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Rainfall over Oman and its teleconnection with El Niño Southern Oscillation
No full textThe Sultanate of Oman is located in the south-eastern part of the Arabian Peninsula and covers the larger part of the southern coasts of the Arabian Peninsula in both arid and semi-arid environments except for the southern part which is swept by the monsoon affecting the Arabian Sea during the period from June to September. The summer rainfall over Oman shows year-to-year variability, and this is caused by oceanic and atmospheric influences. In the present study, we tried to explore the influence of El Niño on the rainfall over Oman using different data sets. The empirical orthogonal function (EOF) technique employed to the zonal wind at 850 hPa for the 30-year period shows that the second and third modes of EOF are showing high variability over the Oman regions. The corresponding PCs were subjected to FFT analysis, and it showed a peak about 5–6 years. In addition to this, the zonal wind over the Oman regions is correlated with the global zonal wind and found a significant correlation (1 % significant level). It has already been proved that the wind and rainfall during summer monsoon is in phase. Moreover, the spectral analysis of rainfall at Masirah station and the Niño3.4 index show the similar mode of variability indicating a direct relationship. The correlation between rainfall and the Niño3.4 index is also showing a positive significant value, and therefore, it can be concluded that the El Niño in the Pacific favours rainfall over the Oman region
Preliminary results of an algorithm to determine the total absorption coefficient of water
No full textAn algorithm to determine the spectral total absorption coefficient of water is presented. The algorithm is based on the Gershun’s equation of α = μKE. The spectral underwater average cosine, μ and vertical attenuation coefficient of net irradiance, KE were obtained from radiative transfer simulations using Hydrolight with large in-situ measured data from the coastal and estuarine waters of Goa. A refined algorithm of spectral μ as in Ref. [1] is used to determine the spectral underwater average cosine. The spectral KE was related to the diffuse attenuation coefficient, Kd. The algorithms to derive absorption were validated using an independent NOMAD optical data at wavelengths 412, 440, 488, 510, 532, 555, 650 and 676 nm. The performance of the algorithm was evident from the high R2, low bias and low RMSE. The values of R2 at wavelengths 412, 440, 488, 510, 532, 555, 650 and 676 nm were 0.95, 0.95, 0.93, 0.93, 0.88, 0.82, 0.62, and 0.65 respectively. The corresponding bias were -0.0064, 0.0076, 0.0038, 0.0044, 0.0122, 0.0124, 0.0362, and 0.0093 respectively. The algorithms for μ and KE provide the spectral weighted average within Z90 and have the advantage of deriving the absorption coefficients from the satellite data
Evaluation of MODIS/CERES downwelling shortwave and longwave radiation data over global tropical oceans
No full textIn the present work, we have evaluated the satellite estimated daily downwelling shortwave (QI) and Longwave (QA) radiation from Moderate Resolution Imaging Spectrometer (MODIS) /Clouds and the Earth's Radiant Energy System (CM) with moored buoy observations of Global Tropical Moored Buoy Array (GTMBA) during 2001-2009. The global observed mean of QI and QA in GTMBA (CM) are 228 (233) W/m2 and 410 (405) W/m2 respectively. The mean QI shows a positive bias (~3- 7 W/m2) whereas QA underestimates with a mean negative bias of ~3-6 W/m2 in the tropical Pacific, Atlantic and Indian Ocean. CM underestimates the buoy observed variability in both QI and QA in all the tropical oceans. The correlation coefficient (CC) values in QI (Qa) are 0.79(0.88) 0.79(0.84) and 0.81(0.94) over the Pacific, Atlantic and Indian ocean respectively. The Root Mean Square Error (RMSE) values in QI ranged between 35-43 W/m2 with lowest values in the Atlantic Ocean and highest in the Indian Ocean. The RMSE values in QA are less as compared to QI and it is ~9 W/m2 in all the tropical ocean. The spatial distributions of QI and QA shows seasonality with lower and higher values coinciding with the Inter Tropical Convergence Zone(ITCZ) locations in the QI and QA
Adrift upon a salinity-stratified sea
Get PDFThe structure and variability of upper-ocean properties in the Bay of Bengal (BoB) modulate air-sea interactions, which profoundly influence the pattern and intensity of monsoonal precipitation across the Indian subcontinent. In turn, the bay receives a massive amount of freshwater through river input at its boundaries and from heavy local rainfall, leading to a salinity-stratified surface ocean and shallow mixed layers. Small-scale oceanographic processes that drive variability in near-surface BoB waters complicate the tight coupling between ocean and atmosphere implicit in this seasonal feedback. Unraveling these ocean dynamics and their impact on air-sea interactions is critical to improving the forecasting of intraseasonal variability in the southwest monsoon. To that end, we deployed a wave-powered, rapidly profiling system capable of measuring the structure and variability of the upper 100 m of the BoB. The evolution of upper-ocean structure along the trajectory of the instrument’s roughly two-week drift, along with direct estimates of vertical fluxes of salt and heat, permit assessment of the contributions of various phenomena to temporal and spatial variability in the surface mixed layer depth. Further, these observations suggest that the particular “barrier-layer” stratification found in the BoB may decrease the influence of the wind on mixing processes in the interior, thus isolating the upper ocean from the interior below, and tightening its coupling to the atmosphere abov
Representation of Bay of Bengal upper-ocean salinity in general circulation models
Get PDFThe Bay of Bengal (BoB) upper-ocean salinity is examined in the National Centers for Environmental Prediction-Climate Forecasting System version 2 (CFSv2) coupled model, Modular Ocean Model version 5 (MOM5), and Indian National Centre for Ocean Information Services Global Ocean Data Assimilation System (INC-GODAS). CFSv2 displays a large positive salinity bias with respect to World Ocean Atlas 2013 in the upper 40 m of the water column. The prescribed annual mean river discharge and excess evaporation are the main contributors to the positive bias in surface salinity. Overestimation of salinity advection also contributes to the high surface salinity in the model during summer. The surface salinity bias in MOM5 is smaller than in CFSv2 due to prescribed local freshwater flux and seasonally varying river discharge. However, the bias is higher around 70 m in summer and 40 m in fall. This bias is attributed to excessive vertical mixing in the upper ocean. Despite the fact that representation of salinity in INC-GODAS is more realistic due to data assimilation, the vertical mixing scheme still imposes systematic errors. The small-scale processes that control oceanographic turbulence are not adequately resolved in any of these models. Better parameterizations based on dedicated observational programs may help improve freshwater representation in regional and global models
Influence of upper ocean on Indian summer monsoon rainfall: studies by observation and NCEP climate forecast system (CFSv2)
No full textThis study explores the role played by ocean processes in influencing Indian summer monsoon rainfall (ISMR) and compares the observed findings with National Centers for Environmental Prediction (NCEP)-coupled model Climate Forecast System, version 2 (CFSv2). The excess and deficit ISMR clearly brings out the distinct signatures in sea surface height (SSH) anomaly, thermocline and mixed layer depth over north Indian Ocean. CFSv2 is successful in simulating SSH anomalies, especially over Arabian Sea and Bay of Bengal region. CFSv2 captures observed findings of SSH anomalies during flood and drought (e.g., Rossby wave propagation which reaches western Bay of Bengal (BoB) during flood years, Rossby wave propagation which did not reach western BoB during drought). It highlights the ability of CFSv2 to simulate the basic ocean processes which governs the SSH variability. These differences are basically generated by upwelling and downwelling caused by the equatorial and coastal Kelvin and Rossby waves, thereby causing difference in SSH anomaly and thermocline, and subsequently modifying the convection centers, which dictates precipitation over the Indian subcontinent region. Since the observed SSH anomaly and thermal structure show distinct characteristic features with respect to strong and weak ISMR variability, the assimilation of real ocean data in terms of satellite products (like SSHA from AVISO/SARAL) bestow great promise for the future improvement
Satellite Coastal and Oceanographic Research Inter-comparison Exercise (SICOME)
Get PDFINCOIS is coordinating Satellite Coastal and Oceanographic Research (SATCORE) project SATCORE programme since XIth plan with an aim of long-term measurements of bio-optical properties in the Indian coastal waters. The principal aim of these measurements is continuous measurement of in situ bio-optical data for validation of existing ocean color algorithms, improvement, development of new bio-optical algorithms in coastal waters of India. INCOIS had identified 12 time series sampling transects along east and west of India for continuous measurement of bio-optical parameters. Regular in situ sampling and analysis at time series stations are carried out by sub-projects sanctioned under SATCORE program to various Research and Academic &D Institutions: Junagadh Agricultural University (Off Okha), NIO, Goa (Off Goa), Goa University (Off Goa), Mangalore University (Off Mangalore), CIFT, Kochi (Off Kochi), Annamalai University (Off Parangipettai), IIT Madras (Off Chennai), Andhra University (Off Visakhapatnam), CSBoB, Andhra University (Off Visakhapatnam), Berhampur University (Off Gopalpur), Jadavpur University (Off Frazergunj), CARI (ICAR) (A & N Islands). To ensure the accuracy of the parameters measured at vasrious laboratories at different time-series locations, Satellite Coastal and Oceanographic Research-Inter-comparison Exercises (SICOME) were conducted during 2014 and 2015. During SICOME samples of Optically Active Substances i.e chlorophyll-a (chl-a), coloured dissolved organic matter (CDOM) and total suspended matter (TSM) were collected from one location. The master samples were immediately analyzed and duplicate samples were sent to different SATCORE laboratories. All the fluorometers were calibrated with teh standards for chlorophyll-a, Chromophoric Dissolved Organic Matter (CDOM) and Turbidity. All five Radiometers were also operated simultaneously to estimate the instrument bias. The document provides results of the instrument and analytical bias for same samples analyzed at various SATCORE laboratories so as to maintain the data quality for international standard
Tropical Indian Ocean response to the decay phase of El Nino in a coupled model and associated changes in south and east-Asian summer monsoon circulation and rainfall
No full textThis study investigates the response of tropical Indian Ocean (TIO) sea surface temperature (SST) to El Niño decay phase and its impacts on South and East Asian summer monsoon in the National Centers for Environmental Prediction Climate Forecast System version 2 free run. The TIO basin-wide warming induced by El Niño at its peak phase (winter; DJF) and next spring (MAM + 1) are reasonably well captured by the model but with weak magnitude. This TIO basin-wide SST warming persists until summer (JJA + 1) and exert strong impact on summer monsoon rainfall and circulation as revealed in the observations. However, TIO SST anomalies are very weak in the model during the El Niño decaying summers. Though El Niño decay is delayed by 2 months in the model, decay of TIO SST warming is faster than the observations. Anomalous latent heat loss from ocean and a feeble southern TIO Rossby waves associated with weak wind response to El Niño are mainly accountable for rapid decay of TIO SST warming by mid-summer in the model. This suggests that JJA + 1 TIO SST response to El Niño decay phase in the model is poorly represented. The model is able to capture the SST anomalies associated with the northwest Pacific anticyclone at the peak phase of El Niño but fail to maintain that during the decay phase in MAM + 1 and JJA + 1. It is found that precipitation and circulation anomalies associated with TIO SST warming over the South and East Asian regions are disorganized in the model during the decay phase of El Niño. Rainfall anomalies over the southwest TIO, west coast of India, northern flank of northwest Pacific anticyclone and over Japan in JJA + 1 are poorly represented by the model. Analysis of lower troposphere stream function and rotational wind component reveals that northwest Pacific anticyclone shifted far eastward to the date line in the model during JJA + 1 unlike in the observations. Anomalous divergence observed over the western TIO and convergence in the northwest Pacific are absent in the model during JJA + 1. Extension of anomalous tropospheric warming from TIO region to equatorial western Pacific is also very weak in the model due to poor representation of TIO SSTs and the subsequent absence of any Kelvin wave response. Anomalous Walker circulation persisted from DJF to JJA + 1 due to El Niño late decay in the model unlike in the observations. This is also found to be responsible for the redundant changes in SST, rainfall and circulation over the Indo-western Pacific in the model. This study demonstrates that it is essential to represent the decay phase of El Niño and the associated TIO response accurately to have realistic simulations of summer monsoon in the decaying year
Potential role of the February–March southern annular mode on the Indian summer monsoon rainfall: a new perspective
No full textRelationship between the Southern Annular Mode (SAM) and the India summer monsoon rainfall (ISMR) has been examined based on the data period 1949–2013. While the entire data period indicates a significant increasing trend in SAM, recent decades 1983–2013 indicate no trend. The relationship between the two strengthened considerably since 1983. Results reveal that the February–March SAM is significantly related with the subsequent ISMR. A positive (negative) SAM during February–March is favorable (unfavorable) for the ensuing summer monsoon rainfall over the Indian sub-continent. The delayed response is relayed through the central Pacific Ocean. We propose a hypothesis that states: when a negative (positive) phase of February–March SAM occurs, it gives rise to an anomalous meridional circulation in a longitudinally locked air–sea coupled system over the central Pacific that persists up to the subsequent boreal summer and propagates from the sub-polar latitudes to the equatorial latitudes inducing a warming (cooling) effect over the central equatorial Pacific region. In turn, this effect concomitantly weakens (strengthens) the monsoon rainfall over the Indian sub-continent. Thus, the February–March SAM could possibly serve as a new precursor to foreshadow the subsequent behavior of the Indian summer monsoon
Introduction to the Special Issue on the Bay of Bengal: From Monsoons to Mixing
Get PDFThe Bay of Bengal has a surprisingly large influence on the world. It nurtures the South Asian summer monsoon, a tremendous ocean-atmosphere-land phenomenon that delivers freshwater to more than a third of the human population on this planet. During summer, southwesterly winds gather moisture from the ocean and carry it deep inland over the Indian subcontinent, bringing welcome rains to a parched land. During winter, the winds reverse to northeasterly, and the ocean circulation responds by dispersing the terrestrial freshwater runoff concentrated in the northern part of the bay. This freshwater impacts the ocean’s structure, circulation, and biogeochemistry in numerous ways and, through modification of sea surface temperature, feeds back to influence air-sea fluxes. Because the atmosphere obtains its moisture and heat for convection from the ocean, the interplay between ocean and atmosphere is crucial for the development and sustenance of the monsoon