Výsledky vyhledávání

  1. 1.
    0585235 - ÚI DATA Vědecká data      2024
    Geletič, Jan - Bauerová, P. - Belda, M. - Bureš, Martin - Eben, Kryštof - Fuka, V. - Karel, J. - Keder, J. - Krč, Pavel - Jareš, R. - Patiño, W. - Radović, J. - Resler, Jaroslav - Řezníček, Hynek - Šindelářová, A. - Vlček, O.

    Scenarios simulations of Prague (D05).

    Popis: Basic information
    This dataset contains simulation results for the so-called Holešovičky domain, an area in the city of Prague, Czech Republic, expected to undergo major traffic infrastructure changes in the near future. Three scenarios were modelled: current infrastructure with traffic intensity projections for 2023 (C1), future outlook with a finished part of city inner ring-road in 2030 (C2) and effect of finishing the northern part of the Prague outer ring-road (C3), which will decrease heavy traffic in the domain. Note that all scenarios have slightly different landcover (trees, buildings, bridges, tunnels etc.), so there could be small areas containing NA values in the maps and GIS files. All times are in UTC (local time, CEST is UTC +02:00).

    For more detailed description of the experiments see the TURBAN project website at https://www.project-turban.eu/.

    General organisation
    Each scenario has two folders; post-processed results from the PALM model as averaged ASCII files that can be viewed in many GIS applications (output-gis) and maps in the PNG format (output-png). Each variable was averaged from original 10min values to 1, 3 and 24-hour averages. The C1 scenario was used as a baseline. In addition to that, also differences for all variables were calculated for the scenarios C2 and C3. In total, the C1 scenario has 3 subfolders with absolute values (prefix abs), the scenarios C2 and C3 have 6 (3 with absolute values and 3 with differences; prefix diff).

    Modelled variables
    Each subfolder includes 7 subfolders with variables. Variable bio_mrt is the Mean Radiant Temperature (MRT), bio_pet is the Physiological Equivalent Temperature (PET), bio_utci is the Universal Thermal Climate Index (UTCI), kc_PM10_02m is the concentration of PM10 at 2m above ground, theta_2m is the potential temperature at 2m above ground, tsurf is the surface temperature and wspeed_10m is the wind speed at 10m above ground.

    File nomenclature
    Each file (PRJ or ASC, PNG) has the same nomenclature. An example (bio_utci_abs-01h_20190724_1200-1300.png) could be parsed as: variable name (bio_utci), processed output (abs-01h), date (20190724) and averaged period (1200-1300). So, the result is a map with hourly averaged UTCI for 24 Jul 2019 between 12:00 and 13:00 UTC.

    Important note
    During the processing phase a few potentially important problems were identified and need to be analysed in detail. One of them are extremely overestimated concentrations due to stable conditions from boundary condition inputs. In certain situations it can happen that the best regional meteorological model can provide inappropriate input conditions for some episode. This needs to be checked in detail before any following interpretation.
    Klíčová slova: air quality * thermal comfort * micro-scale * CFD modeling * cities
    Obor OECD: Meteorology and atmospheric sciences
    Trvalý link: https://hdl.handle.net/11104/0353007
    Vkladatel: admin
    Datum publikování: 17.4.2024
     
     
    Licence:
    Uveďte původ Mezinárodní licence
     
    ÚložištěPřístupKomentář
    Zenodo.orgpovolen
    Grant CEP: GA TA ČR(CZ) TO01000219
    Institucionální podpora: RVO:67985807
  2. 2.
    0585232 - ÚI DATA Vědecká data      2024
    Geletič, Jan

    Satellite remote sensing dataset for urban climate in Bergen and Prague.

    Popis: Shared dataset contains remote sensing data necessary for a land surface temperature (LST) calculation. Layers were processed for two cities; Bergen (Norway) and Prague (Czech Republic). Original data were downloaded from the U.S. Geological Survey (https://doi.org/10.5066/P975CC9B). For a LST calculation, a land surface emissivity (LSE) algorithm was used.

    Processing of LANDSAT-8 and LANDSAT-9 data
    Reading metadata file for each scene (*MTL.txt)
    Reprojection of scene (note: Bergen scenes have two UTM Zones; 31N and 32N)
    Cloud cover raster (see folder 01_CloudCover)
    Calculation Top-Of-Atmosphere (TOA) reflectance for bands 10 and 11 (TB_10 and TB_11), saving to folder 02_TOA-reflectance
    Calculating of NDVI and Fractional Vegetation Cover (FVC), saving to folder 03_FVC-NDVI
    Calculating of LSE for both bands, same as different and mean LSE (folder 04_LSE)
    Calculating of LST
    Saving of metadata file (see *metadata.txt)
    Klíčová slova: land and surface temperature * landsat * Prague * Bergen * Land surface emissivity
    Obor OECD: Meteorology and atmospheric sciences
    Trvalý link: https://hdl.handle.net/11104/0353010
    Vkladatel: admin
    Datum publikování: 17.4.2024
     
     
    Licence:
    Uveďte původ Mezinárodní licence
     
    ÚložištěPřístupKomentář
    Zenodo.orgpovolen
    Grant CEP: GA TA ČR(CZ) TO01000219
    Institucionální podpora: RVO:67985807
  3. 3.
    0585178 - ÚI DATA Vědecká data      2024
    Bauerová, P. - Šindelářová, A. - Keder, J. - Vlček, O. - Patiño, W. - Resler, Jaroslav - Krč, Pavel - Řezníček, Hynek - Geletič, Jan - Bureš, Martin - Eben, Kryštof - Belda, M. - Radović, J. - Fuka, V. - Jareš, R. - Ezau, I.

    TURDATA: a database of low-cost air quality and remote sensing measurements for the validation of micro-scale models in the real Prague urban environments.

    Popis: TURDATA is a supplementary data set for the TURBAN project Prague observation campaign described in the manuscript Bauerová et al. 2024 (submitted for publication). The measurement campaign focused on air pollution and meteorological measurement, including vertical profiles in selected part of Prague city centre called here as Legerova domain. Within this area, one professional meteorological station (MS) Prague Karlov and one reference traffic air quality monitoring (AIM) station Prague 2-Legerova (classified as traffic hotspot) are located. To gain high spatial and temporal resolution data, the supplementary measurement network was established, which consisted of:
    - 20 combined low-cost sensor (LCS) stations for monitoring of PM10, PM2.5, NO2 and O3 concentrations (using Plantower PMS7003 particle counters and Envea Cairsense electrochemical sensors) placed in different sites and different height levels AGL (higher = H, lower = L),
    - 1 mobile telescopic meteorological mast for measuring temperature, relative humidity, wind velocity and direction and air pressure (using 2D ultrasonic anemometer Gill WindSonic 60 and weather station Gill MetConnect THP),
    - 1 MTP-5-He microwave radiometer (MWR; Attex) for temperature vertical profile,
    - 1 StreamLine XR Doppler LIDAR (HALO Photonics) for wind vertical profile.
    Klíčová slova: air quality * monitoring * low-cost sensor network * street * LIDAR
    Obor OECD: Meteorology and atmospheric sciences
    Trvalý link: https://hdl.handle.net/11104/0352954
    Vkladatel: admin
    Datum publikování: 16.4.2024
     
     
    Licence:
    Uveďte původ Mezinárodní licence
     
    ÚložištěPřístupKomentář
    Zenodo.orgpovolen
    Grant CEP: GA TA ČR(CZ) TO01000219
    Institucionální podpora: RVO:67985807


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