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Risk assessment and prediction of natural fires in the immediate vicinity\nsurface sources of drinking water.
Trnka, Miroslav ; Kudláčková, Lucie ; Čermák, P. ; Balek, Jan ; Novotný, Jan ; Homolová, Lucie ; Semerádová, Daniela ; Brovkina, Olga ; Štěpánek, Petr ; Zahradníček, Pavel ; Skalák, Petr ; Bláhová, Monika ; Benáček, Patrik ; Fischer, Milan ; Sedlák, Pavel ; Janouš, Dalibor ; Žalud, Zdeněk ; Marek, Michal V. ; Možný, M. ; Hájková, L. ; Chuchma, F. ; Knozová, G. ; Beranová, J. ; Zatloukal, V. ; Albert, J. ; Mašková, R. ; Cienciala, E. ; Vizina, A. ; Nesládková, M. ; Melišová, E. ; Hanel, M.
The methodology formulates a procedure for assessing the risks of the occurrence and spread of natural fires in the immediate vicinity of surface sources of drinking water. The methodology\nproposes methods for estimating the consequences of natural fires on surface water quality, forecasting the change in the risk of fires due to climate change and the procedure for determining the risk of secondary pollution of reservoirs due to changes in run off after a natural fire. On this basis, the methodology proposes and diversifies preventíve and operational measures.The measures were designed in connection to modeling results for the Hadce pilot síte near the Švihov reservoir and the experience with the adverse effects of extensive deforestation on the water quality in the Vranov and Vír reservoirs.
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Non-conventional data assimilation in high resolution numerical weather prediction model with study of the slow manifold of the model
Benáček, Patrik ; Brožková, Radmila (advisor) ; Derková, Mária (referee) ; Randriamampianina, Roger (referee)
Satellite instruments currently provide the largest source of infor- mation to today's data assimilation (DA) systems for numerical weather predic- tion (NWP). With the development of high-resolution models, the efficient use of observations at high density is essential to improve small-scale information in the weather forecast. However, a large amount of satellite radiances has to be removed from DA by horizontal data thinning due to uncorrelated observation error assumptions. Moreover, satellite radiances include systematic errors (biases) that may be even larger than the observation signal itself, and must be properly removed prior to DA. Although the Variational Bias Correction (VarBC) scheme is widely used by global NWP centers, there are still open questions regarding its use in Limited-Area Models (LAMs). This thesis aims to tackle the obser- vation error difficulties in assimilating polar satellite radiances in the meso-scale ALADIN system. Firstly, we evaluate spatial- and inter-channel error correla- tions to enhance the positive effect of data thinning. Secondly, we study satellite radiance bias characteristics with the key aspects of the VarBC in LAMs, and we compare the different VarBC configurations with regards to forecast performance. This work is a step towards improving the...
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Non-conventional data assimilation in high resolution numerical weather prediction model with study of the slow manifold of the model
Benáček, Patrik ; Brožková, Radmila (advisor) ; Derková, Mária (referee) ; Randriamampianina, Roger (referee)
Satellite instruments currently provide the largest source of infor- mation to today's data assimilation (DA) systems for numerical weather predic- tion (NWP). With the development of high-resolution models, the efficient use of observations at high density is essential to improve small-scale information in the weather forecast. However, a large amount of satellite radiances has to be removed from DA by horizontal data thinning due to uncorrelated observation error assumptions. Moreover, satellite radiances include systematic errors (biases) that may be even larger than the observation signal itself, and must be properly removed prior to DA. Although the Variational Bias Correction (VarBC) scheme is widely used by global NWP centers, there are still open questions regarding its use in Limited-Area Models (LAMs). This thesis aims to tackle the obser- vation error difficulties in assimilating polar satellite radiances in the meso-scale ALADIN system. Firstly, we evaluate spatial- and inter-channel error correla- tions to enhance the positive effect of data thinning. Secondly, we study satellite radiance bias characteristics with the key aspects of the VarBC in LAMs, and we compare the different VarBC configurations with regards to forecast performance. This work is a step towards improving the...
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Study of bias correction for data assimilation in NWP model ALADIN
Benáček, Patrik ; Brožková, Radmila (advisor) ; Sokol, Zbyněk (referee)
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.
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