Assessing the influence of large-scale environmental conditions on rainfall structure of Atlantic tropical cyclones: An observational study

2020 ◽  
pp. 1-40
Author(s):  
Kim Dasol ◽  
Chang-Hoi Ho ◽  
Hiroyuki Murakami ◽  
Doo-Sun R. Park
Keyword(s):  
High Pressure ◽  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Tropical Cyclones ◽  
North Atlantic ◽  
Environmental Conditions ◽  
Large Scale ◽  
Environmental Flows ◽  
Sea Surface

AbstractUnderstanding the mechanisms related to the variations in the rainfall structure of tropical cyclones (TCs) is crucial in improving forecasting systems of TC rainfall and its impact. Using satellite precipitation and reanalysis data, we examined the influence of along-track large-scale environmental conditions on inner-core rainfall strength (RS) and total rainfall area (RA) for Atlantic TCs during the TC season (July to November) from 1998 to 2019. Factor analysis revealed three major factors associated with variations in RS and RA: large-scale low- and high-pressure systems (F1), environmental flows, sea surface temperature, and humidity (F2), and maximum wind speed of TCs (F3). Results from our study indicate that RS increases with an increase in the inherent primary circulation of TCs (i.e., F3), but is less affected by large-scale environmental conditions (i.e., F1 and F2), whereas RA is primarily influenced by large-scale low- and high-pressure systems (i.e., F1) over the entire North Atlantic and partially influenced by environmental flows, sea surface temperature, humidity, and maximum wind speed (i.e., F2 and F3). A multi-variable regression model based on the three factors accounted for the variations of RS and RA across the entire basin. In addition, regional distributions of mean RS and RA from the model significantly resembled those from observations. Therefore, our study suggests that large-scale environmental conditions over the North Atlantic are important predictors for TC rainfall forecasts, particularly regarding RA.

scholarly journals The Relationship between Sea Surface Temperature and Maximum Intensification Rate of Tropical Cyclones in the North Atlantic

2016 ◽  
Vol 73 (12) ◽  
pp. 4979-4988 ◽  
Author(s):  
Jing Xu ◽  
Yuqing Wang ◽  
Zhe-Min Tan
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Tropical Cyclones ◽  
North Atlantic ◽  
Empirical Relationship ◽  
Vertical Wind Shear ◽  
Sea Surface ◽  
The North ◽  
Increasing Trend ◽  
The North Atlantic

Abstract An empirical relationship between sea surface temperature (SST) and the maximum potential intensification rate (MPIR) of tropical cyclones (TCs) over the North Atlantic has been developed based on the best-track TC data and the observed SST during 1988–2014. Similar to the empirical relationship between SST and the maximum potential intensity of TCs previously documented, results from this study show a nonlinear increasing trend of the MPIR with increasing SST, with a more rapid increasing trend when SST is higher than 27°C. Further analyses indicate that about 28% of intensifying TCs over the North Atlantic reached 50% of their MPIR and only 7% reached 80% of their MPIR at the time when they were at their lifetime maximum intensification rates. Moreover, a TC tended to have a larger intensification rate when it was located in regions with higher SST and lower vertical wind shear (VWS). This indicates that although the MPIR–SST relationship is much stronger than that for the IR rate versus SST for most TCs, the actual intensification rate of a TC is determined by not only the SST but also other environmental effects, such as VWS. Additional results from a simplified dynamical system previously developed for TC intensity prediction suggest an SST-dependent TC MPIR, similar to that fitted from observations. However, the MPIR obtained from the observational fitting seems to underestimate the MPIR in regions with low SST at higher latitudes where VWS is often large. Nevertheless, this study provides the observational evidence for the existence of the MPIR for TCs.

scholarly journals North Atlantic climate variability in coupled models and data

2008 ◽  
Vol 15 (1) ◽  
pp. 13-24 ◽  
Author(s):  
S. K. Kravtsov ◽  
W. K. Dewar ◽  
M. Ghil ◽  
P. S. Berloff ◽  
J. C. McWilliams
Keyword(s):  
Climate Variability ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Large Scale ◽  
Climate Models ◽  
Three Dimensional ◽  
Sea Surface ◽  
Coupled Models ◽  
Ocean Atmosphere

Abstract. We show that the observed zonally averaged jet in the Northern Hemisphere atmosphere exhibits two spatial patterns with broadband variability in the decadal and inter-decadal range; these patterns are consistent with an important role of local, mid-latitude ocean–atmosphere coupling. A key aspect of this behaviour is the fundamentally nonlinear bi-stability of the atmospheric jet's latitudinal position, which enables relatively small sea-surface temperature anomalies associated with ocean processes to affect the large-scale atmospheric winds. The wind anomalies induce, in turn, complex three-dimensional anomalies in the ocean's main thermocline; in particular, they may be responsible for recently reported cooling of the upper ocean. Both observed modes of variability, decadal and inter-decadal, have been found in our intermediate climate models. One mode resembles North Atlantic tri-polar sea-surface temperature (SST) patterns described elsewhere. The other mode, with mono-polar SST pattern, is novel; its key aspects include interaction of oceanic turbulence with the large-scale oceanic flow. To the extent these anomalies exist, the interpretation of observed climate variability in terms of natural and human-induced changes will be affected. Coupled mid-latitude ocean-atmosphere modes do, however, suggest some degree of predictability is possible.

scholarly journals A spatiotemporal reconstruction of sea-surface temperatures in the North Atlantic during Dansgaard–Oeschger events 5–8

2018 ◽  
Vol 14 (6) ◽  
pp. 901-922 ◽  
Author(s):  
Mari F. Jensen ◽  
Aleksi Nummelin ◽  
Søren B. Nielsen ◽  
Henrik Sadatzki ◽  
Evangeline Sessford ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
General Circulation ◽  
Sea Surface ◽  
Reconstruction Method ◽  
Sea Surface Temperatures ◽  
Proxy Data ◽  
Surface Temperatures ◽  
Temperature Reconstructions

Abstract. Here, we establish a spatiotemporal evolution of the sea-surface temperatures in the North Atlantic over Dansgaard–Oeschger (DO) events 5–8 (approximately 30–40 kyr) using the proxy surrogate reconstruction method. Proxy data suggest a large variability in North Atlantic sea-surface temperatures during the DO events of the last glacial period. However, proxy data availability is limited and cannot provide a full spatial picture of the oceanic changes. Therefore, we combine fully coupled, general circulation model simulations with planktic foraminifera based sea-surface temperature reconstructions to obtain a broader spatial picture of the ocean state during DO events 5–8. The resulting spatial sea-surface temperature patterns agree over a number of different general circulation models and simulations. We find that sea-surface temperature variability over the DO events is characterized by colder conditions in the subpolar North Atlantic during stadials than during interstadials, and the variability is linked to changes in the Atlantic Meridional Overturning circulation and in the sea-ice cover. Forced simulations are needed to capture the strength of the temperature variability and to reconstruct the variability in other climatic records not directly linked to the sea-surface temperature reconstructions. This is the first time the proxy surrogate reconstruction method has been applied to oceanic variability during MIS3. Our results remain robust, even when age uncertainties of proxy data, the number of available temperature reconstructions, and different climate models are considered. However, we also highlight shortcomings of the methodology that should be addressed in future implementations.

Sign in / Sign up

Export Citation Format

Share Document