Reinhold Steinacker

The MAP Special Observing Period

Intense weather over major mountain ranges such as the Alps brings a high cost to society in the form of floods, windstorms, and threats to aviation. The Mesoscale Alpine Programme (MAP; see Table 1 for a list of acronyms) is a measured response of the international atmospheric and hydrologic community to the challenge of improving the understanding and prediction of these events. It relies on intense international cooperation to assemble an alpine-scale dataset suitable to advance the basic knowledge and prediction techniques. The following scientific objectives for MAP were published in the MAP Design Proposal (Binder and Schär 1996).

The Convective and Orographically Induced Precipitation Study:A Research and Development Project of the World Weather Research Program for Improving Quantitative Precipitation Forecasting in Low-mountain Regions

Abstract The international field campaign called the Convective and Orographically-induced Precipitation Study (COPS) took place from June to August 2007 in southwestern Germany/eastern France. The overarching goal of COPS is to advance the quality of forecasts of orographically-induced convective precipitation by four-dimensional observations and modeling of its life cycle. COPS was endorsed as one of the Research and Development Projects of the World Weather Research Program (WWRP), and combines the efforts of institutions and scientists from eight countries. A strong collaboration between instrument principal investigators and experts on mesoscale modeling has been established within COPS. In order to study the relative importance of large-scale and small-scale forcing leading to convection initiation in low mountains, COPS is coordinated with a one-year General Observations Period in central Europe, the WWRP Forecast Demonstration Project MAP D-PHASE, and the first summertime European THORPEX Regional...

A Transparent Method for the Analysis and Quality Evaluation of Irregularly Distributed and Noisy Observational Data

Observational errors may have a serious impact on objective analyses. Before conducting an objective analysis, that is, interpolating irregularly spaced observations to a uniform grid, the data should be checked thoroughly for errors. For this procedure a piecewise functional fitting approach is proposed, which is based on a variational algorithm. As for thin-plate splines, an integral of squares of second temporal and/or spatial derivatives is minimized. The second derivatives are obtained from overlapping finite elements using a polynomial approach. In a slightly different mode, the same approach may also be used to interpolate the observational data to a regular grid. The method is formulated for and applied to scalar and vector quantities in a one- and a twodimensional domain. The basic advantages of the method are on the one hand the fact that no first guess or (prognostic) model field is necessary and on the other hand that no a priori knowledge about structure or weighting functions is required. Furthermore the spatial anisotropy of meteorological fields may be treated explicitly. One of the most valuable features of the method is its simplicity. For a single station it is possible to recalculate by hand each step, which may make the procedure transparent. The comparatively inexpensive computational effort renders it especially well suited to model-independent quality assessment procedures and mesoscale objective analyses. It is presently used within the framework of the Mesoscale Alpine Programme.

A Mesoscale Data Analysis and Downscaling Method over Complex Terrain

Abstract 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 s...

Minimum Temperatures, Diurnal Temperature Ranges, and Temperature Inversions in Limestone Sinkholes of Different Sizes and Shapes

Abstract Air temperature data from five enclosed limestone sinkholes of various sizes and shapes on the Hetzkogel Plateau near Lunz, Austria (1300 m MSL), have been analyzed to determine the effect of sinkhole geometry on temperature minima, diurnal temperature ranges, temperature inversion strengths, and vertical temperature gradients. Data were analyzed for a non-snow-covered October night and for a snow-covered December night when the temperature fell as low as −28.5°C. A surprising finding is that temperatures were similar in two sinkholes with very different drainage areas and depths. A three-layer model was used to show that the sky-view factor is the most important topographic parameter controlling cooling for basins in this size range in near-calm, clear-sky conditions and that the cooling slows when net longwave radiation at the floor of the sinkhole is nearly balanced by the ground heat flux.

Inversion Breakup in Small Rocky Mountain and Alpine Basins

Comparisons are made between the postsunrise breakup of temperature inversions in two similar closed basins in very different climate settings, one in the eastern Alps and one in the Rocky Mountains. The small, highaltitude, limestone sinkholes have both experienced extreme temperature minima below 2508C and both develop strong nighttime inversions. On undisturbed clear nights, temperature inversions reach to 120-m heights in both sinkholes but are much stronger in the drier Rocky Mountain basin (24 vs 13 K). Inversion destruction takes place 2.6‐3 h after sunrise in these basins and is accomplished primarily by subsidence warming associated with the removal of air from the base of the inversion by the upslope flows that develop over heated sidewalls. A conceptual model of this destruction is presented, emphasizing the asymmetry of the boundary layer development around the basin and the effects of solar shading by the surrounding ridgeline. Differences in inversion strengths and postsunrise heating rates between the two basins are caused by differences in the surface energy budget, with drier soil and a higher sensible heat flux in the Rocky Mountain sinkhole. Inversions in the small basins break up more quickly following sunrise than for previously studied valleys. The pattern of inversion breakup in the non-snow-covered basins is the same as that reported in snow-covered Colorado valleys. The similar breakup patterns in valleys and basins suggest that along-valley wind systems play no role in the breakups, since the small basins have no along-valley wind system.

Assessment of GPM-IMERG and Other Precipitation Products against Gauge Data under Different Topographic and Climatic Conditions in Iran: Preliminary Results

The new generation of weather observatory satellites, namely Global Precipitation Measurement (GPM) constellation satellites, is the lead observatory of the 10 highly advanced earth orbiting weather research satellites. Indeed, GPM is the first satellite that has been designed to measure light rain and snowfall, in addition to heavy tropical rainfall. This work compares the final run of the Integrated Multi-satellitE Retrievals for GPM (IMERG) product, the post real time of TRMM and Multi-satellite Precipitation Analysis (TMPA-3B42) and the Era-Interim product from the European Centre for Medium Range Weather Forecasts (ECMWF) against the Iran Meteorological Organization (IMO) daily precipitation measured by the synoptic rain-gauges over four regions with different topography and climate conditions in Iran. Assessment is implemented for a one-year period from March 2014 to February 2015. Overall, in daily scale the results reveal that all three products lead to underestimation but IMERG performs better than other products and underestimates precipitation slightly in all four regions. Based on monthly and seasonal scale, in Guilan all products, in Bushehr and Kermanshah ERA-Interim and in Tehran IMERG and ERA-Interim tend to underestimate. The correlation coefficient between IMERG and the rain-gauge data in daily scale is far superior to that of Era-Interim and TMPA-3B42. On the basis of daily timescale of bias in comparison with the ground data, the IMERG product far outperforms ERA-Interim and 3B42 products. According to the categorical verification technique in this study, IMERG yields better results for detection of precipitation events on the basis of Probability of Detection (POD), Critical Success Index (CSI) and False Alarm Ratio (FAR) in those areas with stratiform and orographic precipitation, such as Tehran and Kermanshah, compared with other satellite/model data sets. In particular, for heavy precipitation (>15 mm/day), IMERG is superior to the other products in all study areas and could be used in future for meteorological and hydrological models, etc.

A Sinkhole Field Experiment in the Eastern Alps

Abstract Because sinkholes are an excellent natural laboratory for studying processes leading to the formation, maintenance, and dissipation of temperature inversions, an extended set of meteorological field experiments was conducted in limestone sinkholes of various sizes and shapes in the eastern Alps during the period from 17 October 2001 through 4 June 2002. The experiments were conducted in an area surrounding the Gruenloch Sinkhole, which in earlier years had recorded the lowest surface minimum temperature in Central Europe, −52.6°C. A dense array of surface temperature sensors and three automatic weather stations were operated continuously during the experimental period, and special experiments enhanced with tethersondes and other equipment were conducted from 2 to 4 June 2002. An overview of the experiments is presented and first results are given.

The convective and orographically-induced precipitation study

Abstract The international field campaign called the Convective and Orographically-induced Precipitation Study (COPS) took place from June to August 2007 in southwestern Germany/eastern France. The overarching goal of COPS is to advance the quality of forecasts of orographically-induced convective precipitation by four-dimensional observations and modeling of its life cycle. COPS was endorsed as one of the Research and Development Projects of the World Weather Research Program (WWRP), and combines the efforts of institutions and scientists from eight countries. A strong collaboration between instrument principal investigators and experts on mesoscale modeling has been established within COPS. In order to study the relative importance of large-scale and small-scale forcing leading to convection initiation in low mountains, COPS is coordinated with a one-year General Observations Period in central Europe, the WWRP Forecast Demonstration Project MAP D-PHASE, and the first summertime European THORPEX Regional...

Comparison of Vertical Soundings and Sidewall Air Temperature Measurements in a Small Alpine Basin

Abstract Tethered balloon soundings from two sites on the floor of a 1-km-diameter limestone sinkhole in the eastern Alps are compared with pseudovertical temperature “soundings” from three lines of temperature dataloggers on the basins northwest, southwest, and southeast sidewalls. Under stable nighttime conditions with low background winds, the pseudovertical profiles from all three lines were good proxies for free air temperature soundings over the basin center, with a mean nighttime cold temperature bias of about 0.4°C and a standard deviation of 0.4°C. Cold biases were highest in the upper basin where relatively warm air subsides to replace air that spills out of the basin through the lowest-altitude saddle. On a windy night, standard deviations increased to 1°–2°C. After sunrise, the varying exposures of the dataloggers to sunlight made the pseudovertical profiles less useful as proxies for free air soundings. The good correspondence between sidewall and free air temperatures during high-static-sta...