A Eulerian Explosive Cyclogenesis climatology from the ERA5 reanalysis, 1979-2018

2020 ◽  
Author(s):  
Thomas Cropper ◽  
Stephanie Allen
Keyword(s):  
Tropical Cyclones ◽  
North Atlantic ◽  
Weather Forecasting ◽  
Southern Oscillation ◽  
Medium Range ◽  
Potential Applications ◽  
Hemisphere Winter ◽  
Avalon Peninsula ◽  
Resolution Data ◽  
Northern Hemisphere Winter

<p>Using the criterion of one Bergeron (24 hPa change over 24 h at 60°), we present the creation of a Eulerian explosive cyclogenesis climatology using hourly-temporal resolution data from the European Centre for Medium Range Weather Forecasting’s ERA5 reanalysis (1979-2018). This approach differs to the typically used Lagrangian methodologies adopted by many studies. The climatology created by this approach results in similar patterns to previous studies.</p><p>Assessments on the dataset are undertaken to analyse the influence of seasonality, teleconnections, climate change and individual events (the method picks up tropical cyclones as well as mid-latitude storms). The location experiencing the most consistent explosive cyclongenesis conditions (15% of the time during the Northern Hemisphere winter) is to the east of the Avalon Peninsula, Newfoundland. The preferred location of explosive cyclogenesis is shown to change in relation to patterns such as the El Niño Southern Oscillation and North Atlantic Oscillation. Potential applications of the dataset are suggested.</p><p>                                                </p>

scholarly journals Tropical cyclone simulations over Bangladesh at convection permitting 4.4 km & 1.5 km resolution

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hamish Steptoe ◽  
Nicholas Henry Savage ◽  
Saeed Sadri ◽  
Kate Salmon ◽  
Zubair Maalick ◽  
...  
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Sea Level ◽  
Tropical Cyclones ◽  
Weather Forecasting ◽  
Sea Level Pressure ◽  
Mean Sea Level ◽  
Level Pressure ◽  
Medium Range ◽  
Gust Speed

AbstractHigh resolution simulations at 4.4 km and 1.5 km resolution have been performed for 12 historical tropical cyclones impacting Bangladesh. We use the European Centre for Medium-Range Weather Forecasting 5th generation Re-Analysis (ERA5) to provide a 9-member ensemble of initial and boundary conditions for the regional configuration of the Met Office Unified Model. The simulations are compared to the original ERA5 data and the International Best Track Archive for Climate Stewardship (IBTrACS) tropical cyclone database for wind speed, gust speed and mean sea-level pressure. The 4.4 km simulations show a typical increase in peak gust speed of 41 to 118 knots relative to ERA5, and a deepening of minimum mean sea-level pressure of up to −27 hPa, relative to ERA5 and IBTrACS data. The downscaled simulations compare more favourably with IBTrACS data than the ERA5 data suggesting tropical cyclone hazards in the ERA5 deterministic output may be underestimated. The dataset is freely available from 10.5281/zenodo.3600201.

scholarly journals An Investigation of Large Along-Track Errors in Extratropical Transitioning North Atlantic Tropical Cyclones in the ECMWF Ensemble

2020 ◽  
Vol 148 (1) ◽  
pp. 457-476
Author(s):  
Nicholas M. Leonardo ◽  
Brian A. Colle
Keyword(s):  
Tropical Cyclones ◽  
North Atlantic ◽  
Potential Vorticity ◽  
Primary Source ◽  
Initial Position ◽  
Ensemble Member ◽  
Medium Range ◽  
Moisture Fluxes ◽  
The Mean ◽  
Along Track

Abstract The synoptic evolution and mechanisms for the largest medium-range (72–120 h) along-track errors of tropical cyclones (TC) are investigated. The mean along-track errors (ATEs) of the 51-member European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble are evaluated for 393 forecasts (85 TCs) during the 2008 to 2016 North Atlantic seasons. The 27 unique forecasts within the upper quintile of most negative ATEs (i.e., slow bias greater than 500 km by 72 h) are inherently fast-moving TCs that undergo extratropical transition as they recurve and interact with a 300-hPa upstream trough and a downstream ridge. Both the trough and ridge are underamplified by only 5–10 m ~60 h before the time of largest ATE. The height errors then grow rapidly due to underpredicted 300–200-hPa potential vorticity advection by both the nondivergent wind and the irrotational wind from the TC’s outflow. Both wind components are underpredicted and result in weak biases in the trough’s developing potential vorticity gradient and associated jet streak. The underamplification of the upstream trough is exacerbated by underpredicted 700-hPa cold advection extending from beneath the trough into the TC at 48–36 h before the largest ATE. Standardized differences are consistent with the mean errors and reveal that weaker divergent outflow is driven by underpredicted near-TC precipitation, which corresponds to underpredicted 700-hPa moisture fluxes near the TC at ~108 h before the largest ATE. The ensemble member ATEs at 72–120 h generally show little correlation with their ATEs before 36 h, suggesting that initial position uncertainty is not the primary source of ATE variability later in the forecast.

scholarly journals North Atlantic Tropical Cyclones and U.S. Flooding

2014 ◽  
Vol 95 (9) ◽  
pp. 1381-1388 ◽  
Author(s):  
Gabriele Villarini ◽  
Radoslaw Goska ◽  
James A. Smith ◽  
Gabriel A. Vecchi
Keyword(s):  
United States ◽  
South Carolina ◽  
Tropical Cyclones ◽  
North Atlantic ◽  
Large Scale ◽  
Southern Oscillation ◽  
The United States ◽  
Climate Indices ◽  
Discharge Data ◽  
Flood Peaks

Riverine flooding associated with North Atlantic tropical cyclones (TCs) is responsible for large societal and economic impacts. The effects of TC flooding are not limited to the coastal regions, but affect large areas away from the coast, and often away from the center of the storm. Despite these important repercussions, inland TC flooding has received relatively little attention in the scientific literature, although there has been growing media attention following Hurricanes Irene (2011) and Sandy (2012). Based on discharge data from 1981 to 2011, the authors provide a climatological view of inland flooding associated with TCs, leveraging the wealth of discharge measurements collected, archived, and disseminated by the U.S. Geological Survey (USGS). Florida and the eastern seaboard of the United States (from South Carolina to Maine and Vermont) are the areas that are the most susceptible to TC flooding, with typical TC flood peaks that are 2 to 6 times larger than the local 10-yr flood peak, causing major flooding. A secondary swath of extensive TC-induced flooding in the central United States is also identified. These results indicate that flooding from TCs is not solely a coastal phenomenon but affects much larger areas of the United States, as far inland as Illinois, Wisconsin, and Michigan. Moreover, the authors highlight the dependence of the frequency and magnitude of TC flood peaks on large-scale climate indices, and the role played by the North Atlantic Oscillation and the El Niño–Southern Oscillation phenomenon (ENSO), suggesting potential sources of extended-range predictability.

scholarly journals Which Orographic Scales Matter Most for Medium‐Range Forecast Skill in the Northern Hemisphere Winter?

2019 ◽  
Vol 11 (12) ◽  
pp. 3893-3910 ◽  
Author(s):  
Takafumi Kanehama ◽  
Irina Sandu ◽  
Anton Beljaars ◽  
Annelize Niekerk ◽  
François Lott
Keyword(s):  
Northern Hemisphere ◽  
Forecast Skill ◽  
Medium Range Forecast ◽  
Medium Range ◽  
Hemisphere Winter ◽  
Northern Hemisphere Winter

scholarly journals Predictors of Tropical Cyclone Numbers and Extreme Hurricane Intensities over the North Atlantic Using Generalized Additive and Linear Models

2009 ◽  
Vol 22 (3) ◽  
pp. 633-648 ◽  
Author(s):  
Olivier Mestre ◽  
Stéphane Hallegatte
Keyword(s):  
Tropical Cyclones ◽  
North Atlantic ◽  
Linear Models ◽  
Southern Oscillation ◽  
Additive Models ◽  
Annual Number ◽  
The North ◽  
The North Atlantic ◽  
Energy Dissipated

Abstract Fluctuations of the annual number of tropical cyclones over the North Atlantic and of the energy dissipated by the most intense hurricane of a season are related to a variety of predictors [global temperature, SST and detrended SST, North Atlantic Oscillation (NAO), Southern Oscillation index (SOI)] using generalized additive and linear models. This study demonstrates that SST and SOI are predictors of interest. The SST is found to influence positively the annual number of tropical cyclones and the intensity of the most intense hurricanes. The use of specific additive models reveals nonlinearity in the responses to SOI that has to be taken into account using changepoint models. The long-term trend in SST is found to influence the annual number of tropical cyclones but does not add information for the prediction of the most intense hurricane intensity.

scholarly journals Complex network approach for detecting tropical cyclones

2021 ◽  
Author(s):  
Shraddha Gupta ◽  
Niklas Boers ◽  
Florian Pappenberger ◽  
Jürgen Kurths
Keyword(s):  
Sea Level ◽  
Tropical Cyclones ◽  
Complex Network ◽  
Time Scales ◽  
Southern Oscillation ◽  
Volcanic Eruptions ◽  
Network Approach ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Climate Networks

AbstractTropical cyclones (TCs) are one of the most destructive natural hazards that pose a serious threat to society, particularly to those in the coastal regions. In this work, we study the temporal evolution of the regional weather conditions in relation to the occurrence of TCs using climate networks. Climate networks encode the interactions among climate variables at different locations on the Earth’s surface, and in particular, time-evolving climate networks have been successfully applied to study different climate phenomena at comparably long time scales, such as the El Niño Southern Oscillation, different monsoon systems, or the climatic impacts of volcanic eruptions. Here, we develop and apply a complex network approach suitable for the investigation of the relatively short-lived TCs. We show that our proposed methodology has the potential to identify TCs and their tracks from mean sea level pressure (MSLP) data. We use the ERA5 reanalysis MSLP data to construct successive networks of overlapping, short-length time windows for the regions under consideration, where we focus on the north Indian Ocean and the tropical north Atlantic Ocean. We compare the spatial features of various topological properties of the network, and the spatial scales involved, in the absence and presence of a cyclone. We find that network measures such as degree and clustering exhibit significant signatures of TCs and have striking similarities with their tracks. The study of the network topology over time scales relevant to TCs allows us to obtain crucial insights into the effects of TCs on the spatial connectivity structure of sea-level pressure fields.

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