upon the ...

Instrumental observations and reconstructions of global and hemispheric temperature evolution reveal a pronounced warming during the past approximately 150 years. One expression of this warming is the observed increase in the occurrence of heatwaves. Conceptually this increase is understood as a shift of the statistical distribution towards warmer temperatures, while changes in the width of the distribution are often considered small. Here we show that this framework fails to explain the record-breaking central European summer temperatures in 2003, although it is consistent with observations from previous years. We find that an event like that of summer 2003 is statistically extremely unlikely, even when the observed warming is taken into account. We propose that a regime with an increased variability of temperatures (in addition to increases in mean temperature) may be able to account for summer 2003. To test this proposal, we simulate possible future European climate with a regional climate model in a scenario with increased atmospheric greenhouse-gas concentrations, and find that temperature variability increases by up to 100%, with maximum changes in central and eastern Europe.

Recent developments in numerical modeling and computer technology will soon allow for limited-area production-type numerical weather prediction at a resolution of 1–2 km. This advance opens exciting prospects for the prediction of airflow and precipitation phenomena in and around mountainous regions, by improving the representation of the underlying topography, and by explicitly simulating (rather than parameterizing) moist convection. During the Special Observation Period (SOP; 7 Sept–15 Nov 1999) of the Mesoscale Alpine Programme (MAP) the Canadian Mesoscale Compressible Community Model (MC2) has been run in real time at a horizontal resolution of 3 km on a computational domain of 350 × 300 × 50 grid points, covering the whole of the Alpine region. An overview of the model configuration and performance will be presented along with simulation and validation results from selected MAP cases. Some critical aspects that require particular attention in future research will also be addressed.

The interaction of a cold front with the Alps is studied by means of real-case numerical simulations for a case occurring at the end of the Alpine Experiment (ALPEX) on 28 April–2 May, 1982. Simulations are performed with the numerical weather prediction model chain Europa-Modell (EM) and its one-way nested high-resolution model (HM) of the German and Swiss Weather Services. The outer EM simulation (56 km horizontal resolution) uses initial and lateral boundary fields taken from the ALPEX-IIIb reanalysis data set. This reanalysis data set is based on the operational EM analysis scheme, but takes into consideration a wide range of field phase data taken during the ALPEX field campaign. A comparison of simulations driven by the ALPEX and ECMWF reanalysis (ERA) data is performed. The simulation driven by the former captures the intensity and vertical depth of the developing lee cyclone substantially better than the corresponding run driven by the ERA. The transient development of the impingement of a cold front on the Alps induces a wide range of mesoscale phenomenon such as flow splitting, mistral, north foehn, cyclogenesis, anticyclonic vortex and bora. These flow evolutions are analyzed using HM simulations with a horizontal resolution of 14 km and visualized performing comprehensive trajectory calculations.

The feasibility of a statistical reconstruction of mesoscale precipitation fields over complex topography from a sparse rain gauge network is examined. Reconstructions of gridded monthly precipitation for the European Alps (resolution 25 km, 1202 grid points) are derived from rain gauge samples (70–200-km interstation distance, 25–150 stations). The statistical model is calibrated over a 15-yr period, and the reconstructed fields are evaluated for the remaining 5 yr of the period 1971–90. The experiments are used to define the statistical setup, to assess the data requirements, and to describe the error statistics of a centennial reconstruction to be used in a forthcoming study. Reduced-space optimal interpolation is employed as the reconstruction method, involving data reduction by empirical orthogonal functions (EOFs) and least squares optimal estimation of EOF coefficients. Also, a procedure to define covariance-guided station samples with a “representative” spatial distribution for the recons...

Observations of fohn in the Alps and other mountainous regions suggest that the underlying dynamics is often affected by gap-like features in elongated ridge-like topography. To assess the dynamics of these flows, idealized numerical experiments are conducted with a hydrostatic numerical model, using f-plane geometry and a free-slip lower boundary condition. The topography is taken to be a two-dimensional ridge oriented in the west/east direction with a valley transect of depth ΔH across it. The upstream flow is westerly, with a constant wind speed U and constant Brunt-Vaisala frequency N. The control parameters defined by this setting are a dimensionless gap depth NΔH/U, the ratio between ridge height and gap depth H/ΔH, a Rossby number describing the south-north width of the ridge, and additional parameters associated with the shape of the gap. With intermediate Rossby numbers (Ro≈1) the setting resembles that of shallow Alpine south-fohn cases, which are characterized by a cross-Alpine flow essentially confined to valley transects. For small dimensionless gap depths and large Rossby numbers, the flow follows the predictions of linear theory and takes on an approximately symmetric pattern with respect to the ridge line. For NΔH/U ≳ 1, flow separation and splitting takes place upstream and downstream of the gap, respectively. The flow within the gap decouples from the flow aloft and is driven by the geostrophic south-north pressure gradient to yield a fohn-like flow. It is demonstrated that the limit f → 0 is singular (i.e. the flow solution does not converge towards the symmetric f = 0 solution), and that there exist multiple stationary solutions for f = 0 (two with northerly and southerly flow across the gap, respectively, and one with north/south symmetry). The existence of these multiple steady states is related to a wake instability, yet vortex shedding is suppressed by the presence of the ridge downstream of the gap. Additional simulations are presented which demonstrate that a transient external forcing can induce transitions between the multiple flow solutions. The relationship of the idealized setting to Alpine shallow fohn is discussed, and additional experiments are conducted to assess the effects of surface friction and of an inversion present to the south of the ridge.

Heavy precipitation events to the south of the Alps are usually associated with a southerly pre-frontal low-level jet advecting moisture toward the southern slopes of the Alps. Here we use idealised numerical simulations to assess the nature of the associated flow regimes and the mechanisms leading to vertical lifting and precipitation. The idealisations comprise: a simplified arc-shaped barrier-like orographic obstacle of Alpine scale; neglection of the tropopause; a stationary two-dimensional upstream flow configuration that includes a frontal structure and a low-level jet; hydrostatic dynamics with free-slip lower boundary conditions; and a simplified set of parameterizations to address dry, moist absolutely stable, and moist conditionally unstable upstream flow configurations.

The validation of regional climate models is usually based on the intercomparison of the model's mean climate with the observed climatology. Albeit a prerequisite for the use of the model in a predictive mode, a successful validation of this type does not strictly test the model's ability to simulate anomalous conditions as might be associated with anthropogenic climate change. Here, we explore an alternate strategy, whereby the model's ability to reproduce the observed interannual variability is tested. The model utilized is an operational numerical weather prediction model of the German Weather Service, and it is tested for its use over East Asia and Japan in a series of 5 month-long January simulations. The model is used in a domain of 5100 x 5100 km 2 , has a horizontal resolution of 56 km, and 20 levels in the vertical. It is driven at its boundaries by the European Center for Medium-Range Weather Forecast (ECMWF) analysis. In validating the integrations, particular emphasis is put on the precipitation fields. For validation we use three different observational data sets: a terrestrial analysis from rain gauges, including the Automated Meteorological Data Acquisition System (AMeDAS) data of the Japan Meteorological Agency, the gridded data set of the Global Precipitation Climatology Project (GPCP), which over sea is largely based upon satellite information, and the ECMWF Re-Analysis (ERA) data set, which is produced by a model in an assimilation mode. It is demonstrated that the synoptic-scale evolution of individual low-pressure systems within the modeling domain is deterministically controlled by the lateral boundary conditions. Precipitation spatially averaged over selected subdomains - compares remarkably well with the observations, both in terms of the monthly amounts and of the temporal evolution throughout the integration period. Using the strategy of a previous study, we analyze the year-to-year variations of the model results, both for the dynamical and precipitation fields. It is found that the modeling error is substantially smaller than the typical year-to-year fluctuations of the interannual variability. Implications of this result, concerning the model's use as a tool for down-scaling climate change, are also discussed.

High-resolution numerical model simulations over the Alpine region are presented that reveal the presence of low-level elongated bands of potential vorticity (PV) downstream of high topography. These PV streamers (or PV banners) occur when the synoptic-scale wind turns into a direction across the Alps. Individual pairs of banners with anomalously positive and negative values of PV can be attributed to flow splitting, either on the scale of the whole of the Alps (primary banners), or on that of individual massifs and peaks of the model topography (secondary banners). The PV bands have amplitudes of up to −2.5 and +5 pvu, a width of 50–150 km, can attain a length of up to 1500 km, and extend in the vertical from the surface up to the 500-hPa level on occasions. The PV banners are associated with zones of enhanced horizontal wind shear. The analysis of daily output from the operational NWP model run of the Swiss Meteorological Institute also demonstrates that such PV streamers are a frequent feature...

The flow of a nonrotating atmosphere with uniform stratification and wind speed past an isolated three-dimensional topographic obstacle is investigated with a nonhydrostatic numerical model having a free-slip lower boundary. When the mountain is sufficiently high, the transient development of a quasi-steady flow occurs in two phases. During the first phase, which occurs over a dimensionless time of O(1), the flow is essentially inviscid and adiabatic, and potential vorticity (PV) is conserved. The transient evolution of the flow during the second phase, which occurs over a dimensionless time of O(10) to O(100), is controlled by dissipation and is accompanied by the generation of PV anomalies. Two cases are examined in which the flow is forced to remain left–right symmetric with respect to the axis of the incident flow. In the first, the dimensionless mountain height NH/U is 1.5, and gravity waves break over the mountain. In the second, NH/U = 3, and a quasi-steady recirculating wake containing a ...

An assessment is made of a regional climate model's skill in simulating the mean climatology and the interannual variability experienced in a specific region. To this end two ensembles comprising three realizations of month-long January and July simulations are undertaken with a limited are a operational NWP model. The modelling suite is driven at its lateral boundaries by analysed meteorological fields and the computational domain covers Europe and the North-western Atlantic with a horizontal resolution of 56 km.

[1] This paper assesses the impacts of horizontal resolution, snow physics, and atmospheric forcing in snow cover simulations by the European Centre for Medium-Range Weather Forecasts (ECWMF) land surface model Hydrology Tiled ECMWF Scheme for Surface Exchanges (HTESSEL). Off-line simulations are carried out forced by the ECMWF deterministic short-term weather forecasts (WFC) with a resolution of 25 km from March 2006 to June 2010. The horizontal-resolution impact on snow cover is addressed by performing simulations at 25, 80, and 200 km forced by WFC. The impact of atmospheric forcing on snow cover is assessed by forcing the model additionally with the ECMWF Era-Interim (ERAI) reanalysis, at 80 km resolution. Snow physics effects are analyzed by performing an extra simulation forced by WFC using a different snow scheme. The simulations are validated against four independent observational data sets: (1) snow water equivalent (SWE) over Switzerland; (2) snow cover duration in Europe (SNOWCLIM); (3) interactive multisensor snow and ice-mapping system (IMS) snow cover; and (4) Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo. ERAI forced simulations show a systematic underestimation of SWE and snow cover fraction, which is due to an underprediction of snowfall by ERAI. The snow physics experiment highlights the sensitivity of the model to the partitioning between rainfall and snowfall when rainfall interception in the snowpack is neglected. The horizontal resolution has a crucial role in characterizing the snow cover over complex terrain (e.g., orographic areas, coastal and lakes regions). However, improved snow physical parameterizations and meteorological forcing are shown to be the key elements to achieve more accurate simulations of the snowpack and of the snow-atmosphere interactions, also over flat terrain.

[1] This paper describes the adaptation of wind fields to steep and complex terrain using fine-scale numerical modeling. The work is motivated by the need of high-resolution flow fields to predict snow transport and snow cover development for avalanche warning purposes. Applying the nonhydrostatic and compressible atmospheric prediction model Advanced Regional Prediction System (ARPS) to steep alpine topography, the boundary layer flow was simulated and evaluated against measurements. The adaptation of the wind field to steep terrain for specific initial and boundary conditions was simulated. The topography used in our study has a length scale of 500 m, a typical height of 150 m, and maximum slopes of 45°. Numerical experiments with idealized triangular ridges were conducted to find an adequate model configuration. This analysis indicates that a high-resolution grid with horizontal spacing of at least 25 m and vertical spacing of 3 m near the surface is necessary to reproduce small-scale flow features such as speed-up, separation, and recirculation. The onset of flow separation is highly sensitive to initial and boundary conditions, slope angle, and surface roughness. The results of the comparison between the model simulations and measurements on our experimental site show that typical wind field characteristics are well reproduced. The simulated wind fields have been used to drive a numerical three-dimensional snow drift model, which is presented in a companion paper by Lehning et al. (2008).

An instability of a cold front possessing a low-level warm-band precursor is examined within an f-plane, quasi- and semigeostrophic framework. The basic frontal state is taken to be two-dimensional and of uniform potential vorticity. Theoretical considerations pinpoint the source and nature of the instability to be a vortex interaction effect acting across the thermal maximum of the warm band. They also reveal that the most unstable mode associated with this flow configuration has a mixed barotropic-baroclinic character and possesses some features (e.g., a wavelength ∼1000 km and a doubling time ∼1½ days) that are akin to surface frontal waves. In addition nonlinear numerical model simulations demonstrate that the frontal wave growth equilibrates rapidly but not before the establishment of a rich mesoscale flow structure. A brief assessment is presented of the relationship of this diagnosed instability to realized atmospheric flow patterns and to other mechanisms that have been postulated for the...

With the development of a version of the Canadian non-hydrostatic MC2 model optimized for massively parallel processors, it has become possible to solve very large weather forecast problems in a time sufficiently short to envision a realtime daily calculation over a domain covering the entire Alps. MAP is a large multinational research program that will gather new knowledge about the heavy precipitation over steep topography; its field phase is to take place during Fall of 1999. The tentative grid dimensions are 490 − 400 − 35 at a horizontal resolution of 2 km, with possibly a need to increase the number of vertical layers. This is a very large problem to be solved with realtime constraints. The model results will be accessible to the forecasters at the MAP Operations Centre in Innsbruck, to assist in the scientific briefings to dispatch the flight plans of the research aircraft. The forecasts are planned to be performed on the NEC-SX/4 (10 PE) at the CSCS (Centro Svizzero di Calcolo Scientifico) in Manno (Canton Ticino, Switzerland), which is affiliated with the ETH. The current state of this joint effort is presented.