Principal Investigator

At a Glance

One of the consequences of global climate change is a predicted increase in the intensity of tropical cyclone (TC) activity and other climate impacts. Key to predicting the severity and duration of such impacts for future decades is understanding the dynamics of these phenomena over the past few centuries. To this end, the Vecchi group is using climate and atmospheric model studies, along with analyses of the observed record, to investigate the nature of these climate impacts. The Group is especially interested in understanding how TCs develop, how they might be predicted, and the role global climate change plays in their generation and severity.


Research Highlight

An important goal of this research is to better understand the extent to which observed multi-decadal to centennial changes in TC activity have been driven by large scale factors (such as ocean temperature changes, greenhouse gases, volcanic eruptions, El Niño) versus random atmospheric fluctuations. The researchers are also exploring the extent to which natural and human-induced climatic factors (such as volcanic eruptions and greenhouse-induced warming) have influenced the character and impact of TC activity. Principal results of their work include the following three highlights:

i. Tropical Cyclone-Climate Connection

What controls global TC frequency remains a crucial and unanswered question. Using theoretical arguments and a hierarchy of climate model simulations (Figure 8.1), the researchers developed a framework to understand the global response of TC frequency to a broad range of climate drivers (Hsieh et al., 2020). This framework starts from the realization that TCs form from pre-existing, weaker, wave systems (TC “seeds”), the sensitivity of which to climate forcing is the main driver of TC frequency change. They developed a theoretically-motivated scaling for “seed” and TC frequency, which is able to explain TC frequency across a range of climates. Future work is aimed at better understanding the regional changes in hurricane frequency.

Figure 8.1.
Top Panel: Depiction of the hierarchy of high-resolution models used to understand the hurricane-climate connection: realistic global simulations (red), ocean only worlds with warm tropics and cold poles (blue) and ocean only worlds with uniform temperatures (green). Exploring hurricane climate connections across a suite of configurations allows us to identify the causal processes [figure by Tsung-Lin Hsieh]. Lower panels show the ability of theoretical scaling arguments developed using the hierarchical modeling approach to predict the response of (a) tropical cyclone “seeds” and (b) tropical cyclone frequency in response to forcing changes [lower panels from Hsieh et al. 2020].

The researchers are also working to understand the controls on “rapid Intensification”, or RI. This refers to tropical cyclones whose peak intensities increase by a Saffir-Simpson Category in less than 24 hours. These storms are among the most difficult to predict on weather timescales and can have dramatic societal consequences because their intensity changes can leave coastal areas with little warning. The researchers have identified, using observations of RI and large-scale climate, a strong constraint from large-scale environmental conditions on the probability of rapid intensification (Ng and Vecchi 2020). This empirical work suggests that statistical models could be built that would be applicable to projecting RI probability from a large suite of climate models.

The Vecchi group has also explored the impact of “extratropical transition” (or ET) on the character of tropical cyclone rainfall, and its change from global warming (Liu et al., 2020; Bieli et al., 2020). The researchers have identified how the Pacific jet stream impacts hurricane frequency in the Atlantic (Zhang et al., 2020), an insight which might help improve more accurate seasonal hurricane predictions. The researchers also studied the sensitivity of ocean temperature and salinity to tropical cyclones, which was intended to obtain a more complete understanding of the coupled ocean-atmosphere mechanisms controlling TC intensity (Sun et al., 2021).

ii. Regional Impacts of Climate Forcing

The researchers have explored the impact of volcanic forcing on global-scale TC and hydroclimate variations — with a particular focus on the similarities and differences between forcing from different 20th century volcanos (Jacobson et al., 2020). Using targeted climate model experiments, they tested the hypothesis that the hydroclimate sensitivity to volcanoes depends on the hemisphere in which the volcanic plume is most pronounced. They noticed different hydroclimate responses to Pinatubo (1991), the most intense volcanic eruption in the 20th century with a stratospheric plume symmetric about the equator; Santa María (1902), whose plume had a northern hemisphere maximum; and Agung (1963), which had its plume primarily in the southern hemisphere. Northern hemisphere volcanoes lead to a drying of semi-arid regions in West Africa (“the Sahel”), while southern hemisphere volcanoes do the opposite. And even though Pinatubo was the strongest volcano in terms of global radiative forcing and surface temperature change, both Santa María and Agung account for larger regional rainfall differences due to displacements of climatological wet/dry regions.

Volcanoes provide case studies to explore the response of the global climate system to radiative forcing and are thought to be one of the main drivers of climatic change over the past millennium (and on longer timescales). This work provides an organizing framework with which to explore the global impacts of volcanoes, and indicates that the best-studied volcano on record (Pinatubo in 1991, which was very symmetric) may be relatively unrepresentative of volcanic forcing on climate in general (since most volcanoes appear to have primarily asymmetric forcing). The researchers have also been exploring the sensitivity of extratropical and subpolar lake freeze statistics to climate changes over the 20th century, in order to build projections for the 21st century.

iii. Understanding Global Surface Warming

Some of the latest generation of climate models have a “climate sensitivity” (warming of the surface resulting from a doubling of CO2 ) that substantially exceeds past model estimates. The researchers explored the mechanisms behind the large inter-model spread of climate sensitivity and used the observational record to evaluate whether models with high or low climate sensitivity are more plausible (Wang et al. 2021). They found that these new models have a climate sensitivity that ranges from less than 2°C to almost 6°C. This spread is due to differences in the way clouds respond to warming; they all show global warming over the historical record that is similar to observations. The researchers found, further, that the agreement over the historical period in global-mean warming is due to the models with high sensitivity of warming to CO2 also having a very large sensitivity of clouds to aerosol changes, which acts to cool the planet over the past century. Thus, these high sensitivity models can capture observed globally-averaged warming only through a strong masking of historical CO2 warming by aerosol-induced cooling.

Because the aerosol cooling is concentrated in the northern hemisphere, the researchers were able to use the historical record of inter-hemispheric warming difference (how the northern hemisphere warms relative to the southern hemisphere) to distinguish between models with high sensitivity to CO2 (and strong historical aerosol response) and low sensitivity to CO2 (and weaker historical aerosol response). They found that the observed inter-hemispheric temperature differences are inconsistent with the high climate sensitivity models, but more consistent with the lower sensitivity models. That is, the observed pattern of historical warming argues against the plausibility of these new, extreme climate-model estimates of climate sensitivity.



Bieli, M, A.H. Sobel, S.J. Camargo, H. Murakami, and G.A. Vecchi, 2020. Application of the Cyclone Phase Space to Extratropical Transition in a Global Climate Model. J. Adv. Model. Earth Systems. (doi:10.1029/2019MS0018780).

Hsieh, T. L., G.A. Vecchi, W. Yang, I.M. Held, and S.T. Garner, 2020. Large-scale control on the frequency of tropical cyclones and seeds: a consistent relationship across a hierarchy of global atmospheric models. Clim. Dyn. (doi:10.1038/s41467- 019-08471-z).

Jacobson, T.W.P., W. Yang, G.A. Vecchi, and L.W. Horowitz, 2020. Impact of Volcanic Aerosol Hemispheric Symmetry on Sahel Rainfall. Clim. Dyn. (doi: 10.1007/s00382-020-05347-7).

Liu, M., L. Yang, J.A. Smith and G.A. Vecchi, 2020. Response of Extreme Rainfall for Landfalling Tropical Cyclones Undergoing Extratropical Transition to Projected Climate Change: Hurricane Irene (2011). Earth’s Future. (doi:10.1029/2019EF0013608).

Ng, C.H.J., and G.A. Vecchi, 2020. Large-Scale Environmental Controls on the Seasonal Statistics of Rapidly Intensifying North Atlantic Tropical Cyclones. Clim. Dyn. (doi:10.1007/ s00382-020-05207-4).

Sun, J., G.A. Vecchi and B.J. Soden, 2021. Sea Surface Salinity Response to Tropical Cyclones based on Satellite Observation. Remote Sensing. (doi: 10.3390/rs13030420).

Wang, C., B.J. Soden, W. Yang, and G.A. Vecchi, 2021. Compensation between cloud feedback and aerosol-cloud interactions in CMIP6 models. Geophys. Res. Lett. (doi:10.1029/2020GL091024).

Zhang, W., G. Villarini, and G.A. Vecchi, 2020. The East Asian Subtropical Jet Stream and Atlantic Tropical Cyclones. Geophys. Res. Lett. (doi: 10.1029/2020GL088851).