The Impact of Moist Singular Vectors and Horizontal Resolution on Short-Range Limited-Area Ensemble Forecasts for Two European Winter Storms

2006 ◽  
Vol 134 (10) ◽  
pp. 2877-2887 ◽  
Author(s):  
André Walser ◽  
Marco Arpagaus ◽  
Christof Appenzeller ◽  
Martin Leutbecher

Abstract This paper studies the impact of different initial condition perturbation methods and horizontal resolutions on short-range limited-area ensemble predictions for two severe winter storms. The methodology consists of 51-member ensembles generated with the global ensemble prediction system (EPS) of the European Centre for Medium-Range Weather Forecasts, which are downscaled with the nonhydrostatic limited-area model Lokal Modell. The resolution dependency is studied by comparing three different limited-area ensembles: (a) 80-km grid spacing, (b) 10-km grid spacing, and (c) 10-km grid spacing with a topography coarse grained to 80-km resolution. The initial condition perturbations of the global ensembles are based on singular vectors (SVs), and the tendencies are not perturbed (i.e., no stochastic physics). Two configurations are considered for the initial condition perturbations: (i) the operational SV configuration: T42 truncation, 48-h optimization time, and dry tangent-linear model, and (ii) the “moist SV” configuration: TL95 truncation, 24-h optimization time, and moist tangent-linear model. Lokal Modell ensembles are analyzed for the European winter storms Lothar and Martin, both occurring in December 1999, with particular attention paid to near-surface wind gusts. It is shown that forecasts using the moist SV configuration predict higher probabilities for strong wind gusts during the storm period compared to forecasts with the operational SV configuration. Similarly, the forecasts with increased horizontal resolution—even with coarse topography—lead to higher probabilities compared with the low-resolution forecasts. Overall, the two case studies suggest that currently developed operational high-resolution limited-area EPSs have a great potential to improve early warnings for severe winter storms, particularly when the driving global EPS employs moist SVs.

2015 ◽  
Vol 16 (4) ◽  
pp. 1843-1856 ◽  
Author(s):  
Silvio Davolio ◽  
Francesco Silvestro ◽  
Piero Malguzzi

Abstract Coupling meteorological and hydrological models is a common and standard practice in the field of flood forecasting. In this study, a numerical weather prediction (NWP) chain based on the BOLogna Limited Area Model (BOLAM) and the MOdello LOCale in Hybrid coordinates (MOLOCH) was coupled with the operational hydrological forecasting chain of the Ligurian Hydro-Meteorological Functional Centre to simulate two major floods that occurred during autumn 2011 in northern Italy. Different atmospheric simulations were performed by varying the grid spacing (between 1.0 and 3.0 km) of the high-resolution meteorological model and the set of initial/boundary conditions driving the NWP chain. The aim was to investigate the impact of these parameters not only from a meteorological perspective, but also in terms of discharge predictions for the two flood events. The operational flood forecasting system was thus used as a tool to validate in a more pragmatic sense the quantitative precipitation forecast obtained from different configurations of the NWP system. The results showed an improvement in flood prediction when a high-resolution grid was employed for atmospheric simulations. In turn, a better description of the evolution of the precipitating convective systems was beneficial for the hydrological prediction. Although the simulations underestimated the severity of both floods, the higher-resolution model chain would have provided useful information to the decision-makers in charge of protecting citizens.


2006 ◽  
Vol 13 (1) ◽  
pp. 53-66 ◽  
Author(s):  
S. Federico ◽  
E. Avolio ◽  
C. Bellecci ◽  
M. Colacino ◽  
R. L. Walko

Abstract. This paper reports preliminary results for a Limited area model Ensemble Prediction System (LEPS), based on RAMS (Regional Atmospheric Modelling System), for eight case studies of moderate-intense precipitation over Calabria, the southernmost tip of the Italian peninsula. LEPS aims to transfer the benefits of a probabilistic forecast from global to regional scales in countries where local orographic forcing is a key factor to force convection. To accomplish this task and to limit computational time in an operational implementation of LEPS, we perform a cluster analysis of ECMWF-EPS runs. Starting from the 51 members that form the ECMWF-EPS we generate five clusters. For each cluster a representative member is selected and used to provide initial and dynamic boundary conditions to RAMS, whose integrations generate LEPS. RAMS runs have 12-km horizontal resolution. To analyze the impact of enhanced horizontal resolution on quantitative precipitation forecasts, LEPS forecasts are compared to a full Brute Force (BF) ensemble. This ensemble is based on RAMS, has 36 km horizontal resolution and is generated by 51 members, nested in each ECMWF-EPS member. LEPS and BF results are compared subjectively and by objective scores. Subjective analysis is based on precipitation and probability maps of case studies whereas objective analysis is made by deterministic and probabilistic scores. Scores and maps are calculated by comparing ensemble precipitation forecasts against reports from the Calabria regional raingauge network. Results show that LEPS provided better rainfall predictions than BF for all case studies selected. This strongly suggests the importance of the enhanced horizontal resolution, compared to ensemble population, for Calabria for these cases. To further explore the impact of local physiographic features on QPF (Quantitative Precipitation Forecasting), LEPS results are also compared with a 6-km horizontal resolution deterministic forecast. Due to local and mesoscale forcing, the high resolution forecast (Hi-Res) has better performance compared to the ensemble mean for rainfall thresholds larger than 10mm but it tends to overestimate precipitation for lower amounts. This yields larger false alarms that have a detrimental effect on objective scores for lower thresholds. To exploit the advantages of a probabilistic forecast compared to a deterministic one, the relation between the ECMWF-EPS 700 hPa geopotential height spread and LEPS performance is analyzed. Results are promising even if additional studies are required.


2012 ◽  
Vol 51 (10) ◽  
pp. 1835-1854 ◽  
Author(s):  
Jure Cedilnik ◽  
Dominique Carrer ◽  
Jean-François Mahfouf ◽  
Jean-Louis Roujean

AbstractThis study examines the impact of daily satellite-derived albedos on short-range forecasts in a limited-area numerical weather prediction (NWP) model over Europe. Contrary to previous studies in which satellite products were used to derive monthly “climatologies,” a daily surface (snow free) albedo is analyzed by a Kalman filter. The filter combines optimally a satellite product derived from the Meteosat Second Generation geostationary satellite [and produced by the Land Surface Analyses–Satellite Application Facility of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)], an albedo climatology, and a priori information given by “persistence.” The surface albedo analyzed for a given day is used as boundary conditions of the NWP model to run forecasts starting the following day. Results from short-range forecasts over a 1-yr period reveal the capacity of satellite information to reduce model biases and RMSE in screen-level temperature (during daytime and intermediate seasons). The impact on forecast scores is larger when considering the analyzed surface albedo rather than another climatologically based albedo product. From comparisons with measurements from three flux-tower stations over mostly homogeneous French forests, it is seen that the model biases in surface net radiation are significantly reduced. An impact on the whole planetary boundary layer, particularly in summer, results from the use of an observed surface albedo. An unexpected behavior produced in summer by the satellite-derived albedo on surface temperature is also explained. The forecast runs presented here, performed in dynamical adaptation mode, will be complemented later on by data assimilation experiments over typically monthly periods.


2008 ◽  
Vol 136 (2) ◽  
pp. 443-462 ◽  
Author(s):  
Xiaoli Li ◽  
Martin Charron ◽  
Lubos Spacek ◽  
Guillem Candille

Abstract A regional ensemble prediction system (REPS) with the limited-area version of the Canadian Global Environmental Multiscale (GEM) model at 15-km horizontal resolution is developed and tested. The total energy norm singular vectors (SVs) targeted over northeastern North America are used for initial and boundary perturbations. Two SV perturbation strategies are tested: dry SVs with dry simplified physics and moist SVs with simplified physics, including stratiform condensation and convective precipitation as well as dry processes. Model physics uncertainties are partly accounted for by stochastically perturbing two parameters: the threshold vertical velocity in the trigger function of the Kain–Fritsch deep convection scheme, and the threshold humidity in the Sundqvist explicit scheme. The perturbations are obtained from first-order Markov processes. Short-range ensemble forecasts in summer with 16 members are performed for five different experiments. The experiments employ different perturbation and piloting strategies, and two different surface schemes. Verification focuses on quantitative precipitation forecasts and is done using a range of probabilistic measures. Results indicate that using moist SVs instead of dry SVs has a stronger impact on precipitation than on dynamical fields. Forecast skill for precipitation is greatly influenced by the dominant synoptic weather systems. For stratiform precipitation caused by strong baroclinic systems, the forecast skill is improved in the moist SV experiments relative to the dry SV experiments. For convective precipitation rates in the range 15–50 mm (24 h)−1 produced by weak synoptic baroclinic systems, all experiments exhibit noticeably poorer forecast skills. Skill improvements due to the Interactions between Soil, Biosphere, and Atmosphere (ISBA) surface scheme and stochastic perturbations are also observed.


2017 ◽  
Author(s):  
Florian Pantillon ◽  
Peter Knippertz ◽  
Ulrich Corsmeier

Abstract. New insights into the synoptic-scale predictability of 25 severe European winter storms of the 1995–2015 period are obtained using the homogeneous ensemble reforecast dataset from the European Centre for Medium-Range Weather Forecasts. The predictability of the storms is assessed with different metrics including the track and intensity to investigate the storms’ dynamics and the Storm Severity Index to estimate the impact of the associated wind gusts. The storms are correctly predicted by the ensemble reforecasts up to 2–4 days ahead only, which restricts the use of ensemble average and spread to short lead times. At longer lead times, the Extreme Forecast Index and Shift of Tails are computed from the deviation of the ensemble reforecasts from the model climate. Based on these indices, the model has some skill in forecasting the area covered by extreme wind gusts up to 10 days, which indicates clear potential for the early warning of storms. However, a large variability is found between the predictability of individual storms and does not appear to be related to the storms’ characteristics. This may be due to the limited sample of 25 cases, but also suggests that each severe storm has its own dynamics and sources of forecast uncertainty.


2006 ◽  
Vol 7 ◽  
pp. 1-8 ◽  
Author(s):  
S. Federico ◽  
E. Avolio ◽  
C. Bellecci ◽  
M. Colacino

Abstract. This paper reports preliminary results of a Limited area model Ensemble Prediction System (LEPS), based on RAMS, for eight case studies of moderate-intense precipitation over Calabria, the southernmost tip of the Italian peninsula. LEPS aims to transfer the benefits of a probabilistic forecast from global to regional scales in countries where local orographic forcing is a key factor to force convection. To accomplish this task and to limit computational time, in order to implement LEPS operational, we perform a cluster analysis of ECMWF-EPS runs. Starting from the 51 members that forms the ECMWF-EPS we generate five clusters. For each cluster a representative member is selected and used to provide initial and dynamic boundary conditions to RAMS, whose integrations generate LEPS. RAMS runs have 12 km horizontal resolution. Hereafter this ensemble will be referred also as LEPS_12L30. To analyze the impact of enhanced horizontal resolution on quantitative precipitation forecast, LEPS_12L30 forecasts are compared to a lower resolution ensemble, based on RAMS that has 50 km horizontal resolution and 51 members, nested in each ECMWF-EPS member. Hereafter this ensemble will be also referred as LEPS_50L30. LEPS_12L30 and LEPS_50L30 results were compared subjectively for all case studies but, for brevity, results are reported for two "representative" cases only. Subjective analysis is based on ensemble-mean precipitation and probability maps. Moreover, a short summary of objective scores. Maps and scores are evaluated against reports of Calabria regional raingauges network. Results show better LEPS_12L30 performance compared to LEPS_50L30. This is obtained for all case studies selected and strongly suggests the importance of the enhanced horizontal resolution, compared to ensemble population, for Calabria, at least for set-ups and case studies selected in this work.


2021 ◽  
Author(s):  
Hélène Bresson ◽  
Annette Rinke ◽  
Vera Schemann ◽  
Mario Mech ◽  
Susanne Crewell ◽  
...  

<p>The Arctic climate changes faster than the ones of other regions, but the relative role of the individual feedback mechanisms contributing to Arctic amplification is still unclear. Atmospheric Rivers (ARs) are narrow and transient river-style moisture flows from the sub-polar regions. The integrated water vapour transport associated with ARs can explain up to 70% of the precipitation variance north of 70°N. However, there are still uncertainties regarding the specific role and the impact of ARs on the Arctic climate variability. For the first time, the high-resolution ICON modelling framework is used over the Arctic region. Pan Arctic simulations (from 13 km down to ca. 6 and 3 km) are performed to investigate processes related with anomalous moisture transport into the Arctic. Based on a case study over the Nordic Seas, the representation of the atmospheric circulation and the spatio-temporal structure of water vapor, temperature and precipitation within the limited-area mode (LAM) of the ICON model is assessed, and compared with reanalysis and in-situ datasets. Preliminary results show that the moisture intrusion is relatively well represented in the ICON-LAM simulations. The study also shows added value in increasing the model horizontal resolution on the AR representation.</p>


2017 ◽  
Vol 17 (10) ◽  
pp. 1795-1810 ◽  
Author(s):  
Florian Pantillon ◽  
Peter Knippertz ◽  
Ulrich Corsmeier

Abstract. New insights into the synoptic-scale predictability of 25 severe European winter storms of the 1995–2015 period are obtained using the homogeneous ensemble reforecast dataset from the European Centre for Medium-Range Weather Forecasts. The predictability of the storms is assessed with different metrics including (a) the track and intensity to investigate the storms' dynamics and (b) the Storm Severity Index to estimate the impact of the associated wind gusts. The storms are well predicted by the whole ensemble up to 2–4 days ahead. At longer lead times, the number of members predicting the observed storms decreases and the ensemble average is not clearly defined for the track and intensity. The Extreme Forecast Index and Shift of Tails are therefore computed from the deviation of the ensemble from the model climate. Based on these indices, the model has some skill in forecasting the area covered by extreme wind gusts up to 10 days, which indicates a clear potential for early warnings. However, large variability is found between the individual storms. The poor predictability of outliers appears related to their physical characteristics such as explosive intensification or small size. Longer datasets with more cases would be needed to further substantiate these points.


2015 ◽  
Vol 17 (1) ◽  
pp. 171-193 ◽  
Author(s):  
Mélanie C. Rochoux ◽  
Stéphane Bélair ◽  
Maria Abrahamowicz ◽  
Pierre Pellerin

Abstract This study presents a numerical analysis of the impact of the horizontal resolution on the forecast capability of the Canadian offline land surface prediction system (SPS; formerly known as GEM-Surf) forced by the 15-km Global Environmental Multiscale (GEM) atmospheric model. This system is used to quantify on a statistical basis the subgrid-scale variability of (near-)surface variables for 25-km grid spacing based on the 2.5- or 10-km SPS run at regional scale over the 2012 summer season. The model bias and the distributions characterizing the subgrid-scale variability drastically depend on the geographic areas as well as on the diurnal cycle. These results show the benefits of high-resolution land surface simulations to account for length scales that are more consistent with the scales at which the actual land surface balance is affected by the heterogeneous geophysical fields (i.e., roughness length, land–water mask, glacier mask, and soil texture). The model bias results highlight the potential of an SPS–GEM two-way coupling strategy for refining predictions near the surface through the upscaling of high-resolution surface heat fluxes to the coarser atmospheric grid spacing, with these fluxes being significantly different from those explicitly resolved at 25 km and featuring nonlinear behavior with respect to the horizontal resolution. Since the computational power of meteorological operational centers progressively increases, making it possible to run high-resolution limited-area models, solving the surface at high resolution in a surface–atmosphere fully coupled system becomes a key aspect for improving numerical weather and environmental forecast performance.


2009 ◽  
Vol 9 (18) ◽  
pp. 7101-7114 ◽  
Author(s):  
J. Arteta ◽  
V. Marécal ◽  
E. D. Rivière

Abstract. The general objective of this series of two papers is to evaluate long duration limited-area simulations with idealised tracers as a possible tool to assess the tracer transport in chemistry-transport models (CTMs). In this second paper we analyse the results of three simulations using different horizontal and vertical resolutions. The goal is to study the impact of the model spatial resolution on convective transport of idealized tracer in the tropics. The reference simulation (REF) uses a 60 km horizontal resolution and 300 m vertically in the upper troposphere/lower stratosphere (UTLS). A 20 km horizontal resolution simulation (HR) is run as well as a simulation with 850 m vertical resolution in the UTLS (CVR). The simulations are run for one month during the SCOUT-O3 field campaign. Aircraft data, TRMM rainrate estimates and radiosoundings have been used to evaluate the simulations. They show that the HR configuration gives generally a better agreement with the measurements than the REF simulation. The CVR simulation gives generally the worst results. The vertical distribution of the tropospheric tracers for the simulations has a similar shape with a ~15 km altitude maximum for the 6h-lifetime tracer of 0.4 ppbv for REF, 1.2 for HR and 0.04 for CVR. These differences are related to the dynamics produced by the three simulations that leads to larger values of the upward velocities on average for HR and lower for CVR compared to REF. HR simulates more frequent and stronger convection leading to enhanced fluxes compared to REF and higher detrainment levels compared to CVR. HR provides also occasional overshoots over the cold point dynamical barrier. For the stratospheric tracers the differences between the three simulations are small. The diurnal cycle of the fluxes of all tracers in the Tropical Tropopause Layer exhibits a maximum linked to the maximum of convective activity.


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