Cold-point tropopause temperature bias modulated by equatorial waves: a reanalysis intercomparison

The tropical Cold-point tropopause temperature (CPT) is a prominent climate variable: it effectively controls the amount of water vapor entering the stratosphere by freeze-drying the air masses that cross through the tropopause near the equator.GNSS radio-occultation measurements (GNSS-RO) provide global coverage of temperature profiles with high vertical resolution, making possible the monitoring of the CPT evolution outside of the few tropical regions covered by radiosondes. Reanalyses are all known to have a modeled CPT that is on average too warm, compared to GNSS-RO measurements. The reanalysis warm CPT biases maximize near the Equator, hinting at a possible role of equatorial waves.Observed equatorial CPT shows spectral peaks coinciding with equatorial wave dispersion curves, i.e. it is modulated by the equatorial waves that propagate through the equatorial tropopause. However, to date the warm biases in reanalysis CPT have only been studied from a systematic and zonal-mean perspective, without accounting for equatorial wave presence. In the present study, we bridge this gap by showing how the reanalysis warm CPT bias varies relative to the phase of equatorial waves. Reanalysis datasets (ERA5, ERA-Interim, JRA55, CFSR and MERRA-2, all with CPT from model levels) are inter-compared to multi-mission GNSS-RO for the years 2007-2018. Equatorial waves are filtered from a 5° x 5° daily grid – the best resolution that GNSS-RO data density permits reliably for 2007-2018 – onto which the reanalyses CPTs are interpolated for a 1-to-1 comparison.A common feature among all reanalysis datasets is as follows: within an equatorial wave’s cold phase, reanalysis CPT biases markedly increase – sometimes by over 1K on top of the average warm bias. The opposite happens within the warm phase of the wave: the bias decreases. This can be explained by the stronger vertical temperature gradients around the colder equatorial CPTs, and the atmospheric models of the reanalyses increasingly struggling there.There is an important caveat to the above: a time-space scale-dependence, where smaller-scale and faster equatorial waves modulate CPT reanalysis bias more. Mixed Rossby-Gravity waves show this behavior most clearly, Kelvin waves about half the magnitude, and equatorial Rossby wave modulation of CPT reanalysis bias is even weaker but still apparent. In contrast, the large-scale and slow-moving MJO does not show any of this bias modulation. Current work is on validating Inertia-Gravity wave results which may contain significant proportions of noise. Analysis of assimilation increments of CPT in the reanalyses shows data assimilation cooling the modeled CPT – enhancing the gradients around it – in all datasets.

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