Hurricanes and Climate Change by James B. Elsner Robert E. Hodges Jill C. Malmstadt & Kelsey N. Scheitlin

Author:James B. Elsner, Robert E. Hodges, Jill C. Malmstadt & Kelsey N. Scheitlin
Language: eng
Format: epub
Publisher: Springer Netherlands, Dordrecht

Fig. 4Scatter plot of daily Mg II core-to-wing ratio values and SSN. The correlation between the two variables is + 0.9

The impact of changes in UV radiation on upper tropospheric temperature is a fast process. Hood (2003) notes that tropical tropopause ( ∼ 15 km) temperatures vary in phase with incoming UV at a zero-day lag. As such the UV impact on hurricane is better represented on a short time scale compared with the sun’s influence on warming the oceans, which occurs on a monthly to yearly timescale. Thus, if EJ08 are correct, we should be able to detect an immediate solar influence on hurricanes by using changes in UV radiation caused by the 27-day solar rotational period.

We do this by defining solar activity during the hurricane season as anomalous if the August–October SSN is substantially different from the SSN during the months of May–July and November. Formally, let , where SSNMJJN is the sunspot number averaged over May, June, July, and November, and SSNASO is the sunspot number averaged over August through October. Negative (positive) anomalies indicate solar activity during the hurricane season is greater (less) than the solar activity during the months prior to and after the season. In general, positive anomalies arise during hurricane seasons when the Schwabe cycle is near a peak but sunspot numbers are relatively low during August, September, or October in response to the phase and intensity of the 27-day solar rotation. Negative anomalies arise during hurricane seasons when the Schwabe cycle is near a trough but sunspot numbers are relatively high during August, September, or October. Thus there is a inverse relationship between total SSN during the hurricane season and the SSN anomaly as defined here.

Hurricane season peripheral month (May, June, July, November) SSN averages reflect the 11-year Schwabe cycle position most directly. It also demonstrates intraseasonal SST variability (Dima et al. 2005), and core month (August, September, October) SSN averages describe the impact of increased upper-level temperatures from increased UV radiation, decreasing a storm’s environmental thermodynamic efficiency and, thus, maximum potential intensity (Emanuel 1988; Holland 1997; EJ08). Therefore, hurricane seasons characterized by positive SSN anomalies (higher inflow temperature and colder outflow temperatures) should correspond with greater hurricane activity.

Table 1 lists the top and bottom 10 hurricane seasons according to the value of the SSN anomaly using the years 1851–2008. The list includes the estimated number of U.S. and major U.S. hurricanes by year along with anomaly values of other covariates known to be related to hurricane activity. These covariates include the NAO (averaged over May and June prior to the hurricane season), the SOI (averaged over the hurricane season months of June through November), and North Atlantic SST (averaged over June through November). The NAO is a precursor signal for hurricane steering and the SOI is an indicator of the El Ninõ-Southern Oscillation and therefore wind shear and subsidence over the tropical Atlantic. Data for the SOI is available back only to 1866. Table 1SSN anomalies and U.S. hurricanes: 1851–2008. The

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