Reanalysis comparisons of upper tropospheric–lower stratospheric jets and multiple tropopauses

Abstract

Abstract. The representation of upper tropospheric–lower stratospheric (UTLS) jet and tropopause characteristics is compared in five modern high-resolution reanalyses for 1980 through 2014. Climatologies of upper tropospheric jet, subvortex jet (the lowermost part of the stratospheric vortex), and multiple tropopause frequency distributions in MERRA (Modern-Era Retrospective analysis for Research and Applications), ERA-I (ERA-Interim; the European Centre for Medium-Range Weather Forecasts, ECMWF, interim reanalysis), JRA-55 (the Japanese 55-year Reanalysis), and CFSR (the Climate Forecast System Reanalysis) are compared with those in MERRA-2. Differences between alternate products from individual reanalysis systems are assessed; in particular, a comparison of CFSR data on model and pressure levels highlights the importance of vertical grid spacing. Most of the differences in distributions of UTLS jets and multiple tropopauses are consistent with the differences in assimilation model grids and resolution – for example, ERA-I (with coarsest native horizontal resolution) typically shows a significant low bias in upper tropospheric jets with respect to MERRA-2, and JRA-55 (the Japanese 55-year Reanalysis) a more modest one, while CFSR (with finest native horizontal resolution) shows a high bias with respect to MERRA-2 in both upper tropospheric jets and multiple tropopauses. Vertical temperature structure and grid spacing are especially important for multiple tropopause characterizations. Substantial differences between MERRA and MERRA-2 are seen in mid- to high-latitude Southern Hemisphere (SH) winter upper tropospheric jets and multiple tropopauses as well as in the upper tropospheric jets associated with tropical circulations during the solstice seasons; some of the largest differences from the other reanalyses are seen in the same times and places. Very good qualitative agreement among the reanalyses is seen between the large-scale climatological features in UTLS jet and multiple tropopause distributions. Quantitative differences may, however, have important consequences for transport and variability studies. Our results highlight the importance of considering reanalyses differences in UTLS studies, especially in relation to resolution and model grids; this is particularly critical when using high-resolution reanalyses as an observational reference for evaluating global chemistry–climate models.

responses to Simon Chabrillat's comments

“…The methods and diagnostics used herein are largely the same as those used by Lawrence et al (2015). In the subsections to follow, we describe the reanalysis fields we use, and how we prepare them and derive the polar processing diagnostics from 30 them. We also provide some information on additional analysis techniques that we use to help interpret our results.…”

“…The depletion of ozone in the lower stratosphere follows from a complex chain of processes that are highly dependent on meteorological conditions (see, e.g., Solomon, 1999;WMO, 2014, for reviews). The activation of chlorine requires the presence of polar stratospheric clouds (PSCs), which form when temperatures are sufficiently low, and grow when temperatures stay low 30 for sufficiently long periods of time (Hanson and Mauersberger, 1988;Solomon, 1999;WMO, 2014, and references therein).…”

“…To calculate MPVG, we bin sPV as a function of 25 equivalent latitude (EqL, the latitude that would enclose the same area between it and the pole as a given PV contour; Butchart and Remsberg, 1986), numerically differentiate, and catalog the maximum value between ±30 and ±80 • EqL. We use ±30 • as a lower limit because relatively large PV gradients can be found in the tropics, which can dominate early/late in the season when the vortex is forming/decaying; we use ±80 • as an upper limit because the small areas represented by points poleward of ±80 • can vary much more dramatically than the lower EqLs, sometimes producing large gradients (e.g., Nash et al, 1996) that 30 are not indicative of the vortex edge.…”

“…Studies comparing with other data sources, such as long-duration balloon flights (Hoffmann et al, 2017, and references therein), are generally restricted to more limited spatial and temporal regimes. In addition, many of the latest generation reanalyses assimilate data sources such as COSMIC GPS-RO and long-duration balloon flights (Fujiwara et al, 2017;Hoffmann et al, 2017;Lambert and Santee, 2018), 30 thus complicating interpretation of differences from those data sources. Also, as noted by Lawrence et al (2015), some of the most useful diagnostics of polar processing, while conceptually simple, depend on having full and dense coverage of the polar regions (e.g., minimum high-latitude temperatures or area of temperatures below a PSC threshold), and/or are based on vortex diagnostics that are defined by potential vorticity (PV) (e.g., vortex area or vortex-edge PV gradients) that do not have corresponding observations.…”

“…All of our analyses are done using daily 12:00UT fields from each reanalysis dataset (we have tested the sensitivity of our analyses to using 00:00UT data and have found we get virtually identical results). Because of the importance of resolution, especially in the vertical dimension, in representing 25 the polar lower stratosphere and threshold processes in general (see, e.g., Manney et al, 2017), we start our analyses from reanalysis data on the native model levels and at or (in the case of spectral models) near the native horizontal resolution. Please see Table 1 for a list of relevant acronyms that we use below to describe the instruments, radiative transfer models, etc., that are used by the reanalyses.…”