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Reconstructions Improvements Using Iteratively Adjusted Statistics, Demonstrated Using Model-Output Annual SST Anomalies and Historical Sampling
Author(s) -
Thomas M. Smith
Publication year - 2016
Publication title -
journal of atmospheric and oceanic technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.774
H-Index - 124
eISSN - 1520-0426
pISSN - 0739-0572
DOI - 10.1175/jtech-d-16-0059.1
Subject(s) - climatology , sampling (signal processing) , sea surface temperature , environmental science , climate model , greenhouse gas , extratropical cyclone , gcm transcription factors , downscaling , climate change , statistics , meteorology , general circulation model , geology , computer science , mathematics , geography , oceanography , filter (signal processing) , computer vision
Historical reconstructions of climate fields, such as sea surface temperature (SST), are important for climate studies and monitoring. Reconstructions use statistics from a well-sampled base period to analyze a sparsely sampled historical period. Here a method is shown for adjusting the base-period statistics using the available historical data so that statistics better represent historical variations. The method is demonstrated using annual SST anomalies from a coupled GCM historical run, 1861–2005, forced by greenhouse gases and aerosols. Simulated data are constructed from the model’s SST using observed historical SST sampling with error estimates added. Reconstructions are performed using the simulated data, and the results are compared to the full model SST without added errors. The results from applying other reconstruction methods to the simulated data are compared. The tests show that the method improves annual SST reconstructions, especially in the early years, when sampling is most sparse and in the extratropics. In particular, the 1881–1900 correlation averaged over 30°–60°S and over 30°–60°N improves from about 0.4 using noniterative reconstruction to about 0.6 using iterative reconstruction. The correlations of annual values in the tropics are about 0.7 with both methods. Incorporating those improvements into an SST reconstruction could better represent extratropical climate variations in the nineteenth and early twentieth centuries, and improve the value of the reconstruction for long-period climate studies and for validating climate models.

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