Assessing the value of Microwave Sounding Unit–radiosonde comparisons in ascertaining errors in climate data records of tropospheric temperatures

Abstract

[1] Multidecadal-scale changes in atmospheric temperature have been measured by both radiosondes and the satellite-borne microwave sounding unit (MSU). Both measurement systems exhibit substantial time varying biases that need to removed to the extent possible from the raw data before they can be used to assess climate trends. A number of methods have been developed for each measurement system, leading to the creation of several homogenized data sets. In this work, we evaluate the agreement between MSU and homogenized radiosonde data sets on multiyear (predominantly 5-year) time scales and find that MSU data sets are often more similar to each other than to radiosonde data sets and vice versa. Furthermore, on these times scales the differences between MSU data sets are often not larger than published internal uncertainty estimates for the RSS product alone and therefore may not be statistically significant when the internal uncertainty in each data set is taken into account. Given the data limitations it is concluded that using radiosondes to validate multidecadal-scale trends in MSU data, or vice versa, or trying to use such metrics alone to pick a 'winner' is an ill-conditioned approach and has limited utility without one or more of additional independent measurements, or methodological, or physical analysis.

Quantification of Local Warming Trend: A Remote Sensing-Based Approach

“…However, its utilization is found to be quite limited in analysing global and regional warming trends [15]. For example, Microwave Sounding Units (MSU) and Advanced Microwave Sounding Units (AMSU) on NOAA satellite data have been analysed during the past several decades (i.e., 1979–2010) in comprehending warming trends over: (i) near global (i.e., ~75°S to 75°N) [16–17]; (ii) tropics (i.e., ~20°S to 20°N) [17–18]; (iii) northern extratropics (i.e., ~20°N to 82.5°N) [17]; and (iv) southern extratropics (i.e., (i.e., ~82.5°S to 20°S) [17]. Despite the importance of these studies, the MSU/AMSU-derived data has limited use in local warming trend analysis because of their coarse spatial resolution (i.e., 2.5° x 2.5°).…”

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

“…Over the past decade many studies based on MSU/ AMSU observations have shown that the tropical tropospheric temperature increases more than the surface temperature on multidecadal time scales (Fu et al 2004;Fu and Johanson 2005;Mears andWentz 2005, Thorne et al 2007;Santer et al 2008), while others suggest reduced tropospheric warming relative to the surface (e.g., Christy et al 2007Christy et al , 2010Douglass et al 2008). Our understanding of tropical tropospheric temperature trends is complicated by the fact that tropical radiosonde stations are limited in number, their trends are cold biased, and the bias magnitude cannot be accurately determined (e.g., Sherwood et al 2005;Randel and Wu 2006;Titchner et al 2009).…”

“…Three research teams, including the University of Alabama in Huntsville (UAH), Remote Sensing Systems (RSS), and the National Oceanic and Atmospheric Administration (NOAA) Center for Satellite Applications and Research (STAR), have developed up-to-date, homogenized datasets for the temperature of the middle troposphere (TMT) (Christy et al 2003;Mears et al 2003;Zou and Wang 2011). These groups employ over 30 years of temperature measurements from MSU and, starting in 1998, AMSU.…”

“…They found large trend differences between MSU/AMSU datasets and enhanced tropical tropospheric amplification relative to both RSS and UAH. Reasons for TMT trend differences stem from different processing choices and bias corrections made by the three research teams, including the choice of satellites included (Mears et al 2003), corrections for the influence of the warm target temperature on the measured brightness temperature (e.g., Christy et al 2000;Mears et al 2003;Po-Chedley and Fu 2012a), and corrections for the drift of satellites through the diurnal cycle (e.g., Christy et al 2000;Fu and Johanson 2005;Mears and Wentz 2005). Recent studies by Po-Chedley andFu (2012a, 2013) suggest that UAH uses a biased NOAA-9 warm target factor that results in artificial cooling in the UAH TMT time series, though UAH has not changed its treatment of NOAA-9 (Christy and Spencer 2013).…”

“…It is therefore very important to remove the effect of diurnal drift on the measured brightness temperature when estimating the magnitude of decadal temperature change. The RSS and NOAA research teams apply a drift correction based on the diurnal cycle from a GCM (Mears et al 2003;Zou and Wang 2011), whereas UAH produces an MSU TMT diurnal correction based on temperature comparisons between three coorbiting satellites carrying AMSU with different local sampling times. UAH does not yet correct the diurnal drift for satellites carrying AMSU, because they attempt to use these satellites during periods when diurnal drift is small (J.…”