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EOS MLS Data


The EOS MLS data describe a piecewise linear representation of vertical profiles of gas phase chemical abundances, temperature, and cloud ice density. The vertical coordinate is log10 (atmospheric pressure) with, typically, 6 breakpoints per decade pressure (. . ., 3.16, 2.15, 1.47, 1.00, 0.68, 0.46, 0.32 hPa, . . .). The vertical range of usefulness depends upon the specific data product and the data version. Some of the MLS observations are "noisy" in nature, with the consequence that negative values are reported - these should not be masked or ignored, as failure to include them (in the averages that are required of these data) will lead to an artificial positive bias.

It is essential that users of MLS data understand and apply the data quality and status indicators available in the data files. These are described, for each released version of MLS data, by MLS Data Quality Documents. These documents also describe the expected precision, resolution, and known artifacts of each product for that data version - and improvement priorities for future data versions. They are available for MLS Version 2.2 (v2.2) data, the first publicly released version, from the MLS Data Documentation page.

The MLS team very strongly encourages users to contact us with any questions on the data and if you find features that seem unreasonable. Although we have done our best to produce a reasonably sound data set within one year of becoming operational, we have no misconceptions that all the data artifacts have been identified. Feedback from users is of great benefit for improving the quality of the next data version. We also welcome, and encourage, users to just inform us that you are using MLS data. By knowing who you are, we can contact you with new data issues as we find them (the MLS team inspects all daily data, and reviews the findings on a weekly basis). Contacts can be made via e-mail to data@mls.jpl.nasa.gov or to the individual(s) listed in the table below.

MLS v2.2 data are available from the NASA Goddard Space Flight Center Earth Sciences (GES) Data and Information Services Center (DISC). The following data resources are available at the MLS website:


The v2.2 standard data products and the status, useful vertical range and MLS contact person for each product is given in the following table. All product data files also contain values for the column above the tropopause determined from MLS temperature using the WMO tropopause definition. The temperature file also contains the inferred tropopause pressure.

EOS MLS Version 2.2 Data
(Products with a * require significant averaging over most
or all of their vertical range in order to obtain a useful signal-to-noise ratio.)
product useful vertical range / hPa MLS contact
*BrO 10 - 3.2 Nathaniel Livesey
livesey@mls.jpl.nasa.gov
ClO 100 - 1 Michelle Santee
mls@mls.jpl.nasa.gov
CO 215 - 0.0046 upper trop. / lower strat.: Nathaniel Livesey
livesey@mls.jpl.nasa.gov
upper strat. / mesosphere: Hugh Pumphrey
H.C.Pumphrey@ed.ac.uk
geopotential height 316 - 0.001 Michael Schwartz
michael@mls.jpl.nasa.gov
H2O 316 - 0.002 troposphere: Bill Read
bill@mls.jpl.nasa.gov
stratosphere: Alyn Lambert
lambert@mls.jpl.nasa.gov
HCl 100 - 0.15 Lucien Froidevaux
lucien@mls.jpl.nasa.gov
HCN 10 - 1 Hugh Pumphrey
H.C.Pumphrey@ed.ac.uk
HNO3 215 - 3.2 Michelle Santee
mls@mls.jpl.nasa.gov
*HO2 22 - 0.032 Herb Pickett
hmp@jpl.nasa.gov
*HOCl 22 - 2.2 Lucien Froidevaux
lucien@mls.jpl.nasa.gov
Ice water content 215 - 68 Dong Wu
dwu@mls.jpl.nasa.gov
Jonathan Jiang
jonathan@mls.jpl.nasa.gov
Ice water path N/A Dong Wu
dwu@mls.jpl.nasa.gov
Jonathan Jiang
jonathan@mls.jpl.nasa.gov
N2O 100 - 0.1 Alyn Lambert
lambert@mls.jpl.nasa.gov
O3 215 - 0.022 troposphere: Nathaniel Livesey
livesey@mls.jpl.nasa.gov
stratosphere: Lucien Froidevaux
lucien@mls.jpl.nasa.gov
OH 32 - 0.0032 Herb Pickett
hmp@jpl.nasa.gov
Relative Humidity 316 - 0.002 Bill Read
bill@mls.jpl.nasa.gov
SO2 215 - 10 Bill Read
bill@mls.jpl.nasa.gov
Temperature 316 - 0.001 Michael Schwartz
michael@mls.jpl.nasa.gov

In addition to the standard data products, the MLS algorithms also produce data for many "diagnositic" products. A typical "diagnostic" product is a product that is retrieved from a different spectral range than a standard product.


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