There is a growing wealth of observations in the field of atmospheric chemistry with notably an increasing number of satellite remote sensing instruments. Chemical reanalyses propagate the information given by observations onto related state variables, with the aim of reducing biases and uncertainties in space and time, but also across the physical and chemical system. This allows for a better understanding of model and observed variability of the Earth system and atmospheric biogeochemical cycles. Along with being powerful methods, reanalyses and inverse models attempt to quantify complex, potentially nonlinear and chaotic systems. The methods rely on assumptions about prior fluxes and atmospheric states, and are still subject to uncertainties in the applied physical and chemical parameterizations.
In that context, it is important to facilitate and promote the comparison of posterior estimates from different products. Such ensembles can be evaluated with additional observations or other sophisticated statistical approaches to find emergent constraints. Large discrepancies in bottom-up and top down fluxes can also help identify shortcomings in the current understanding of the underlying processes. The comprehensive analysis will greatly enhance our understanding of the drivers of variability in atmospheric chemistry, and provide target areas for data and model improvement.
As part of the IGAC AMIGO working group on Chemical Reanalysis And flux iNvErsionS (CRANES), this page provide an overview of current atmospheric chemistry reanalyses. If your favorite chemical reanalysis is not part of this list, feel free to signal us.
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