This paper presents the Integrated Nowcasting through Comprehensive Analysis (INCA) system, which has been developed for use in mountainous terrain. Analysis and nowcasting fields include temperature, humidity, wind, precipitation amount, precipitation type, cloudiness, and global radiation. The analysis part of the system combines surface station data with remote sensing data in such a way that the observations at the station locations are reproduced, whereas the remote sensing data provide the spatial structure for the interpolation. The nowcasting part employs classical correlation-based motion vectors derived from previous consecutive analyses. In the case of precipitation the nowcast includes an intensity-dependent elevation effect. After 2-6 h of forecast time the nowcast is merged into an NWP forecast provided by a limited-area model, using a predefined temporal weighting function. Cross validation of the analysis and verification of the nowcast are performed. Analysis quality is high for temperature, but comparatively low for wind and precipitation, because of the limited representativeness of station data in mountainous terrain, which can be only partially compensated by the analysis algorithm. Significant added value of the system compared to the NWP forecast is found in the first few hours of the nowcast. At longer lead times the effects of the latest observations becomes small, but in the case of temperature the downscaling of the NWP forecast within the INCA system continues to provide some improvement compared to the direct NWP output.
Meteorological events affecting the evolution of temperature inversions or cold-air pools in the 1-km-diameter, high-altitude (~1300 m MSL) Grünloch basin in the eastern Alps are investigated using data from lines of temperature dataloggers running up the basin sidewalls, nearby weather stations, and weather charts. Nighttime cold-air-pool events observed from October 2001 to June 2002 are categorized into undisturbed inversion evolution, late buildups, early breakups, mixing events, layered erosion at the inversion top, temperature disturbances occurring in the lower or upper elevations of the pool, and inversion buildup caused by the temporary clearing of clouds. In addition, persistent multiday cold-air pools are sometimes seen. Analyses show that strong winds and cloud cover are the governing meteorological parameters that cause the inversion behavior to deviate from its undisturbed state, but wind direction can also play an important role in the life cycle of the cold-air pools, because it governs the interaction with steep or gentle slopes of the underlying topography. Undisturbed cold-air pools are unusual in the Grünloch basin. A schematic diagram illustrates the different types of cold-air-pool events.
A mesoscale data analysis method for meteorological station reports is presented. Irregularly distributed measured values are combined with measurement-independent a priori information about the modification of analysis fields due to topographic forcing. As a physical constraint to a thin-plate spline interpolation, the so-called "fingerprint method" recognizes patterns of topographic impact in the data and allows for the transfer of information to data-sparse areas. The results of the method are small-scale interpolation fields on a regular grid including topographically induced patterns that are not resolved by the station network. Presently, the fingerprint method is designed for the analysis of scalar meteorological variables like reduced pressure or air temperature. The principles for the fingerprint technique are based on idealized influence fields. They are calculated for thermal and dynamic surface forcing. For the former, the effects of reduced air volumes in valleys, the elevated heat sources, and the stability of the valley atmosphere are taken into account. The increase of temperature under ideal conditions in comparison to flat terrain is determined on a 1-km grid using height and surface geometry information. For the latter, a perturbation of an originally constant cross-Alpine temperature gradient is calculated by a topographical weighting. As a result, the gradient is steep where the mountain range is high and steep. If, during the interpolation process, some signal of the idealized patterns is found in the station data, it is used to downscale the analysis. It is shown by a cross validation of a case study that the interpolation of a mean sea level pressure field over the Alpine region is improved objectively by the method. Thermally induced mesoscale patterns are visible in the interpolated pressure field.
Abstract. The ability of radar-rain gauge merging algorithms to precisely analyse convective precipitation patterns is of high interest for many applications, e.g. hydrological modelling, thunderstorm warnings, and, as a reference, to spatially validate numerical weather prediction models. However, due to drawbacks of methods like crossvalidation and due to the limited availability of reference data sets on high temporal and spatial scales, an adequate validation is usually hardly possible, especially on an operational basis. The present study evaluates the skill of very high-resolution and frequently updated precipitation analyses (rapid-INCA) by means of a very dense weather station network (WegenerNet), operated in a limited domain of the southeastern parts of Austria (Styria). Based on case studies and a longer-term validation over the convective season 2011, a general underestimation of the rapid-INCA precipitation amounts is shown by both continuous and categorical verification measures, although the temporal and spatial variability of the errors is -by convective nature -high. The contribution of the rain gauge measurements to the analysis skill is crucial. However, the capability of the analyses to precisely assess the convective precipitation distribution predominantly depends on the representativeness of the stations under the prevalent convective condition.
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