India's Ocean Observation Network: Relevance to Society

AbstractSustained and real-time ocean observation systems using moored data buoys are vital for understanding ocean dynamics and the variability required for improving oceanographic services, including weather prediction, ocean state forecast, and climate change studies. This paper presents the effectiveness of India's moored data buoy network in capturing the response in the ocean during the cyclonic disturbances formed in the Bay of Bengal (BoB) and the Arabian Sea (AS) during the last 5-year period. The moored buoy network provided critical information about the evolution and intensification of low-pressure systems and supported the India Meteorological Department to improve prediction capabilities by incorporating real-time data. The lowest mean sea-level pressure of 920 hPa was recorded in the BoB during the very severe cyclonic storm Phailin. The warning systems adopted for the effective dissemination of the ocean forecast services to the user community have significantly reduced the loss of life and property in coastal states.

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Best Practices for Increasing Data Return: Case Study From Indian Ocean Observation Network

Marine Technology Society Journal ◽

10.4031/mtsj.53.5.17 ◽

2019 ◽

Vol 53 (5) ◽

pp. 30-42

Author(s):

Ramasamy Venkatesan ◽

Manickavasagam Arul Muthiah ◽

Gopalakrishnan Vengatesan ◽

Balakrishnan Kesavakumar ◽

Narayanaswamy Vedachalam

Keyword(s):

Indian Ocean ◽

Weather Prediction ◽

Ocean Dynamics ◽

Observation Network ◽

Observation Systems ◽

Restoration Techniques ◽

Rapid Restoration ◽

Cyclone Tracking ◽

The Indian Ocean

AbstractSustained real-time ocean observation systems using moored data buoys are vital for understanding ocean dynamics and variability, which are essential for improving oceanographic services including weather prediction, ocean state forecast, cyclone tracking, tsunami monitoring, and climate change studies. This paper describes the significant rapid restoration techniques implemented to increase the availability of the Indian Ocean observation networks over the past two decades. The efforts have helped in achieving availability of 97.9%, 82.3%, and 98.7% for the meteorological sensors, subsea surface oceanographic sensors, and tsunami buoy network, respectively.

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Implementation of a Real-time Data Display System for a Catchment Scale Automated Weather Observation Network

Korean Journal of Agricultural and Forest Meteorology ◽

10.5532/kjafm.2013.15.4.304 ◽

2013 ◽

Vol 15 (4) ◽

pp. 304-311 ◽

Cited By ~ 3

Author(s):

Myung Ryong Jung ◽

Jin-Hee Kim ◽

Young Eel Moon ◽

Jin I. Yun

Keyword(s):

Real Time ◽

Data Display ◽

Display System ◽

Time Data ◽

Catchment Scale ◽

Observation Network ◽

Real Time Data ◽

Weather Observation

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Verification of real-time WRF-ARW forecast in IMD during monsoon 2010

MAUSAM ◽

10.54302/mausam.v67i2.1301 ◽

2021 ◽

Vol 67 (2) ◽

pp. 333-356

Author(s):

ANANDA K. DAS ◽

P. K. KUNDU ◽

S. K. ROY BHOWMIK ◽

M. RATHEE

Keyword(s):

Real Time ◽

Meteorological Parameters ◽

Mesoscale Model ◽

Monsoon Season ◽

Weather Prediction ◽

India Meteorological Department ◽

Forecast Errors ◽

Orographic Rainfall ◽

Skill Scores ◽

Model Efficiency

Performance of the mesoscale model WRF-ARW has been evaluated for whole monsoon season of 2011. The real-time model forecasts are generated day to day in India meteorological Department for short-range weather prediction over the Indian region. Verification of rainfall forecasts has been carried out against observed rainfall analysis whereas for all other meteorological parameters verification analysis which was generated using WRFDA assimilation system. Traditional continuous scores and categorical skill scores are computed over seven different zones in India in the verification of rainfall. For other parameters (upper-air as well as surface), continuous scores are evaluated with temporal and spatial features during whole season. The forecast errors of meteorological parameters other than rainfall are analyzed to portray the model efficiency in maintaining monsoon features in large scale along with localized pattern. In the study, time series of errors throughout the season also has been maneuvered to evaluate model forecasts during diverse phases of monsoon. Categorical scores suggest the model forecasts are reliable up to moderate rainfall category for all seven zones. But, rainfall areas with rainfall above 35.5 mm per day associated with migrated weather system from Indian seas could not be predicted as the model displaces them in the forecast. The verification for a whole monsoon season has shown that the model has capability to predict orographic rainfall for the interactive areas with low level monsoon flow over Western Ghats. The model efficiency are in general brought out for a single monsoon season and errors characteristics are discussed for further improvement which could not perceived during real-time use of the model.

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Real-time mesoscale modeling for short range prediction of weather over Maitri region in Antarctica

MAUSAM ◽

10.54302/mausam.v62i4.339 ◽

2021 ◽

Vol 62 (4) ◽

pp. 535-546

Author(s):

S.K.ROY BHOWMIK ◽

ANUPAM KUMAR ◽

ANANDA K.DAS

Keyword(s):

Real Time ◽

Case Studies ◽

Sea Level ◽

Short Range ◽

Wrf Model ◽

India Meteorological Department ◽

Horizontal Resolution ◽

Sea Level Pressure ◽

Mean Sea Level ◽

Level Pressure

The main objective of this paper is to implement Polar WRF model for the Maitri (Lat. 70° 45 S, Long. 11° 44 E) region at the horizontal resolution of 15 km using initial and boundary conditions of the Global Forecast System T-382 operational at the India Meteorological Department (IMD). The study evaluates the performance of the model using the conventional approach of case studies. The results of the case studies illustrated in this paper reveal that the model is capable of capturing synoptic and meso-scale weather systems. Forecast fields are consistent with the corresponding analysis fields. Synoptic charts of mean sea level pressure prepared by the Weather Service of South Africa at Pretoria are used for the model validation. The model derived meteograms of mean sea level pressure are compared against the corresponding observations. The study demonstrates the usefulness of the forecast products for short range forecasting of weather over the Maitri region. The forecast outputs are made available in the real-time mode in the national web site of IMD www.imd.gov.in. The study is expected to benefit weather forecasters at Maitri.

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Ambulatory Assessment

European Psychologist ◽

10.1027/1016-9040.14.2.109 ◽

2009 ◽

Vol 14 (2) ◽

pp. 109-119 ◽

Cited By ~ 66

Author(s):

Ulrich W. Ebner-Priemer ◽

Timothy J. Trull

Keyword(s):

Real Time ◽

Clinical Psychology ◽

Real Life ◽

Ambulatory Assessment ◽

Computer Assisted ◽

Affective Valence ◽

Time Data ◽

Physiological Processes ◽

Context Specific ◽

Questionnaire Studies

Convergent experimental data, autobiographical studies, and investigations on daily life have all demonstrated that gathering information retrospectively is a highly dubious methodology. Retrospection is subject to multiple systematic distortions (i.e., affective valence effect, mood congruent memory effect, duration neglect; peak end rule) as it is based on (often biased) storage and recollection of memories of the original experience or the behavior that are of interest. The method of choice to circumvent these biases is the use of electronic diaries to collect self-reported symptoms, behaviors, or physiological processes in real time. Different terms have been used for this kind of methodology: ambulatory assessment, ecological momentary assessment, experience sampling method, and real-time data capture. Even though the terms differ, they have in common the use of computer-assisted methodology to assess self-reported symptoms, behaviors, or physiological processes, while the participant undergoes normal daily activities. In this review we discuss the main features and advantages of ambulatory assessment regarding clinical psychology and psychiatry: (a) the use of realtime assessment to circumvent biased recollection, (b) assessment in real life to enhance generalizability, (c) repeated assessment to investigate within person processes, (d) multimodal assessment, including psychological, physiological and behavioral data, (e) the opportunity to assess and investigate context-specific relationships, and (f) the possibility of giving feedback in real time. Using prototypic examples from the literature of clinical psychology and psychiatry, we demonstrate that ambulatory assessment can answer specific research questions better than laboratory or questionnaire studies.

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