This data set is only available for a restricted user group, please contact us if you want to access these data.
RESTRICTED only accessable in CEN/MPI net or via CliSAP login What does that mean?
MODIS stands for MODerate resolution Imaging Spectroradiometer. This sensor, equipped with over 30 spectral channels from the visible into the infrared frequency range operates from aboard the EOS-TERRA and EOS-AQUA satellites since 2000 and 2002, respectively. Thanks to its high spectral resolution and the large number of different channels a large number of different atmospheric parameters can be retrieved. Here we refer to the columnar water vapor content and precipitable water content (PWC) data sets.
Similar to the data sets of the MODIS temperature profile data set the water vapor content and PWC data sets are derived by means of a statistical regression analysis. Vertical profiles of temperature, moisture and ozone measured globally by radiosondes are used to compute MODIS infrared band radiances using a radiative transfer / transmission model. A regression analysis between the computed radiances and the measured atmospheric profiles is carried out to derive the regression coefficients. These are subsequently applied to the actual MODIS radiance measurements to retrieve the profiles of atmospheric parameters - here the humidity which is subsequently vertically integrated to obtain estimates of the columnar water vapor content and PWC.
In addition, one can exploit that the degree with which near infrared (NIR) solar radiation reflected at the Earth's surface is absorbed in the atmosphere is a function of the atmospheric water vapor content. Therefore, radiances measured by the 5 MODIS NIR bands centered around the water vapor absorption line at 0.94 µm are used to derive the NIR columnar water vapor content with a look-up table procedure. Elements of the look-up table were pre-calculated using a radiative transfer / transmittance model and a spectroscopic data base.
This is part of the level-3 MOD08/MYD08 data set derived from level-2 MOD05/MYD05 data of the MODIS Collection 6.1 product family, downloaded August 2018.
Last update of data set at ICDC: March 15, 2019
Period and temporal resolution:
Coverage and spatial resolution:
The offered water vapor content data contain as a measure of uncertainty on the one hand the standard deviation of all level-2 grid cells used for the computation of the Level-3 product.
On the other hand, for some of the products so-called "quality assessed" level-3 data sets are offered. These are the result of a weighted averaging of the level-2 data where the confidence flags of the level-2 products are used as weights (in some modified way).
The distribution of these confidence intervals (from the level-2 data) is illustrated in the level-3 data via quality flag maps which contain the global distribution of the numbers of questionable, good, very good, and total useful level-2 pixels per level-3 grid cell.
This data set is from Collection 6.1 of the MODIS product family. Hence a substantial number inconsistencies and potential retrieval problems, which have been identified in the past product families (4, 5), has been taken care of in this newest MODIS product family (6). The main improvement in this newest release 6.1 over release 6.0 is the mitigation of the impact of electronic cross-talk between adjacent atmospheric frequency bands.
We refer to the documents listed in the References.
Please cite the data as follows:
Platnick, S., et al., 2017. MODIS Atmosphere L3 Daily Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: dx.doi.org/10.5067/MODIS/MOD08_D3.061, last access date: 5/3/2019
(if MODIS EOS-AQUA data are used accordingly: dx.doi.org/10.5067/MODIS/MYD08_D3.061)
and acknowledge the source of your data download as:
Original MODIS collection 6.1 water vapor data provided in hdf format by https://ladsweb.modaps.eosdis.nasa.gov/ were downloaded in netCDF file format from the Integrated Climate Data Centre (ICDC), CliSAP, University of Hamburg, Hamburg, Germany, http://icdc.cen.uni-hamburg.de