Title:		Temperature and water vapor mixing ratio profiles retrieved from the AERI.
Location:	Orange Site during the PERDIGAO Field Campaign
Lat/Lon:	39.713 degN, -7.736 degE
Date updated: 	2 March 2018
Contacts:       Dave Turner, NOAA (dave.turner@noaa.gov)
                Petra Klein, Univ Oklahoma (pkklein@ou.edu)

--- Background

The AERIoe algorithm (Turner and Loehnert 2014, Turner and Blumberg 2018) retrieves profiles of temperature and water vapor mixing ratio, together with cloud properties for a single-layer cloud (i.e., LWP, effective radius), from AERI-observed infrared radiance spectrum.  The data can be used to characterize the evolution of the planetary boundary layer and boundary layer clouds.  

This dataset was collected at the "Orange Site" in Portugal during the PERDIGAO 2017 field campaign.  The AERIoe retrieval was run at 15-minute resolution, but retrievals can be performed at the maximum temporal resolution of the AERI instrument (order 30 s) -- if this higher temporal resolution is desired, please contact Dave Turner.

This is a physical-iterative retrieval method.  The retrieval of thermodynamic profiles from spectral infrared radiance observations is an ill-posed problem, and thus constraints need to be included in the retrieval algorithm to provide physically plausible results.  Here, we use a climatology of 1571 radiosonde profiles collected Lisbon Portugal during the late spring/early summer as our prior information in an optimal estimation framework.  As the method uses an optimal estimation framework, a full error covariance matrix of each solution is included in the output file.  The 1-sigma uncertainty of each retrieved variable, which is derived from the error covariance matrix, is included for each scientific field and is named "sigma_X", where "X" is the name of the scientific field (e.g., 'temperature').  The information content in the AERI observations, which is in the "dfs" field, on the thermodynamic profiles is primarily concentrated in the lowest 3 km or up to cloud base; the retrieved data should not be used above that level (or used with caution).

There is an overall "qc_flag" field that is set when a retrieval should not be trusted.  However, the logic that sets this flag didn't work correctly, and it should not be used.  Instead, consider all retrievals that have a value for "converged_flag" greater than 0 and less than 9 as valid.  If you have any questions, contact Dave Turner.

Normally, numerical weather prediction (NWP) model output is used as an additional observation in the retrieval in order to constrain the middle-to-upper troposphere (i.e., above 4 km AGL).  However, I did not have NWP output handy, so I used temporally interpolated radiosonde observations from the Orange Site above 4 km for this purpose.

--- Version information

This is Release_2_7 of the AERIoe algorithm.  It has the same basic characteristics as Release_2_x.


--- Details on the AERI

The AERI (Atmospheric Emitted Radiance Interferometer) is a hardened, operational infrared spectrometer that was developed at the University of Wisconsin - Madison for the Department of Energy Atmospheric Radiation Measurement (ARM) program.  Details of the AERI, including how it is calibrated, are provided by Knuteson et al. (2004 a,b).  

The AERI used in this field campaign was part of the Collaborative Lower Atmospheric Mobile Profiling System (CLAMPS-1; Wagner et al. 2018), which was developed by the University of Oklahoma and the NOAA National Severe Storms Laboratory.  The AERIoe retrievals were performed by Dave Turner.


--- References

Knuteson, R.O., and coauthors, 2004: Atmospheric Emitted Radiance Interferometer. Part 1: Instrument design. J. Atmos. Oceanic Technol., 21, 1763-1776.                

Knuteson, R.O., and coauthors, 2004: Atmospheric Emitted Radiance Interferometer. Part 2: Instrument performance. J. Atmos. Oceanic Technol., 21, 1777-1789.                

Turner, D.D., and U. Loehnert, 2014: Information content and uncertainties in thermodynamic profiles and liquid cloud properties retrieved from the ground-based Atmospheric Emitted Radiance Interferometer (AERI). J. Appl. Meteor. Clim., 53, 752-771, doi:10.1175/JAMC-D-13-0126.1.

Turner, D.D., and W.G. Blumberg, 2018: Improvements to the AERIoe thermodynamic profile retrieval algorithm. IEEE Selected Topics Appl. Earth Obs. Remote Sens., submitted.

Wagner, T.J., P.M. Klein, and D.D. Turner, 2018: A new generation of ground-based mobile platforms for active and passive profiling of the boundary layer. Bull. Amer. Meteor. Soc., submitted

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