Paduano, Angelo · Scarano, Francesco · Casalino, Damiano · et al.
200 rows × 10 cols · 39 KB · csv, jpeg
hybrid · semantic + lexical · 470 datasets ranked · 1.02s
Paduano, Angelo · Scarano, Francesco · Casalino, Damiano · et al.
200 rows × 10 cols · 39 KB · csv, jpeg
10 numeric
The interaction between acoustic waves and turbulent grazing flow over an acoustic liner is investigated using Lattice-Boltzmann Very-Large-Eddy simulations. A single-degree-of-freedom liner with 11 streamwise-aligned cavities is studied in a grazing flow impedance tube. The conditions replicate reference experiments from the Federal University of Santa Catarina. The influence of grazing flow (with a centerline Mach number of 0.32), acoustic wave amplitude, frequency, and propagation direction relative to the mean flow is analysed. Impedance is computed using both direct (i.e. the in-situ method) and model-fitting inference (i.e. the mode-matching method) methods. The former reveals strong spatial variations; however, averaged values throughout the sample show minimal differences between upstream and downstream propagating waves, in contrast to what is obtained with the latter method. Flow analyses reveal that the orifices displace the flow away from the face sheet, with this effect amplified by acoustic waves and dependent on the wave propagation direction. Consequently, the boundary layer displacement thickness ($\delta^*$) increases along the streamwise direction compared to a smooth wall and exhibits localised humps downstream of each orifice. The growth of $\delta^*$ alters the flow dynamics within the orifices by weakening the shear layer at downstream positions. This influences the acoustic-induced mass flow rate through the orifices at equal Sound Pressure Level, suggesting that acoustic energy is dissipated differently along the liner. The asymmetry of the flow field experienced by the acoustic wave, depending on its propagation direction, highlights the need to consider a spatially evolving turbulent flow when studying the acoustic-flow interaction and measuring impedance.
1 files · 29 KB · netcdf
NOAA Coral Reef Watch (v3.1 CoralTemp) Daily Global 5km Satellite Sea Surface Temperature Anomaly. This is a product of NOAA Coral Reef Watch Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature_anomaly (degree_C) mask (pixel characteristics flag array, pixel_classification)
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7-day average sea surface temperature (SST) from the AVHRR and VIIRS instruments aboard the NOAA and MetOp satellites, 2006-present, is generated by NOAA/NESDIS/STAR using the Advanced Clear-Sky Processor for Oceans (ACSPO) processing system. Only nighttime overpasses are used and composited into daily mean grids (~830 m), then the daily composite grids are averaged into gridded 7-day temperature averages. More info: https://eastcoast.coastwatch.noaa.gov/cw_avhrr-viirs_sst.php cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][level][latitude][longitude]): sst (sea_surface_subskin_temperature, degree_C)
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Climatological 7-day average sea surface temperature (SST) from 2007 to 2025, i.e. there are 52 7-day periods each representing a 2007-2025 mean SST for that period. The 18-year period for averaging begins May 21, 2007 and ends May 20, 2025. Data are merged from the AVHRR and VIIRS instruments aboard the NOAA and MetOp satellites. SST is generated by NOAA/NESDIS/STAR using the Advanced Clear-Sky Processor for Oceans (ACSPO) processing system. Only nighttime overpasses are used and composited into daily mean grids (~830 m), then the daily composite grids are averaged into gridded 7-day temperature averages. Finally, the 18-year climatological average for each 7-day period is averaged from the 7-day files. More info: https://eastcoast.coastwatch.noaa.gov/cw_avhrr-viirs_sst.php cdm_data_type = Grid VARIABLES (all of which use the dimensions [sevenDayPeriodOfYear][level][latitude][longitude]): sst (sea_surface_subskin_temperature, degree_C)
1 files · 16 KB · netcdf
Jet Propulsion Laboratory data from a local source. cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][level][latitude][longitude]): sst (Analysed SST with land and ice masks applied, degree_C)
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Jet Propulsion Laboratory SST MUR data from a local source. cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][level][latitude][longitude]): sst (Analysed SST with land and ice masks applied, degree_C)
1 files · 15 KB · netcdf
Jet Propulsion Laboratory data from a local source. cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][level][latitude][longitude]): sst (Analysed SST with land and ice masks applied, degree_C)
1 files · 30 KB · netcdf
NOAA Coral Reef Watch Daily (v3.1) Global 5km Satellite Sea Surface Temperature (CoralTemp). CoralTemp is derived from three different but related 5km daily gap-free SST data sets and provides an internally consistent SST product that stretches from 1985 to present: Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Sea Surface Temperature Reanalysis (1985-2002), Geo-Polar Blended Night-only Sea Surface Temperature Reanalysis (2002-2016), Geo-Polar Blended Night-only Sea Surface Temperature Near Real-Time (2017 to present). cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): analysed_sst (analysed sea surface temperature, degree_C) sea_ice_fraction (1)
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Sea surface temperature retrievals produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from Visible and Infrared Imager/Radiometer Suite (VIIRS) sensor cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][altitude][rows][cols]): l2p_flags swath_latitude (Latitude, degrees_north) swath_longitude (Longitude, degrees_east) sea_surface_temperature (sea surface subskin temperature, degree_C) sses_bias (SSES bias estimate, degree_C) sses_standard_deviation (degree_C) graphics (graphics overlay planes)
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Sea surface temperature retrievals produced by NOAA/NESDIS/STAR office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, degree_C) sses_bias (SSES bias estimate, kelvin) sses_standard_deviation (kelvin) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction (1) wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime (time difference of highest weighted input SST from reference time. Is equal to sst_dtime for pixels where L3S-LEO-PM_N is available, seconds) sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 17 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/STAR office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, kelvin) sses_bias (SSES bias estimate, kelvin) sses_standard_deviation (kelvin) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction (1) wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime (time difference of highest weighted input SST from reference time. Is equal to sst_dtime for pixels where L3S-LEO-PM_N is available, seconds) sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 17 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/STAR office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, kelvin) sses_bias (SSES bias estimate, kelvin) sses_standard_deviation (kelvin) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction (1) wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime (time difference of highest weighted input SST from reference time. Is equal to sst_dtime for pixels where L3S-LEO-PM_N is available, seconds) sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 40 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/OSPO office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, degree_C) sses_bias (SSES bias estimate, degree_C) sses_standard_deviation (degree_C) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 40 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/OSPO office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, degree_C) sses_bias (SSES bias estimate, degree_C) sses_standard_deviation (degree_C) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 17 KB · netcdf
Sea surface temperature retrievals produced by NOAA/NESDIS/STAR office cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (sea surface sub-skin temperature, degree_C) sses_bias (SSES bias estimate, degree_C) sses_standard_deviation (degree_C) l2p_flags l3s_flags sst_count (Count of input L3U SST pixels) quality_level (quality level of SST pixel) sst_source (Source of major (highest weight) contribution to sst) satellite_zenith_angle (degrees) dt_analysis (deviation from SST reference, kelvin) sea_ice_fraction (1) wind_speed (m s-1) sst_dtime (time difference from reference time, seconds) measurement_dtime (time difference of highest weighted input SST from reference time. Is equal to sst_dtime for pixels where L3S-LEO-PM_N is available, seconds) sst_gradient_magnitude (SST gradient magnitude value, kelvin/km) sst_front_position (Binary SST front position indicator)
1 files · 19 KB · netcdf
This is a product of NOAA Coral Reef Watch Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite, derived from CoralTemp v1.0. cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (analysed sea surface temperature, degree_C) mask (Pixel characteristics flag array, pixel_classification) sea_surface_temperature_anomaly (degree_C)
1 files · 19 KB · netcdf
This is a product of NOAA Coral Reef Watch Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite, derived from CoralTemp v1.0. cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sea_surface_temperature (analysed sea surface temperature, degree_C) mask (Pixel characteristics flag array, pixel_classification) sea_surface_temperature_anomaly (degree_C)
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A daily Sea Surface Temperature (SST) Anomaly product created by ERD based on JPL MUR's climatology (2003-2014) of the Jet Propulsion Laboratory's (JPL) Multi-scale Ultra-high Resolution (MUR), merged, multi-sensor L4 v4.1 Foundation SST analysis product (part of the Group for High-Resolution Sea Surface Temperature (GHRSST) project). The data for the most recent 4 days is usually revised everyday. The data for other days is sometimes revised. cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sstAnom (sea surface temperature anomaly, degree_C) mask (sea/land field composite mask)
1 files · 16 KB · netcdf
This monthly Sea Surface Temperature (SST) Anomaly product is a simple mean of the daily anomaly product created by ERD for a given month. The daily anomalies were created by ERD based on JPL MUR's climatology (2003-2014) of the Jet Propulsion Laboratory's (JPL) Multi-scale Ultra-high Resolution (MUR), merged, multi-sensor L4 v4.1 Foundation SST analysis product (part of the Group for High-Resolution Sea Surface Temperature (GHRSST) project). cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): sstAnom (Sea Surface Temperature Anomaly Monthly Mean, degree_C) mask (sea/land field composite mask)
1 files · 26 KB · netcdf
A low-resolution version of the Multi-scale Ultra-high Resolution (MUR) Sea Surface Temperature (SST) analysis, a merged, multi-sensor L4 Foundation SST analysis product from Jet Propulsion Laboratory (JPL). cdm_data_type = Grid VARIABLES (all of which use the dimensions [time][latitude][longitude]): analysed_sst (analysed sea surface temperature, degree_C) analysis_error (estimated error standard deviation of analysed_sst, degree_C) mask (sea/land field composite mask) sea_ice_fraction (sea ice area fraction) sst_anomaly (SST anomaly from a seasonal SST climatology based on the MUR data over 2003-2014 period, kelvin)