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Change in precipitation distribution as temperature rises expressed in diagnostic and prognostic data
Sokol, Zbyněk ; Řezáčová, Daniela
We summarize the main results that show how the distribution of precipitation changes with increasing temperature. Hourly rainfall totals from 97 rain gauge stations in the Czech Republic for the years 1997 to 2019 are used for the evaluation. Ground temperature, ground dew point temperature and temperature at the lifting condensation level are used to express the temperature change. The results show how an increase in temperature and a corresponding increase in saturation humidity (CC scaling) affects the distribution of precipitation in the study area. In general, the increase in precipitation as a function of observed temperature is clearly evident for the upper quantile values, but only for certain temperature intervals. It confirms the findings of other studies. In this paper, data from reanalyses performed by the ALADIN-CLIMAT/CZ model are treated similarly to the measured data.\n
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Validation of reanalysis for Central Europe PERUN/Reanalysis
Beranová, Romana ; Rulfová, Zuzana ; Sokol, Zbyněk
PERUN/Reanalysis is based on the ALADIN numerical forecast model, which has been adapted for climatological calculations. To serve as one of the reference sets for estimating expected climate changes in the coming decades, it needs to undergo validation against station measurements and possibly against other commonly used data sets. In this conference paper, we will examine the validation of basic meteorological quantities across the computational domain of the ALADIN model. To achieve this, we will use station data from the ECA&D database, station data in the regular network (Eobs), and the ERA5 global reanalysis. Validation will be conducted for the period from 1990 to 2014. During validation, our primary focus will be on air temperature (minimum, maximum, and mean) and precipitation. We will also examine additional variables, including wind speed.\n
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(IN)DEPENDENCE OF AEROSOL ACTIVATION ON CLOUD POSITION
Zíková, Naděžda ; Pokorná, Petra ; Sedlák, Pavel ; Sokol, Zbyněk ; Ždímal, Vladimír
Five in situ campaigns focused on aerosol-cloud interactions were conducted at Mount Milešovka in the Czech Republic to gain more insight into aerosol activation and its dependence on meteorological parameters, mainly vertical air velocity and position within the cloud. The activated fraction was calculated from the difference of concentrations measured behind the whole air inlet and the PM2.5 inlet. The liquid water content (LWC) was calculated from visibility, cloud base position was estimated from ceilometer data. Vertical air velocity was estimated from cloud radar. No strong dependence was found between visibility and vertical velocity, suggesting that the clouds at the station are mostly of advection or inversion origin. Both visibility and LWC depend on the position within the cloud, with the highest LWC values found when the station was between 100 and 400 m above the cloud base, independently of the actual value.
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Diagnostics of background error covariances in a connected global and regional data assimilation system
Bučánek, Antonín ; Brožková, Radmila (advisor) ; Sokol, Zbyněk (referee) ; Derková, Mária (referee)
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...
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Model of error covariances for the assimilation of radar reflectivity into a NWP model
Sedláková, Klára ; Sokol, Zbyněk (advisor) ; Zacharov, Petr (referee)
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...
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Precipitation nowcasting for the warm part of the year
Mejsnar, Jan ; Sokol, Zbyněk (advisor) ; Jaňour, Zbyněk (referee) ; Žák, Michal (referee)
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.
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Precipitation nowcasting for the warm part of the year
Mejsnar, Jan ; Sokol, Zbyněk (advisor) ; Jaňour, Zbyněk (referee) ; Žák, Michal (referee)
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.
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Diagnostics of background error covariances in a connected global and regional data assimilation system
Bučánek, Antonín ; Brožková, Radmila (advisor) ; Sokol, Zbyněk (referee) ; Derková, Mária (referee)
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...
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Model of error covariances for the assimilation of radar reflectivity into a NWP model
Sedláková, Klára ; Sokol, Zbyněk (advisor) ; Zacharov, Petr (referee)
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...
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