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.

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Abstract. Elevation effects in long-term (monthly to inter-annual) precipitation data have been widely studied and are taken into account in the regionalization of point-like precipitation amounts by using methods like external drift kriging and cokriging. On the daily or hourly time scale, precipitation-elevation gradients are more variable, and difficult to parameterize. For example, application of the annual relative precipitation-elevation gradient to each 12-h sub-period reproduces the annual total, but at the cost of a large root-mean-square error. If the precipitation-elevation gradient is parameterized as a function of precipitation rate, the error can be substantially reduced. It is shown that the form of the parameterization suggested by the observations conforms to what one would expect based on the physics of the orographic precipitation process (the seeder-feeder mechanism). At low precipitation rates, orographic precipitation is "conversion-limited", thus increasing roughly linearly with precipitation rate. At higher rates, orographic precipitation becomes "condensation-limited" thus leading to an additive rather than multiplicative orographic precipitation enhancement. Also it is found that for large elevation differences it becomes increasingly important to take into account those events where the mountain station receives precipitation but the valley station remains dry.

Abstract. National Meteorological and Hydrological Services (NMHSs) increase their efforts to deliver impactbased weather forecasts and warnings. At the same time, a desired increase in cost-efficiency prompts these services to automatize their weather station networks and to reduce the number of human observers, which leads to a lack of "ground truth" information about weather phenomena and their impact. A possible alternative is to encourage the general public to submit weather observations, which may include crucial information especially in high-impact situations.We wish to provide an overview of the state and properties of existing collaborations between NMHSs and voluntary weather observers or storm spotters across Europe. For that purpose, we performed a survey among 30 European NMHSs, from which 22 NMHSs returned our questionnaire. This study summarizes the most important findings and evaluates the use of "crowdsourced" information. 86 % of the surveyed NMHSs utilize information provided by the general public, 50 % have established official collaborations with spotter groups, and 18 % have formalized them. The observations are most commonly used for a real-time improvement of severe weather warnings, their verification, and an establishment of a climatology of severe weather events.The importance of these volunteered weather and impact observations has strongly risen over the past decade. We expect that this trend will continue and that storm spotters will become an essential part in severe weather warning, like they have been for decades in the United States of America. A rising number of incoming reports implies that quality management will become an increasing issue, and we finally discuss an idea how to handle this challenge.

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