Carl Fortelius

An Overview of the Urban Boundary Layer Atmosphere Network in Helsinki

The Helsinki Urban Boundary-Layer Atmosphere Network (UrBAN: http://urban.fmi.fi) is a dedicated research-grade observational network where the physical processes in the atmosphere above the city are studied. Helsinki UrBAN is the most poleward intensive urban research observation network in the world and thus will allow studying some unique features such as strong seasonality. The networks key purpose is for the understanding of the physical processes in the urban boundary layer and associated fluxes of heat, momentum, moisture, and other gases. A further purpose is to secure a research-grade database, which can be used internationally to validate and develop numerical models of air quality and weather prediction. Scintillometers, a scanning Doppler lidar, ceilometers, a sodar, eddy-covariance stations, and radiometers are used. This equipment is supplemented by auxiliary measurements, which were primarily set up for general weather and/or air-quality mandatory purposes, such as vertical soundings and t...

The use of numerical weather forecast model predictions as a source of data for irrigation modelling

The use of numerical weather forecast model data as a source of data for soil moisture modelling was tested. Results show that the potential evaporation calculated using the Penman-Monteith equation can be estimated accurately using data obtained from the output of a high resolution numerical atmospheric model (HIRLAM, High Resolution Limited Area Model). The mean bias error was 0.26 mm for a 36-hour sum and the root mean square error was 2.14 mm. The evaporation obtained directly from HIRLAM was systematically smaller because this direct model output represents the real evaporation rather than the potential evaporation. The precipitation forecasts were less accurate. When the accuracy of parameters required for the calculation of potential evaporation were studied for one station, no serious bias was found. When two different irrigation models (AMBAV and SWAP) were run over one summer using either measured or HIRLAM data as the input, the results given by the models were quite similar regardless of input data source. The largest differences between the model outputs were caused by the formulation of crop and soil characteristics in the irrigation models. Copyright

Applicability of Large-Scale Convection and Condensation Parameterization to Meso-γ-Scale HIRLAM: A Case Study of a Convective Event

Abstract This paper presents a case study of a single cold air outbreak event with widespread convective precipitation over southern Finland on 25 May 2001. The purpose of the study is to investigate the applicability of the convection and condensation scheme of the High-Resolution Limited Area Model (HIRLAM) on meso-γ-scales. The study concentrates on the issue of grid-size-dependent convection parameterization. An explicit approach without the convection scheme is also examined. At the same time, the performance of an experimental nonhydrostatic version of HIRLAM is evaluated. Model simulations are conducted with three different horizontal grid spacings: 11, 5.6, and 2.8 km. Model results are compared to observed radar reflectivity data utilizing a radar simulation model, which calculates radar reflectivities from three-dimensional model output. The best results are obtained using nonhydrostatic dynamics and a grid-size-dependent convection scheme with a 5.6-km grid interval. However, even the best conf...

Application of Radar Wind Observations for Low-Level NWP Wind Forecast Validation

AbstractThe Finnish Meteorological Institute has produced a new numerical weather prediction model–based wind atlas of Finland. The wind atlas provides information on local wind conditions in terms of annual and monthly wind speed and direction averages. In the context of the wind atlas project, low-level Applications of Research to Operations at Mesoscale (AROME) model wind forecasts have been validated against radar radial wind observations and, as a comparison, against conventional radiosonde observations to confirm the realism of the wind forecasts. The results indicate that the systematic and random errors in the AROME wind forecasts are relatively small and are of the same order of magnitude independent of the validating observation type. The validation benefits from the high spatial and temporal resolution of the radar observations. There are over 4000 times as many radar observations as radiosonde observations available for the considered validation period of July 2008–May 2009.

Chapter 3.3 Forward and inverse modelling of radioactive pollutants dispersion after Chernobyl accident

Abstract The paper re-analyses the consequences of Chernobyl catastrophe for the radionuclide contamination of the European region. In the re-analysis, we tried to use the best available information and establish the ground for the source-apportionment studies, similar to those conducted by the team for ETEX experiment. The modelling tool used in the simulations was the Finnish Emergency and Air Quality modelling system SILAM v.3.8, which is based on a Lagrangian Monte-Carlo random-walk. The system was run through the 1-month-long period with the source-term information for 22 nuclides, which altogether comprise >99% of the total inventory of the release, and varying vertical emission profile, which reflected the different stages of the accident. This information and detailed meteorological data from the state-of-the-art NWP model HIRLAM, which was re-run for the considered period, resulted in accurate reproduction of the contamination pattern and its motions over Europe. Comparison of the simulated deposition map with the results of the radioactive deposition atlas of Europe showed very good agreement between the patterns. However, source-apportionment simulations showed insufficient both temporal resolution and spatial coverage of the data, and thus are not discussed in details.