Removing Diurnal Cycle Contamination in Satellite-Derived Tropospheric Temperatures: Understanding Tropical Tropospheric Trend Discrepancies 

Friday, 19 December 2014
Stephen Po-Chedley, University of Washington Seattle Campus, Seattle, WA, United States, Tyler James Thorsen, University of Washington, Seattle, WA, United States and Qiang Fu, Univ Washington, Seattle, WA, United States
Tropical mid-tropospheric temperature (TMT) time series have been constructed by several independent research teams using satellite microwave sounding unit (MSU) measurements beginning in 1978 and advanced MSU (AMSU) measurements since 1998. Despite careful efforts to homogenize the MSU/AMSU measurements, tropical TMT trends disagree by a factor of three even though each analysis uses the same basic data. Previous studies suggest that the discrepancy in tropical TMT temperature trends is largely caused by differences in both the NOAA-9 warm target factor and diurnal drift corrections used by various teams to homogenize the MSU/AMSU measurements. This work introduces a new observationally-based method for removing biases related to satellite diurnal drift. The method relies on minimizing inter-satellite and inter-node drifts by subtracting out a common diurnal cycle determined via linear regression. It is demonstrated that this method is effective at removing intersatellite biases and biases between the ascending (PM) and descending (AM) node of individual satellites in the TMT time series. After TMT bias correction, the ratio of tropical tropospheric temperature trends relative to surface temperature trends is in accord with the ratio from global climate models. It is shown that bias corrections for diurnal drift based on a climate model produce tropical trends very similar to those from the observationally-based correction, with a trend differences smaller than 0.02 K decade-1. Differences among various TMT datasets are explored further. Tropical trends from this work are comparable to those from the Remote Sensing System (RSS) and NOAA datasets despite small differences. Larger differences between this work and UAH are attributed to differences in the treatment of the NOAA-9 target factor and the UAH diurnal cycle correction.