This BENSON_readme20230105.txt file was generated on 20230105 by Sally Benson. ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Dataset for: Natural marine cloud brightening in the Southern Ocean 2. Author Information Principal Investigator Contact Information Name: Gerald G. (Jay) Mace Institution: Department of Atmospheric Sciences, University of Utah Address: 135 South 1460 East, RM 819, WBB (William Browning Building) Salt Lake City, Utah 84112, USA Email: jay.mace@utah.edu Associate or Co-investigator Contact Information Name: Sally Benson Institution: Department of Atmospheric Sciences, University of Utah Address: 135 South 1460 East, RM 819, WBB (William Browning Building) Salt Lake City, Utah 84112, USA Email: sally.benson@utah.edu Associate or Co-investigator Contact Information Name: Ruhi Humphries Institution: Climate Science Centre, CSIRO Oceans and Atmosphere Address: Building 101, Clunies Ross Street, Black Mountain ACT 2601, Australia Email: ruhi.humphries@csiro.au Associate or Co-investigator Contact Information Name: Peter M. Gombert Institution: Department of Atmospheric Sciences, University of Utah Address: 135 South 1460 East, RM 819, WBB (William Browning Building) Salt Lake City, Utah 84112, USA Email: u1113223@utah.edu Associate or Co-investigator Contact Information Name: Elizabeth Sterner Institution: Department of Atmospheric Sciences, University of Utah Address: 135 South 1460 East, RM 819, WBB (William Browning Building) Salt Lake City, Utah 84112, USA Email: elizabeth.sterner@utah.edu Alternate Contact Information Name: Gerald G. (Jay) Mace Institution: Department of Atmospheric Sciences, University of Utah Address: 135 South 1460 East, RM 819, WBB (William Browning Building) Salt Lake City, Utah 84112, USA Email: jay.mace@utah.edu 3. Date of data collection (single date, range, approximate date) 20200601-20221101 4. Geographic location of data collection (where was data collected?): Department of Atmospheric Sciences, University of Utah, Salt Lake City, Salt Lake County, Utah, USA 5. Information about funding sources that supported the collection of the data: NASA grant 80NSSC21k1969 DOE ASR grants DE-SC00222001 and DE-SC0018995. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: Open Access 2. Links to publications that cite or use the data: Mace, G. G., Benson, S., Humphries, R., Gombert P. M., Sterner, E.: Natural marine cloud brightening in the Southern Ocean, Atmospheric Chemistry and Physics. 3. Links to other publicly accessible locations of the data: None 4. Links/relationships to ancillary data sets: None 5. Was data derived from another source? Yes If yes, list source(s): MODIS Characterization Support Team (MCST), 2017. MODIS Geolocation Fields Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MOD03.061 https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD03 Platnick, S., Ackerman, S., King, M., et al., 2015. MODIS Atmosphere L2 Cloud Product (06_L2). NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MOD06_L2.061 https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD06_L2#product-information MODIS Ocean Color Level-3 Mapped 8day at 4km, NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group. Moderate-resolution Imaging Spectroradiometer (MODIS) Aqua Chlorophyll Data; 2022 Reprocessing. NASA OB.DAAC, Greenbelt, MD, USA. doi: 10.5067/AQUA/MODIS/L3M/CHL/2022. https://oceandata.sci.gsfc.nasa.gov/api/file_search/ CERES Single Scanner Footprint (SSF) TOA/Surface Fluxes, Clouds and Aerosols Edition 4A CER_SSF_Aqua-FM3-MODIS_Edition4A_400403.2014013104.hdf NASA/LARC/SD/ASDC. (2014). CERES Single Scanner Footprint (SSF) TOA/Surface Fluxes, Clouds and Aerosols Aqua-FM3 Edition4A [Data set]. NASA Langley Atmospheric Science Data Center DAAC. Retrieved from https://doi.org/10.5067/AQUA/CERES/SSF-FM3_L2.004A 6. Recommended citation for the data: Mace, G. G., Benson, S., Humphries, R., Gombert P. M., Sterner, E. 2023. Dataset for: "Natural marine cloud brightening in the Southern Ocean." Atmospheric Chemistry and Physics. The Hive: University of Utah Research Data Repository. https://doi.org/10.7278/S50d-bpx8-gmtt --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: read_mod06_clouds_sb_test.pro Short description: Creates netcdf files of the MODIS data within each 1 degree Lat by 2 degree Lon grid box of the MODIS granule. B. Filename: match_ocean_histo.pro Short description: Appends chlor-a variable to each netcdf file. C. Filename: read_ceres_ssf.pro Short description: Appends CERES short wave albedo to each netcdf file. D. Filename: plot_modis_histograms.pro Short description: Accumulates all the small netcdf files for each month into one big monthly netcdf file. E. Filename: plot_modis_hist_daily_monthly_means.pro Short description: Creates monthly mean values for different latitude regions. F. Filename: plot_modis_hist_full_dataset.pro Short description: Creates plots using the big monthly netcdf files. G. Filename: mls_minnis_albedo.pro Short description: Parameterizes the albedo for a given visable optical depth and solar zenith angle. 2. Relationship between files: These files are IDL code files used to create the results for the paper from the datasets listed in section 5 of "SHARING/ACCESS INFORMATION". 3. Additional related data collected that was not included in the current data package: None 4. Are there multiple versions of the dataset? No -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: We acquired four MODIS datasets, from both the AQUA and TERRA satellites, to use in our analysis. The MOD03 product gives the 1km geolocation fields, as described by the LAADS DAAC website, last accessed on January 5, 2023, at https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD03. The MOD06_L2 product give the MODIS cloud retrievals, as described by the LAADS DAAC website, last accessed on January 5, 2023, at https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD06_L2. The near-surface concentration of chlorophyll-a is calculated from MODIS reflectances and stored in a level 3 mapped product, as described in "Ocean Level-3 Standard Mapped Image Products June 4, 2010," last accessed on January 5, 2023, at https://oceancolor.gsfc.nasa.gov/docs/format/Ocean_Level-3_SMI_Products.pdf. The short wave albedo comes from the CERES instrument, as described in "CERES_SSF_Terra-Aqua_Edition4A Data Quality Summary (3/3/2022)," last accessed on January 5, 2023, at https://ceres.larc.nasa.gov/documents/DQ_summaries/CER_SSF_Terra-Aqua_Edition4A.pdf. 2. Methods for processing the data: We analyzed the summer seasons in the Southern Ocean. A summer season is considered to be a consecutive November, December, January, and February. We analyzed data for four summer seasons, 2015-2016, 2016-2017, 2017-2018, and 2018-2019. We selected an area in the Southern Ocean defined by a latitude-longitude box with a South West corner of -76 Lat 40 Lon and a North East corner of -45 Lat 152 Lon. The MODIS granule must at least touch the inside of this latitude-longitude box. We divide the latitude-longitude region into a 1 degree latitude by 2 degree longitude grid. We subset the data from our four datasets inside each grid box, and calculate mean values and distributions of the cloud retrievals, chlorophyll-a, and shortwave albedo. This is called the "Histogram Method." These are the "Histogram Method" steps. First, read in a mod03 and mod06 file. Using the variables cloud_effective_radius (re), cloud_top_temperature (temp), and cloud_optical_thickness (tau), we calculate the cloud particle number density (Nd). This calculation is only performed on pixels where cloud_effective_radius and cloud_water_path (lwp) are greater than 0 and cloud_phase is liquid. For our analysis, the MODIS pixels must meet the following conditions, and are called “good data.” The cloud_effective_radius must be between 0 and 50 microns. Cloud_water_path must be less than 300.0 g/m2 and have a liquid phase. Sensor zenith angle must be less than 30 degrees and solar zenith angle less than 60 degrees. Next, we construct the lat-lon grid system with a 2 degrees longitude by 1 degree latitude grid box size. We gather the data in each grid box. To calculate data means and distributions in a grid box, we require 100 pixels at 5km resolution to be in the grid box and we require 10 pixels of “good data” to be in the grid box. We require less than 10% of the cloud_top_temperatures in the grid box to be less than -20C. In addition, we require the sensor_zenith_angle to be less than 30 degrees and the solar_zenith_angle to be less than 60 degrees. At this point we create histograms of the data in the grid box. The following are the lower and upper size limits and bin widths of the distributions. For LWP, 0 to 300 with bin width of 20 g/m2. For Re, 0 to 30 with bin width of 2 microns. For optical depth (tau), 0 to 50 with bin width of 2.5. For number density (Nd), 0 to 300 with bin width of 10 per cubic cm. For temperature, -65 to 20 Celsius with bin width of 2.0 degrees. The phase flag has values of 0=missing, 1=clear, 2=liquid, 3=ice, and 4=undetermined. We also calculate mean values of the liquid phase pixels in the grid box for Nd between 0 and 300 per cm3, Re greater than 0, and lwp less than 250 g/m2. These histograms and means are written out to a file for each grid box with qualified pixels. It is these files for each grid box that are used in the statistical results of the paper. 3. Instrument- or software-specific information needed to interpret the data: Step 1: Aquire MOD03 and MOD06_L2 MODIS data, MODIS Ocean Color Level-3 mapped chlor-a, and CERES SSF Edition4A. Step 2: Create netcdf files of the modis data within each 1x2 degree gridbox of the modis granule. These netcdf files will be called histogram files. Run the IDL code read_mod06_clouds_sb_test.pro Output filename example: MYD06_L2.A2018027.1320.061.2018030175749_lat_-62_lon_16_histo.cdf Step 3: Append chlor-a variable to each histogram file. Run the IDL code match_ocean_histo.pro Step 4: Append CERES sw albedo to each histogram file. Run the IDL code read_ceres_ssf.pro Step 5: Accumulate all the histogram files for each month into one big monthly historgram file. This makes the data easier to work with because IDL doesn't have to open and close so many files. Run the IDL code plot_modis_histograms.pro This code normalizes the short wave albedo to 45 degree solar zenith angle Step 6: Create monthly mean values. Run the IDL code plot_modis_hist_daily_monthly_means.pro Step 7: Create other plots. Run the IDL code plot_modis_hist_full_dataset.pro 4. Standards and calibration information, if appropriate: None 5. Environmental/experimental conditions: None 6. Describe any quality-assurance procedures performed on the data: None 7. People involved with sample collection, processing, analysis and/or submission: None ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: [FILENAME] ----------------------------------------- Not Applicable. The IDL code files are internally documented. 1. Number of variables: 2. Number of cases/rows: 3. Variable List A. Name: [variable name] Description: [description of the variable] Value labels if appropriate B. Name: [variable name] Description: [description of the variable] Value labels if appropriate 4. Missing data codes: Code/symbol Definition Code/symbol Definition 5. Specialized formats of other abbreviations used