Speaker
Description
The significant climate feedback of stratospheric water vapor (SWV) necessitates accurate estimates of SWV budget changes, with the strongest impacts expected in the tropical and extratropical lower stratosphere, often referred to as the lowermost stratosphere (LMS). Common data sources to quantify SWV variability over the past 3-4 decades in this critical region include satellite observations (e.g., MLS, SWOOSH), long-term in-situ measurements (e.g., Boulder FPH, JULIA), and Lagrangian models driven by meteorological reanalyses (e.g., CLaMS driven by ERA5). To estimate SWV trends and disentangle anthropogenic contributions, it is essential to first quantify natural variability, particularly on decadal time scales.
Based on our previous studies, which primarily employed satellite and CLaMS data, we demonstrate the presence of a robust multi-decadal variation in SWV that distinctly separates the past 40 years into two wet periods (1986–1997; 2010–2020) and one dry period (1998–2009). This multi-decadal variability complicates the detection of long-term anthropogenic trends relevant for assessing surface climate impacts, especially in the near term. In the extratropical LMS, the current quality of satellite data and model simulations appears insufficient for reliable long-term trend assessments, underscoring the importance of long-term in-situ observations, such as those from JULIA. We present preliminary results comparing climatologies in the LMS derived from JULIA, CLaMS, and ERA5.
| You plan to attend | On site (at FZ Jülich) |
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