Is the Poleward Migration of Tropical Cyclone Maximum Intensity Associated with a Poleward Migration of Tropical Cyclone Genesis?
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Clim Dyn DOI 10.1007/s00382-017-3636-7 Is the poleward migration of tropical cyclone maximum intensity associated with a poleward migration of tropical cyclone genesis? Anne Sophie Daloz1 · Suzana J. Camargo2 Received: 29 November 2016 / Accepted: 16 March 2017 © Springer-Verlag Berlin Heidelberg 2017 Abstract A recent study showed that the global average 1 Introduction latitude where tropical cyclones achieve their lifetime- maximum intensity has been migrating poleward at a rate Kossin et al. (2014) showed that in the past few dec- of about one-half degree of latitude per decade over the last ades (1982–2009) the large-scale environment of tropi- 30 years in each hemisphere. However, it does not answer cal cyclones has evolved over the tropics and subtropics. a critical question: is the poleward migration of tropical Indeed, favorable conditions for the development of tropical cyclone lifetime-maximum intensity associated with a pole- cyclones have migrated towards higher latitudes (vertical ward migration of tropical cyclone genesis? In this study wind shear and potential intensity), moving from the trop- we will examine this question. First we analyze changes ics closer to the subtropics. With a globally homogenized in the environmental variables associated with tropical record of intensity (Kossin et al. 2013) and a global best- cyclone genesis, namely entropy deficit, potential intensity, track archive (Knapp et al. 2010), they also demonstrated vertical wind shear, vorticity, skin temperature and specific that the location where observed tropical cyclones reach humidity at 500 hPa in reanalysis datasets between 1980 their maximum intensity has been migrating towards higher and 2013. Then, a selection of these variables is combined latitudes. More recently, Kossin et al. (2016) used observa- into two tropical cyclone genesis indices that empirically tions and simulations to examine the changes in lifetime- relate tropical cyclone genesis to large-scale variables. We maximum intensity and tropical cyclone exposure for the find a shift toward greater (smaller) average potential num- present and future climates over the western North Pacific ber of genesis at higher (lower) latitudes over most regions Ocean. The projections of tropical cyclones were simu- of the Pacific Ocean, which is consistent with a migration lated by, and downscaled from, an ensemble of numerical of tropical cyclone genesis towards higher latitudes. We Coupled Model Intercomparison Project Phase 5 (CMIP5) then examine the global best track archive and find coher- models (Taylor et al. 2012). They showed a poleward ent and significant poleward shifts in mean genesis position migration of lifetime-maximum intensity (LMI) latitude in over the Pacific Ocean basins. the present century and continuing into the future using one of the representative concentration pathways (RCP8.5). A Keywords Tropical cyclone genesis · Poleward possible mechanism responsible for these global and local migration · Tropical cyclone genesis index · Observations changes is the expansion of the tropics (Lucas et al. 2014), however this link has not been proved yet. The current study expands on the findings by Kossin * Anne Sophie Daloz et al. (2014, 2016) by analyzing the possible origin of the [email protected] poleward migration of the LMI latitude. More precisely, we Is the pole- 1 Space and Science Engineering Center, University would like to answer the following question: of Wisconsin-Madison, 1225 West Dayton Street, Madison, ward migration of tropical cyclones’ LMI location related WI 53706, USA to a poleward migration in tropical cyclone genesis loca- 2 Lamont-Doherty Earth Observatory, Columbia University, tion? Tropical cyclones are very sensitive to the large-scale Palisades, NY, USA environment both during their genesis and development Vol.:(0123456789)1 3 A. S. Daloz, S. J. Camargo stage. A reasonable hypothesis is that the poleward migra- indices, the Genesis potential index (GPI) and the tropical tion of the favorable large-scale environment would modify cyclone genesis index (TCGI). Emanuel and Nolan (2004) not only the position where tropical cyclones reach their developed the original GPI based on potential intensity (PI; maximum intensity but also shift the location of tropi- Bister and Emanuel 1998) rather than SST in order to avoid cal cyclone genesis to higher latitudes. A recent study by the use of a specific threshold that could potentially vary Colbert et al. (2013) showed that changes in the large-scale with global warming. PI is the theoretical maximum inten- environment of tropical cyclones could modify the genesis sity that a tropical cyclone can reach under specific environ- location, leading to changes in the occurrence of recurving mental conditions as defined in Emanuel (1988). A revised storm tracks. version of the GPI, that is used in this study is described Kossin et al. (2014) argues that by restricting their in Emanuel (2010). The main difference between the two analysis of tropical cyclone data to the lifetime-maximum versions of GPI is the dependence on water vapor, which intensity only, instead of the full storm track, mitigates included the relative humidity on the original GPI, but now the uncertainty existent in observed tropical cyclone data. considers the entropy deficit (Emanuel 2008). We also con- In this study we consider observed tropical cyclone gen- sider the tropical cyclone genesis index, or TCGI (Tippett esis, therefore reintroducing some inherent uncertainty in et al. 2011; Camargo et al. 2014). The original TCGI devel- our analysis. Indeed, the reliability of the tropical cyclone oped in Tippett et al. (2011) compares positively with the tracks archives is problematic as discussed in many studies GPI. The main difference between the GPI and the TCGI is (e.g. Kamahori et al. 2006; Lander 2008; Knapp and Kruk their different functional dependence; as the TCGI is based 2010). One well known problem of observed TC tracks is on a Poison regression, it has an exponential dependence the presence of data inhomogeneity due to the introduc- on the environmental variables. Furthermore, the deriva- tion of aircraft and satellite observations. Therefore, we tion of the TCGI can be reproduced and redone with any will restrict our analysis to the period after 1980 in order to combination of environmental variables and observed TC mitigate these biases. Another important issue is that sev- data. Camargo et al. (2014) showed that in order to repli- eral centers use different averaging periods for measuring cate the projections of the reduction in the frequency of tropical cyclone wind speed, as well different thresholds tropical cyclones under a warming climate, it was neces- for genesis. Here we will use a common global threshold sary to use as predictors for the TCGI the column satura- in our definition of tropical cyclone genesis as explained in tion deficit and PI instead of relative humidity and relative Sect. 2. As storms are more accurately monitored at their SST, as considered in Tippett et al. (2011). An intercom- peak than at the beginning of their lifetime, when they parison among four genesis indices including the GPI and are weaker, we are aware that considering observed tropi- the TCGI by Menkes et al. (2012) revealed that the impact cal cyclone genesis data has its caveats. Therefore, we also of using different reanalysis datasets for deriving the indi- analyze the possible changes in environmental variables ces is much weaker than using different indices. They also and tropical cyclone genesis indices in order to increase the showed that the indices have some skill in representing the robustness and confidence of our results. meridional distribution of genesis. With exception of the Previous studies have investigated the relationship TCGI, genesis indices usually have a meridional distribu- between climate and tropical cyclone activity using indi- tion that is too broad extending too close to the Equator. ces that relate large-scale environmental conditions to On the other hand, the GPI has the best interhemispheric the number of tropical cyclone genesis. These indices are balance in the frequency of tropical cyclones. One impor- known as genesis indices and are based on the empirical tant drawback from these indices is that they only provide relationship between several environmental factors and insights on the relationship between the large-scale envi- the occurrence of tropical cyclone genesis. Gray (1979) ronment and tropical cyclone genesis, but do not include developed the first genesis index, called genesis potential other important local influences, such as African easterly (GP) index. The predictors included sea surface tempera- waves. ture (SST), mid-level relative humidity, vertical wind shear First, we examine the changes in the environment of and low-level vorticity to represent tropical cyclone genesis tropical cyclones in the past three decades (1980–2013) climatology. The index was able to reproduce key features in two reanalysis datasets to determine if there has been a of observed genesis climatology. Since then, several other poleward shift in the regions favorable for tropical cyclone indices have been created using different predictors or dif- genesis. Tropical cyclones genesis and intensification are ferent functional dependences (DeMaria et al. 2001; Royer influenced by environmental variables such as vertical et al. 1998; Sall et al. 2006; Bye and Keay 2008; Kotal wind shear, vorticity, humidity, SST and PI (Gray 1979; et al. 2009; Murakami and Wang 2010; Bruyère et al. 2012; Emanuel 1988; Bister and Emanuel 1998). These large- Tang and Emanuel 2012; Holland and Bruyère 2014; Tang scale environmental variables could potentially evolve with and Camargo 2014). In this study, we focus on two of these the expansion of the tropics, and, therefore, modify global 1 3 Is the poleward migration of tropical cyclone maximum intensity associated with a poleward… tropical cyclone activity. An increase (decrease) in PI, The selection of genesis points in the best track data SST, vorticity or humidity (vertical wind shear) is known over each basin is not a trivial procedure.