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Format & Content

Monthly Product (08_M3) File Format Basics 

Figures showing MODIS Products are stored in Hierarchical Data Format (HDF)

MODIS Atmosphere Monthly (08_M3) product files are stored in Hierarchical Data Format (HDF). HDF is a multi-object file format for sharing scientific data in multi-platform distributed environments. HDF files should only be accessed through HDF library subroutine and function calls, which can be downloaded from the HDF web site.

Each of the global gridded statistical fields within the HDF file is stored as a Scientific Data Set (SDS). L3 Atmosphere products contain hundreds of 1°×1° global gridded Scientific Data Sets (SDSs) or statistics derived from up to 31 consecutive days of the Daily (08_D3) product.  (The Daily product is derived from L2 products of Aerosol (04_L2), Water Vapor (05_L2), Cloud (06_L2), and Atmospheric Profile (07_L2)). The grid domain or size is 360x180 pixels, which corresponds to 360 degrees of longitude and 180 degrees of latitude.

There are a number of general L3 Monthly algorithm characteristics:

  • Only the L3 Daily files are used as input. (Greatly improves algorithm efficiency.)
  • L3 Daily and L3 Multiday HDF files use an identical grid, SDS dimensions, and histogram bin definitions. (This is an algorithm requirement.)
  • There is no “valid range” check, only “Fill_Value” L3 Daily (08_D3) grid cells are universally excluded from L3 Multiday statistics.
  • One of three weighting schemes are used to compute Monthly statistics from Daily statistics:
    1. Unweighted, where each L3 Daily grid cell is given equal weight in the L3 Multiday mean. This is a simple time-averaged mean, useful for computing such things as temperature averages over a multi-day period.
    2. Pixel Count Weighted, where each L3 Daily grid cell is weighted by the valid L2 Pixel Counts in that grid. This is a count-averaged mean that ensures computed means match means computed from histograms -- useful for example, for cloud optical properties.
    3. Min Num Days (Aerosol derived products only), where each L3 Daily grid cell is given equal weight in the L3 Multiday mean, however there is a requirement that at least three (3) days have a valid data value. This is a simple time-averaged mean, but requires at least 3 days to have valid data. This is a new weighting scheme implemented in Collection 061 (6.1), it's useful for computing Aerosol statistics over a monthly period, which minimized cloud and snow/ice contamination of the Monthly Aerosol statistics.

Monthly Product File (08_M3) Parameter List (primary parameters only)

Parameters derived from the L2 Aerosol (04_L2) Product

Aerosol Combined Ocean and Land

Scattering_Angle Derived from the 04_L2 SDS "Scattering_Angle".
Aerosol_Optical_Depth_Land_Ocean Derived from the 04_L2 SDS "Optical_Depth_Land_And_Ocean". Note that the land part of this SDS is taken from the 04_L2 SDS Corrected_Optical_Depth_Land at 0.55 microns and the ocean part of this SDS is taken from the 04_L2 SDS Effective_Optical_Depth_Best_Ocean (a parameter that is not propagated into L3 by itself).

Aerosol Land Only 

Aerosol_Optical_Depth_Land Derived from the 04_L2 SDS "Corrected_Optical_Depth_Land". Three solutions (computed at 0.47, 0.55, and 0.66 microns) are retained. Note that this parameter group contains three joint histograms for optical depth computed using 0.47 vs. 0.55 microns, 0.47 vs. 0.66 microns, and 0.55 vs. 0.66 microns.

Aerosol Ocean Only

Aerosol_Optical_Depth_Average_Ocean Derived from the 04_L2 SDS "Effective_Optical_Depth_Average_Ocean".
Aerosol_Optical_Depth_Small_Ocean Derived from the 04_L2 SDS "Optical_Depth_Ratio_Small_Ocean_0.55micron". Only the L2 "best" solution is retained in L3. The "average" solution is computed in L2 but not propagated to L3.
Aerosol_PSML003_Ocean Derived from the 04_L2 SDS "Cloud_Condensation_Nuclei_Ocean".
Aerosol_Optical_Depth_by_models_ocean Derived from the 04_L2 SDS "Optical_Depth_by_models_ocean". The parameter has solutions at 9 models.
AEROSOL: DEEP BLUE ()
Deep_Blue_Aerosol_Optical_Depth_Land Derived from the 04_L2 SDS "Deep_Blue_Aerosol_Optical_Depth_Land ".
AOD_550_Dark_Target_Deep_Blue_Combined Derived from the 04_L2 SDS "". Combines Dark Target and Deep Blue Aerosol.
Parameters derived from the L2 Water Vapor (05_L2) Product

Water Vapor

Water_Vapor_Near_Infrared_Clear
Water_Vapor_Near_Infrared_Cloud
Derived from the 05_L2 SDS "Water_Vapor_Near_Infrared" and aggregated into a clear or cloud category from the 05_L2 SDS "Quality_Assurance_Near_Infrared".
Parameters derived from the L2 Cloud (06_L2) Product

Cirrus Detection

Cirrus_Reflectance
Contrail_Reflectance
Derived from the 06_L2 SDS "Cirrus_Reflectance" and aggregated into a cirrus or contrail category from the 06_L2 SDS "Cirrus_Reflectance_Flag".
Cirrus_Fraction_SWIR
Contrail_Fraction_SWIR
Derived from the 06_L2 SDS "Cirrus_Reflectance_Flag" and aggregated into a cirrus or contrail category from the 06_L2 SDS "Cirrus_Reflectance_Flag". This flag differentiates between BadData, Non-Cirrus, Cirrus, or Contrail at 1km resolution.

Cloud Top Properties

Cloud_Top_Temperature
Cloud_Top_Temperature_Day
Cloud_Top_Temperature_Night
Derived from the 06_L2 SDS "Cloud_Top_Temperature" and aggregated into Day or Night categories from the 06_L2 SDS "Cloud_Mask_5km".
Cloud_Top_Pressure
Cloud_Top_Pressure_Day
Cloud_Top_Pressure_Night
Derived from the 06_L2 SDS "Cloud_Top_Pressure" and aggregated into Day or Night categories from the 06_L2 SDS "Cloud_Mask_5km".
Cloud_Top_Height
Cloud_Top_Height_Day
Cloud_Top_Height_Night
Derived from the 06_L2 SDS "Cloud_Top_Height" and aggregated into Day or Night categories from the 06_L2 SDS "Cloud_Mask_5km".
Cloud_Effective_Emissivity
Cloud_Effective_Emissivity_Day
Cloud_Effective_Emissivity_Night
Derived from the 06_L2 SDS "Cloud_Effective_Emissivity" and aggregated into Day or Night categories from the 06_L2 SDS "Cloud_Mask_5km".
Cloud_Phase_Infrared
Cloud_Phase_Infrared_Day
Cloud_Phase_Infrared_Night
Derived from the 06_L2 SDS "Cloud_Phase_Infrared" and aggregated into Day or Night categories from the 06_L2 SDS "Cloud_Mask_5km". The bins of the Histogram Counts statistic corresponds to clear (1st bin), liquid water clouds (2nd bin), ice clouds (3rd bin), undetermined phase clouds (4th bin). (Note there are no mixed phase clouds in C6 and later).
Cloud_Fraction
Cloud_Fraction_Day
Cloud_Fraction_Night
This is the primary L3 Cloud Fraction parameter from Cloud Mask. This is derived from the 06_L2 SDS "Cloud_Fraction" and aggregated into Day or Night categories using the day/night flag from the 06_L2 SDS "Cloud_Mask_5km".
Cirrus_Fraction_Infrared
High_Cloud_Fraction_Infrared
Derived from the Cirrus and High Cloud Flags in the 06_L2 SDS "Quality_Assurance_5km". The numbers computed are actually ratios of cirrus clouds (or high clouds) to all clouds. They are not true cloud fractions, where clear sky pixels are accounted for in the denominator. (Note that in the upcoming Collection 006, these numbers will change to true cloud fractions where clear sky pixels will be accounted for in the denominator.)

Cloud Optical Properties

Cloud_Optical_Thickness_Liquid
Cloud_Optical_Thickness_Ice
Cloud_Optical_Thickness_Undetermined
Cloud_Optical_Thickness_Combined
Derived from the 06_L2 SDS "Cloud_Optical_Thickness" and aggregated into Cloud Phase categories (liquid water, ice, undetermined, & combined) using the Primary Cloud Retrieval Phase Flag from the 06_L2 SDS "Quality_Assurance_1km". Note that the liquid water and ice cloud parameters contain joint histograms vs. Cloud Effective Radius, vs. Cloud Top Temperature, vs. Cloud Top Pressure, & vs. Cloud Effective Emissivity (for ice clouds only)
Cloud_Effective_Radius_Liquid
Cloud_Effective_Radius_Ice
Cloud_Effective_Radius_Undetermined
Derived from the 06_L2 SDS "Cloud_Effective_Radius" and aggregated into Cloud Phase categories (liquid water, ice, undetermined) using the Primary Cloud Retrieval Phase Flag from the 06_L2 SDS "Quality_Assurance_1km". Note that the liquid water and ice cloud parameters contain joint histograms vs. Cloud Top Temperature & vs. Cloud Top Pressure
Cloud_Water_Path_Liquid
Cloud_Water_Path_Ice
Cloud_Water_Path_Undetermined
Derived from the 06_L2 SDS "Cloud_Water_Path" and aggregated into Cloud Phase categories (liquid water, ice, undetermined) using the Primary Cloud Retrieval Phase Flag from the 06_L2 SDS "Quality_Assurance_1km".
Cloud_Fraction_Liquid
Cloud_Fraction_Ice
Cloud_Fraction_Undetermined
Cloud_Fraction_Combined
This is the Cloud Fraction (really the successful cloud retrieval fraction) from the Cloud Optical Properties retrieval aggregated into Cloud Phase categories: liquid water, ice, undetermined, combined from the 06_L2 SDS "Quality_Assurance_1km". The SDS's are an interpretation of the Primary Cloud Retrieval Phase Flag (cloud optical properties decision tree outcome) determined from the Cloud Mask, IR and SWIR tests, which is read from the 06_L2 SDS "Quality_Assurance_1km".
Parameters derived from the L2 Profiles (07_L2) Product

Atmosphere Profile

Total_Ozone Derived from the 07_L2 SDS "Total_Ozone".
Total_Totals Derived from the 07_L2 SDS "Total_Totals".
Lifted_Index Derived from the 07_L2 SDS "Lifted_Index".
K_Index Derived from the 07_L2 SDS "K_Index".
Atmospheric_Water_Vapor
Atmospheric_Water_Vapor_Low
Atmospheric_Water_Vapor_High
Derived from the 07_L2 SDS's "Water_Vapor, "Water_Vapor_Low", and "Water_Vapor_High", respectively. The keywords "Low" and "High" refer to the lower and higher portions of the atmospheric column. Note that the parameter "Water Vapor" is also refered to as "Precipitable Water".

Monthly Product (08_M3) Statistic List 

A number of statistical summaries are computed, depending on the science parameter being considered. Statistics for a given Level-2 measurement might include:

Simple Statistics of the Mean

  • Mean_Mean
  • Mean_Min
  • Mean_Max
  • Mean_Std

Mean of the Standard Deviation

  • Std_Deviation_Mean

QA Weighted Statistics

  • QA_Mean_Mean
  • QA_Mean_Std
  • QA_Mean_Min
  • QA_Mean_Max
  • QA_Std_Deviation_Mean

Histograms of the quantity within each grid box

  • Histogram_Counts

Histograms of the confidence placed in each measurement

  • Confidence_Histograms

Mean and Standard Deviation of the Fraction of pixels that satisfy some condition (e.g. cloudy, clear)

  • FMean
  • FStd

Total number of observations (pixels) within each grid box

  • Pixel_Counts

Parameters of Log-Normal Distributions

  • Log_Mean_Mean
  • Log_Mean_Std
  • Log_Mean_Min
  • Log_Mean_Max
  • Log_Std_Deviation_Mean

Parameters of QA Weighted Log-Normal Distributions

  • QA_Log_Mean_Mean
  • QA_Log_Mean_Std
  • QA_Log_Mean_Min
  • QA_Log_Mean_Max
  • QA_Log_Std_Deviation_Mean

Regressions and/or Histograms derived from comparing one science parameter to another, statistics may be computed for a subset that satisfies some condition

  • Joint_Histogram_vs_Effect_Radius
  • Joint_Histogram_vs_Temperature
  • Joint_Histogram_vs_Emissivity
  • Joint_Histogram_47vs55
  • Joint_Histogram_47vs66
  • Joint_Histogram_55vs66

Monthly Product (08_M3) Statistic Computation Details 

Below are more details on the computation of each statistic:

Mean

For the multiday product, assume that x1, x2, ..., xn represent the L3 Daily value of a parameter over a 1 x 1 degree grid box, wi is the weighting factor (1 for the unweighted case and the pixel count value for the pc-weighted case), then the simple statistics are defined as:

In these equations, (1) will be referred to as the 'regular' mean, (2) not computed in the multiday, (3) as the regular standard deviation, (4) not computed in the multiday, (5) as the minimum, and (6) as the maximum.

The simple statistics also include daily log regular mean, log standard deviation, log QA mean, and log QA standard deviation. These log quantities are calculated as shown in equations (1) and (3), except that x1, x2, ..., xn are replaced by their logarithms.

The histograms and joint histograms report the counts of the pixels falling into predetermined numerical intervals.

The pixel counts are used to represent the number of pixels for the parameters which do not have QA flags, while the confidence-histograms-counts are used to represent the number of counts for each parameter that falls within each QA bin (e.g., questionable, good, very good, and total).