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  • 1
    Language: English
    In: Monthly weather review, 2019-03-01, Vol.147 (3), p.987-1006
    Description: Abstract A Bayesian precipitation nowcasting system based on the ensemble Kalman filter is formulated. Starting from the last available radar observations, the prediction step of the filter consists of a stochastic radar extrapolation technique, while the correction step updates the radar extrapolation nowcast using information from the most recent forecast by the numerical weather prediction model (NWP). The result is a flow-dependent and seamless blending scheme that is based on the spread of the nowcast and NWP ensembles, used as the definition of the forecast error. To simplify the matrix operations, the Bayesian update is performed in the subspace spanned by the principal components, hence the term reduced space. Synthetic data experiments demonstrated that the Bayesian nowcast correctly captures the flow dependency in both the NWP forecast and the radar extrapolation skills. Four experiments with real precipitation data and a relatively small ensemble size (21 members) represented a first test under realistic conditions, such as stratiform wintertime precipitation and localized summertime convection. The skill was quantified in terms of fractions skill score at 32-km scale and 2.0 mm h−1 intensity. The results indicate that the system is able to produce blended forecasts that are at least as skillful as the nowcast-only or the NWP-only forecasts at any lead time.
    ISSN: 0027-0644
    E-ISSN: 1520-0493
    Source: Academic Search Ultimate
    Source: Alma/SFX Local Collection
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  • 2
    Language: English
    In: Monthly weather review, 2020-06-01, Vol.148 (6), p.2391-2410
    Description: Abstract Currently, major efforts are under way to refine the horizontal resolution of weather and climate models to kilometer-scale grid spacing (Δx). 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 Δx 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.
    ISSN: 0027-0644
    E-ISSN: 1520-0493
    Source: Academic Search Ultimate
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  • 3
    Language: English
    In: Monthly weather review, 2010, Vol.138 (9), p.3683-3689
    Description: Abstract 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.
    Subject(s): Earth, ocean, space ; External geophysics ; Convection, turbulence, diffusion. Boundary layer structure and dynamics ; Exact sciences and technology ; Meteorology
    ISSN: 0027-0644
    E-ISSN: 1520-0493
    Source: Academic Search Ultimate
    Source: Alma/SFX Local Collection
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  • 4
    Language: English
    In: Atmospheric science letters, 2016-05, Vol.17 (5), p.315-325
    Description: Hail is the costliest atmospheric hazard in Switzerland, causing substantial damage to agriculture, cars and buildings every year. In this study, a 12‐year statistic of objectively identified cold fronts and a radar‐based hail statistic are combined to investigate the co‐occurrence of cold fronts and hail in Switzerland. In a first step, an automated front identification scheme, which has previously been designed for and applied to global reanalysis data, is modified for a high‐resolution regional analysis data set. This front detection method is then adapted, tested and applied to the Consortium for Small Scale Modelling (COSMO) analysis data for the extended hail season (May to September) in the years 2002–2013. The resulting cold front statistic is presented and discussed. In a second step, the frequency of cold fronts is linked to a high‐resolution radar‐based hail statistic to determine the relative fraction of hail initiation events in pre‐frontal environments. Up to 45% of all detected hail events in north‐eastern and southern Switzerland form in pre‐frontal zones. Similar fractions are identified upstream of the Jura and the Black Forest mountains. The percentage of front‐related hail formation is highest in regions where hail is statistically less frequent, with the exception of southern Switzerland. Furthermore, it is shown that fronts create wind‐sheared environments, which are favourable for hail cells.
    Subject(s): climatology ; high impact weather ; front ; thunderstorm ; hail ; severe weather
    ISSN: 1530-261X
    E-ISSN: 1530-261X
    Source: NORA - Norwegian Open Research Archives
    Source: Directory of Open Access Journals
    Source: ProQuest Central
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  • 5
    Language: English
    In: Quarterly journal of the Royal Meteorological Society, 2018-04, Vol.144 (713), p.1218-1256
    Description: Data assimilation (DA) methods for convective‐scale numerical weather prediction at operational centres are surveyed. The operational methods include variational methods (3D‐Var and 4D‐Var), ensemble methods (LETKF) and hybrids between variational and ensemble methods (3DEnVar and 4DEnVar). At several operational centres, other assimilation algorithms, like latent heat nudging, are additionally applied to improve the model initial state, with emphasis on convective scales. It is demonstrated that the quality of forecasts based on initial data from convective‐scale DA is significantly better than the quality of forecasts from simple downscaling of larger‐scale initial data. However, the duration of positive impact depends on the weather situation, the size of the computational domain and the data that are assimilated. Furthermore it is shown that more advanced methods applied at convective scales provide improvements over simpler methods. This motivates continued research and development in convective‐scale DA. Challenges in research and development for improvements of convective‐scale DA are also reviewed and discussed. The difficulty of handling the wide range of spatial and temporal scales makes development of multi‐scale assimilation methods and space–time covariance localization techniques important. Improved utilization of observations is also important. In order to extract more information from existing observing systems of convective‐scale phenomena (e.g. weather radar data and satellite image data), it is necessary to provide improved statistical descriptions of the observation errors associated with these observations. Data assimilation methods for convective‐scale numerical weather prediction at operational centres are surveyed. It is demonstrated that the quality of forecasts based on initial data from convective‐scale data assimilation is significantly better than the quality of forecasts from simple downscaling. Furthermore it is shown that more advanced methods applied at convective scales provide improvements over simpler methods.
    Subject(s): numerical weather prediction ; convective‐scale ; data assimilation ; Weather ; Surveys ; Meteorological stations, Radar ; Numerical weather forecasting ; Methods
    ISSN: 0035-9009
    E-ISSN: 1477-870X
    Source: Alma/SFX Local Collection
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  • 6
    Language: English
    In: Quarterly journal of the Royal Meteorological Society, 2018-04, Vol.144 (713), p.1279-1296
    Description: Ensemble data assimilation methods such as the ensemble Kalman filter (EnKF) are a key component of probabilistic weather forecasting. They represent the uncertainty in the initial conditions by an ensemble that incorporates information coming from the physical model with the latest observations. High‐resolution numerical weather prediction models run at operational centres are able to resolve nonlinear and non‐Gaussian physical phenomena such as convection. There is therefore a growing need to develop ensemble assimilation algorithms able to deal with non‐Gaussianity while staying computationally feasible. In the present article, we address some of these needs by proposing a new hybrid algorithm based on the ensemble Kalman particle filter. It is fully formulated in ensemble space and uses a deterministic scheme such that it has the ensemble transform Kalman filter (ETKF) instead of the stochastic EnKF as a limiting case. A new criterion for choosing the proportion of particle filter and ETKF updates is also proposed. The new algorithm is implemented in the Consortium for Small‐scale Modeling (COSMO) framework and numerical experiments in a quasi‐operational convective‐scale set‐up are conducted. The results show the feasibility of the new algorithm in practice and indicate the strong potential of such local hybrid methods, in particular for forecasting non‐Gaussian variables such as wind and hourly precipitation. High‐dimensional non‐Gaussian filtering problems, such as those encountered in convective‐scale data assimilation, call for the development of new ensemble data assimilation methods. We propose a new algorithm, the LETKPF, which is a hybrid between the LETKF and the PF. Numerical experiments with COSMO in a set‐up similar to the one used operationally at MeteoSwiss show promising results, in particular for forecasting of non‐Gaussian variables such as wind and precipitation.
    Subject(s): localization ; high‐dimensional filtering ; convective scale ; data assimilation ; particle filter ; ensemble Kalman filter ; Numerical weather forecasting ; Analysis ; Precipitation (Meteorology)
    ISSN: 0035-9009
    E-ISSN: 1477-870X
    Source: Alma/SFX Local Collection
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  • 7
    Language: English
    In: Iberoamericana (Madrid, Spain), 2014-06-01, Vol.6 (23), p.281-300
    ISSN: 1577-3388
    E-ISSN: 2255-520X
    Source: JSTOR Arts & Sciences XI
    Source: Directory of Open Access Journals
    Source: Alma/SFX Local Collection
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  • 8
    Language: English
    In: Monthly weather review, 2002, Vol.130 (10), p.2459-2480
    Subject(s): Earth, ocean, space ; External geophysics ; Geophysics. Techniques, methods, instrumentation and models ; Exact sciences and technology ; Meteorology ; Weather analysis and prediction
    ISSN: 0027-0644
    E-ISSN: 1520-0493
    Source: Academic Search Ultimate
    Source: Alma/SFX Local Collection
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  • 9
    Article
    Article
    2008
    ISSN: 1350-4827 
    Language: English
    In: Meteorological applications, 2008-12, Vol.15 (4), p.503-511
    Description: Radar‐derived quantitative precipitation estimates (QPE) are becoming an increasingly important element in high‐resolution numerical weather prediction (NWP). As such they complement conventional data like surface or upper‐air observations. Unlike the latter, radar data exhibit a highly variable quality, in that they are affected by a number of factors that limit their accuracy in estimating precipitation at the surface. In the context of assimilating radar‐derived QPE in high‐resolution NWP models this poses two salient questions, i.e. how is a specific assimilation scheme affected by errors in the observations, and how can such variable quality be accounted for? This paper addresses the first question and presents a sensitivity study of the Latent Heat Nudging (LHN) scheme in a meso‐gamma scale NWP model to gross errors in the radar data, notably non‐rain echoes. It was found that non‐rain, or clutter, echoes as small as one model pixel can trigger the release of convective instabilities when forced by the LHN scheme, producing model precipitation that is large compared to the original non‐rain signal. Enhancement factors from 3 up to 50 have been found for moderate to high values of CAPE and low to medium intensity clutter signals. Furthermore, the response of the model atmosphere to the forcing was found to be very quick, i.e. on the time scale of convection (less than 10 min for strong forcing to a couple of hours for moderate forcing). Large coherent areas of non‐rain echoes were found to be more likely to initiate such erroneous precipitation enhancement than scattered gridbox‐sized signals. Finally, non‐rain echoes resulting from anomalous propagation of the radar beam, by virtue of the usually very stable conditions with which they are associated, are not very conducive to rainfall amplification. However, a strong spurious vertical circulation, along with undesired mixing, may be induced and adversely impact the local structure of the simulation. Copyright © 2008 Royal Meteorological Society
    Subject(s): convection ; radar ; data assimilation ; NWP
    ISSN: 1350-4827
    E-ISSN: 1469-8080
    Source: Alma/SFX Local Collection
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  • 10
    Language: English
    In: Optics letters, 2006, Vol.31 (10), p.1426-1428
    Description: The phenomenological approach introduced by Benisty [Appl. Phys. Lett. 76, 532 (2000)] to model out-of-plane radiation losses in planar photonic crystals with a low vertical refractive index contrast is extended to the case of in-plane disorder. The model is experimentally validated by means of optical measurements on GaAs-based structures. For the present fabrication techniques the disorder-induced contribution is found to be negligible compared with the other loss mechanisms.
    Subject(s): Optical and optoelectronic circuits ; Fundamental areas of phenomenology (including applications) ; Exact sciences and technology ; Electronics ; Optics ; Circuit properties ; Wave optics ; Electric, optical and optoelectronic circuits ; Physics ; Integrated optics. Optical fibers and wave guides ; Applied sciences ; Optical materials ; Photonic bandgap materials ; Diffraction and scattering
    ISSN: 0146-9592
    E-ISSN: 1539-4794
    Source: OSA Publishing
    Source: © ProQuest LLC All rights reserved〈img src="https://exlibris-pub.s3.amazonaws.com/PQ_Logo.jpg" style="vertical-align:middle;margin-left:7px"〉
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