Abstract
Evaluation of CESM1 (WACCM) free-running and specified dynamics atmospheric composition simulations using global multispecies satellite data records
Highlights
State-of-the-art chemistry–climate models (CCMs) are known to reproduce the main features of stratospheric climatology and change, there have always been some differences between models (e.g., Waugh and Eyring, 2008; StratosphereTroposphere Processes And their Role in Climate (SPARC), 2010; Dhomse et al, 2018)
Our work focuses on the stratosphere, but both FR-Whole Atmosphere Community Climate Model (WACCM) and specified dynamics (SD)-WACCM average O3 values at low latitudes are lower than the observed means from 215 to 261 hPa; in this region, there are known Microwave Limb Sounder (MLS) positive biases versus tropical ozonesonde data, and this could account for part of the apparent model low bias
The importance of meteorological variability was recently emphasized by Chipperfield et al (2018), who included MLS data through the end of 2017 in their comparisons to simulations from a chemical transport model; they showed that the MLS data exhibited large increases in the Southern Hemisphere (SH) lower stratosphere in 2017, which led to a positive tendency for 2005– 2017 trends in that region, in contrast to slight declines in the Northern Hemisphere (NH), in general agreement with the results shown here, which include one more year (2018) of MLS data
Summary
State-of-the-art chemistry–climate models (CCMs) are known to reproduce the main features of stratospheric climatology and change, there have always been some differences between models (e.g., Waugh and Eyring, 2008; SPARC, 2010; Dhomse et al, 2018). There have been essentially no trend studies using Aura MLS data by themselves This data set covers a sufficiently long period that it becomes useful to investigate such trends, as the analyses deal with one data set only, which can remove potential issues with data merging prior to 2005, whether related to poorer sampling or to uncertainties in bias removal between data sets. 3. Climatological comparisons between models and Aura MLS data are provided, in order to assess whether any obvious biases exist; this includes an overview of the main short-term variations, namely the annual oscillation (AO) and semiannual oscillation (SAO). More detailed comparisons of deseasonalized anomaly time series are provided, where we evaluate how well the two model versions fit the data sets, both in terms of closeness of fits and variability.
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