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Bedka, Sarah T.

Publications and source records attributed to Bedka, Sarah T..

CERES MODIS Cloud Product Retrievals for Edition 4--Part I: Algorithm Changes

The Edition 2 (Ed2) cloud property retrieval algorithm system was upgraded and applied to the MODerate-resolution Imaging Spectroradiometer (MODIS) data for the Clouds and the Earth's Radiant Energy System (CERES) Edition 4 (Ed4) products. New calibrations for solar channels and the use of the 1.24-μm channel for cloud optical depth (COD) over snow improve the daytime consistency between Terra and Aqua MODIS retrievals. Use of additional spectral channels and revised logic enhanced the cloud-top phase retrieval accuracy. A new ice crystal reflectance model and a CO₂-channel algorithm retrieved higher ice clouds, while a new regional lapse rate technique produced more accurate water cloud heights than in Ed2. Ice cloud base heights are more accurate due to a new cloud thickness parameterization. Overall, CODs increased, especially over the polar (PO) regions. The mean particle sizes increased slightly for water clouds, but more so for ice clouds in the PO areas. New experimental parameters introduced in Ed4 are limited in utility, but will be revised for the next CERES edition. As part of the Ed4 retrieval evaluation, the average properties are compared with those from other algorithms and the differences between individual reference data and matched Ed4 retrievals are explored. Part II of this article provides a comprehensive, objective evaluation of selected parameters. More accurate interpretation of the CERES radiation measurements has resulted from the use of the Ed4 cloud properties.

54 ENVIRONMENTAL SCIENCES↗

Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

Cloud properties play a critical role in climate change. Monitoring cloud properties over long time periods is needed to detect changes and to validate and constrain models. The Clouds and the Earth's Radiant Energy System (CERES) project has developed several cloud datasets from Aqua and Terra MODIS data to better interpret broadband radiation measurements and improve understanding of the role of clouds in the radiation budget. The algorithms applied to MODIS data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new cloud climate data record. These datasets can be useful for a variety of studies. This paper presents results of the MODIS and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.

Minnis, Patrick↗

Estimating Contrail Climate Effects from Satellite Data

An automated contrail detection algorithm (CDA) is developed to exploit six of the infrared channels on the 1-km MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites. The CDA is refined and balanced using visual error analysis. It is applied to MODIS data taken by Terra and Aqua over the United States during 2006 and 2008. The results are consistent with flight track data, but differ markedly from earlier analyses. Contrail coverage is a factor of 4 less than other retrievals and the retrieved contrail optical depths and radiative forcing are smaller by approx.30%. The discrepancies appear to be due to the inability to detect wider, older contrails that comprise a significant amount of the contrail coverage. An example of applying the algorithm to MODIS data over the entire Northern Hemisphere is also presented. Overestimates of contrail coverage are apparent in some tropical regions. Methods for improving the algorithm are discussed and are to be implemented before analyzing large amounts of Northern Hemisphere data. The results should be valuable for guiding and validating climate models seeking to account for aviation effects on climate.

Minnis, Patrick↗