scholarly journals Global wave number-4 pattern in the southern subtropical sea surface temperature

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Balaji Senapati ◽  
Mihir K. Dash ◽  
Swadhin K. Behera
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Wave Number ◽  
The South ◽  
South Eastern ◽  
Eastern Australia ◽  
Zonal Wavenumber ◽  
Sst Anomaly

AbstractExploratory analysis using empirical orthogonal function revealed the presence of a stationary zonal wavenumber-4 (W4) pattern in the sea surface temperature (SST) anomaly in the southern subtropics (20°S–55°S). The signal over the Southern subtropics is seasonally phase-locked to the austral summer and persists up to mid-autumn. Thermodynamic coupling of atmosphere and the upper ocean helps in generating the W4 pattern, which later terminates due to the breaking of that coupled feedback. It is found that the presence of anomalous SST due to W4 mode in the surrounding of Australia affects the rainfall over the continent by modulating the local atmospheric circulation. During positive phase of W4 event, the presence of cold SST anomaly over the south-eastern and -western side of Australia creates an anomalous divergence circulation. This favours the moisture transport towards south-eastern Australia, resulting in more rainfall in February. The scenario reverses in case of a negative W4 event. There is also a difference of one month between the occurrence of positive and negative W4 peaks. This asymmetry seems to be responsible for the weak SST signal to the South of Australia. Correlation analysis suggests that the W4 pattern in SST is independent of other natural variabilities such as Southern Annular Mode, and Indian Ocean Dipole as well as a rather weak relationship with El Niño/Southern Oscillation.

scholarly journals On the impact of atmospheric vs oceanic resolutions on the representation of the sea surface temperature in the South Eastern Tropical Atlantic

2020 ◽  
Vol 54 (11-12) ◽  
pp. 4733-4757 ◽  
Author(s):  
Alba de la Vara ◽  
William Cabos ◽  
Dmitry V. Sein ◽  
Dmitry Sidorenko ◽  
Nikolay V. Koldunov ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Tropical Atlantic ◽  
The South ◽  
South Eastern ◽  
The Impact

Optimal Tropical Sea Surface Temperature Forcing of North American Drought

2010 ◽  
Vol 23 (14) ◽  
pp. 3907-3917 ◽  
Author(s):  
Sang-Ik Shin ◽  
Prashant D. Sardeshmukh ◽  
Robert S. Webb
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North American ◽  
General Circulation ◽  
Southern Oscillation ◽  
Circulation Model ◽  
Sea Surface ◽  
Drought Severity ◽  
Sst Anomaly

Abstract The optimal anomalous sea surface temperature (SST) pattern for forcing North American drought is identified through atmospheric general circulation model integrations in which the response of the Palmer drought severity index (PDSI) is determined for each of 43 prescribed localized SST anomaly “patches” in a regular array over the tropical oceans. The robustness and relevance of the optimal pattern are established through the consistency of results obtained using two different models, and also by the good correspondence of the projection time series of historical tropical SST anomaly fields on the optimal pattern with the time series of the simulated PDSI in separate model integrations with prescribed time-varying observed global SST fields for 1920–2005. It is noteworthy that this optimal drought forcing pattern differs markedly in the Pacific Ocean from the dominant SST pattern associated with El Niño–Southern Oscillation (ENSO), and also shows a large sensitivity of North American drought to Indian and Atlantic Ocean SSTs.

scholarly journals A Verified Estimation of the El Niño Index Niño-3.4 since 1877

2009 ◽  
Vol 22 (14) ◽  
pp. 3979-3992 ◽  
Author(s):  
Lucia Bunge ◽  
Allan J. Clarke
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
Correlation Coefficients ◽  
Sea Surface ◽  
Monthly Time Series ◽  
Sst Anomaly

Abstract Decadal and longer time-scale variabilities of the best known El Niño–Southern Oscillation (ENSO) indexes are poorly correlated before 1950, and so knowledge of interdecadal variability and trend in ENSO indexes is dubious, especially before 1950. To address this problem, the authors constructed and compared physically related monthly ENSO indexes. The base index was El Niño index Niño-3.4, the sea surface temperature (SST) anomaly averaged over the equatorial box bounded by 5°N, 5°S, 170°W, and 120°W; the authors also constructed indexes based on the nighttime marine air temperature over the Niño-3.4 region (NMAT3.4) and an equatorial Southern Oscillation index (ESOI). The Niño-3.4 index used the “uninterpolated” sea surface temperature data from the Second Hadley Centre Sea Surface Temperature dataset (HadSST2), a dataset with smaller uncertainty and better geographical coverage than others. In constructing the index, data at each point for a given month were weighted to take into account the typical considerable spatial variation of the SST anomaly over the Niño-3.4 box as well as the number of observations at that point for that month. Missing monthly data were interpolated and “noise” was reduced by using the result that Niño-3.4 has essentially the same calendar month amplitude structure every year. This 12-point calendar month structure from April to March was obtained by an EOF analysis over the last 58 yr and then was fitted to the entire monthly time series using a least squares approach. Equivalent procedures were followed for NMAT3.4 and ESOI. The new ESOI uses Darwin atmospheric pressure in the west and is based on theory that allows for variations of the atmospheric boundary layer depth across the Pacific. The new Niño-3.4 index was compared with NMAT3.4, the new ESOI, and with a record of δ18O from a coral at Palmyra, an atoll inside the region Niño-3.4 (Cobb et al.). Correlation coefficients between Niño-3.4 and the three monthly indexes mentioned above before 1950 are 0.84, 0.87, 0.73 and 0.93, 0.86, 0.73 for decadal time scales. These relatively high correlation coefficients between physically related but independent monthly time series suggest that this study has improved knowledge of low-frequency variability. All four indexes are consistent with a rise in Niño-3.4 SST and the weakening of the equatorial Pacific winds since about 1970.

scholarly journals Why Did Large Differences Arise in the Sea Surface Temperature Datasets across the Tropical Pacific during 2012?

2013 ◽  
Vol 30 (12) ◽  
pp. 2944-2953 ◽  
Author(s):  
Boyin Huang ◽  
Michelle L’Heureux ◽  
Jay Lawrimore ◽  
Chunying Liu ◽  
Huai-Min Zhang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Oscillation ◽  
Tropical Pacific ◽  
Sea Surface ◽  
Bias Adjustment ◽  
The Status ◽  
Sst Anomaly ◽  
The Tropical Pacific

Abstract During June–November 2012, pronounced differences in tropical Pacific sea surface temperature (SST) anomalies were observed between three widely used SST products: the extended reconstructed SST version 3b (ERSSTv3b), and the optimum interpolation SST version 2 analyses (OISST), produced weekly (OISSTwk) and daily (OISSTdy). During June–August 2012, the Niño-3.4 SST anomaly (SSTA) index was 0.2°–0.3°C lower in ERSSTv3b than in OISSTwk and OISSTdy, while it was 0.3°–0.4°C higher from September to November 2012. Such differences in the Niño-3.4 SSTA index can impact the assessment of the status of the El Niño–Southern Oscillation, which is determined using a threshold of ±0.5°C in the Niño-3.4 SSTA index. To investigate the reasons for the differences between ERSSTv3b and OISSTdy/OISSTwk, an experimental analysis (called ERSSTsat) is created that is similar to ERSSTv3b but includes satellite-derived SSTs. However, significant differences in the Niño-3.4 SSTA index remained between ERSSTsat and OISSTdy/OISSTwk. Comparisons of ERSSTsat and OISSTdy indicate that their differences are mostly associated with the different schemes for bias adjustment applied to the satellite-based SSTs. It is therefore suggested that the differences in the Niño-3.4 SSTA index between ERSSTv3b and OISSTdy cannot be solely due to the inclusion of but by the bias adjustment methodology of satellite data in OISSTdy. Finally, the SST products are compared with observations from ships, buoys, and satellites. On the monthly time scale, the area-averaged Niño-3.4 SSTA index in the tropical Pacific is more consistent with in situ observations in ERSSTv3b than in OISSTdy. In contrast, pointwise observations across the tropical Pacific are more consistent with OISSTdy than ERSSTv3b. It is therefore suggested that the differences among SST products are partially due to a structural uncertainty of various SST estimates.

Long range forecasts of the numbers of Helicoverpa punctigera and H. armigera (Lepidoptera: Noctuidae) in Australia using the Southern Oscillation Index and the Sea Surface Temperature

2000 ◽  
Vol 90 (2) ◽  
pp. 133-146 ◽  
Author(s):  
D.A. Maelzer ◽  
M.P. Zalucki
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Pest Management ◽  
Southern Oscillation Index ◽  
Southern Oscillation ◽  
Sea Surface ◽  
Multiple Regressions ◽  
Eastern Australia ◽  
Trap Catches

The use of long-term forecasts of pest pressure is central to better pest management. We relate the Southern Oscillation Index (SOI) and the Sea Surface Temperature (SST) to long-term light-trap catches of the two key moth pests of Australian agriculture, Helicoverpa punctigera (Wallengren) and H. armigera (Hübner), at Narrabri, New South Wales over 11 years, and for H. punctigera only at Turretfield, South Australia over 22 years. At Narrabri, the size of the first spring generation of both species was significantly correlated with the SOI in certain months, sometimes up to 15 months before the date of trapping. Differences in the SOI and SST between significant months were used to build composite variables in multiple regressions which gave fitted values of the trap catches to less than 25% of the observed values. The regressions suggested that useful forecasts of both species could be made 6–15 months ahead. The influence of the two weather variables on trap catches of H. punctigera at Turretfield were not as strong as at Narrabri, probably because the SOI was not as strongly related to rainfall in southern Australia as it is in eastern Australia. The best fits were again given by multiple regressions with SOI plus SST variables, to within 40% of the observed values. The reliability of both variables as predictors of moth numbers may be limited by the lack of stability in the SOI-rainfall correlation over the historical record. As no other data set is available to test the regressions, they can only be tested by future use. The use of long-term forecasts in pest management is discussed, and preliminary analyses of other long sets of insect numbers suggest that the Southern Oscillation Index may be a useful predictor of insect numbers in other parts of the world.

Relative contributions of North and South Pacific sea surface temperature anomalies to ENSO

2020 ◽  
Author(s):  
Ruiqiang Ding ◽  
Yu-heng Tseng ◽  
Jianping Li
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Southern Oscillation ◽  
South Pacific ◽  
Sea Surface ◽  
Coupling Mechanism ◽  
The South ◽  
Enso Events ◽  
The North ◽  
Sst Forcing

<p>Variations in the sea surface temperature (SST) field in both the North Pacific [represented by the Victoria mode (VM)] and the South Pacific [represented by the South Pacific Quadrapole (SPQ) mode] are related to the state of the El Niño-Southern Oscillation (ENSO) three seasons later. Here, with the aid of observational data and numerical experiments, we demonstrate that both VM and SPQ SST forcing can influence the development of ENSO events through a similar air–sea coupling mechanism. By comparing ENSO amplitudes induced by the VM and SPQ, as well as the percentages of strong ENSO events followed by the VM and SPQ events, we find that the VM and SPQ make comparable contributions and therefore have similar levels of importance to ENSO. Additional analysis indicates that although VM or SPQ SST forcing alone may serve as a good predictor for ENSO events, it is more effective to consider their combined influence. A prediction model based on both VM and SPQ indices is developed, which is capable of yielding skillful forecasts for ENSO at lead times of three seasons.</p>

scholarly journals Interannual Variability and Trends in Sea Surface Temperature, Lower and Middle Atmosphere Temperature at Different Latitudes for 1980–2019

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 454
Author(s):  
Andrew R. Jakovlev ◽  
Sergei P. Smyshlyaev ◽  
Vener Y. Galin
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Lower Stratosphere ◽  
Middle Atmosphere ◽  
Southern Oscillation ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Sea Surface ◽  
The Arctic ◽  
The Impact

The influence of sea-surface temperature (SST) on the lower troposphere and lower stratosphere temperature in the tropical, middle, and polar latitudes is studied for 1980–2019 based on the MERRA2, ERA5, and Met Office reanalysis data, and numerical modeling with a chemistry-climate model (CCM) of the lower and middle atmosphere. The variability of SST is analyzed according to Met Office and ERA5 data, while the variability of atmospheric temperature is investigated according to MERRA2 and ERA5 data. Analysis of sea surface temperature trends based on reanalysis data revealed that a significant positive SST trend of about 0.1 degrees per decade is observed over the globe. In the middle latitudes of the Northern Hemisphere, the trend (about 0.2 degrees per decade) is 2 times higher than the global average, and 5 times higher than in the Southern Hemisphere (about 0.04 degrees per decade). At polar latitudes, opposite SST trends are observed in the Arctic (positive) and Antarctic (negative). The impact of the El Niño Southern Oscillation phenomenon on the temperature of the lower and middle atmosphere in the middle and polar latitudes of the Northern and Southern Hemispheres is discussed. To assess the relative influence of SST, CO2, and other greenhouse gases’ variability on the temperature of the lower troposphere and lower stratosphere, numerical calculations with a CCM were performed for several scenarios of accounting for the SST and carbon dioxide variability. The results of numerical experiments with a CCM demonstrated that the influence of SST prevails in the troposphere, while for the stratosphere, an increase in the CO2 content plays the most important role.

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