Corrigendum

Matic Pikovnik aFaculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia

Search for other papers by Matic Pikovnik in
Current site
Google Scholar
PubMed
Close
,
Žiga Zaplotnik aFaculty of Mathematics and Physics, University of Ljubljana, Ljubljana, Slovenia

Search for other papers by Žiga Zaplotnik in
Current site
Google Scholar
PubMed
Close
, and
Lina Boljka bGeophysical Institute, University of Bergen and Bjerknes Centre for Climate Research, Bergen, Norway

Search for other papers by Lina Boljka in
Current site
Google Scholar
PubMed
Close
Free access

Zaplotnik’s current affiliation: European Centre for Medium-Range Weather Forecasts, Bonn, Germany

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Matic Pikovnik, matic.pikovnik@fmf.uni-lj.si

Zaplotnik’s current affiliation: European Centre for Medium-Range Weather Forecasts, Bonn, Germany

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Matic Pikovnik, matic.pikovnik@fmf.uni-lj.si

We recently became aware of errors in the article Zaplotnik et al. (2022). They resulted from a problem in the code that computed trends of the standardized time series of zonal-mean meridional precipitation gradient Pϕ for the Tropical Rainfall Measuring Mission (TRMM) data over the 1998–2018 period (TRMM 2019). The error affected Figs. 6c and 6d as well as the computation of TRMM correlations shown in Fig. 7 in Zaplotnik et al. (2022). Here, we provide updated figures for Figs. 6 and 7. Comparison of Figs. 6c and 6d herein with Figs. 6c and 6d in Zaplotnik et al. (2022) suggests an even better alignment of Pϕ among precipitation datasets from ERA5, TRMM, and the Global Precipitation Climatology Project (GPCP). In section 4a, we also stated that “the TRMM dataset shows no statistically significant correlations with either ERA5 or ERA-Interim HC strength.” Our results now hint otherwise; they show that particularly the southern Hadley cell (HC) strength and its main driver, the meridional gradient of diabatic heating Qϕ, moderately correlate with the meridional gradient of precipitation derived from TRMM. This applies to both ERA5 and ERA-Interim. The ERA-Interim northern HC strength also now moderately correlates with Pϕ. While the aforementioned errors do not alter the general conclusions, they even further prove it is meaningful to relate the changes in HC strength to the changes in the meridional gradient of precipitation.

Fig. 6.
Fig. 6.

Comparison of the trends of standardized time series. HC strength change 〈δψ〉 and contribution of diabatic heating to the change of HC strength Qϕ are from ERA5. They are compared to the mean meridional gradient of total diabatic heating Qϕdiab, precipitation Pϕ=[P]/Rϕ in ERA5, GPCP, and TRMM for (a),(c) NHC and (b),(d) SHC over two time periods: (a),(b) 1979–2018 and (c),(d) 1998–2018. The ψ values for SHC in (b) and (d) are multiplied by −1, such that their positive trends suggest HC strengthening. For similar reasons, meridional precipitation gradients in the NHC in (a) and (c) are also multiplied by −1.

Citation: Journal of Climate 36, 16; 10.1175/JCLI-D-23-0381.1

Fig. 7.
Fig. 7.

Correlation between the HC strength (〈δψ〉) in ERA-Interim and ERA5, the contribution of meridional gradient of the diabatic heating to the HC strength (Qϕ) in ERA-Interim and ERA5, and the mean meridional precipitation gradient (Pϕ) in ERA-Interim, ERA5, GPCP, and TRMM data for (a) NHC and (b) SHC. Only correlations exceeding 95% significance threshold are shown.

Citation: Journal of Climate 36, 16; 10.1175/JCLI-D-23-0381.1

REFERENCES

  • TRMM, 2011: TRMM (TMPA/3B43) Rainfall Estimate L3 1 month 0.25 degree x 0.25 degree V7, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed 12 December 2019, 10.5067/TRMM/TMPA/MONTH/7.

  • Zaplotnik, Ž., M. Pikovnik, and L. Boljka, 2022: Recent Hadley circulation strengthening: A trend or multidecadal variability? J. Climate, 35, 41574176, https://doi.org/10.1175/JCLI-D-21-0204.1.

    • Search Google Scholar
    • Export Citation
Save
  • TRMM, 2011: TRMM (TMPA/3B43) Rainfall Estimate L3 1 month 0.25 degree x 0.25 degree V7, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed 12 December 2019, 10.5067/TRMM/TMPA/MONTH/7.

  • Zaplotnik, Ž., M. Pikovnik, and L. Boljka, 2022: Recent Hadley circulation strengthening: A trend or multidecadal variability? J. Climate, 35, 41574176, https://doi.org/10.1175/JCLI-D-21-0204.1.

    • Search Google Scholar
    • Export Citation
  • Fig. 6.

    Comparison of the trends of standardized time series. HC strength change 〈δψ〉 and contribution of diabatic heating to the change of HC strength Qϕ are from ERA5. They are compared to the mean meridional gradient of total diabatic heating Qϕdiab, precipitation Pϕ=[P]/Rϕ in ERA5, GPCP, and TRMM for (a),(c) NHC and (b),(d) SHC over two time periods: (a),(b) 1979–2018 and (c),(d) 1998–2018. The ψ values for SHC in (b) and (d) are multiplied by −1, such that their positive trends suggest HC strengthening. For similar reasons, meridional precipitation gradients in the NHC in (a) and (c) are also multiplied by −1.

  • Fig. 7.

    Correlation between the HC strength (〈δψ〉) in ERA-Interim and ERA5, the contribution of meridional gradient of the diabatic heating to the HC strength (Qϕ) in ERA-Interim and ERA5, and the mean meridional precipitation gradient (Pϕ) in ERA-Interim, ERA5, GPCP, and TRMM data for (a) NHC and (b) SHC. Only correlations exceeding 95% significance threshold are shown.

All Time Past Year Past 30 Days
Abstract Views 242 25 0
Full Text Views 1948 1863 392
PDF Downloads 143 70 5