netcdf cor1goecnvv2X1.a1.20190422.115957 {
dimensions:
	time = 1 ;
	nlines = 728 ;
	npixels = 672 ;
variables:
	double time(time) ;
		time:date_time_stamp = "2019-04-22T11:59:57Z" ;
		time:long_name = "Modified Julian Day of the Nominal Satellite Image Timestamp" ;
		time:units = "days since 1858-11-17T00:00:00.000" ;
		time:definition = "http://tycho.usno.navy.mil/mjd.html" ;
		time:comments = "MJD equals 51544.0 at Jan/01/2000 00:00" ;
	float latitude(nlines) ;
		latitude:long_name = "Latitude" ;
		latitude:scale_factor = 57.29578f ;
		latitude:_FillValue = -999.f ;
		latitude:units = "degrees_north" ;
	float longitude(npixels) ;
		longitude:long_name = "Longitude" ;
		longitude:scale_factor = 57.29578f ;
		longitude:_FillValue = -999.f ;
		longitude:units = "degrees_east" ;
	double scan_time(nlines) ;
		scan_time:long_name = "Observation Time (MJD) for Current Line" ;
		scan_time:units = "days since 1858-11-17T00:00:00.000" ;
		scan_time:definition = "http://tycho.usno.navy.mil/mjd.html" ;
		scan_time:comments = "MJD equals 51544.0 at Jan/01/2000 00:00" ;
	ushort ir_brightness_temperature(time, nlines, npixels) ;
		ir_brightness_temperature:long_name = "IR Brightness Temperature Image" ;
		ir_brightness_temperature:valid_range = 15000US, 35000US ;
		ir_brightness_temperature:units = "degrees_Kelvin" ;
		ir_brightness_temperature:scale_factor = 0.01f ;
		ir_brightness_temperature:_FillValue = 65535US ;
		ir_brightness_temperature:coordinates = "longitude latitude time" ;
	ushort ot_id_number(time, nlines, npixels) ;
		ot_id_number:long_name = "IR Overshooting Top Identification Number" ;
		ot_id_number:valid_range = 1US, 9999US ;
		ot_id_number:units = "unitless" ;
		ot_id_number:_FillValue = 0US ;
		ot_id_number:coordinates = "longitude latitude time" ;
		ot_id_number:comments = "The IR Overshooting Top Identification Number field shows all pixels that belong to an individual overshooting top updraft region.  The ID numbers apply uniquely to each satellite scan, i.e. ID number 1 in one scan will likely not be the same feature as ID number 1 in the next scan, and therefore cannot be used to track an overshooting top throughout its lifetime." ;
	ubyte ot_probability(time, nlines, npixels) ;
		ot_probability:long_name = "Overshooting Top Probability" ;
		ot_probability:valid_range = 1UB, 100UB ;
		ot_probability:units = "unitless" ;
		ot_probability:_FillValue = 0UB ;
		ot_probability:coordinates = "longitude latitude time" ;
		ot_probability:scale_factor = 0.01f ;
	ubyte hiwc_probability(time, nlines, npixels) ;
		hiwc_probability:long_name = "High Ice Water Content Probability" ;
		hiwc_probability:valid_range = 1UB, 100UB ;
		hiwc_probability:units = "unitless" ;
		hiwc_probability:_FillValue = 0UB ;
		hiwc_probability:coordinates = "longitude latitude time" ;
		hiwc_probability:scale_factor = 0.01f ;
	ushort distance_to_overshooting_top(time, nlines, npixels) ;
		distance_to_overshooting_top:long_name = "Distance to Nearest Overshooting Cloud Top or any Pixel with Visible Detection Rating over 3" ;
		distance_to_overshooting_top:valid_range = 0US, 65534US ;
		distance_to_overshooting_top:units = "kilometers" ;
		distance_to_overshooting_top:_FillValue = 65535US ;
		distance_to_overshooting_top:coordinates = "longitude latitude time" ;
		distance_to_overshooting_top:scale_factor = 0.01f ;
	ushort cloud_optical_depth(time, nlines, npixels) ;
		cloud_optical_depth:long_name = "Cloud Optical Depth" ;
		cloud_optical_depth:valid_range = 0US, 15000US ;
		cloud_optical_depth:units = "unitless" ;
		cloud_optical_depth:_FillValue = 65535US ;
		cloud_optical_depth:coordinates = "longitude latitude time" ;
		cloud_optical_depth:scale_factor = 0.01f ;
		cloud_optical_depth:comments = "Cloud optical depth is derived based on the difference between the observed reflectance and a prediction of reflectance for anvil clouds given the pixel viewing, solar zenith, and relative azimuth angles. The anvil reflectance prediction is based on analysis of one year of anvil clouds observed by GOES-13, GOES-15, and Himawari-8. Spatial analyses and thresholding of IR brightness temperatures were combined to define anvil clouds as is described for the ir_anvil_detection variable above. Anvil pixels were filtered to ensure spatial homogeneity in reflectance and IR temperature. Reflectances are binned by angles and a kernel-based approach introduced by Roujean et al. (1992) is used to extrapolate anvil reflectance for bins with little to no samples. The observed minus predicted anvil reflectance is then statistically related to cloud optical depth derived using the Visible Infrared Solar-infrared Split-Window Technique (VISST) developed within the NASA LaRC CERES Cloud Subsystem (Minnis et al. 2011). An optical depth of 150 is the maximum value retrieved by VISST, which corresponds to a reflectance that is slightly brighter than predicted for anvils. The fit is exponential so optical depth rapidly drops for clouds darker than the anvil reflectance prediction. This approach is considered experimental at the present time and a publication describing it is currently in preparation." ;
	short parallax_correction_longitude(time, nlines, npixels) ;
		parallax_correction_longitude:long_name = "Longitudinal Parallax Correction for OT and Anvil" ;
		parallax_correction_longitude:valid_range = -32767s, 32767s ;
		parallax_correction_longitude:units = "degrees_east" ;
		parallax_correction_longitude:_FillValue = -32768s ;
		parallax_correction_longitude:coordinates = "longitude latitude time" ;
		parallax_correction_longitude:scale_factor = 0.001f ;
	short parallax_correction_latitude(time, nlines, npixels) ;
		parallax_correction_latitude:long_name = "Latitudinal Parallax Correction for OT and Anvil" ;
		parallax_correction_latitude:valid_range = -32767s, 32767s ;
		parallax_correction_latitude:units = "degrees_north" ;
		parallax_correction_latitude:_FillValue = -32768s ;
		parallax_correction_latitude:coordinates = "longitude latitude time" ;
		parallax_correction_latitude:scale_factor = 0.001f ;
	ushort ot_anvilmean_brightness_temperature_difference(time, nlines, npixels) ;
		ot_anvilmean_brightness_temperature_difference:long_name = "Overshooting Top Minus Anvil Brightness Temperature Difference" ;
		ot_anvilmean_brightness_temperature_difference:valid_range = 1US, 5000US ;
		ot_anvilmean_brightness_temperature_difference:units = "degrees_Kelvin" ;
		ot_anvilmean_brightness_temperature_difference:_FillValue = 0US ;
		ot_anvilmean_brightness_temperature_difference:coordinates = "longitude latitude time" ;
		ot_anvilmean_brightness_temperature_difference:scale_factor = 0.01f ;
	ushort tropopause_temperature(time, nlines, npixels) ;
		tropopause_temperature:long_name = "Temperature of the Tropopause Retrieved from MERRA-2 Reanalysis" ;
		tropopause_temperature:valid_range = 15000US, 35000US ;
		tropopause_temperature:units = "degrees_Kelvin" ;
		tropopause_temperature:_FillValue = 65535US ;
		tropopause_temperature:coordinates = "longitude latitude time" ;
		tropopause_temperature:scale_factor = 0.01f ;
	ushort tropopause_height(time, nlines, npixels) ;
		tropopause_height:long_name = "Height of the Tropopause Retrieved from MERRA-2 Reanalysis" ;
		tropopause_height:valid_range = 1US, 50000US ;
		tropopause_height:units = "kilometers" ;
		tropopause_height:_FillValue = 65535US ;
		tropopause_height:coordinates = "longitude latitude time" ;
		tropopause_height:scale_factor = 0.001f ;
		tropopause_height:comments = "The retrieval of tropopause height and pressure is based on 4D interpolation of numerical model data. The hypsometric relation is employed in the vertical interpolation process." ;
	ushort tropopause_pressure(time, nlines, npixels) ;
		tropopause_pressure:long_name = "Pressure at the Tropopause Retrieved from MERRA-2 Reanalysis" ;
		tropopause_pressure:valid_range = 1US, 50000US ;
		tropopause_pressure:units = "hPa" ;
		tropopause_pressure:_FillValue = 65535US ;
		tropopause_pressure:coordinates = "longitude latitude time" ;
		tropopause_pressure:scale_factor = 0.01f ;
		tropopause_pressure:comments = "The retrieval of tropopause height and pressure is based on 4D interpolation of numerical model data. The hypsometric relation is employed in the vertical interpolation process." ;
	ushort cloud_top_height(time, nlines, npixels) ;
		cloud_top_height:long_name = "Cloud Top Height Retrieved from MERRA-2 Reanalysis" ;
		cloud_top_height:valid_range = 1US, 50000US ;
		cloud_top_height:units = "kilometers" ;
		cloud_top_height:_FillValue = 65535US ;
		cloud_top_height:coordinates = "longitude latitude time" ;
		cloud_top_height:scale_factor = 0.001f ;
		cloud_top_height:comments = "The retrieval of cloud top height is based on matching the infrared temperature of anvil cloud pixels with an interpolated numerical model profile. The tropopause defined by the numerical model using the WMO lapse-rate definition, and the temperature profile above the tropopause is modified to cool at a rate of 4.5 K/km for GOES-8 to -15, MTSAT-1R and -2, and Meteosat 8-11, 6 K/km for Himawari-8/9 and GOES-16/17, and 7.3 K/km for MODIS. The lapse rates are based on the findings of Griffin et al. (JAMC, 2016) and other empirical analyses. Modification of the temperature profile addresses situations where the IR temperature within overshooting tops or very cold anvils is colder than any temperature in the model profile, which would lead to non-retrieval of cloud height. The IR temperature to model matching process is only applied to pixels considered to be anvil clouds. It begins at the 500 hPa level and proceeds upward until the closest match between observation and model temperature is found. The hypsometric relation is employed in the vertical interpolation process. IR temperature and cloud top pressure is used to derive potential temperature. This approach is considered experimental at the present time, and validation using CALIPSO cloud height retrievals is ongoing." ;
	ushort cloud_top_pressure(time, nlines, npixels) ;
		cloud_top_pressure:long_name = "Cloud Top Pressure Retrieved from MERRA-2 Reanalysis" ;
		cloud_top_pressure:valid_range = 1US, 50000US ;
		cloud_top_pressure:units = "hPa" ;
		cloud_top_pressure:_FillValue = 65535US ;
		cloud_top_pressure:coordinates = "longitude latitude time" ;
		cloud_top_pressure:scale_factor = 0.01f ;
		cloud_top_pressure:comments = "The retrieval of cloud top pressure is based on matching the infrared temperature of anvil cloud pixels with an interpolated numerical model profile. The tropopause defined by the numerical model using the WMO lapse-rate definition, and the temperature profile above the tropopause is modified to cool at a rate of 4.5 K/km for GOES-8 to -15, MTSAT-1R and -2, and Meteosat 8-11, 6 K/km for Himawari-8/9 and GOES-16/17, and 7.3 K/km for MODIS. The lapse rates are based on the findings of Griffin et al. (JAMC, 2016) and other empirical analyses. Modification of the temperature profile addresses situations where the IR temperature within overshooting tops or very cold anvils is colder than any temperature in the model profile, which would lead to non-retrieval of cloud height. The IR temperature to model matching process is only applied to pixels considered to be anvil clouds. It begins at the 500 hPa level and proceeds upward until the closest match between observation and model temperature is found. The hypsometric relation is employed in the vertical interpolation process. IR temperature and cloud top pressure is used to derive potential temperature. This approach is considered experimental at the present time, and validation using CALIPSO cloud height retrievals is ongoing." ;
	ushort cloud_top_potential_temperature(time, nlines, npixels) ;
		cloud_top_potential_temperature:long_name = "Cloud Top Potential Temperature Retrieved from MERRA-2 Reanalysis" ;
		cloud_top_potential_temperature:valid_range = 1US, 50000US ;
		cloud_top_potential_temperature:units = "degrees_Kelvin" ;
		cloud_top_potential_temperature:_FillValue = 65535US ;
		cloud_top_potential_temperature:coordinates = "longitude latitude time" ;
		cloud_top_potential_temperature:scale_factor = 0.01f ;
		cloud_top_potential_temperature:comments = "The retrieval of cloud top potential temperature is based on matching the infrared temperature of anvil cloud pixels with an interpolated numerical model profile. The tropopause defined by the numerical model using the WMO lapse-rate definition, and the temperature profile above the tropopause is modified to cool at a rate of 4.5 K/km for GOES-8 to -15, MTSAT-1R and -2, and Meteosat 8-11, 6 K/km for Himawari-8/9 and GOES-16/17, and 7.3 K/km for MODIS. The lapse rates are based on the findings of Griffin et al. (JAMC, 2016) and other empirical analyses. Modification of the temperature profile addresses situations where the IR temperature within overshooting tops or very cold anvils is colder than any temperature in the model profile, which would lead to non-retrieval of cloud height. The IR temperature to model matching process is only applied to pixels considered to be anvil clouds. It begins at the 500 hPa level and proceeds upward until the closest match between observation and model temperature is found. The hypsometric relation is employed in the vertical interpolation process. IR temperature and cloud top pressure is used to derive potential temperature. This approach is considered experimental at the present time, and validation using CALIPSO cloud height retrievals is ongoing." ;
	ubyte ir_anvil_detection(time, nlines, npixels) ;
		ir_anvil_detection:long_name = "Anvil Cloud Detection Using IR Brightness Temperature" ;
		ir_anvil_detection:valid_range = 1s, 255s ;
		ir_anvil_detection:units = "count" ;
		ir_anvil_detection:_FillValue = 0UB ;
		ir_anvil_detection:coordinates = "longitude latitude time" ;
		ir_anvil_detection:comments = "This anvil rating indicates confidence in anvil detection, where values over 10 roughly correspond to human perception of anvil cloud extent and values over 100 indicate a very high level of confidence. The rating exploits the spatial uniformity of a BT-score, which is constructed from the difference between tropopause temperature and pixel\'s IR temperature. Spatial uniformity is estimated from the characteristics of BT-score\'s regional histogram and subsequently adjusted by the presence of cold pixels nearby and other factors." ;
	ushort visible_reflectance(time, nlines, npixels) ;
		visible_reflectance:long_name = "Visible Reflectance Image" ;
		visible_reflectance:valid_range = 1US, 50000US ;
		visible_reflectance:units = "percent" ;
		visible_reflectance:_FillValue = 65535US ;
		visible_reflectance:coordinates = "longitude latitude time" ;
		visible_reflectance:scale_factor = 0.01f ;
	ubyte ot_rating_visible(time, nlines, npixels) ;
		ot_rating_visible:long_name = "Visible Texture Detection Rating" ;
		ot_rating_visible:valid_range = 1s, 255s ;
		ot_rating_visible:units = "count" ;
		ot_rating_visible:_FillValue = 0UB ;
		ot_rating_visible:coordinates = "longitude latitude time" ;
	ubyte visible_anvil_detection(time, nlines, npixels) ;
		visible_anvil_detection:long_name = "Anvil Cloud Detection in Visible Band" ;
		visible_anvil_detection:valid_range = 1s, 255s ;
		visible_anvil_detection:units = "unitless" ;
		visible_anvil_detection:_FillValue = 0UB ;
		visible_anvil_detection:coordinates = "longitude latitude time" ;

// global attributes:
		:title = "Geostationary Visible and Infrared Imager Deep Convective Storm Detection and Characterization Dataset From NASA Langley Research Center" ;
		:summary = "This file contains products designed to identify 1) deep convective anvil clouds, 2) cold or textured updraft and gravity wave regions embedded within the anvils, and 3) areas where ice crystal icing due to high ice water content could occur using visible and infrared imager observations and numerical model analyses.\nAlgorithm development was sponsored by the NOAA GOES-R Risk Reduction Research Program, the NASA ROSES Severe Weather Research Program, and the NASA ARMD Advanced Air Transport Technology Project." ;
		:reference1 = "Khlopenkov, K. V., Bedka, K. M., Cooney, J. W., & Itterly, K. (2021). Recent advances in detection of overshooting cloud tops from longwave infrared satellite imagery. Journal of Geophysical Research: Atmospheres. Submitted" ;
		:reference2 = "Yost, C. R., Bedka, K. M., Minnis, P., Nguyen, L., Strapp, J. W., Palikonda, R., Khlopenkov, K., Spangenberg, D., Smith Jr., W. L., Protat, A., and Delanoe, J., 2018: A prototype method for diagnosing high ice water content probability using satellite imager data, Atmos. Meas. Tech., 11, 1615-1637, https://doi.org/10.5194/amt-11-1615-2018" ;
		:creator_name = "Kristopher Bedka and Konstantin Khlopenkov" ;
		:creator_email = "kristopher.m.bedka@nasa.gov, konstantin.khlopenkov@nasa.gov" ;
		:institution = "NASA Langley Research Center" ;
		:date_created = "2021-01-20T00:30:53Z" ;
		:platform = "GOES-16" ;
		:sensor = "Advanced Baseline Imager" ;
		:product_version = "2.0" ;
		:license = "No constraints on data access or use" ;
		:keywords = "EARTH SCIENCE > ATMOSPHERE > CONVECTIVE CLOUDS/SYSTEMS (OBSERVED/ANALYZED) > CUMULONIMBUS" ;
		:keywords_vocabulary = "NASA Global Change Master Directory (GCMD) Earth Science Keywords, Version 8.6" ;
		:spatial_resolution = "2.0 km" ;
		:geospatial_lat_min = "-38.99" ;
		:geospatial_lat_max = "-26.01" ;
		:geospatial_lon_min = "-69.99" ;
		:geospatial_lon_max = "-58.01" ;
		:time_coverage_start = "2019-04-22T11:59:57Z" ;
		:time_coverage_end = "2019-04-22T12:00:29Z" ;
		:numerical_model_data_source = "MERRA-2" ;
}