Detection of a tropospheric ozone anomaly using a newly developed ozone retrieval algorithm for an up-looking infrared interferometer

Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): D06304, doi:10.1029/2008JD010270.On 2 June 2003, the Baltimore Bomem Atmospheric Emitted Radiance Interferometer (BBAERI) recorded an infrared spectral time series indicating the presence of a tropospheric ozone anomaly. The measurements were collected during an Atmospheric Infrared Sounder (AIRS) validation campaign called the 2003 AIRS BBAERI Ocean Validation Experiment (ABOVE03) conducted at the United States Coast Guard Chesapeake Light station located 14 miles due east of Virginia Beach, Virginia (36.91°N, 75.71°W). Ozone retrievals were performed with the Kurt Lightner Ozone BBAERI Retrieval (KLOBBER) algorithm, which retrieves tropospheric column ozone, surface to 300 mbar, from zenith-viewing atmospheric thermal emission spectra. KLOBBER is modeled after the AIRS retrieval algorithm consisting of a synthetic statistical regression followed by a physical retrieval. The physical retrieval is implemented using the k-Compressed Atmospheric Radiative Transfer Algorithm (kCARTA) to compute spectra. The time series of retrieved integrated ozone column on 2 June 2003 displays spikes of about 10 Dobson units, well above the error of the KLOBBER algorithm. Using instrumentation at Chesapeake Light, satellite imaging, trace gas retrievals from satellites, and Potential Vorticity (PV) computations, it was determined that these sudden increases in column ozone likely were caused by a combination of midtropospheric biomass burning products from forest fires in Siberia, Russia, and stratospheric intrusion by a tropopause fold occurring over central Canada and the midwestern United States.NASA for its support through grant NAG5- 1156-7 for AIRS Validation and grant NNG04GN42G for development of AIRS trace gas products, and through a subcontract with JPL on the AIRS Project prime contract NAS7-03001 for continuing optimization and validation of AIRS trace gas products.

Ozone concentration profile retrieval from ground-based high-resolution thermal infrared spectra.

Simulations of the Atmospheric Emitted Radiance Interferometer (AERI), a ground-based, high-resolution infrared detection system, are used to produce retrieved atmospheric ozone concentration profiles. A line-by-line transmittance model, FASCD3P, is used for the forward model and a maximum likelihood retrieval scheme is employed for the inverse model. An a priori data set consisting of 83 midlatitude winter ozone sondes is used to condition the inversion. Three iterations are required to reduce the radiance residuals to less than the instrument noise. The retrieval accuracy below 300mb is within 25% of truth. Above 300mb, variance within the a priori data is the dominant source of retrieval error. This is due to the number of retrieved layers (27) being higher than the amount of independent information present in the radiance spectra (approximately 4) so much of the retrieval information above 300mb comes from the a priori data

Emissivity and reflection model for calculating unpolarized isotropic water surface-leaving radiance in the infrared. I: Theoretical development and calculations

Although published sea surface infrared (IR) emissivity models have gained widespread acceptance for remote sensing applications, discrepancies have been identified against field observations obtained from IR Fourier transform spectrometers at view angles approximately > 40 degrees. We therefore propose, in this two-part paper, an alternative approach for calculating surface-leaving IR radiance that treats both emissivity and atmospheric reflection in a systematic yet practical manner. This first part presents the theoretical basis, development, and computations of the proposed model

Developments in ocean infrared emissivity/reflection modeling

Much progress has been made toward modeling the spectral infrared (IR) emissivity of wind-roughened water surfaces. Existing emissivity models explicitly calculate the ensemble mean emissivity of the wavy surface for a given observer zenith angle and local wind speed. However, field observations of emissivity spectra obtained by the Marine Atmospheric Emitted Radiance Interferometer (M-AERI) suggest that emissivity models are deficient at larger view angles and wind speeds. In this preliminary work, we attempt to identify and explain the sources of error in these models using M-AERI data acquired at sea (e.g., during AEROSE 2004). Our results demonstrate that proper accounting for non-unity surface emissivity must ultimately include appropriate specification of the reflected IR radiation field, especially in window channels. Atmospheric IR surface reflectance becomes important for high accuracy applications (e.g., sea surface skin temperature), that rely on window channel observations at zenith angles 45 deg. Lookup tables of ensemble mean effective incidence angle, rather than mean emissivity, are generated using different published mean square slope PDF models. These results roughly agree with recent findings. Lookup tables of ensemble mean local zenith incidence angle are also generated. This new approach to emissivity/reflection modeling will be refined and validated against M-AERI field data from several previous oceanographic cruises, and will be the subject of a forthcoming paper

Radiance and Jacobian intercomparison of radiative transfer models applied to HIRS and AMSU channels

International audienceThe goals of this study are the evaluation of current fast radiative transfer models (RTMs) and line-by-line (LBL) models. The intercomparison focuses on the modeling of 11 representative sounding channels routinely used at numerical weather prediction centers: 7 HIRS (High-resolution Infrared Sounder) and 4 AMSU (advanced microwave sounding unit) channels. Interest in this topic was evident by the participation of 24 scientists from 16 institutions. An ensemble of 42 diverse atmospheres was used and results compiled for 19 infrared models and 10 microwave models, including several LBL RTMs. For the first time, not only radiances but also Jacobians (of temperature, water vapor, and ozone) were compared to various LBL models for many channels. In the infrared, LBL models typically agree to within 0.05-0.15 K (standard deviation) in terms of top-of-the-atmosphere brightness temperature (BT). Individual differences up to 0.5 K still exist, systematic in some channels, and linked to the type of atmosphere in others. The best fast models emulate LBL BTs to within 0.25 K, but no model achieves this desirable level of success for all channels. The ozone modeling is particularly challenging. In the microwave, fast models generally do quite well against the LBL model to which they were tuned. However, significant differences were noted among LBL models. Extending the intercomparison to the Jacobians proved very useful in detecting subtle or more obvious modeling errors. In addition, total and single gas optical depths were calculated, which provided additional insight on the nature of differences