Large Uncertainty in Observed Meridional Stream Function Tropical Expansion
- 1Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT 84112, USA
- 2Department of Geology and Geological Engineering, Colorado School of Mines, Golden, CO 80401, USA
- 1Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT 84112, USA
- 2Department of Geology and Geological Engineering, Colorado School of Mines, Golden, CO 80401, USA
Abstract. Recent tropical expansion rate estimates vary substantially, as a multitude of methods and reanalysis datasets yield conflicting results. Among the many methods of estimating the tropical width, the meridional stream function 500 hPa zero-crossing is the most widely used, as it is directly related to the poleward edge of the Hadley Cell (HC). Other common metrics use atmospheric phenomena associated with the HC as a proxy, for instance the zonal surface wind zero-crossing. As each of these metrics require different data, each with varying error, the level of data-driven uncertainty differs between each metric. While previous work has analyzed the statistical and dynamical relationships between metrics, to date no study has quantified and compared the uncertainty in different HC metrics. In this study, we use ERA5 ensemble members, which include small perturbations in atmospheric variables based on the data error, to quantify the uncertainty associated with six commonly used HC metrics as well as the range of their trend estimates. In the Northern Hemisphere, the tropical expansion rate calculated by the stream function is roughly 0.05 degrees per decade, while the Southern Hemisphere rate is 0.2 degrees per decade. Of the six metrics, only the meridional stream function and precipitation minus evaporation have substantial uncertainties. The stream function errors are large due to uncertainty in the underlying meridional wind data and the presence of large regions of near-neutral circulation at the poleward edge of the tropics. These errors have decreased in recent decades because of improvements in the assimilated observations. Despite these improvements, we recommended using the zonal surface wind zero crossing to analyze tropical extent trends in reanalyses. This is particularly important in the Northern Hemisphere, before the year 2000, and when studying individual seasons other than winter.
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Daniel Baldassare et al.
Status: open (until 25 Feb 2023)
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AC1: 'Comment on egusphere-2022-1438', Daniel Baldassare, 04 Jan 2023
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As requested by Dr. Nili Harnik I have made corrections to typos in the Supplement in Text S1, S2 and S3 in the figure references.
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RC1: 'Comment on egusphere-2022-1438', Anonymous Referee #1, 16 Jan 2023
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Review in file
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RC2: 'Comment on egusphere-2022-1438', Anonymous Referee #2, 03 Feb 2023
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In this manuscript the authors attempt to estimate the observed uncertainty in recent Hadley cell extent trends/changes as seen in ERA5. For this the authors analyze the spread across ERA5 members in different Hadley cell metrics. Lastly, the authors link the uncertainty in the HC extent to the uncertainty in the magnitude of the circulation around its edge. The overall motivation for this research, as stated in the abstract and introduction, is the different expansion rates across different Hadley cell metrics, reported by previous studies. In this manuscript, however, the authors do not address this issue. In fact, the ERA5 uncertainty of each metric, is not as large as the inter-metric spread, reported before, nor as the trend it self of each metric. So I am not sure that this manuscript helps us better constrain the different Hadley cell expansion rates. Moreover, as discussed in previous studies (which the author cite), the lack of correlation between the different metrics suggests that they represent and driven by different processes, and we thus not necessarily expect to observe the same trend in each metric. Only reporting the uncertainty in the Hadley cell trends (which seem to be small, relative to the signal and the inter-metric spread), in my opinion, is not sufficient for publication. The most important conclusion here is the reduction in uncertainty across ERA5 members over the years. But this is a technical result.Below I list several more comments (major and minor):1. The introduction, in my opinion, should be broaden to give a larger context for this problem, and why its important to investigate the expansion of the circulation. The authors should discuss how/where the Hadley cell is projected to change in coming decades, the mechanisms underlying recent and future Hadley cell changes, and the impacts of such expansion.2. How much the ERA5 spread is different than large-ensemble spread, which has been documented in previous work (e.g., Grise et al 2019).3. The missing December in the beginning of ERA5 should not be a motivation to define the annual mean from March to February. This does not allow a proper comparisons to previous work. I suggest using, only for the first year, January and February, for NH winter, and DJF for other years. And use January to December as the canonical definition for the annual mean.4. Please itemize the different paragraphs in the methods section discussing each metric.5. The Hadley cell extent is usually found by doing an interpolation of the data to a finer grid; have you done the same here?6. In the normalized STD you divide the inter-member spread with interannual variability, but these two may represent different processes. I am thus worried that this metric does not represent a normalized uncertainty.7. In Sec. 3.5 the authors argue that the uncertainty in Hadley cell expansion is linked to the gradient of the streamfunction at the Hadley cell edge. However, such link is based on correlation of only eight points, where 5 of them do not follow the regression line, and show no sign of correlation. I am thus not convinced by the authors' arguments, and suggest to remove this analysis along with its discussion.
Daniel Baldassare et al.
Data sets
ERA5 Accessed from Copernicus Hersbach et al., 2020 https://cds.climate.copernicus.eu
Model code and software
ERA5 Analysis Python Code Daniel Baldassare https://doi.org/10.5281/zenodo.7430530
Daniel Baldassare et al.
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