scholarly journals Sea level pressure variability over the southern Indian Ocean inferred from a glaciochemical record in Princess Elizabeth Land, east Antarctica

2004 ◽  
Vol 109 (D16) ◽  
Author(s):  
Cunde Xiao
Keyword(s):  
Indian Ocean ◽  
Sea Level ◽  
East Antarctica ◽  
Southern Indian Ocean ◽  
Sea Level Pressure ◽  
Level Pressure

scholarly journals Does sea level pressure modulate the dynamic and thermodynamic forcing in the tropical Indian Ocean?

2011 ◽  
Vol 33 (7) ◽  
pp. 1991-2002 ◽  
Author(s):  
P. G. Nisha ◽  
P. M. Muraleedharan ◽  
M. G. Keerthi ◽  
P. V. Sathe ◽  
M. Ravichandran
Keyword(s):  
Indian Ocean ◽  
Sea Level ◽  
Tropical Indian Ocean ◽  
Sea Level Pressure ◽  
Level Pressure

scholarly journals Variations in the Three-Dimensional Structure of the Atmospheric Circulation with Different Flavors of El Niño

2009 ◽  
Vol 22 (11) ◽  
pp. 2978-2991 ◽  
Author(s):  
Kevin E. Trenberth ◽  
Lesley Smith
Keyword(s):  
Indian Ocean ◽  
Sea Level ◽  
Atmospheric Circulation ◽  
El Niño ◽  
El Nino ◽  
Three Dimensional ◽  
Positive Sign ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
The Tropics

Abstract Two rather different flavors of El Niño are revealed when the full three-dimensional spatial structure of the temperature field and atmospheric circulation monthly mean anomalies is analyzed using the Japanese Reanalysis (JRA-25) temperatures from 1979 through 2004 for a core region of the tropics from 30°N to 30°S, with results projected globally onto various other fields. The first two empirical orthogonal functions (EOFs) both have primary relationships to El Niño–Southern Oscillation (ENSO) but feature rather different vertical and spatial structures. By construction the two patterns are orthogonal, but their signatures in sea level pressure, precipitation, outgoing longwave radiation (OLR), and tropospheric diabatic heating are quite similar. Moreover, they are significantly related, with EOF-2 leading EOF-1 by about 4–6 months, indicating that they play complementary roles in the evolution of ENSO events, and with each mode playing greater or lesser roles in different events and seasons. The dominant pattern (EOF-1) in its positive sign features highly coherent zonal mean warming throughout the tropical troposphere from 30°N to 30°S that increases in magnitude with height to 200 hPa, drops to zero about 100 hPa at the tropopause, and has reverse sign to 30 hPa with peak values at 70 hPa. It correlates strongly with global mean surface temperatures. EOF-2 emphasizes off-equatorial centers of action and strong Rossby wave temperature signatures that are coherent throughout the troposphere, with the strongest values in the Pacific that extend into the extratropics and a sign reversal at and above 150 hPa. Near the surface, both patterns feature boomerang-shaped opposite temperatures in the western tropical and subtropical Pacific, with similar sea level pressure patterns, but with EOF-1 more focused in equatorial regions. Both patterns are strongest during the boreal winter half-year when anomalous precipitation in the tropics and associated latent heating drive teleconnections throughout the world. For El Niño in northern winter EOF-1 has more precipitation in the eastern tropical Pacific, while EOF-2 has much drier conditions over northern Australia and the Indian Ocean. In northern summer, the main differences are in the South Pacific and Indian Ocean. Differences in teleconnections suggest great sensitivity to small changes in forcings in association with seasonal variations in the mean state.

scholarly journals Strong Wind Speed Events over Antarctica and Its Surrounding Oceans

2019 ◽  
Vol 32 (12) ◽  
pp. 3451-3470 ◽  
Author(s):  
Lejiang Yu ◽  
Shiyuan Zhong
Keyword(s):  
Wind Speed ◽  
Sea Level ◽  
Surface Wind ◽  
Coastal Region ◽  
Southern Annular Mode ◽  
East Antarctica ◽  
Strong Wind ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Wind Events

AbstractStrong wind events (SWEs) over Antarctica and its surrounding oceans are investigated using gridded surface wind data from the ERA-Interim for the 1979–2017 period. Throughout the year, SWEs are more prevalent over the coastal region of East Antarctica where mean surface wind speeds are also higher. The occurrences of SWEs appear to be accompanied by positive anomalies in surface temperature and negative (positive) anomalies in mean sea level pressure related to cyclone (anticyclone) activity over the Ronne and Ross Ice Shelves and coastal regions (the inland areas of East Antarctica). The interannual variability of the SWE occurrences appears to be related to the southern annular mode (SAM) and, to a lesser degree, ENSO. The trends of SWE in the recent four decades exhibit considerable regional variations that are consistent with the trends in seasonal mean wind speed and surface air temperature, and can be largely explained by the variations in the sea level pressure trends across the region.

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.

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 Analysis of Atmospheric and Ionospheric Variations Due to Impacts of Super Typhoon Mangkhut (1822) in the Northwest Pacific Ocean

2021 ◽  
Vol 13 (4) ◽  
pp. 661
Author(s):  
Mohamed Freeshah ◽  
Xiaohong Zhang ◽  
Erman Şentürk ◽  
Muhammad Arqim Adil ◽  
B. G. Mousa ◽  
...  
Keyword(s):  
Wind Speed ◽  
Pacific Ocean ◽  
Tropical Cyclone ◽  
Sea Level ◽  
Northwest Pacific ◽  
Northwest Pacific Ocean ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Super Typhoon ◽  
The Northwest Pacific Ocean

The Northwest Pacific Ocean (NWP) is one of the most vulnerable regions that has been hit by typhoons. In September 2018, Mangkhut was the 22nd Tropical Cyclone (TC) over the NWP regions (so, the event was numbered as 1822). In this paper, we investigated the highest amplitude ionospheric variations, along with the atmospheric anomalies, such as the sea-level pressure, Mangkhut’s cloud system, and the meridional and zonal wind during the typhoon. Regional Ionosphere Maps (RIMs) were created through the Hong Kong Continuously Operating Reference Stations (HKCORS) and International GNSS Service (IGS) data around the area of Mangkhut typhoon. RIMs were utilized to analyze the ionospheric Total Electron Content (TEC) response over the maximum wind speed points (maximum spots) under the meticulous observations of the solar-terrestrial environment and geomagnetic storm indices. Ionospheric vertical TEC (VTEC) time sequences over the maximum spots are detected by three methods: interquartile range method (IQR), enhanced average difference (EAD), and range of ten days (RTD) during the super typhoon Mangkhut. The research findings indicated significant ionospheric variations over the maximum spots during this powerful tropical cyclone within a few hours before the extreme wind speed. Moreover, the ionosphere showed a positive response where the maximum VTEC amplitude variations coincided with the cyclone rainbands or typhoon edges rather than the center of the storm. The sea-level pressure tends to decrease around the typhoon periphery, and the highest ionospheric VTEC amplitude was observed when the low-pressure cell covers the largest area. The possible mechanism of the ionospheric response is based on strong convective cells that create the gravity waves over tropical cyclones. Moreover, the critical change state in the meridional wind happened on the same day of maximum ionospheric variations on the 256th day of the year (DOY 256). This comprehensive analysis suggests that the meridional winds and their resulting waves may contribute in one way or another to upper atmosphere-ionosphere coupling.

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