scholarly journals Interannual variability of the Arabian Sea warm pool intensity and its association with monsoon onset over Kerala

MAUSAM ◽  
2021 ◽  
Vol 58 (3) ◽  
pp. 345-350
Author(s):  
O. P. SINGH
Keyword(s):  
Arabian Sea ◽  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Warm Pool ◽  
Monsoon Onset ◽  
Sea Surface ◽  
Onset Date ◽  
Peak Intensity ◽  
Sst Anomalies ◽  
Lakshadweep Sea

In this paper the relationships between the Arabian Sea warm pool intensity, Southern Oscillation (SO) and the monsoon onset have been discussed. The results show that the peak intensity of the warm pool in the Lakshadweep Sea is significantly correlated with the monsoon onset date over Kerala. Warmer Sea Surface Temperature (SST) anomalies in the warm pool region during April-May are associated with delayed monsoon onset over Kerala though the cause-and-effect relationship is not known. The Southern Oscillation Index (SOI) of March can provide predictive indications of the peak intensity of the warm pool which, normally occurs during April.

scholarly journals Evolutions of sea level high and warm pool in the southeastern Arabian Sea and their association with Asian monsoons : A study on cause-and-effect relationships

MAUSAM ◽  
2021 ◽  
Vol 59 (1) ◽  
pp. 87-94
Author(s):  
O. P. SINGH
Keyword(s):  
Sea Level ◽  
Summer Monsoon ◽  
El Niño ◽  
Arabian Sea ◽  
El Nino ◽  
Southern Oscillation ◽  
Monsoon Season ◽  
Warm Pool ◽  
Sea Surface ◽  
Southeastern Arabian Sea

The present study aims at gaining more insight into the evolution of warm pool and associated sea level dome in the southeastern Arabian Sea before the summer monsoon onset.  The results show that the Sea Surface Temperature (SST) maximum in the warm pool region is found during April close to the southwest coast of India.  The Sea Surface Height (SSH) maximum over the same region is observed during December. The collapse of sea level dome begins well in advance during the pre-monsoon whereas the warm pool collapses after the onset of summer monsoon during June.  Therefore, there is a lag of about three to four months between the collapses of the sea level high and the warm pool.  Most interesting aspect is the dramatic increase of SST from September and SSH from October which is continued throughout the post monsoon season (October - December). Therefore, both the collapse and evolution of warm pool are dramatic events before and after the summer monsoon.                    There are considerable variations in the intensity of warm pool and the height of sea level dome on interannual scale.  The variation during El-Nino Southern Oscillation (ENSO) epoch of 1987-88 has revealed many interesting features.  During El-Nino year 1987 the warm pool intensity reached its peak in June whereas during La Nina year 1988 the warm pool attained its maximum intensity much earlier, i.e., in April. 

Diagnosing Sources of U.S. Seasonal Forecast Skill

2006 ◽  
Vol 19 (13) ◽  
pp. 3279-3293 ◽  
Author(s):  
X. Quan ◽  
M. Hoerling ◽  
J. Whitaker ◽  
G. Bates ◽  
T. Xu
Keyword(s):  
Air Temperature ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Diagnostic Methods ◽  
Sea Surface ◽  
Empirical Methods ◽  
Spatial Coverage ◽  
Sst Anomalies

Abstract In this study the authors diagnose the sources for the contiguous U.S. seasonal forecast skill that are related to sea surface temperature (SST) variations using a combination of dynamical and empirical methods. The dynamical methods include ensemble simulations with four atmospheric general circulation models (AGCMs) forced by observed monthly global SSTs from 1950 to 1999, and ensemble AGCM experiments forced by idealized SST anomalies. The empirical methods involve a suite of reductions of the AGCM simulations. These include uni- and multivariate regression models that encapsulate the simultaneous and one-season lag linear connections between seasonal mean tropical SST anomalies and U.S. precipitation and surface air temperature. Nearly all of the AGCM skill in U.S. precipitation and surface air temperature, arising from global SST influences, can be explained by a single degree of freedom in the tropical SST field—that associated with the linear atmospheric signal of El Niño–Southern Oscillation (ENSO). The results support previous findings regarding the preeminence of ENSO as a U.S. skill source. The diagnostic methods used here exposed another skill source that appeared to be of non-ENSO origins. In late autumn, when the AGCM simulation skill of U.S. temperatures peaked in absolute value and in spatial coverage, the majority of that originated from SST variability in the subtropical west Pacific Ocean and the South China Sea. Hindcast experiments were performed for 1950–99 that revealed most of the simulation skill of the U.S. seasonal climate to be recoverable at one-season lag. The skill attributable to the AGCMs was shown to achieve parity with that attributable to empirical models derived purely from observational data. The diagnostics promote the interpretation that only limited advances in U.S. seasonal prediction skill should be expected from methods seeking to capitalize on sea surface predictors alone, and that advances that may occur in future decades could be readily masked by inherent multidecadal fluctuations in skill of coupled ocean–atmosphere systems.

A Model Study on Understanding the Influence of Arabian Sea Mini Warm Pool on Monsoon Onset Vortex Formation

2011 ◽  
Vol 169 (9) ◽  
pp. 1693-1706 ◽  
Author(s):  
R. Deepa ◽  
C. Gnanaseelan ◽  
M. Deshpande ◽  
P. S. Salvekar
Keyword(s):  
Arabian Sea ◽  
Vortex Formation ◽  
Warm Pool ◽  
Monsoon Onset ◽  
Model Study ◽  
Monsoon Onset Vortex

scholarly journals Model Vector Autoregressive Exogenous dan Aplikasinya pada Curah Hujan Kota Makassar

2020 ◽  
Vol 2 (2) ◽  
pp. 108
Author(s):  
S. Sukarna ◽  
Wahidah Sanusi ◽  
Serly Diliyanti Restu Ningsih
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Rainfall Data ◽  
Sea Surface ◽  
Dipole Mode ◽  
Rainfall Forecasting ◽  
Dipole Mode Index ◽  
Mode Index

Jenis penelitian ini adalah penelitian terapan yang bertujuan untuk meramalkan curah hujan di Kota Makassar dengan menggunakan model VARX. Model VARX dikembangkan dari model VAR dengan menambahkan faktor eksogen yang mempengaruhi curah hujan seperti Sea Surface Temperature (SST) Nino 3.4, Southern Oscillation Index (SOI), dan Dipole Mode Index (DMI). Data curah hujan yang digunakan pada penelitian ini adalah data curah hujan bulanan di Kota Makassar dari tahun 1987-2016 di tiga stasiun yaitu Panaikang, Paotere, dan Biring Romang sebagai faktor endogen. Data ini diperoleh dari Balai Besar Meteorologi, Klimatologi, dan Geofisika (BBMKG) Wilayah IV Makassar. Pembentukan model VARX melalui beberapa tahap yaitu: uji stasioneritas, penentuan panjang lag optimal, uji kausalitas, diagnostik model, pembentukan model VARX dan peramalan. Hasil penelitian menunjukkan bahwa rata-rata puncak curah hujan di Kota Makassar terjadi di bulan Maret kemudian turun secara eksponensial. Pada bulan Mei peluang terjadinya hujan sangat sedikit. Model yang didapat pada penelitian ini layak digunakan untuk meramalkan curah hujan pada periode berikutnya.Kata Kunci: Model VARX, model VAR, curah hujan, peramalan.This type of research is applied research that aims to predict rainfall in Makassar city VARX model using. The model was developed from the VARX model VAR by adding exogenous factors that influence the precipitation like Sea Surface Temperature (SST) Nino 3.4, the Southern Oscillation Index (SOI), and Dipole Mode Index (DMI). Rainfall data used in this researrchis the monthly rainfall data in Makassar city from 1987-2016 year on three stations, namely Panaikang, Paotere, and Biring Romang as endogenous factors. This data is retrieved from the Great Hall the Meteorology, Climatology, and Geophysics Region IV Makassar. VARX model formation through several stages, namely : test stasioneritas, the determination of the optimal lag length, test causality, diagnostic models, the establishment of the model of forecasting and VARX. The result showed that the average peak rainfall in Makassar city occurred in March and then come down exponentially. In May the chance of occurrence of very little rain.The model obtained in this study deserves to be used to predict rainfall in the next period.Keywords: Model VARX, model VAR, rainfall, forecasting

scholarly journals Climate change drivers influencing Indian mackerel fishery in south-eastern Arabian Sea off Kerala, India

2020 ◽  
Vol 67 (3) ◽  
Author(s):  
P U Zacharia ◽  
V.H. Sajna ◽  
G. Rojith ◽  
G.N. Roshen ◽  
Dhanya Joseph ◽  
...  
Keyword(s):  
Environmental Variables ◽  
Arabian Sea ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Residual Variance ◽  
Catch Per Unit Effort ◽  
Indian Mackerel ◽  
South Eastern ◽  
Eastern Arabian Sea ◽  
Positive Direct

The Indian mackerel Rastrelligerkanagurta(Cuvier, 1816) is one of the most important marine fishery resources along the south-eastern Arabian Sea along the coast of Kerala, south India. The effect of selected environmental variables on the Relative effort (Effort) and weighted catch per unit effort (cpue)of the fish were investigated using simple correlation and Path analysis. Six major oceanographic variables, namely sea surface temperature (SST), sea surface chlorophyll-a concentration (SSC), sea surface salinity (SSS), Precipitation (Pr) Indian Ocean Dipole (IOD) and Southern Oscillation Index (SOI) (ENSO index) were selected for the present study. Among these SST had the highest direct negative effect (-0.282, p<0.01), followed by SSS (-0.152, p<0.1) and IOD (-0.006, p<0.01). The highest positive direct effect on the cpue was exhibited by Pr (0.514, p<0.001) followed by SSC and SOI (0.178, p<0.01). The environmental variables also exerted indirect effects on cpue through Effort. The residual variance indicated that there are spurious effects exerted by environmental variables not included in the study. According to the coefficient of determination (R2), the relative importance of the influence of causally dependent environmental variables on the cpue of Indian mackerel is Pr> SSC >SSS.

Variability of Sea Surface Salinity in the Southeastern Arabian Sea: Driving mechanisms and influence on the Arabian Sea mini Warm Pool

2020 ◽  
Author(s):  
Akhil Valiya Parambil ◽  
Matthieu Lengaigne ◽  
Jerome Vialard ◽  
Krishnamohan Krishnapillai Sukumarapillai ◽  
Keerthi Madhavan Girijakumari
Keyword(s):  
Indian Ocean ◽  
Seasonal Cycle ◽  
Arabian Sea ◽  
Vertical Mixing ◽  
Warm Pool ◽  
Sea Surface ◽  
Interannual Variations ◽  
Salinity Stratification ◽  
Driving Mechanisms ◽  
Southeastern Arabian Sea

&lt;p&gt;With sea surface temperatures (SST) exceeding 30&amp;#730;C in May, the southeastern Arabian Sea (SEAS) hosts one of the warmest open ocean region globally, which appears to play an important role in the summer monsoon onset. Freshwater input from the Bay of Bengal precede the SEAS warm pool build-up by a few months, and are believed to influence its temperature through its impact on oceanic stability and vertical mixing of heat. SSS interannual variations in the SEAS region have not been extensively described before, and their potential feedback on the warm pool build-up and the monsoon are still debated. In the present study, we describe the SEAS SSS seasonal and interannual variability, its driving mechanisms and potential impact on the monsoon. To that end, we analyse experiments performed with a regional 25-km ocean model, both forced and coupled to a regional atmospheric model. The forced and coupled simulations both reproduce the main oceanic features in the SEAS region, including the salinity seasonal cycle and interannual variability. Winter salinity stratification inhibits the vertical mixing of heat, thereby warming the mixed layer by ~0.5&amp;#176;C.month&lt;sup&gt;-1&lt;/sup&gt;. This salinity-induced warming is however compensated by a salinity-induced cooling by air-sea fluxes. Salinity stratification indeed yields a thinner mixed layer which is more efficiently cooled by negative surface heat fluxes at this season. Overall, salinity has thus a negligible impact on the SST seasonal cycle. SEAS SSS interannual variations are largely remotely driven by the Indian Ocean Dipole (IOD), an indigenous interannual climate mode in the equatorial Indian Ocean. The IOD remotely impacts coastal currents along the Indian coastline, and hence modulates freshwater transport from the Bay of Bengal into the SEAS. This yields positive SSS anomalies in the SEAS during the boreal winter that follows positive IOD events. Those SSS anomalies however do not appear to significantly alter the interannual surface layer heat budget. Coupled model sensitivity experiments, in which the influence of haline stratification on vertical mixing is neglected, further confirm that the SEAS winter freshening does not significantly influence the SEAS warm-pool build-up nor the monsoon onset&lt;/p&gt;

Exploring records of typhoon variability in eastern China over the past 2000 years

2020 ◽  
Vol 132 (11-12) ◽  
pp. 2243-2252 ◽  
Author(s):  
Yang Yang ◽  
Liang Zhou ◽  
Alexandre Normandeau ◽  
Jianjun Jia ◽  
Qijun Yin ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
East Asian Monsoon ◽  
Southern Oscillation ◽  
Eastern China ◽  
Warm Pool ◽  
Sea Surface ◽  
Northwestern Pacific ◽  
The Past ◽  
Past 2000 Years

Abstract How climate controls tropical cyclone variability has critical implications for modern human society but is not well understood due to the short length of observational records. To probe this knowledge gap, we present a synthesis of intense typhoon activity from the northwestern Pacific over the past 2000 years, which is supported by a new, well-resolved tidal flat sedimentary record from the Jiangsu coast, eastern China. The record reveals nine intervals of typhoon frequency, indicating that the frequency of intense typhoons has varied on multi-centennial scales over the past 2000 years. Our synthesis shows strong evidence for a seesaw pattern of intense typhoon frequency between southeastern China and Japan and Korea. This pattern can be explained by the El Niño and Southern Oscillation–East Asian Monsoon–sea surface temperature hypothesis, which potentially explains the basin-wide typhoon climate in the northwestern Pacific region. A shift in typhoon activity was identified from 550–280 to 280–50 yr B.P. during the Little Ice Age, when typhoon activity changed from active to quiescent or vice versa. Centennial-scale shifts in Intertropical Convergence Zone and Western Pacific Warm Pool sea surface temperature are likely to be the primary forcing mechanisms driving this shift. Results obtained here provide links between typhoon activity and the El Niño and Southern Oscillation, the East Asian Monsoon, and the Western Pacific Warm Pool sea surface temperature, and therefore improve our ability to fully assess intense typhoon activity in future climate warming.

scholarly journals Correlations between Interannual SST Oscillations and Modeled Swell Impacts on Turbulent Mixing*

2015 ◽  
Vol 29 (1) ◽  
pp. 293-311 ◽  
Author(s):  
Yalin Fan ◽  
W. Erick Rogers ◽  
Tommy G. Jensen
Keyword(s):  
Indian Ocean ◽  
Southern Ocean ◽  
Turbulent Mixing ◽  
Southern Oscillation ◽  
Wind Waves ◽  
Sea Surface ◽  
Interannual Variations ◽  
The Indian Ocean ◽  
Wave Models ◽  
Sst Anomalies

Abstract The possibility of teleconnections between Southern Ocean swells and sea surface temperature (SST) anomalies on interannual time scales in the eastern Pacific Niño-3 region and southeastern Indian Ocean is investigated using numerical wave models. Two alternative parameterizations for swell dissipation are used. It is found that swell dissipation in the models is not directly correlated with large interannual variations such as El Niño–Southern Oscillation (ENSO) or the Indian Ocean dipole (IOD). However, using one of the two swell dissipation parameterizations, a correlation is found between observed SST anomalies and the modification of turbulent kinetic energy flux (TKEF) by Southern Ocean swells due to the damping of short wind waves: modeled reduction of TKEF is opposite in phase to the SST anomalies in the Niño-3 region, indicating a potential positive feedback. The modeled bimonthly averaged TKEF reduction in the southeastern Indian Ocean is also well correlated with the IOD mode.

scholarly journals Cold Tongue and Warm Pool ENSO Events in CMIP5: Mean State and Future Projections

2014 ◽  
Vol 27 (8) ◽  
pp. 2861-2885 ◽  
Author(s):  
Andréa S. Taschetto ◽  
Alexander Sen Gupta ◽  
Nicolas C. Jourdain ◽  
Agus Santoso ◽  
Caroline C. Ummenhofer ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Heat Content ◽  
Coupled Model ◽  
Warm Pool ◽  
Cmip5 Models ◽  
Cold Tongue ◽  
Future Projections ◽  
Enso Events ◽  
Almost All ◽  
Sst Anomalies

Abstract The representation of the El Niño–Southern Oscillation (ENSO) under historical forcing and future projections is analyzed in 34 models from the Coupled Model Intercomparison Project phase 5 (CMIP5). Most models realistically simulate the observed intensity and location of maximum sea surface temperature (SST) anomalies during ENSO events. However, there exist systematic biases in the westward extent of ENSO-related SST anomalies, driven by unrealistic westward displacement and enhancement of the equatorial wind stress in the western Pacific. Almost all CMIP5 models capture the observed asymmetry in magnitude between the warm and cold events (i.e., El Niños are stronger than La Niñas) and between the two types of El Niños: that is, cold tongue (CT) El Niños are stronger than warm pool (WP) El Niños. However, most models fail to reproduce the asymmetry between the two types of La Niñas, with CT stronger than WP events, which is opposite to observations. Most models capture the observed peak in ENSO amplitude around December; however, the seasonal evolution of ENSO has a large range of behavior across the models. The CMIP5 models generally reproduce the duration of CT El Niños but have biases in the evolution of the other types of events. The evolution of WP El Niños suggests that the decay of this event occurs through heat content discharge in the models rather than the advection of SST via anomalous zonal currents, as seems to occur in observations. No consistent changes are seen across the models in the location and magnitude of maximum SST anomalies, frequency, or temporal evolution of these events in a warmer world.

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