André Walser

MAP D-PHASE: Real-Time Demonstration of Weather Forecast Quality in the Alpine Region

Demonstration of probabilistic hydrological and atmospheric simulation of flood events in the Alpine region (D-PHASE) is made by the Forecast Demonstration Project in connection with the Mesoscale Alpine Programme (MAP). Its focus lies in the end-to-end flood forecasting in a mountainous region such as the Alps and surrounding lower ranges. Its scope ranges from radar observations and atmospheric and hydrological modeling to the decision making by the civil protection agents. More than 30 atmospheric high-resolution deterministic and probabilistic models coupled to some seven hydrological models in various combinations provided real-time online information. This information was available for many different catchments across the Alps over a demonstration period of 6 months in summer/ fall 2007. The Web-based exchange platform additionally contained nowcasting information from various operational services and feedback channels for the forecasters and end users. D-PHASE applications include objective model verification and intercomparison, the assessment of (subjective) end user feedback, and evaluation of the overall gain from the coupling of the various components in the end-to-end forecasting system.

Predictability of Precipitation in a Cloud-Resolving Model

Abstract 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 ...

Probabilistic Flood Forecasting with a Limited-Area Ensemble Prediction System: Selected Case Studies

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 km 2 ). 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 m 2 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 Real-Time Ultrafinescale Forecast Support during the Special Observing Period of the MAP

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.

Calibrated Precipitation Forecasts for a Limited-Area Ensemble Forecast System Using Reforecasts

Abstract The calibration of numerical weather forecasts using reforecasts has been shown to increase the skill of weather predictions. Here, the precipitation forecasts from the Consortium for Small Scale Modeling Limited Area Ensemble Prediction System (COSMO-LEPS) are improved using a 30-yr-long set of reforecasts. The probabilistic forecasts are calibrated on the exceedance of return periods, independently from available observations. Besides correcting for systematic model errors, the spatial and temporal variability in the amplitude of rare precipitation events is implicitly captured when issuing forecasts of return periods. These forecast products are especially useful for issuing warnings of upcoming events. A way to visualize those calibrated ensemble forecasts conveniently for end users and to present verification results of the return period–based forecasts for Switzerland is proposed. It is presented that, depending on the lead time and return period, calibrating COSMO-LEPS with reforecasts inc...

Information-Based Skill Scores for Probabilistic Forecasts

Abstract The information content, that is, the predictive capability, of a forecast system is often quantified with skill scores. This paper introduces two ranked mutual information skill (RMIS) scores, RMISO and RMISY, for the evaluation of probabilistic forecasts. These scores are based on the concept of mutual information of random variables as developed in information theory. Like the ranked probability skill score (RPSS)—another and often applied skill score—the new scores compare cumulative probabilities for multiple event thresholds. The RMISO quantifies the fraction of information in the observational data that is explained by the forecasts. The RMISY quantifies the amount of useful information in the forecasts. Like the RPSS, the new scores are biased, but they can be debiased with a simple and robust method. This and additional promising characteristics of the scores are discussed with ensemble forecast assessment experiments.

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

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...