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Human-induced weakening of the Northern Hemisphere tropical circulation


By accounting for most of the poleward atmospheric heat and moisture transport in the tropics, the Hadley circulation largely affects the latitudinal patterns of precipitation and temperature at low latitudes. To increase our preparednesses for human-induced climate change, it is thus critical to accurately assess the response of the Hadley circulation to anthropogenic emissions1,2,3. However, at present, there is a large uncertainty in recent Northern Hemisphere Hadley circulation strength changes4. Not only do climate models simulate a weakening of the circulation5, whereas atmospheric reanalyses mostly show an intensification of the circulation4,5,6,7,8, but atmospheric reanalyses were found to have artificial biases in the strength of the circulation5, resulting in unknown impacts of human emissions on recent Hadley circulation changes. Here we constrain the recent changes in the Hadley circulation using sea-level pressure measurements and show that, in agreement with the latest suite of climate models, the circulation has considerably weakened over recent decades. We further show that the weakening of the circulation is attributable to anthropogenic emissions, which increases our confidence in human-induced tropical climate change projections. Given the large climate impacts of the circulation at low latitudes, the recent human-induced weakening of the flow suggests wider consequences for the regional tropical–subtropical climate.

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Fig. 1: Recent changes in the Hadley circulation strength.
Fig. 2: Detection–attribution analysis of the Hadley circulation weakening.

Data availability

The data used in the manuscript are publicly available for CMIP6 (, ICOADS (provided by the NOAA PSL at, HadSLP2 (, CMIP5 (, ERA5 ( and JRA-55, NCEP2 and NOAA 20CRv3 (

Code availability

Codes used to calculate the meridional mass streamfunction and meridional gradient are available at


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R.C. is grateful for the support by the Willner Family Leadership Institute for the Weizmann Institute of Science and the Zuckerman STEM Leadership Program. J.Y. received M2LInES research funding by the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures programme.

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R.C. downloaded and analysed the data and, together with J.Y., discussed and wrote the paper.

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Correspondence to Rei Chemke.

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The authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Spatial distribution of Hadley circulation changes.

a, The 1960–2014 trends of the meridional mass streamfunction in CMIP6 mean (kg s−1 year−1). b, The response to anthropogenic emissions (difference between the 2080–2099 and 1980–1999 periods) of the meridional mass streamfunction in CMIP6 mean (kg s−1). Stippling shows regions in which at least 80% of the models agree on the sign of change. Black contours show the climatological (averaged over the 1980–1999 period) meridional mass streamfunction, in which solid contours indicate positive values and dashed contours indicate negative values (with minimum values and spacing of ±2 × 1010 kg s−1).

Extended Data Fig. 2 Changes in the Hadley circulation strength and PSLy in observations and reanalyses.

a, The evolution, relative to the 1980–1999 period, of Ψmax in CMIP6 mean (black line) and in the reanalyses mean (green line), and PSLy in the reanalyses mean (red line) and in the ICOADS (blue line). Shadings show the range across the models/reanalyses (ERA5, JRA-55, NCEP2). b, The evolution, relative to the 1960–1975 period, of PSLy in NOAA 20CRv3 (blue line) and HadSLP2 (red line), along with their linear regressions. Note that NOAA 20CRv3 is a reanalysis product and thus caution should be taken when interpreting its PSLy trends.

Extended Data Fig. 3 Changes in the Hadley circulation strength and PSLy in climate models.

a, The evolution, relative to the 1960–1975 period, of Ψmax (black) and PSLy (red) in CMIP5 mean; their correlation is in the lower-left corner. Shadings show the range across the models. b, The 1960–2014 trends in Ψmax plotted against the 1960–2014 trends in PSLy, estimated by averaging over both ocean and land, across CMIP6 models (red dots); their correlation is in the upper-left corner. Red line shows the linear regression and the orange shading the 95% of linear regression values (Methods). The evolution, relative to the 1960–1975 period (c) and in absolute values (d), of the Hadley circulation strength (Ψmax, black line) and PSLy, estimated by averaging over both ocean and land (red line) in CMIP6 mean; their correlation is in the lower-left corner. Shadings show the range across the models.

Extended Data Fig. 4 Recent changes in the Hadley circulation strength.

As in Fig. 1 in the manuscript but using Ψavg (the averaged streamfunction between 5° and 25° and between 1,000 mb and 100 mb) (a,b) and Ψmax, and PSLy from the extended ICOADS data through 2021 (c,d); the regressions are estimated over the 1960–2021 period.

Extended Data Fig. 5 Recent changes in the Hadley circulation strength using HadSLP2.

As in Fig. 1 in the manuscript but using the observed PSLy from HadSLP2. The PSLy is estimated by averaging over both ocean and land and the linear regressions are estimated over the 1960–2012 period. CMIP6 data here are regridded to the same resolution as in HadSLP2.

Extended Data Fig. 6 Recent PSLy variability and correlation with Hadley circulation trends.

a, The occurrence frequency of the interannual variability (s.d.) of the detrended 1960–2014 PSLy across CMIP6 models. The vertical black line shows the interannual variability in the observed PSLy (Obs). b, Correlation coefficients between the trends, from 1960 to each year, of the Hadley cell strength (Ψmax) and PSLy across CMIP6 models (the correlation is calculated similarly to that in Fig. 1b).

Extended Data Fig. 7 ICOADS data.

a, Evolution of the number of longitudinal grid boxes with available data in the ICOADS at the latitude of PSLy. b, Number of years, out of the 55 years analysed in this study, with available ICOADS data at each location. The horizontal black lines indicate the region in which PSLy is evaluated. White colours represent missing values. Sea-level pressure from the ICOADS at latitude 9° as a function of longitude in unsmoothed (c) and smoothed (d) data during two consecutive years, 2013 (in blue) and 2014 (in red). Shadings highlight regions of missing values.

Extended Data Fig. 8 Analysis of the momentum budget.

The CMIP6 mean climatology (averaged over the 1980–1999 period; panels a and c) and the 1960–2014 trends (panels b and d) of the different terms, averaged between 10° and 20°, in the zonal mean (top row) zonal momentum equation vertically integrated between 1,000 mb to 500 mb and (bottom row) meridional surface momentum equation. \({\overline{uv}}_{y}\) and \({\overline{{u}^{{\prime} }{v}^{{\prime} }}}_{y}\) are the mean and eddy meridional components of the zonal momentum flux convergence, respectively, \({\overline{uw}}_{p}\) and \({\overline{{u}^{{\prime} }{w}^{{\prime} }}}_{p}\) are the mean and eddy vertical components of the zonal momentum flux convergence, respectively, \(f\,\overline{v}\) is the Coriolis force acting on the meridional wind, Du is dissipation effects on the zonal wind, \({\overline{vv}}_{y}\) and \({\overline{{v}^{{\prime} }{v}^{{\prime} }}}_{y}\) are the mean and eddy meridional components of the meridional momentum flux convergence, respectively, \({\overline{vw}}_{p}\) and \({\overline{{v}^{{\prime} }{w}^{{\prime} }}}_{p}\) are the mean and eddy vertical components of the meridional momentum flux convergence, respectively, \(f\overline{u}\) is the Coriolis force acting on the zonal wind and Dv is dissipation effects on the meridional wind. Du and Dv are estimated as residuals. Eddies are calculated as deviations from monthly and zonal means. Error bars show the 95% confidence interval.

Extended Data Table 1 List of the CMIP6 models analysed in this study and their availability (marked by asterisks)
Extended Data Table 2 List of the CMIP5 models analysed in this study

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Chemke, R., Yuval, J. Human-induced weakening of the Northern Hemisphere tropical circulation. Nature 617, 529–532 (2023).

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