scholarly journals Seasonal climate modeling over the Indian Ocean by employing a 4D-VAR coupled data assimilation approach

2009 ◽  
Vol 114 (C11) ◽  
Author(s):  
Takashi Mochizuki ◽  
Nozomi Sugiura ◽  
Toshiyuki Awaji ◽  
Takahiro Toyoda
Keyword(s):  
Indian Ocean ◽  
Data Assimilation ◽  
Climate Modeling ◽  
Seasonal Climate ◽  
The Indian Ocean ◽  
Coupled Data Assimilation

Implementation of altimeter data assimilation on a regional wave forecasting system and its impact on wave and swell surge forecast in the Indian Ocean

2021 ◽  
Vol 237 ◽  
pp. 109585
Author(s):  
M. Seemanth ◽  
P.G. Remya ◽  
Suchandra Aich Bhowmick ◽  
Rashmi Sharma ◽  
T.M. Balakrishnan Nair ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Data Assimilation ◽  
Altimeter Data ◽  
Forecasting System ◽  
The Indian Ocean ◽  
Wave Forecasting

Initialization and Data Assimilation in Models of the Indian Ocean

1987 ◽  
Vol 17 (11) ◽  
pp. 1965-1977 ◽  
Author(s):  
A. M. Moore ◽  
N. S. Cooper ◽  
D. L. T. Anderson
Keyword(s):  
Indian Ocean ◽  
Data Assimilation ◽  
The Indian Ocean

Estimation of Uncertainty in the Atmospheric Pressure Measurement From the Indian Ocean Moored Buoy Systems

2021 ◽  
Vol 55 (1) ◽  
pp. 137-146
Author(s):  
Ramasamy Venkatesan ◽  
Krishnamoorthy Ramesh ◽  
Manickavasagam Arul Muthiah ◽  
Narayanaswamy Vedachalam ◽  
Pothikasalam Murugesh ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Atmospheric Pressure ◽  
Climate Modeling ◽  
Satellite Telemetry ◽  
Experimental Studies ◽  
Pressure Sensors ◽  
Pressure Head ◽  
Barometric Pressure ◽  
Key Factor ◽  
The Indian Ocean

AbstractPrecise and accurate monitoring of atmospheric pressure by barometric pressure sensors used in moored buoys in the Indian Ocean is a key factor in cyclone monitoring and climate studies. Underperformance of these sensors has significant impacts on societal protection, weather predictions, and climate modeling. Experimental studies are carried out on the barometric pressure sensors used in moored buoys to quantitatively estimate the uncertainties due to sensor accuracy, drift, static pressure head, and satellite telemetry resolution. The overall measurement uncertainty of the pressure sensors is identified to be ±0.13 hPa, which is within the accuracy limits recommended by the World Meteorological Organization (WMO).

scholarly journals High-Resolution Operational Ocean Forecast and Reanalysis System for the Indian Ocean

2020 ◽  
Vol 101 (8) ◽  
pp. E1340-E1356 ◽  
Author(s):  
P. A. Francis ◽  
A. K. Jithin ◽  
J. B. Effy ◽  
A. Chatterjee ◽  
K. Chakraborty ◽  
...  
Keyword(s):  
High Resolution ◽  
Indian Ocean ◽  
Data Assimilation ◽  
Coastal Waters ◽  
General Circulation ◽  
High Performance ◽  
Coast Guard ◽  
Ocean Modeling ◽  
Regional Ocean Modeling System ◽  
The Indian Ocean

Abstract A good understanding of the general circulation features of the oceans, particularly of the coastal waters, and ability to predict the key oceanographic parameters with good accuracy and sufficient lead time are necessary for the safe conduct of maritime activities such as fishing, shipping, and offshore industries. Considering these requirements and buoyed by the advancements in the field of ocean modeling, data assimilation, and ocean observation networks along with the availability of the high-performance computational facility in India, Indian National Centre for Ocean Information Services has set up a “High-Resolution Operational Ocean Forecast and Reanalysis System” (HOOFS) with an aim to provide accurate ocean analysis and forecasts for the public, researchers, and other types of users like navigators and the Indian Coast Guard. Major components of HOOFS are (i) a suite of numerical ocean models configured for the Indian Ocean and the coastal waters using the Regional Ocean Modeling System (ROMS) for forecasting physical and biogeochemical state of the ocean and (ii) the data assimilation based on local ensemble transform Kalman filter that assimilates in situ and satellite observations in ROMS. Apart from the routine forecasts of key oceanographic parameters, a few important applications such as (i) Potential Fishing Zone forecasting system and (ii) Search and Rescue Aid Tool are also developed as part of the HOOFS project. The architecture of HOOFS, an account of the quality of ocean analysis and forecasts produced by it and important applications developed based on HOOFS are briefly discussed in this article.

Ensemble based regional ocean data assimilation system for the Indian Ocean: Implementation and evaluation

2019 ◽  
Vol 143 ◽  
pp. 101470
Author(s):  
Balaji Baduru ◽  
Biswamoy Paul ◽  
Deep Sankar Banerjee ◽  
Sivareddy Sanikommu ◽  
Arya Paul
Keyword(s):  
Indian Ocean ◽  
Data Assimilation ◽  
Ocean Data Assimilation ◽  
The Indian Ocean ◽  
Data Assimilation System ◽  
Assimilation System

Two Regimes of the Equatorial Warm Pool. Part II: Hybrid Coupled GCM Experiments

2008 ◽  
Vol 21 (14) ◽  
pp. 3545-3560 ◽  
Author(s):  
Masahiro Watanabe
Keyword(s):  
Simple Model ◽  
Indian Ocean ◽  
General Circulation ◽  
Climate Model ◽  
Climate Modeling ◽  
Circulation Model ◽  
Warm Pool ◽  
Bjerknes Feedback ◽  
The Pacific ◽  
The Indian Ocean

Abstract In this second of a two-part study, the two regimes in a simple tropical climate model identified in Part I are verified using a hybrid coupled general circulation model (HCM) that can reproduce the observed climatology and the interannual variability reasonably well. Defining a ratio of basin width between the Pacific and Indian Oceans, a series of parameter sweep experiments was conducted with idealized tropical land geometry. Consistent with the simple model, the HCM simulates two distinct states: the split warm pool regime with large vacillation between the two ocean basins and the single warm pool regime representing current climate. The former is suddenly switched to the latter as the Pacific becomes wider than the Indian Ocean. Furthermore, the vacillation in the split regime reveals a preferred transition route that the warm phase in the Pacific follows that in the Indian Ocean. This route occurs due to convectively coupled Kelvin waves that accompany precipitation anomalies over land. Additional experiments show that the inclusion of the idealized Eurasian continent stabilizes the split regime by reducing the Bjerknes feedback in the Indian Ocean, suggesting the atmosphere–ocean–land interaction at work in maintaining the observed warm pool. No difference in cloud feedback was found between two regimes; this feature may, however, be model dependent. Both the simple model and the HCM results suggest that the tropical atmosphere–ocean system inherently involves multiple solutions, which may have an implication on climate modeling as well as on the understanding of the observed mean climate.

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