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Tim Boyer
,
V. V. Gopalakrishna
,
Franco Reseghetti
,
Amit Naik
,
V. Suneel
,
M. Ravichandran
,
N. P. Mohammed Ali
,
M. M. Mohammed Rafeeq
, and
R. Anthony Chico

Abstract

Long time series of XBT data in the Bay of Bengal and the Arabian Sea are valuable datasets for exploring and understanding climate variability. However, such studies of interannual and longer-scale variability of temperature require an understanding, and, if possible, a correction of errors introduced by biases in the XBT and expendable conductivity–temperature–depth (XCTD) data. Two cruises in each basin were undertaken in 2008/09 on which series of tests of XBTs and XCTDs dropped simultaneously with CTD casts were performed. The XBT and XCTD depths were corrected by comparison with CTD data using a modification of an existing algorithm. Significant probe-to-probe fall-rate equation (FRE) velocity and deceleration coefficient variability was found within a cruise, as well as cruise-to-cruise variability. A small (∼0.01°C) temperature bias was also identified for XBTs on each cruise. No new FRE can be proposed for either the Bay of Bengal or the Arabian Sea for XBTs. For the more consistent XCTD, basin-specific FREs are possible for the Bay of Bengal, but not for the Arabian Sea. The XCTD FRE velocity coefficients are significantly higher than the XCTD manufacturers’ FRE coefficient or those from previous tests, possibly resulting from the influence of temperature on XCTD FRE. Mean temperature anomalies versus a long-term mean climatology for XBT data using the present default FRE have a bias (which is positive for three cruises and negative for one cruise) compared to the mean temperature anomalies for CTD data. Some improvement is found when applying newly calculated cruise-specific FREs. This temperature error must be accounted for in any study of temperature change in the regions.

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

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.

Full access
R. A. Weller
,
J. T. Farrar
,
Hyodae Seo
,
Channing Prend
,
Debasis Sengupta
,
J. Sree Lekha
,
M. Ravichandran
, and
R. Venkatesen

Abstract

Time series of surface meteorology and air–sea fluxes from the northern Bay of Bengal are analyzed, quantifying annual and seasonal means, variability, and the potential for surface fluxes to contribute significantly to variability in surface temperature and salinity. Strong signals were associated with solar insolation and its modulation by cloud cover, and, in the 5- to 50-day range, with intraseasonal oscillations (ISOs). The northeast (NE) monsoon (DJF) was typically cloud free, with strong latent heat loss and several moderate wind events, and had the only seasonal mean ocean heat loss. The spring intermonsoon (MAM) was cloud free and had light winds and the strongest ocean heating. Strong ISOs and Tropical Cyclone Komen were seen in the southwest (SW) monsoon (JJA), when 65% of the 2.2-m total rain fell, and oceanic mean heating was small. The fall intermonsoon (SON) initially had moderate convective systems and mean ocean heating, with a transition to drier winds and mean ocean heat loss in the last month. Observed surface freshwater flux applied to a layer of the observed thickness produced drops in salinity with timing and magnitude similar to the initial drops in salinity in the summer monsoon, but did not reproduce the salinity variability of the fall intermonsoon. Observed surface heat flux has the potential to cause the temperature trends of the different seasons, but uncertainty in how shortwave radiation is absorbed in the upper ocean limits quantifying the role of surface forcing in the evolution of mixed layer temperature.

Open access
K. Nisha
,
Suryachandra A. Rao
,
V. V. Gopalakrishna
,
R. R. Rao
,
M. S. Girishkumar
,
T. Pankajakshan
,
M. Ravichandran
,
S. Rajesh
,
K. Girish
,
Z. Johnson
,
M. Anuradha
,
S. S. M. Gavaskar
,
V. Suneel
, and
S. M. Krishna

Abstract

Repeat XBT transects made at near-fortnightly intervals in the Lakshadweep Sea (southeastern Arabian Sea) and ocean data assimilation products are examined to describe the year-to-year variability in the observed near-surface thermal inversions during the winter seasons of 2002–06. Despite the existence of a large low-salinity water intrusion into the Lakshadweep Sea, there was an unusually lower number of near-surface thermal inversions during the winter 2005/06 compared to the other winters. The possible causative mechanisms are examined. During the summer monsoon of 2005 and the following winter season, unusually heavy rainfall occurred over the southwestern Bay of Bengal and the Lakshadweep Sea compared to other years in the study. Furthermore, during the winter of 2005, both the East India Coastal Current and the Winter Monsoon Current were stronger compared to the other years, transporting larger quantities of low salinity waters from the Bay of Bengal into the Lakshadweep Sea where a relatively cooler near-surface thermal regime persisted owing to prolonged upwelling until November 2005. In addition, the observed local surface wind field was relatively stronger, and the net surface heat gain to the ocean was weaker over the Lakshadweep Sea during the postmonsoon season of 2005. Thus, in winter 2005/06, the combination of prolonged upwelling and stronger surface wind field resulting in anomalous net surface heat loss caused weaker secondary warming of the near-surface waters in the Lakshadweep Sea. This led to a weaker horizontal sea surface temperature (SST) gradient between the Lakshadweep Sea and the intruding Bay of Bengal waters and, hence, a reduced number of thermal inversions compared to other winters despite the presence of stronger vertical haline stratification.

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
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
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.

Full access
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