999 resultados para instabilità, Colquhoun, albero decisionale, temporali, COSMO model
Resumo:
La previsione dei temporali rappresenta una delle operazioni più impegnative e complesse per chi svolge il mestiere di meteorologo, soprattutto se effettuata con molte ore di anticipo rispetto all'evento; ciò è riconducibile alla molteplicità di parametri da cui questi fenomeni dipendono ed all'incertezza che si riscontra nella simulazione degli indici di instabilità. In questo elaborato viene presentata ed approfondita una tecnica di elaborazione dei dati provenienti da radiosondaggi previsti, con lo scopo di migliorare la previsione dei temporali relativa al giorno successivo. Nel 1987 Colquhoun elaborò un albero decisionale per la previsione di temporali in Australia, basato sul superamento di soglie degli indici di instabilità. Qui di seguito, si propone di testare la validità dello stesso schema decisionale alla previsione di temporali in Pianura Padana ed in particolare in Emilia Romagna, procedendo ad un confronto tra gli eventi previsti ed i fenomeni osservati; la previsione si basa sull'output dell'albero decisionale utilizzando gli indici di instabilità previsti dai LAM COSMO-I7 e COSMO-I2 nel periodo +24/+48 ore, mentre l'osservazione dei temporali viene ricavata tramite consultazione quotidiana di METAR,SYNOP,SYREP, e mappe di fulminazioni relative al quadriennio 2010-2013. L'indice assunto per valutare l'affidabilità delle previsioni fornite è il Threat Score che presenta due limiti fondamentali: la dipendenza dal numero di eventi e l'incapacità di differenziare i falsi allarmi dai mancati allarmi. Ciò nonostante, questo indice rappresenta il miglior modo per ricavare una informazione complessiva e definire se la previsione fornita corrisponde ad una buona previsione. Lo stesso test viene effettuato sull'albero decisionale in uso presso la sala operativa di ARPA-SIM e dal confronto con l'albero di Colquhoun si deducono i limiti legati alla modellistica numerica che fornisce i dati in input. Infine il test sui parametri termodinamici previsti dai modelli COSMO-I2 e COSMO-I7 dimostra gli errori commessi sulla previsione a +24 e +36 ore dalle simulazioni. Questo lavoro si pone all'interno di un progetto più ampio di verifica della modellistica numerica sviluppata dal consorzio COSMO, al quale l'Italia aderisce attraverso la collaborazione di ARPA Emilia Romagna, ARPA Piemonte ed Aeronautica Militare. In particolare sono sottoposte a test le performances dei due modelli LAM sviluppati completamente in Italia ed utilizzati anche dal Dipartimento della protezione civile nazionale.
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Arctic flaw polynyas are considered to be highly productive areas for the formation of sea-ice throughout the winter season. Most estimates of sea-ice production are based on the surface energy balance equation and use global reanalyses as atmospheric forcing, which are too coarse to take into account the impact of polynyas on the atmosphere. Additional errors in the estimates of polynya ice production may result from the methods of calculating atmospheric energy fluxes and the assumption of a thin-ice distribution within polynyas. The present study uses simulations using the mesoscale weather prediction model of the Consortium for Small-scale Modelling (COSMO), where polynya area is prescribed from satellite data. The polynya area is either assumed to be ice-free or to be covered with thin ice of 10 cm. Simulations have been performed for two winter periods (2007/08 and 2008/09). When using a realistic thin-ice thickness of 10 cm, sea-ice production in Laptev polynyas amount to 30 km3 and 73 km3 for the winters 2007/08 and 2008/09, respectively. The higher turbulent energy fluxes of open-water polynyas result in a 50-70% increase in sea-ice production (49 km3 in 2007/08 and 123 km3 in 2008/09). Our results suggest that previous studies have overestimated ice production in the Laptev Sea.
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The present work studies a km-scale data assimilation scheme based on a LETKF developed for the COSMO model. The aim is to evaluate the impact of the assimilation of two different types of data: temperature, humidity, pressure and wind data from conventional networks (SYNOP, TEMP, AIREP reports) and 3d reflectivity from radar volume. A 3-hourly continuous assimilation cycle has been implemented over an Italian domain, based on a 20 member ensemble, with boundary conditions provided from ECMWF ENS. Three different experiments have been run for evaluating the performance of the assimilation on one week in October 2014 during which Genova flood and Parma flood took place: a control run of the data assimilation cycle with assimilation of data from conventional networks only, a second run in which the SPPT scheme is activated into the COSMO model, a third run in which also reflectivity volumes from meteorological radar are assimilated. Objective evaluation of the experiments has been carried out both on case studies and on the entire week: check of the analysis increments, computing the Desroziers statistics for SYNOP, TEMP, AIREP and RADAR, over the Italian domain, verification of the analyses against data not assimilated (temperature at the lowest model level objectively verified against SYNOP data), and objective verification of the deterministic forecasts initialised with the KENDA analyses for each of the three experiments.
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The importance of renewable energies for the European electricity market is growing rapidly. This presents transmission grids and the power market in general with new challenges which stem from the higher spatiotemporal variability of power generation. This uncertainty is due to the fact that renewable power production results from weather phenomena, thus making it difficult to plan and control. We present a sensitivity study of a total solar eclipse in central Europe in March. The weather in Germany and Europe was modeled using the German Weather Service's local area models COSMO-DE and COSMO-EU, respectively (http://www.cosmo-model.org/). The simulations were performed with and without considering a solar eclipse for the following 3 situations: 1. An idealized, clear-sky situation for the entire model area (Europe, COSMO-EU) 2. A real weather situation with mostly cloudy skies (Germany, COSMO-DE) 3. A real weather situation with mostly clear skies (Germany, COSMO-DE) The data should help to evaluate the effects of a total solar eclipse on the weather in the planetary boundary layer. The results show that a total solar eclipse has significant effects particularly on the main variables for renewable energy production, such as solar irradiation and temperature near the ground.
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The existence of sting jets as a potential source of damaging surface winds during the passage of extratropical cyclones has recently been recognized However, there are still very few published studies on the subject Furthermore, although ills known that other models are capable of reproducing sting jets, in the published literature only one numerical model [the Met Office Unified Model (MetUM)] has been used to numerically analyze these phenomena This article alms to improve our understanding of the processes that contribute to the development of sting jets and show that model differences affect the evolution of modeled sting jets A sting jet event during the passage of a cyclone over the United Kingdom on 26 February 2002 has been simulated using two mesoscale models namely the MetUM and the Consortium for Small Scale Modeling (COSMO) model to compare their performance Given the known critical importance of vertical resolution in the simulation of sting jets the vertical resolution of both models has been enhanced with respect to their operational versions Both simulations have been verified against surface measurements of maximum gusts, satellite imagery and Met Office operational synoptic analyses, as well as operational analyses from the ECMWF It is shown that both models are capable of reproducing sting jets with similar, though not identical. features Through the comparison of the results from these two models, the relevance of physical mechanisms, such as evaporative cooling and the release of conditional symmetric instability, in the generation and evolution of sting jets is also discussed
Resumo:
The warm conveyor belt (WCB) of an extratropical cyclone generally splits into two branches. One branch (WCB1) turns anticyclonically into the downstream upper-level tropospheric ridge, while the second branch (WCB2) wraps cyclonically around the cyclone centre. Here, the WCB split in a typical North Atlantic cold-season cyclone is analysed using two numerical models: the Met Office Unified Model and the COSMO model. The WCB flow is defined using off-line trajectory analysis. The two models represent the WCB split consistently. The split occurs early in the evolution of the WCB with WCB1 experiencing maximum ascent at lower latitudes and with higher moisture content than WCB2. WCB1 ascends abruptly along the cold front where the resolved ascent rates are greatest and there is also line convection. In contrast, WCB2 remains at lower levels for longer before undergoing saturated large-scale ascent over the system's warm front. The greater moisture in WCB1 inflow results in greater net potential temperature change from latent heat release, which determines the final isentropic level of each branch. WCB1 also exhibits lower outflow potential vorticity values than WCB2. Complementary diagnostics in the two models are utilised to study the influence of individual diabatic processes on the WCB. Total diabatic heating rates along the WCB branches are comparable in the two models with microphysical processes in the large-scale cloud schemes being the major contributor to this heating. However, the different convective parameterisation schemes used by the models cause significantly different contributions to the total heating. These results have implications for studies on the influence of the WCB outflow in Rossby wave evolution and breaking. Key aspects are the net potential temperature change and the isentropic level of the outflow which together will influence the relative mass going into each WCB branch and the associated negative PV anomalies at the tropopause-level flow.
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Proxy data are essential for the investigation of climate variability on time scales larger than the historical meteorological observation period. The potential value of a proxy depends on our ability to understand and quantify the physical processes that relate the corresponding climate parameter and the signal in the proxy archive. These processes can be explored under present-day conditions. In this thesis, both statistical and physical models are applied for their analysis, focusing on two specific types of proxies, lake sediment data and stable water isotopes.rnIn the first part of this work, the basis is established for statistically calibrating new proxies from lake sediments in western Germany. A comprehensive meteorological and hydrological data set is compiled and statistically analyzed. In this way, meteorological times series are identified that can be applied for the calibration of various climate proxies. A particular focus is laid on the investigation of extreme weather events, which have rarely been the objective of paleoclimate reconstructions so far. Subsequently, a concrete example of a proxy calibration is presented. Maxima in the quartz grain concentration from a lake sediment core are compared to recent windstorms. The latter are identified from the meteorological data with the help of a newly developed windstorm index, combining local measurements and reanalysis data. The statistical significance of the correlation between extreme windstorms and signals in the sediment is verified with the help of a Monte Carlo method. This correlation is fundamental for employing lake sediment data as a new proxy to reconstruct windstorm records of the geological past.rnThe second part of this thesis deals with the analysis and simulation of stable water isotopes in atmospheric vapor on daily time scales. In this way, a better understanding of the physical processes determining these isotope ratios can be obtained, which is an important prerequisite for the interpretation of isotope data from ice cores and the reconstruction of past temperature. In particular, the focus here is on the deuterium excess and its relation to the environmental conditions during evaporation of water from the ocean. As a basis for the diagnostic analysis and for evaluating the simulations, isotope measurements from Rehovot (Israel) are used, provided by the Weizmann Institute of Science. First, a Lagrangian moisture source diagnostic is employed in order to establish quantitative linkages between the measurements and the evaporation conditions of the vapor (and thus to calibrate the isotope signal). A strong negative correlation between relative humidity in the source regions and measured deuterium excess is found. On the contrary, sea surface temperature in the evaporation regions does not correlate well with deuterium excess. Although requiring confirmation by isotope data from different regions and longer time scales, this weak correlation might be of major importance for the reconstruction of moisture source temperatures from ice core data. Second, the Lagrangian source diagnostic is combined with a Craig-Gordon fractionation parameterization for the identified evaporation events in order to simulate the isotope ratios at Rehovot. In this way, the Craig-Gordon model can be directly evaluated with atmospheric isotope data, and better constraints for uncertain model parameters can be obtained. A comparison of the simulated deuterium excess with the measurements reveals that a much better agreement can be achieved using a wind speed independent formulation of the non-equilibrium fractionation factor instead of the classical parameterization introduced by Merlivat and Jouzel, which is widely applied in isotope GCMs. Finally, the first steps of the implementation of water isotope physics in the limited-area COSMO model are described, and an approach is outlined that allows to compare simulated isotope ratios to measurements in an event-based manner by using a water tagging technique. The good agreement between model results from several case studies and measurements at Rehovot demonstrates the applicability of the approach. Because the model can be run with high, potentially cloud-resolving spatial resolution, and because it contains sophisticated parameterizations of many atmospheric processes, a complete implementation of isotope physics will allow detailed, process-oriented studies of the complex variability of stable isotopes in atmospheric waters in future research.rn
Potential vorticity and moisture in extratropical cyclones : climatology and sensitivity experiments
Resumo:
The development of extratropical cyclones can be seen as an interplay of three positive potential vorticity (PV) anomalies: an upper-level stratospheric intrusion, low-tropospheric diabatically produced PV, and a warm anomaly at the surface acting as a surrogate PV anomaly. In the mature stage they become vertically aligned and form a “PV tower” associated with strong cyclonic circulation. This paradigm of extratropical cyclone development provides the basis of this thesis, which will use a climatological dataset and numerical model experiments to investigate the amplitude of the three anomalies and the processes leading in particular to the formation of the diabatically produced low-tropospheric PV anomaly.rnrnThe first part of this study, based on the interim ECMWF Re-Analysis (ERA-Interim) dataset, quantifies the amplitude of the three PV anomalies in mature extratropical cyclones in different regions in the Northern Hemisphere on a climatological basis. A tracking algorithm is applied to sea level pressure (SLP) fields to identify cyclone tracks. Surface potential temperature anomalies ∆θ and vertical profiles of PV anomalies ∆PV are calculated at the time of the cyclones’ minimum SLP and during the intensification phase 24 hours before in a vertical cylinder with a radius of 200 km around the surface cyclone center. To compare the characteristics of the cyclones, they are grouped according to their location (8 regions) and intensity, where the central SLP is used as a measure of intensity. Composites of ∆PV profiles and ∆θ are calculated for each region and intensity class at the time of minimum SLP and during the cyclone intensification phase.rnrnDuring the cyclones’ development stage the amplitudes of all three anomalies increase on average. In the mature stage all three anomalies are typically larger for intense than for weak winter cyclones [e.g., 0.6 versus 0.2 potential vorticity units (PVU) at lower levels, and 1.5 versus 0.5 PVU at upper levels].rnThe regional variability of the cyclones’ vertical structure and the profile evolution is prominent (cyclones in some regions are more sensitive to the amplitude of a particular anomaly than in other regions). Values of ∆θ and low-level ∆PV are on average larger in the western parts of the oceans than in the eastern parts. In addition, a large seasonal variability can be identified, with fewer and weaker cyclones especially in the summer, associated with higher low-tropospheric PV values, but also with a higher tropopause and much weaker surface potential temperature anomalies (compared to winter cyclones).rnrnIn the second part, we were interested in the diabatic low-level part of PV towers. Evaporative sources were identified of moisture that was involved in PV production through condensation. Lagrangian backward trajectories were calculated from the region with high PV values at low-levels in the cyclones. PV production regions were identified along these trajectories and from these regions a new set of backward trajectories was calculated and moisture uptakes were traced along them. The main contribution from surface evaporation to the specific humidity of the trajectories is collected 12-72 hours prior to therntime of PV production. The uptake region for weaker cyclones with less PV in the centre is typically more localized with reduced uptake values compared to intense cyclones. However, in a qualitative sense uptakes and other variables along single trajectories do not vary much between cyclones of different intensity in different regions.rnrnA sensitivity study with the COSMO model comprises the last part of this work. The study aims at investigating the influence of synthetic moisture modification in the cyclone environment in different stages of its development. Moisture was eliminated in three regions, which were identified as important moisture source regions for PV production. Moisture suppression affected the cyclone the most in its early phase. It led to cyclolysis shortly after its genesis. Nevertheles, a new cyclone formed on the other side of a dry box and developed relatively quickly. Also in other experiments, moisture elimination led to strong intensity reduction of the surface cyclone, limited upper-level development, and delayed or missing interaction between the two.rnrnIn summary, this thesis provides novel insight into the structure of different intensity categories of extratropical cyclones from a PV perspective, which corroborates the findings from a series of previous case studies. It reveals that all three PV anomalies are typically enhanced for more intense cyclones, with important regional differences concerning the relative amplitude of the three anomalies. The moisture source analysis is the first of this kind to study the evaporation-condensation cycle related to the intensification of extratropical cyclones. Interestingly, most of the evaporation occurs during the 3 days prior to the time of maximum cyclone intensity and typically extends over fairly large areas along the track of the cyclone. The numerical model case study complements this analysis by analyzing the impact of regionally confined moisture sources for the evolution of the cyclone.
Resumo:
Il telerilevamento satellitare costituisce una delle tecniche di osservazione maggiormente efficace nel monitoraggio e nello studio dell'estensione del manto nevoso. Il manto ricopre un ruolo di estrema importanza quale risorsa idrica per gli ecosistemi e per le applicazioni agricole e industriali. Inoltre, è un indicatore climatologico in un contesto di cambiamenti climatici regionali e globali. In questo senso, la copertura nevosa è da considerarsi come una importante risorsa economica e sociale. Lo scopo della presente tesi è di produrre mappe di copertura nevosa giornaliere per la stima dell'estensione del manto nevoso della regione Emilia-Romagna e di analizzare la sua variabilità spazio-temporale nel periodo 2000-2020. Le mappe sono state sviluppate sulla base dei prodotti di neve, M*D10A1, del sensore MODIS, che consistono in mappe di classificazione della copertura in funzione dell'indice NDSI. Inizialmente, è stato costruito un albero decisionale con criteri a soglia multipla in grado di rielaborare la classificazione della superficie del sensore e produrre mappe di copertura nevosa sulla base di tre classi: neve, no-neve e nube. L'accuratezza delle mappe è stata validata tramite test statistici effettuati confrontandole con i dati di altezza del manto nevoso in situ di 24 stazioni meteorologiche, per il periodo di compresenza dei dati 2000-2012. I risultati della procedura di validazione hanno mostrato come, in generale, vi sia buon accordo tra il dato satellitare e la rispettiva osservazione al suolo, soprattutto nei pressi di stazioni lontane da vegetazione sempreverde e/o di ambiente urbano. Infine, è stata valutata la variabilità climatologica dell'estensione del manto nevoso tramite l'elaborazione degli indici di neve SCF, SCD e diversi indici SCA. L'attenzione è stata particolarmente focalizzata sugli indici di massima estensione invernale del manto, del valore mediano e del numero di giorni con estensione superiore al 39.5% della regione.
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Previous versions of the Consortium for Small-scale Modelling (COSMO) numerical weather prediction model have used a constant sea-ice surface temperature, but observations show a high degree of variability on sub-daily timescales. To account for this, we have implemented a thermodynamic sea-ice module in COSMO and performed simulations at a resolution of 15 km and 5 km for the Laptev Sea area in April 2008. Temporal and spatial variability of surface and 2-m air temperature are verified by four automatic weather stations deployed along the edge of the western New Siberian polynya during the Transdrift XIII-2 expedition and by surface temperature charts derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. A remarkable agreement between the new model results and these observations demonstrates that the implemented sea-ice module can be applied for short-range simulations. Prescribing the polynya areas daily, our COSMO simulations provide a high-resolution and high-quality atmospheric data set for the Laptev Sea for the period 14-30 April 2008. Based on this data set, we derive a mean total sea-ice production rate of 0.53 km3/day for all Laptev Sea polynyas under the assumption that the polynyas are ice-free and a rate of 0.30 km3/day if a 10-cm-thin ice layer is assumed. Our results indicate that ice production in Laptev Sea polynyas has been overestimated in previous studies.
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In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.
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The topography of many floodplains in the developed world has now been surveyed with high resolution sensors such as airborne LiDAR (Light Detection and Ranging), giving accurate Digital Elevation Models (DEMs) that facilitate accurate flood inundation modelling. This is not always the case for remote rivers in developing countries. However, the accuracy of DEMs produced for modelling studies on such rivers should be enhanced in the near future by the high resolution TanDEM-X WorldDEM. In a parallel development, increasing use is now being made of flood extents derived from high resolution Synthetic Aperture Radar (SAR) images for calibrating, validating and assimilating observations into flood inundation models in order to improve these. This paper discusses an additional use of SAR flood extents, namely to improve the accuracy of the TanDEM-X DEM in the floodplain covered by the flood extents, thereby permanently improving this DEM for future flood modelling and other studies. The method is based on the fact that for larger rivers the water elevation generally changes only slowly along a reach, so that the boundary of the flood extent (the waterline) can be regarded locally as a quasi-contour. As a result, heights of adjacent pixels along a small section of waterline can be regarded as samples with a common population mean. The height of the central pixel in the section can be replaced with the average of these heights, leading to a more accurate estimate. While this will result in a reduction in the height errors along a waterline, the waterline is a linear feature in a two-dimensional space. However, improvements to the DEM heights between adjacent pairs of waterlines can also be made, because DEM heights enclosed by the higher waterline of a pair must be at least no higher than the corrected heights along the higher waterline, whereas DEM heights not enclosed by the lower waterline must in general be no lower than the corrected heights along the lower waterline. In addition, DEM heights between the higher and lower waterlines can also be assigned smaller errors because of the reduced errors on the corrected waterline heights. The method was tested on a section of the TanDEM-X Intermediate DEM (IDEM) covering an 11km reach of the Warwickshire Avon, England. Flood extents from four COSMO-SKyMed images were available at various stages of a flood in November 2012, and a LiDAR DEM was available for validation. In the area covered by the flood extents, the original IDEM heights had a mean difference from the corresponding LiDAR heights of 0.5 m with a standard deviation of 2.0 m, while the corrected heights had a mean difference of 0.3 m with standard deviation 1.2 m. These figures show that significant reductions in IDEM height bias and error can be made using the method, with the corrected error being only 60% of the original. Even if only a single SAR image obtained near the peak of the flood was used, the corrected error was only 66% of the original. The method should also be capable of improving the final TanDEM-X DEM and other DEMs, and may also be of use with data from the SWOT (Surface Water and Ocean Topography) satellite.
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A statistical-dynamical downscaling method is used to estimate future changes of wind energy output (Eout) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.
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The predictability of high impact weather events on multiple time scales is a crucial issue both in scientific and socio-economic terms. In this study, a statistical-dynamical downscaling (SDD) approach is applied to an ensemble of decadal hindcasts obtained with the Max-Planck-Institute Earth System Model (MPI-ESM) to estimate the decadal predictability of peak wind speeds (as a proxy for gusts) over Europe. Yearly initialized decadal ensemble simulations with ten members are investigated for the period 1979–2005. The SDD approach is trained with COSMO-CLM regional climate model simulations and ERA-Interim reanalysis data and applied to the MPI-ESM hindcasts. The simulations for the period 1990–1993, which was characterized by several windstorm clusters, are analyzed in detail. The anomalies of the 95 % peak wind quantile of the MPI-ESM hindcasts are in line with the positive anomalies in reanalysis data for this period. To evaluate both the skill of the decadal predictability system and the added value of the downscaling approach, quantile verification skill scores are calculated for both the MPI-ESM large-scale wind speeds and the SDD simulated regional peak winds. Skill scores are predominantly positive for the decadal predictability system, with the highest values for short lead times and for (peak) wind speeds equal or above the 75 % quantile. This provides evidence that the analyzed hindcasts and the downscaling technique are suitable for estimating wind and peak wind speeds over Central Europe on decadal time scales. The skill scores for SDD simulated peak winds are slightly lower than those for large-scale wind speeds. This behavior can be largely attributed to the fact that peak winds are a proxy for gusts, and thus have a higher variability than wind speeds. The introduced cost-efficient downscaling technique has the advantage of estimating not only wind speeds but also estimates peak winds (a proxy for gusts) and can be easily applied to large ensemble datasets like operational decadal prediction systems.
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The polynyas of the Laptev Sea are regions of particular interest due to the strong formation of Arctic sea-ice. In order to simulate the polynya dynamics and to quantify ice production, we apply the Finite Element Sea-Ice Ocean Model FESOM. In previous simulations FESOM has been forced with daily atmospheric NCEP (National Centers for Environmental Prediction) 1. For the periods 1 April to 9 May 2008 and 1 January to 8 February 2009 we examine the impact of different forcing data: daily and 6-hourly NCEP reanalyses 1 (1.875° x 1.875°), 6-hourly NCEP reanalyses 2 (1.875° x 1.875°), 6-hourly analyses from the GME (Global Model of the German Weather Service) (0.5° x 0.5°) and high-resolution hourly COSMO (Consortium for Small-Scale Modeling) data (5 km x 5 km). In all FESOM simulations, except for those with 6-hourly and daily NCEP 1 data, the openings and closings of polynyas are simulated in principle agreement with satellite products. Over the fast-ice area the wind fields of all atmospheric data are similar and close to in situ measurements. Over the polynya areas, however, there are strong differences between the forcing data with respect to air temperature and turbulent heat flux. These differences have a strong impact on sea-ice production rates. Depending on the forcing fields polynya ice production ranges from 1.4 km3 to 7.8 km3 during 1 April to 9 May 2011 and from 25.7 km3 to 66.2 km3 during 1 January to 8 February 2009. Therefore, atmospheric forcing data with high spatial and temporal resolution which account for the presence of the polynyas are needed to reduce the uncertainty in quantifying ice production in polynyas.