Reply to comment by T. Mölg et al. on “Recent glacial recession in the Rwenzori Mountains of East Africa due to rising air temperature”

Abstract

[1] Debate persists as to the extent to which recent glacial recession observed in tropical highlands is driven primarily by changes in air temperature [e.g., Bradley et al., 2006; Thompson et al., 2006] and atmospheric humidity [e.g. Kaser et al., 2004; Molg and Hardy, 2004]. Uncertainty has also been expressed in the relationship between temperature trends at the surface and higher elevations in the tropical free troposphere [e.g., Christy et al., 2003; Christy and Norris, 2004; Douglass et al., 2004; Fu et al., 2004; Tett and Thorne, 2004] where alpine glaciers reside. We therefore welcome the constructive comments of Molg et al. [2006] regarding our original paper and appreciate the opportunity to clarify arguments made therein [Taylor et al., 2006]. We agree with Molg et al. that the surface energy balance and mass balance are best able to describe the relationship between climate parameters and glacier change [e.g., Wagnon et al., 1999; Molg and Hardy, 2004]. For the Rwenzori Mountains, measurements that would form the basis of a glacier mass balance model do not exist. This point was recognized explicitly in the original paper, ‘‘The absence of continuous and proximate meteorological observations in the Rwenzori Mountains prevents direct analysis of the climatic factors driving observed glacial recession.’’ Although a definitive, quantitative understanding of the climate variables responsible for glacier mass losses in the Rwenzori Mountains remains elusive, we dispute the assertion of Molg et al. that air temperature (Ta) is unlikely to be the main driver of observed glacial recession and argue that trends of increasing air temperature are better supported by currently available evidence than decreasing humidity posited by Molg et al. [2] The essential scientific criticism of our paper by Molg et al. [2006] is the validity of the assumption that Ta trends observed in gridded CRUTS 2.0 climate data sets [New et al., 2002] and at meteorological stations between 960 and 1869 meters above sea level (masl), reflect Ta trends in the middle troposphere (4800 to 5100 masl) where glaciers in the Rwenzori Mountains occur. Molg et al. suggest that we have disregarded evidence of inconsistencies between Ta trends at the surface and in the tropical troposphere, but the literature [Hense et al., 1988; Gaffen et al., 2000; Bradley et al., 2004] and evidence they cite is selective. Significant uncertainty persists in temperature data for the tropical troposphere whether these derive from satellite-borne Microwave Sounding Unit (MSU) observations or in situ measurements using radiosondes, particularly in data-poor regions like East Africa. Indeed, linear Ta trends in the tropical troposphere can vary significantly based simply upon choice of start and end date as is the case in the paper by Gaffen et al. [2000] using MSU data in which at 500 hPa a cooling trend is detected between 1979 and 1997 but an overall warming trend occurs between 1960 and 1997. Nevertheless, recent studies that employ diurnal corrections to MSU observations between 1979 and 2003 [Mears and Wentz, 2005] and homogenized radiosonde data sets (HadAT2) between 1958 and 2002 [Thorne et al., 2005], show that the middle troposphere warmed at a similar or slightly greater rate to the surface in the tropics [Fu and Johanson, 2005; Santer et al., 2005], consistent with the sign and (within error) magnitude of Ta trends (+0.13 C per decade) at the surface from climate model (HadCRU2v) predictions [Jones and Moberg, 2003]. [3] Molg et al. [2006] use NCEP reanalysis data [Kalnay et al., 1996] for the grid cell (30 E, 0 N) to support their claim that a discrepancy exists between Ta trends at the lower troposphere (850 hPa) and mid-troposphere (600 hPa) in the Rwenzori Mountains (their Figure 1). There is, however, widespread consensus within the climate community that reanalysis data are unsuitable for trend analysis in climate change studies as ‘‘. . .known discontinuities in reanalyzed data sets indicate that further research is required to reduce time-dependent errors to a level suitable for climate change studies’’ [Intergovernmental Panel on Climate Change, 2001, p. 120]. The existence of systematic, time-varying biases in reanalysis data is also highlighted by more recent studies [Bengtsson et al., 2004; Simmons et al., 2004; Sterl, 2004; Thorne et al., 2005]. Molg et al. consider biases in the NCEP data associated with the introduction of satellite observations in 1979 to reanalysis data sets (see caption in their Figure 1) but not other inconsistencies that arise from the wide range of data sources including modeled processes [Pepin and Seidel, 2005]. In contrast to inferences drawn by Molg et al. using NCEP data, upper air temperature records from gridded HadAT2 radiosonde data [Thorne et al., 2005] for the most proximate (and only) grid cell to the Rwenzori GEOPHYSICAL RESEARCH LETTERS, VOL. 33, L20405, doi:10.1029/2006GL027606, 2006 Click Here for Full Article