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Baran S.,Debrecen University | Horanyi A.,Hungarian Meteorological Service | Nemoda D.,Debrecen University
Meteorology and Atmospheric Physics | Year: 2014

Weather forecasting is based on the outputs of deterministic numerical weather forecasting models. Multiple runs of these models with different initial conditions result in forecast ensembles which are used for estimating the distribution of future atmospheric variables. However, these ensembles are usually under-dispersive and uncalibrated, so post-processing is required. In the present work, Bayesian model averaging (BMA) is applied for calibrating ensembles of temperature forecasts produced by the operational limited area model ensemble prediction system of the Hungarian Meteorological Service (HMS). We describe two possible BMA models for temperature data of the HMS and show that BMA post-processing significantly improves calibration and probabilistic forecasts although the accuracy of point forecasts is rather unchanged. © 2014 Springer-Verlag Wien.

Voros M.,Hungarian Meteorological Service | Lstvanovics V.,Hungarian Academy of Sciences | Weidinger T.,Eotvos Lorand University
Boreal Environment Research | Year: 2010

Owing to its uniquely large surface area/depth ratio, the temperature of Lake Balaton is highly sensitive to atmospheric events. In the ALADIN weather prediction model, which is used operationally in Hungary, lakes are not properly represented, as their temperature is initialized from interpolated values of sea surface temperature and considered to be constant for the duration of the forecast. The FLake model as a lake parameterization offers a more detailed but still computationally inexpensive solution to this deficiency. We investigated whether the model could be applied to Lake Balaton. We tested the performance of a standalone version of the FLake model by using observations and atmospheric model data. In the off-line simulations, FLake performed well on Lake Balaton with default settings in predicting surface temperatures, and less well in capturing the bottom water temperatures and stratification. © 2010.

Many methods have been worked out to estimate precipitation rainfall from meteorological satellite radiances sensed by microwave (on-board low-orbiting satellites) and infrared (on-board geostationary satellites) sensors. Validation of such estimated precipitation products have become more and more important.This paper describes the validation study limited to the geographical area of Hungary of three satellite-based rain estimates for hydrology purposes. These estimates were recently developed in the frame of the Hydrology SAF project, launched by EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) in 2005. While two of these products were estimated using microwave-based method, one of them was estimated using a combination of infrared (IR) and microwave (MW) radiances.The validation studies carried out at the Hungarian Meteorological Service covered statistical analyses of instantaneous values over monthly periods and case-by-case analyses. Statistics were evaluated for every month, and focus was given to the differences between summer and winter to depict the seasonal features of the rainfall estimates. All three products gave best results in summer months (probability of detection was between 0.5 and 0.7 compared to 0.1 and 0.2 in winter; and false alarm rate was 0.3-0.6 in summer compared to 0.8-0.9 in winter), due to the much easier detection of deep convective clouds by satellites. Correlation was between 0.2 and 0.4 in summer months for every product, whereas in the winter it was under 0.1. In case studies, the location of convective cells formed in the summer was reflected well by MW observation; the combined products showed overestimated area of low precipitation.Significant underestimation of heavy rainfall (mean error of -15 to 20. mm/h) was found in the case of the infrared-microwave (IR-MW) mixed product. According to case studies, the MW-based retrievals overestimated high precipitation intensities of the convective cells. However, in the monthly statistics the mean error was negative (-5 to 10. mm/h) which demonstrated that the overestimation was not systematic.Winter results revealed that light rainfall had low probability of detection both by MW and IR-MW combined measurements. However, the case study presented for a winter day showed for all the three products well detection of liquid precipitation. Overall results exposed more reliable detection of convective than stratiform precipitation. © 2012 Elsevier B.V.

Szentimrey T.,Hungarian Meteorological Service
Idojaras | Year: 2013

The so-called variable correction methods form a special type of methods developed for daily data homogenization. Their common assumption is that in case of daily data series, the corrections for inhomogeneity have to vary according to the meteorological situation of each day in order to represent the extremes. In this paper we express our objections to these variable correction methods, especially to their underlying principles. Since the exact theoretical mathematical formulation of the question of daily data homogenization is generally neglected, we also try to formulate and analyze this problem in accordance with mathematical conventions.

Aims of the spectral radiation measurements can be devided to two wider areas: one is to get information about the radiation source, and the other is to get information about the properties of the space between the radiation source and the detector if output signal from the radiation source is known. In the latter case either the optical properties of the certain space or some optical parameter of an object placed in there is to be studied. The sun can be the object of the study or it can be used as natural radiation source to investigate some important properties of the atmosphere. The term 'solar spectrophotometry' refers to this. Although detection of spectral distribution of the solar radiation is considered a special area that is relatively rarely used even today in atmospheric physical measurements, it still has big significance. In addition to the 'mere' knowledge of spectal solar irradiance, the measured data can be used in a considerably wide range. In special cases, the narrow spectral range informations about the radiation can be very useful. Typical example is the erythemally weighted UV radiation. Though it does not give spectral information, the spectral range that is characterized by it, is considerably narrower than that of the classical radiation components. So this type of measurements is also discussed here. Main applied physical and technical principles of solar spectrophotometry, as well as spectrophotometers working in the UV, visible, and near infrared spectral range used at the Hungarian Meteorological Service (HMS), are shown in this paper. Measurement results and results from studies and researches using these data are also shown and analyzed. Also some special studies performed occasionally are shown. Today the primary base for operation of high accuracy measurement systems is the calibration. Since we have reference instruments, QA/QC procedures are of crucial importance in our measuring practice. Our activitiy as we operate WMO Regional Center for Solar Radiation in Region VI gives even bigger emphasis to that.

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