scholarly journals Diurnal Rainfall On Tropical Cyclone Cempaka And Dahlia As Observed By TRMM

Megasains ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 42-45
Author(s):  
REZA BAYU PERDANA
Keyword(s):  
Time Series ◽  
Tropical Cyclone ◽  
Tropical Rainfall Measurement Mission ◽  
Tropical Rainfall ◽  
Diurnal Rainfall

Dua siklon tropis teramati di perairan bagian selatan Indonesia pada akhir 2017, menjadi siklon tropis pertama dan kedua yang terjadi di wilayah tanggung jawab Indonesia setelah siklon tropis Bakung pada 2010. Siklon tropis Cempaka terbentuk di perairan sebelah selatan Provinsi Jawa Tengah dan menyebabkan curah hujan tinggi di wilayah selatan pulau Jawa. Siklon tropis Dahlia terbentuk di sebelah selatan Provinsi Banten dengan pengaruh yang lebih kecil terhadap curah hujan di daratan disebabkan jarak yang lebih jauh. Tujuan dari penelitian ini adalah untuk mengetahui siklus harian curah hujan yang terjadi pada kedua siklon tropis tersebut, serta siklus harian yang terjadi pada wilayah terdampak saat terjadi siklon tropis. Data yang digunakan pada penelitian ini adalah curah hujan rata-rata per tiga jam dari Tropical Rainfall Measurement Mission (TRMM), khususnya data 3B42RT. Metode yang digunakan pada penelitian ini adalah analisis time series. Hasil dari penelitian ini menunjukkan bahwa ketika terjadi siklon tropis, curah hujan mencapai puncak pada malam sampai dini hari, kemudian melemah pada pagi sampai sore hari. Pada daerah terdampak di daratan, puncak hujan terjadi pada siang dan malam hari, dan melemah pada sore dan dini hari.

scholarly journals Seasonal Nature and Trends of Tropical Cyclone Frequency and Intensity over the North Indian Ocean

2020 ◽  
Vol 15 (3) ◽  
pp. 526-534
Author(s):  
Abhisek Pal ◽  
Soumendu Chatterjee
Keyword(s):  
Time Series ◽  
Tropical Cyclone ◽  
Indian Ocean ◽  
Monsoon Season ◽  
North Indian Ocean ◽  
Post Monsoon ◽  
The North ◽  
Increasing Trend ◽  
Post Monsoon Season ◽  
Cyclone Frequency

Tropical cyclone (TC) genesis over the North Indian Ocean (NIO) region showed significant amount of both spatial and temporal variability.It was observed that the TC genesis was significantly suppressed during the monsoon (June-September) compared to pre-monsoon (March-May) and post-monsoon (October-December) season specifically in terms of severe cyclonic storms (SCS) frequency. The Bay of Bengal (BoB) was characterized by higher TC frequency but lower intensity compared to the Arabian Sea (AS). It was also observed that the TC genesis locations were shifted significantly seasonally.The movement of the TCs also portrayed some significant seasonal differences. The pre-monsoon and post-monsoon season was responsible for generating TCs with higher values of accumulated cyclone energy (ACE) compared to the monsoon. The time series of TC frequency showed a statistically significant decreasing trend whereas the time series of ACE showed astatistically significant increasing trend over the NIO.

scholarly journals Dynamic wavelet correlation analysis for multivariate climate time series

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Josué M. Polanco-Martínez ◽  
Javier Fernández-Macho ◽  
Martín Medina-Elizalde
Keyword(s):  
Time Series ◽  
Tropical Cyclone ◽  
North Atlantic ◽  
Large Scale ◽  
Southern Oscillation ◽  
Atlantic Multidecadal Oscillation ◽  
Last Millennium ◽  
Climate Data ◽  
The North ◽  
Climate Time Series

AbstractThe wavelet local multiple correlation (WLMC) is introduced for the first time in the study of climate dynamics inferred from multivariate climate time series. To exemplify the use of WLMC with real climate data, we analyse Last Millennium (LM) relationships among several large-scale reconstructed climate variables characterizing North Atlantic: i.e. sea surface temperatures (SST) from the tropical cyclone main developmental region (MDR), the El Niño-Southern Oscillation (ENSO), the North Atlantic Multidecadal Oscillation (AMO), and tropical cyclone counts (TC). We examine the former three large-scale variables because they are known to influence North Atlantic tropical cyclone activity and because their underlying drivers are still under investigation. WLMC results obtained for these multivariate climate time series suggest that: (1) MDRSST and AMO show the highest correlation with each other and with respect to the TC record over the last millennium, and: (2) MDRSST is the dominant climate variable that explains TC temporal variability. WLMC results confirm that this method is able to capture the most fundamental information contained in multivariate climate time series and is suitable to investigate correlation among climate time series in a multivariate context.

scholarly journals Quantifying the statistical distribution of Tropical Cyclone Activity in the historical record of the Dominican Republic

2017 ◽  
Vol 21 (4) ◽  
pp. 159-167
Author(s):  
Santo Trinidad Alvarez Ysabel ◽  
Gustavo Adolfo Agredo Cardona ◽  
David Felipe Rincón
Keyword(s):  
Time Series ◽  
Tropical Cyclone ◽  
Dominican Republic ◽  
Tropical Cyclone Activity ◽  
Seasonal Distribution ◽  
Caribbean Basin ◽  
Cyclone Activity ◽  
Long Time ◽  
The Caribbean ◽  
Tropical Cyclone Tracks

 In this study, we re-examined the Official Hurricane Database from the National Hurricane Center (HURDAT-NHC), an agency associated with NOAA, for tropical cyclone activity from 1851 to 2012for the Dominican Republic on the island of Hispaniola in the Caribbean Basin.  We performed analyses at two different levels for the island (i.e., all of the storm tracks in the Caribbean Basin near to the study area that made landfall and all of the events that crossed the Dominican Republic from a radius of 300 km from the coastline). This study includes the statistical occurrence of these phenomena during the study period and the climatological analysis of all tropical cyclone tracks (112 total events) by decadal seasonal distribution, fifty-year seasonal distribution and monthly seasonal distribution to show the lowest and highest activities. We performed wavelet analysis on the continuous data over a long time series to determine the important frequencies. This analysis provided a general statistical conclusion resulting from the data collected. A landfall probability for the study area corresponding to the long time series of (it’s 162) years within a radius of ~100, ~185 and ~300 km, based on the historical climatology tropical cyclone tracks, reveals the likelihood of a strike for a major or a minor hurricane. We present a review of the tropical cyclone activities that passed the Dominican Republic, which also forms part of the author’s dissertation. 

Exploring Temporal Rainfall Variability and Trends Over a Tropical Region Using Tropical Rainfall Measurement Mission (TRMM) and Observatory Data

2021 ◽  
Vol 5 (2) ◽  
pp. 56-71
Author(s):  
Anu David Raj ◽  
K. R. Sooryamol ◽  
Aju David Raj
Keyword(s):  
Time Scales ◽  
Water Resource Management ◽  
Rainfall Variability ◽  
Winter Season ◽  
India Meteorological Department ◽  
Southwest Monsoon ◽  
Rainfall Data ◽  
Tropical Rainfall Measurement Mission ◽  
Tropical Rainfall ◽  
Observatory Data

Kerala is the gateway of the Indian southwest monsoon. The Tropical Rainfall Measurement Mission (TRMM) rainfall data is an efficient approach to rainfall measurement. This study explores the temporal variability in rainfall and trends over Kerala from 1998-2019 using TRMM data and observatory data procured from India Meteorological Department (IMD). Direct comparison with observatory data at various time scales proved the reliability of the TRMM data (monthly, seasonal and annual). The temporal rainfall converted by averaging the data on an annual, monthly and seasonal time scale, and the results have confirmed that the rainfall estimated based on satellite data is dependable. The station wise comparison of rainfall in monsoon season provides satisfactory results. However, estimation of rainfall in mountainous areas is challenging task using the TRMM. In the basins of humid tropical regions, TRMM data can be a valuable source of rainfall data for water resource management and monitoring with some vigilance. In Kerala, the study found an insignificant increase in the southwest monsoon and winter season rainfall during last two decades. The rainfall over Kerala showed uncertainty in the distribution of monthly, seasonal and yearly time scales. This study provides a preview of recent weather patterns that would enable us to make better decisions and improve public policy against climate change.

scholarly journals Quantifying Interagency Differences in Tropical Cyclone Best-Track Wind Speed Estimates

2010 ◽  
Vol 138 (4) ◽  
pp. 1459-1473 ◽  
Author(s):  
Kenneth R. Knapp ◽  
Michael C. Kruk
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Tropical Cyclone ◽  
Temporal Changes ◽  
Data Availability ◽  
Spatially Inhomogeneous ◽  
The World ◽  
Using Data ◽  
Over Time

Abstract Numerous agencies around the world perform postseason analysis of tropical cyclone position and intensity, a process described as “best tracking.” However, this process is temporally and spatially inhomogeneous because data availability, operational techniques, and knowledge have changed over time and differ among agencies. The net result is that positions and intensities often vary for any given storm for different agencies. In light of these differences, it is imperative to analyze and document the interagency differences in tropical cyclone intensities. To that end, maximum sustained winds from different agencies were compared using data from the International Best Track Archive for Climate Stewardship (IBTrACS) global tropical cyclone dataset. Comparisons were made for a recent 5-yr period to investigate the current differences, where linear systematic differences were evident. Time series of the comparisons also showed temporal changes in the systematic differences, which suggest changes in operational procedures. Initial attempts were made to normalize maximum sustained winds by correcting for known changes in operational procedures. The result was mixed, in that the adjustments removed some but not all of the systematic differences. This suggests that more details on operational procedures are needed and that a complete reanalysis of tropical cyclone intensities should be performed.

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