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M. J. McPhaden
,
G. Meyers
,
K. Ando
,
Y. Masumoto
,
V. S. N. Murty
,
M. Ravichandran
,
F. Syamsudin
,
J. Vialard
,
L. Yu
, and
W. Yu

The Indian Ocean is unique among the three tropical ocean basins in that it is blocked at 25°N by the Asian landmass. Seasonal heating and cooling of the land sets the stage for dramatic monsoon wind reversals, strong ocean-atmosphere interactions, and intense seasonal rains over the Indian subcontinent, Southeast Asia, East Africa, and Australia. Recurrence of these monsoon rains is critical to agricultural production that supports a third of the world's population. The Indian Ocean also remotely influences the evolution of El Nino-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), North American weather, and hurricane activity. Despite its importance in the regional and global climate system though, the Indian Ocean is the most poorly observed and least well understood of the three tropical oceans.

This article describes the Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA), a new observational network designed to address outstanding scientific questions related to Indian Ocean variability and the monsoons. RAMA is a multinationally supported element of the Indian Ocean Observing System (IndOOS), a combination of complementary satellite and in situ measurement platforms for climate research and forecasting. The article discusses the scientific rationale, design criteria, and implementation of the array. Initial RAMA data are presented to illustrate how they contribute to improved documentation and understanding of phenomena in the region. Applications of the data for societal benefit are also described.

Full access
M. J. McPhaden
,
G. Meyers
,
K. Ando
,
Y. Masumoto
,
V. S. N. Murty
,
M. Ravichandran
,
F. Syamsudin
,
J. Vialard
,
L. Yu
, and
W. Yu
Full access
A. V. S. Chaitanya
,
M. Lengaigne
,
J. Vialard
,
V. V. Gopalakrishna
,
F. Durand
,
C. Kranthikumar
,
S. Amritash
,
V. Suneel
,
F. Papa
, and
M. Ravichandran

Being the only tropical ocean bounded by a continent to the north, the Indian Ocean is home to the most powerful monsoon system on Earth. Monsoonal rains and winds induce huge river discharges and strong coastal currents in the northern Bay of Bengal. To date, the paucity of salinity data has prevented a thorough description of the spreading of this freshwater into the bay. The potential impact of the salinity on cyclones and regional climate in the Bay of Bengal is, however, a strong incentive for a better description of the water cycle in this region. Since May 2005, the National Institute of Oceanography conducts a program in which fishermen collect seawater samples in knee-deep water at eight stations along the Indian coastline every 5 days. Comparison with open-ocean samples shows that this cost-effective sampling strategy is representative of offshore salinity evolution. This new dataset reveals a salinity drop exceeding 10 g kg−1 in the northern part of the bay at the end of the summer monsoon. This freshening signal propagates southward in a narrow (~100 km wide) strip along the eastern coast of India, and reaches its southern tip after 2.5 months. Satellite-derived alongshore-current data shows that the southward propagation of this “river in the sea” is consistent with transport by seasonal coastal currents, while other processes are responsible for the ensuing erosion of this coastal freshening. This simple procedure of coastal seawater samples collection could further be used to monitor phytoplankton concentration, bacterial content, and isotopic composition of seawater along the Indian coastline.

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L. M. Beal
,
J. Vialard
,
M. K. Roxy
,
J. Li
,
M. Andres
,
H. Annamalai
,
M. Feng
,
W. Han
,
R. Hood
,
T. Lee
,
M. Lengaigne
,
R. Lumpkin
,
Y. Masumoto
,
M. J. McPhaden
,
M. Ravichandran
,
T. Shinoda
,
B. M. Sloyan
,
P. G. Strutton
,
A. C. Subramanian
,
T. Tozuka
,
C. C. Ummenhofer
,
A. S. Unnikrishnan
,
J. Wiggert
,
L. Yu
,
L. Cheng
,
D. G. Desbruyères
, and
V. Parvathi
Full access
L. M. Beal
,
J. Vialard
,
M. K. Roxy
,
J. Li
,
M. Andres
,
H. Annamalai
,
M. Feng
,
W. Han
,
R. Hood
,
T. Lee
,
M. Lengaigne
,
R. Lumpkin
,
Y. Masumoto
,
M. J. McPhaden
,
M. Ravichandran
,
T. Shinoda
,
B. M. Sloyan
,
P. G. Strutton
,
A. C. Subramanian
,
T. Tozuka
,
C. C. Ummenhofer
,
A. S. Unnikrishnan
,
J. Wiggert
,
L. Yu
,
L. Cheng
,
D. G. Desbruyères
, and
V. Parvathi

Abstract

The Indian Ocean Observing System (IndOOS), established in 2006, is a multinational network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific challenges, a 3-yr international review of the IndOOS by more than 60 scientific experts now highlights the need for an enhanced observing network that can better meet societal challenges, and provide more reliable forecasts. Here we present core findings from this review, including the need for 1) chemical, biological, and ecosystem measurements alongside physical parameters; 2) expansion into the western tropics to improve understanding of the monsoon circulation; 3) better-resolved upper ocean processes to improve understanding of air–sea coupling and yield better subseasonal to seasonal predictions; and 4) expansion into key coastal regions and the deep ocean to better constrain the basinwide energy budget. These goals will require new agreements and partnerships with and among Indian Ocean rim countries, creating opportunities for them to enhance their monitoring and forecasting capacity as part of IndOOS-2.

Free access
G. S. Bhat
,
S. Gadgil
,
P. V. Hareesh Kumar
,
S. R. Kalsi
,
P. Madhusoodanan
,
V. S. N. Murty
,
C. V. K. Prasada Rao
,
V. Ramesh Babu
,
L. V. G. Rao
,
R. R. Rao
,
M. Ravichandran
,
K. G. Reddy
,
P. Sanjeeva Rao
,
D. Sengupta
,
D. R. Sikka
,
J. Swain
, and
P. N. Vinayachandran

The first observational experiment under the Indian Climate Research Programme, called the Bay of Bengal Monsoon Experiment (BOBMEX), was carried out during July–August 1999. BOBMEX was aimed at measurements of important variables of the atmosphere, ocean, and their interface to gain deeper insight into some of the processes that govern the variability of organized convection over the bay. Simultaneous time series observations were carried out in the northern and southern Bay of Bengal from ships and moored buoys. About 80 scientists from 15 different institutions in India collaborated during BOBMEX to make observations in most-hostile conditions of the raging monsoon. In this paper, the objectives and the design of BOBMEX are described and some initial results presented.

During the BOBMEX field phase there were several active spells of convection over the bay, separated by weak spells. Observation with high-resolution radiosondes, launched for the first time over the northern bay, showed that the magnitudes of the convective available potential energy (CAPE) and the convective inhibition energy were comparable to those for the atmosphere over the west Pacific warm pool. CAPE decreased by 2–3 kg−1 following convection, and recovered in a time period of 1–2 days. The surface wind speed was generally higher than 8 m s−1.

The thermohaline structure as well as its time evolution during the BOBMEX field phase were found to be different in the northern bay than in the southern bay. Over both the regions, the SST decreased during rain events and increased in cloud-free conditions. Over the season as a whole, the upper-layer salinity decreased for the north bay and increased for the south bay. The variation in SST during 1999 was found to be of smaller amplitude than in 1998. Further analysis of the surface fluxes and currents is expected to give insight into the nature of coupling.

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Suryachandra A. Rao
,
B. N. Goswami
,
A. K. Sahai
,
E. N. Rajagopal
,
P. Mukhopadhyay
,
M. Rajeevan
,
S. Nayak
,
L. S. Rathore
,
S. S. C. Shenoi
,
K. J. Ramesh
,
R. S. Nanjundiah
,
M. Ravichandran
,
A. K. Mitra
,
D. S. Pai
,
S. K. R. Bhowmik
,
A. Hazra
,
S. Mahapatra
,
S. K. Saha
,
H. S. Chaudhari
,
S. Joseph
,
P. Sreenivas
,
S. Pokhrel
,
P. A. Pillai
,
R. Chattopadhyay
,
M. Deshpande
,
R. P. M. Krishna
,
Renu S. Das
,
V. S. Prasad
,
S. Abhilash
,
S. Panickal
,
R. Krishnan
,
S. Kumar
,
D. A. Ramu
,
S. S. Reddy
,
A. Arora
,
T. Goswami
,
A. Rai
,
A. Srivastava
,
M. Pradhan
,
S. Tirkey
,
M. Ganai
,
R. Mandal
,
A. Dey
,
S. Sarkar
,
S. Malviya
,
A. Dhakate
,
K. Salunke
, and
Parvinder Maini

Abstract

In spite of the summer monsoon’s importance in determining the life and economy of an agriculture-dependent country like India, committed efforts toward improving its prediction and simulation have been limited. Hence, a focused mission mode program Monsoon Mission (MM) was founded in 2012 to spur progress in this direction. This article explains the efforts made by the Earth System Science Organization (ESSO), Ministry of Earth Sciences (MoES), Government of India, in implementing MM to develop a dynamical prediction framework to improve monsoon prediction. Climate Forecast System, version 2 (CFSv2), and the Met Office Unified Model (UM) were chosen as the base models. The efforts in this program have resulted in 1) unparalleled skill of 0.63 for seasonal prediction of the Indian monsoon (for the period 1981–2010) in a high-resolution (∼38 km) seasonal prediction system, relative to present-generation seasonal prediction models; 2) extended-range predictions by a CFS-based grand multimodel ensemble (MME) prediction system; and 3) a gain of 2-day lead time from very high-resolution (12.5 km) Global Forecast System (GFS)-based short-range predictions up to 10 days. These prediction skills are on par with other global leading weather and climate centers, and are better in some areas. Several developmental activities like coupled data assimilation, changes in convective parameterization, cloud microphysics schemes, and parameterization of land surface processes (including snow and sea ice) led to the improvements such as reducing the strong model biases in the Indian summer monsoon simulation and elsewhere in the tropics.

Open access
P. A. Francis
,
A. K. Jithin
,
J. B. Effy
,
A. Chatterjee
,
K. Chakraborty
,
A. Paul
,
B. Balaji
,
S. S. C. Shenoi
,
P. Biswamoy
,
A. Mukherjee
,
P. Singh
,
B. Deepsankar
,
S. Siva Reddy
,
P. N. Vinayachandran
,
M. S. Girish Kumar
,
T. V. S. Udaya Bhaskar
,
M. Ravichandran
,
A. S. Unnikrishnan
,
D. Shankar
,
A. Prakash
,
S. G. Aparna
,
R. Harikumar
,
K. Kaviyazhahu
,
K. Suprit
,
R. V. Shesu
,
N. Kiran Kumar
,
N. Srinivasa Rao
,
K. Annapurnaiah
,
R. Venkatesan
,
A. S. Rao
,
E. N. Rajagopal
,
V. S. Prasad
,
M. D. Gupta
,
T. M. Balakrishnan Nair
,
E. P. R. Rao
, and
B. V. Satyanarayana

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.

Free access
P. A. Francis
,
A. K. Jithin
,
J. B. Effy
,
A. Chatterjee
,
K. Chakraborty
,
A. Paul
,
B. Balaji
,
S. S. C. Shenoi
,
P. Biswamoy
,
A. Mukherjee
,
P. Singh
,
B. Deepsankar
,
S. Siva Reddy
,
P. N. Vinayachandran
,
M. S. Girish Kumar
,
T. V. S. Udaya Bhaskar
,
M. Ravichandran
,
A. S. Unnikrishnan
,
D. Shankar
,
A. Prakash
,
S. G. Aparna
,
R. Harikumar
,
K. Kaviyazhahu
,
K. Suprit
,
R. V. Shesu
,
N. Kiran Kumar
,
N. Srinivasa Rao
,
K. Annapurnaiah
,
R. Venkatesan
,
A. S. Rao
,
E. N. Rajagopal
,
V. S. Prasad
,
M. D. Gupta
,
T. M. Balakrishnan Nair
,
E. P. R. Rao
, and
B. V. Satyanarayana
Full access
Hemantha W. Wijesekera
,
Emily Shroyer
,
Amit Tandon
,
M. Ravichandran
,
Debasis Sengupta
,
S. U. P. Jinadasa
,
Harindra J. S. Fernando
,
Neeraj Agrawal
,
K. Arulananthan
,
G. S. Bhat
,
Mark Baumgartner
,
Jared Buckley
,
Luca Centurioni
,
Patrick Conry
,
J. Thomas Farrar
,
Arnold L. Gordon
,
Verena Hormann
,
Ewa Jarosz
,
Tommy G. Jensen
,
Shaun Johnston
,
Matthias Lankhorst
,
Craig M. Lee
,
Laura S. Leo
,
Iossif Lozovatsky
,
Andrew J. Lucas
,
Jennifer Mackinnon
,
Amala Mahadevan
,
Jonathan Nash
,
Melissa M. Omand
,
Hieu Pham
,
Robert Pinkel
,
Luc Rainville
,
Sanjiv Ramachandran
,
Daniel L. Rudnick
,
Sutanu Sarkar
,
Uwe Send
,
Rashmi Sharma
,
Harper Simmons
,
Kathleen M. Stafford
,
Louis St. Laurent
,
Karan Venayagamoorthy
,
Ramasamy Venkatesan
,
William J. Teague
,
David W. Wang
,
Amy F. Waterhouse
,
Robert Weller
, and
Caitlin B. Whalen

Abstract

Air–Sea Interactions in the Northern Indian Ocean (ASIRI) is an international research effort (2013–17) aimed at understanding and quantifying coupled atmosphere–ocean dynamics of the Bay of Bengal (BoB) with relevance to Indian Ocean monsoons. Working collaboratively, more than 20 research institutions are acquiring field observations coupled with operational and high-resolution models to address scientific issues that have stymied the monsoon predictability. ASIRI combines new and mature observational technologies to resolve submesoscale to regional-scale currents and hydrophysical fields. These data reveal BoB’s sharp frontal features, submesoscale variability, low-salinity lenses and filaments, and shallow mixed layers, with relatively weak turbulent mixing. Observed physical features include energetic high-frequency internal waves in the southern BoB, energetic mesoscale and submesoscale features including an intrathermocline eddy in the central BoB, and a high-resolution view of the exchange along the periphery of Sri Lanka, which includes the 100-km-wide East India Coastal Current (EICC) carrying low-salinity water out of the BoB and an adjacent, broad northward flow (∼300 km wide) that carries high-salinity water into BoB during the northeast monsoon. Atmospheric boundary layer (ABL) observations during the decaying phase of the Madden–Julian oscillation (MJO) permit the study of multiscale atmospheric processes associated with non-MJO phenomena and their impacts on the marine boundary layer. Underway analyses that integrate observations and numerical simulations shed light on how air–sea interactions control the ABL and upper-ocean processes.

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