A Destructive Tropical Cyclone Season in the Sw Indian Ocean: January-February 1984

Abstract This study investigates the predictability of tropical cyclone (TC) seasonal count anomalies using the Centro Euro-Mediterraneo per i Cambiamenti Climatici–Istituto Nazionale di Geofisica e Vulcanologia (CMCC-INGV) Seasonal Prediction System (SPS). To this aim, nine-member ensemble forecasts for the period 1992–2001 for two starting dates per year were performed. The skill in reproducing the observed TC counts has been evaluated after the application of a TC location and tracking detection method to the retrospective forecasts. The SPS displays good skill in predicting the observed TC count anomalies, particularly over the tropical Pacific and Atlantic Oceans. The simulated TC activity exhibits realistic geographical distribution and interannual variability, thus indicating that the model is able to reproduce the major basic mechanisms that link the TCs’ occurrence with the large-scale circulation. TC count anomalies prediction has been found to be sensitive to the subsurface assimilation in the ocean for initialization. Comparing the results with control simulations performed without assimilated initial conditions, the results indicate that the assimilation significantly improves the prediction of the TC count anomalies over the eastern North Pacific Ocean (ENP) and northern Indian Ocean (NI) during boreal summer. During the austral counterpart, significant progresses over the area surrounding Australia (AUS) and in terms of the probabilistic quality of the predictions also over the southern Indian Ocean (SI) were evidenced. The analysis shows that the improvement in the prediction of anomalous TC counts follows the enhancement in forecasting daily anomalies in sea surface temperature due to subsurface ocean initialization. Furthermore, the skill changes appear to be in part related to forecast differences in convective available potential energy (CAPE) over the ENP and the North Atlantic Ocean (ATL), in wind shear over the NI, and in both CAPE and wind shear over the SI.

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Extended Prediction of North Indian Ocean Tropical Cyclones

Weather and Forecasting ◽

10.1175/waf-d-11-00083.1 ◽

2012 ◽

Vol 27 (3) ◽

pp. 757-769 ◽

Cited By ~ 31

Author(s):

James I. Belanger ◽

Peter J. Webster ◽

Judith A. Curry ◽

Mark T. Jelinek

Keyword(s):

Tropical Cyclone ◽

Indian Ocean ◽

Tropical Cyclones ◽

North Indian Ocean ◽

Ensemble Prediction ◽

Tropical Cyclone Genesis ◽

Lead Times ◽

Prediction System ◽

Ensemble Prediction System ◽

The North

Abstract This analysis examines the predictability of several key forecasting parameters using the ECMWF Variable Ensemble Prediction System (VarEPS) for tropical cyclones (TCs) in the North Indian Ocean (NIO) including tropical cyclone genesis, pregenesis and postgenesis track and intensity projections, and regional outlooks of tropical cyclone activity for the Arabian Sea and the Bay of Bengal. Based on the evaluation period from 2007 to 2010, the VarEPS TC genesis forecasts demonstrate low false-alarm rates and moderate to high probabilities of detection for lead times of 1–7 days. In addition, VarEPS pregenesis track forecasts on average perform better than VarEPS postgenesis forecasts through 120 h and feature a total track error growth of 41 n mi day−1. VarEPS provides superior postgenesis track forecasts for lead times greater than 12 h compared to other models, including the Met Office global model (UKMET), the Navy Operational Global Atmospheric Prediction System (NOGAPS), and the Global Forecasting System (GFS), and slightly lower track errors than the Joint Typhoon Warning Center. This paper concludes with a discussion of how VarEPS can provide much of this extended predictability within a probabilistic framework for the region.

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Progress toward Cloud-Cleared Infrared radiance assimilation in a global modeling framework: Application to the 2017 Atlantic Tropical Cyclone Season.

10.5194/egusphere-egu21-2870 ◽

2021 ◽

Author(s):

Niama Boukachaba ◽

Oreste Reale ◽

Erica L. McGrath-Spangler ◽

Manisha Ganeshan ◽

Will McCarty ◽

...

Keyword(s):

Tropical Cyclone ◽

Strong Impact ◽

Modeling Framework ◽

Atmospheric Infrared Sounder ◽

Clear Sky ◽

Earth Observing System ◽

Infrared Radiance ◽

Radiance Assimilation ◽

The Impact ◽

Tropical Cyclone Season

<p>Previous work by this team has demonstrated that assimilation of IR radiances in partially cloudy regions is beneficial to numerical weather predictions (NWPs), improving the representation of tropical cyclones (TCs) in global analyses and forecasts. The specific technique used by this team is based on the &#8220;cloud-clearing CC&#8221; methodology. Cloud-cleared hyperspectral IR radiances (CCRs), if thinned more aggressively than clear-sky radiances, have shown a strong impact on the analyzed representation and structure of TCs. However, the use of CCRs in an operational context is limited by 1) latency; and 2) external dependencies present in the original cloud-clearing algorithm. In this study, the Atmospheric InfraRed Sounder (AIRS) CC algorithm was (a) ported to NASA high end computing resources (HEC), (b) deprived of external dependencies, and (c) parallelized improving the processing by a factor of 70. The revised AIRS CC algorithm is now customizable, allowing user&#8217;s choice of channel selection, user&#8217;s model's fields as first guess, and could perform in real time. This study examines the benefits achieved when assimilating CCRs using the NASA&#8217;s Goddard Earth Observing System (GEOS) hybrid 4DEnVar system. The focus is on the 2017 Atlantic hurricane season with three infamous hurricanes (Harvey, Irma, and Maria) investigated in depth.&#160; The impact of assimilating customized CCRs on the analyzed representation of tropical cyclone horizontal and vertical structure and on forecast skill is discussed.</p>

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On the Tropical Cyclone Activity and Associated Environmental Features over North Indian Ocean in the Context of Climate Change

Journal of Climate Change ◽

10.3233/jcc-150001 ◽

2015 ◽

Vol 1 (1,2) ◽

pp. 1-26 ◽

Cited By ~ 9

Author(s):

M. Mohapatra ◽

B. Geetha ◽

S. Balachandran ◽

L.S. Rathore

Keyword(s):

Climate Change ◽

Tropical Cyclone ◽

Indian Ocean ◽

North Indian Ocean ◽

Tropical Cyclone Activity ◽

Cyclone Activity ◽

Environmental Features

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

Current World Environment ◽

10.12944/cwe.15.3.16 ◽

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.

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