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MODEL OF ERROR COVARIANCES FOR THE ASSIMILATION OF RADAR REFLECTIVITY INTO NWP MODEL Predicting events with a severe convection is not easy due to the small spatial scale and rapid development of this phenomenon. But being able to predict such events is important in view of the dangerous phenomena that accompany these events, such as flash floods, strong winds, hailstorms or atmospheric electricity. Improved forecast can be achieved by more precisely defined initial conditions that enter the model. These data must match the scale of the studied phenomenon. Therefore, radar data is used in this case. Although the NWP model should describe real processes due to the simplifications and approximations the model's behavior does not entirely correspond the reality. Therefore, if we want the model to generate precipitation, we must ensure that the values of the model variables and their relationship are such that the process is started. To find out these relationships, we want to use a covariant model. In this paper, we focused on the correlation analysis of the model variables in the regions of convection between radar reflection, its conversion to the intensity of precipitation and other model variables. The COSMO data with a horizontal resolution of 2.8 km were used, which were describing approximately...

The thesis deals with the preparation of initial conditions for nume- rical weather prediction in high resolution limited area models. It focuses on the problem of preserving the large-scale part of the global driving model analysis, which can not be determined in sufficient quality in limited-area models. For this purpose, the so-called BlendVar scheme is used. The scheme consists of the appli- cation of the Digital Filter (DF) Blending method, which assures the transmission of a large-scale part of the analysis of the driving model to the limited area model, and of the three-dimensional variational method (3D-Var) at high resolution. The thesis focuses on the appropriate background error specification, which is one of the key components of 3D-Var. Different approaches to modeling of background errors are examined, including the possibility of taking into account the flow- dependent character of background errors. Approaches are also evaluated from the point of view of practical implementation. Study of evolution of background errors during DF Blending and BlendVar assimilation cycles leads to a new pro- posal for the preparation of a background error covariance matrix suitable for the BlendVar assimilation scheme. The use of the new background error covariance matrix gives the required property...

Current precipitation nowcasting systems primarily use the extrapolation of observed radar reflectivity. I used the extrapolation and studied limits of the forecast using the concept of the decorrelation time (DCT). I used data from two radars covering the territory of the Czech Republic from warm parts of four years and calculated DCT in dependence on several selected conditions describing the state of the atmosphere. I found that the mean DCT for the extrapolation is 45.4 minutes. On average the increase of the DCT in comparison when the persistence forecast is employed is 13.4 minutes. However, in dependence on current conditions the DCT may increase or decrease in more than 40 %. I also explored time evolution of the DCT during two storm events. I found that the DCT may significantly change in time, which is the consequence of changing character of the atmosphere during the storm development.

UTILIZATION OF ANALYSIS OF THE SPATIAL RELATIONSHIPS BETWEEN METEOROLO- GICAL VARIABLES IN DATA ASSIMILATION INTO A NUMERICAL WEATHER PREDICTION MODEL Quality of initial conditions has a big impact on the accuracy of numerical forecast. The aim of the preparation of the initial conditions is to modify the first guess of the atmospheric state based on the observed data of the meteorological variables so it fit the actual atmospheric state. At present these conditions are usually prepared by objective analysis or by assimilating measured data into model fields. One of the method of the data assimilation is a 3D variational method (3D VAR). It prepares the initial model conditions so that the model fields correspond to actual measured values, while maintaining the spatial relationships between the values of model variables. By utulising the spatial relationships we can improve the initial conditions and so the forecast. In this work we concentrate on study of the spatial relationship in the convective storms based on correlation analysis of the model variables. We used the model data from COSMO model with horizontal resolution 2.8 km, which were describing 152 convective storms in all the vertical levels. The analysis proved storng relationship between vertical speed, vertical speed and air...

The thesis is divided in two parts. The first part deals with the areal distribution of short-term convective rainfalls with regard to the influence of altitude. Precipitation estimates based on combination of rain gauge and radar data are used for this purpose. Statistical tests proved that the areal distribution of hourly convective rainfalls does not depend on altitude. Besides data containing precipitation events only, all measured data were statistically analysed regardless of the fact whether precipitation occurred or not. In this case it was found out that the relationship between hourly rainfall totals and altitude depends on the considered threshold of rainfall totals. When all data were considered, i.e. a threshold value was set to zero, an increase of rainfall totals well correlated with altitude. The dependence slowly disappeared with an increasing threshold. The areal distribution of 6 hour rainfall totals proved higher values in the area of south Bohemia. The most frequent synoptic patterns were northwest cyclonic situations (NWC) and cyclone over the Central Europe (C). The second part of the thesis is focused on satellite data exploitation, as measured by meteorological satellite Meteosat Second Generation, for convective precipitation estimates. The Convective Rainfall Rate (CRR) algorithm,...

Satellite sensor AMSU-A provides passive measurements of the radiation emitted from the earth's surface and the atmosphere. The radiances contain temperature and humidity information, but in order for this information to be directly assimilated in a numerical weather prediction (NWP) system, biases between the observed radiances and those simulated from the model first guess must be corrected. After the introduction we recall a notion of analysis, data assimilation and implementation in numerical model ALADIN, which is used by the Czech Hydrometeorological Institute. Then we introduce two radiance-bias correction schemes so-called Harris and Kelly method and variational correction method VarBC. In the last part of my thesis are presented the results of both correction methods for satellite measurements, available in one month periods, and effect of correction demonstrated on the figures.

The diploma thesis deals with the dependence of short-term intensive precipitations on the altitude of the Czech Republic. Data from the warm period of the year were used, it means from 1st April to 30th September, because there are the most frequent occurrence of the convective phenomena, which are the cause of the intensive precipitations. It was used data of 3 years: 2002, 2004 and 2005. These data represent the results of radar's measurement from weather radar Network CZRAD (radars Skalky, Brdy), for the year 2005 it was used also data corrected according to the rain gauges network (adjustment). The emphasis is placed on the study of 1-hour precipitation amounts, their comparison with results of 3-hours, 6-hours, 12-hours and 24-hours precipitation amounts and the interpretation in graphs, tables and cartograms. The analyses of 1-hour precipitation amounts showed very slow trend from the lowlands till the altitudes of 600 - 800 m a. s. l. The precipitation amounts descended towards the mountains. During longer precipitations the maximum values were situated mostly in the altitude 500 m a. s. l., whereas the precipitation amounts rose to this altitude, upward descended. Maxima are mostly situated in piedmont windward slopes. It was also used daily rainfall totals from the same years, which...