scholarly journals Seasonal-To-Interannual Variability of Sea-Surface Temperatures in The Inter-Americas Seas: Pattern-Dependent Biases in The Regional Ocean Modeling System

2021 ◽  
Vol 13 (2) ◽  
pp. 20
Author(s):  
Ana Lucia Caicedo Laurido ◽  
Ángel G. Muñoz Solórsano ◽  
Xandre Chourio ◽  
Cristian Andrés Tobar Mosquera ◽  
Sadid Latandret

The Inter-Americas Seas (IAS), involving the Gulf of Mexico, the Caribbean and a section of the eastern tropical Pacific Ocean bordering Central America, Colombia and Ecuador, exhibits very active ocean-land-atmosphere interactions that impact socio-economic activities within and beyond the region, and that are still not well understood or represented in state-of-the-art models. On seasonal-to-interannual timescales, the main source of variability of this geographical area is related to interactions between the Pacific and the Atlantic oceans, involving to anomalous sea-surface temperature (SST) patterns like El Niño-Southern Oscillation (ENSO), and regional features in the Caribbean linked to the bi-modal seasonality of the Caribbean Low-Level Jet. This study investigates seasonal-to-interannual IAS surface-temperature anomalies in observations, and their representation in am eddy-permitting, 1/9o-resolution simulation using the Regional Ocean Modeling System (ROMS), interannually-forced by the Climate Forecast System Reanalysis. Here, rather than analyzing model biases locally (i.e., gridbox-by-gridbox), a non-local SST pattern-based diagnostic was conducted via a principal component analysis. The approach allowed to identify magnitude, variance and spatial systematic errors in SST patterns related to the Western Hemisphere Warm Pool, ENSO, the Inter-American Seas Dipole, and several other variability modes. These biases are mainly related to errors in surface heat fluxes, misrepresentation of air-sea interactions impacting surface latent cooling in the Caribbean, and too strong sub-surface thermal stratification, mostly off the coast of Ecuador and northern Peru.

2012 ◽  
Vol 9 (6) ◽  
pp. 3795-3850 ◽  
Author(s):  
G. Esnaola ◽  
J. Sáenz ◽  
E. Zorita ◽  
A. Fontán ◽  
V. Valencia ◽  
...  

Abstract. The combination of remotely sensed gappy sea surface temperature (SST) images with the missing data filling Data Interpolating EOFs (DINEOF) technique followed by a Principal Component Analysis of the reconstructed data, has been used to identify the time evolution and the daily scale variability of the winter-time surface signal of the Iberian Poleward Current (IPC) during the 1981–2010 period. An exhaustive comparison with the existing bibliography, and the vertical temperature and salinity profiles related to its extremes over the Bay of Biscay area, show that the obtained time series accurately reflect the variability of the IPC. A physical mechanism involving both atmospheric and oceanic variables is proposed in relation to the variability of the IPC. It jointly takes into account several mechanisms that have separately been related to the variability of the IPC, i.e. the south-westerly winds, the Joint Effect of Baroclinicity And Relief (JEBAR) effect, the topographic β effect and a weakened North Atlantic Gyre. This mechanism emerges from an atmospheric 500 hPa circulation anomaly that has not a simple relationship with any of the most common North Atlantic teleconnection patterns. It then generates mutually coherent SST and sea level anomaly patterns in the North Atlantic area due to the action of anomalous wind-stress and heat-fluxes, and locally, it also generates the conditions for the mentioned mechanisms in the Bay of Biscay area.


2010 ◽  
Vol 138 (4) ◽  
pp. 1186-1205 ◽  
Author(s):  
Ki-Young Heo ◽  
Kyung-Ja Ha

Abstract This study examined the impact of air–sea coupling using a coupled atmosphere–ocean modeling system consisting of the Coupled Ocean–Atmosphere Mesoscale Prediction System as the atmospheric component and the Regional Ocean Modeling System as the oceanic component. Numerical experiments for advection and steam fog events were carried out to clarify the modulation of the formation and dissipation of sea fogs by the air–sea temperature difference (air temperature minus sea surface temperature) and the atmospheric stability. The coupled simulation showed that advection fog is obviously controlled by low-level atmospheric stability and downward latent heat flux with oceanic cooling through air–sea coupling. In particular, air–sea coupling stabilizes the low-level atmosphere at the dissipation stage, and then suppresses vertical mixing, which retards the dissipation of advection fog. In the case of a steam fog event, the upward turbulent heat fluxes are increased significantly from the formation time to the mature time. A decrease in sea surface temperature cools the low-level atmosphere, which increases the condensation rate and low-level atmospheric stability, eventually retarding the dissipation of steam fog.


Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 454
Author(s):  
Andrew R. Jakovlev ◽  
Sergei P. Smyshlyaev ◽  
Vener Y. Galin

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.


2000 ◽  
Vol 203 (15) ◽  
pp. 2311-2322 ◽  
Author(s):  
B. Culik ◽  
J. Hennicke ◽  
T. Martin

We satellite-tracked five Humboldt penguins during the strong 1997/98 El Nino Southern Oscillation (ENSO) from their breeding island Pan de Azucar (26 degrees 09′S, 70 degrees 40′W) in Northern Chile and related their activities at sea to satellite-derived information on sea surface temperature (SST), sea surface temperature anomaly (SSTA), wind direction and speed, chlorophyll a concentrations and statistical data on fishery landings. We found that Humboldt penguins migrated by up to 895 km as marine productivity decreased. The total daily dive duration was highly correlated with SSTA, ranging from 3.1 to 12.5 h when the water was at its warmest (+4 degrees C). Birds travelled between 2 and 116 km every day, travelling further when SSTA was highest. Diving depths (maximum 54 m), however, were not increased with respect to previous years. Two penguins migrated south and, independently of each other, located an area of high chlorophyll a concentration 150 km off the coast. Humboldt penguins seem to use day length, temperature gradients, wind direction and olfaction to adapt to changing environmental conditions and to find suitable feeding grounds. This makes Humboldt penguins biological in situ detectors of highly productive marine areas, with a potential use in the verification of trends detected by remote sensors on board satellites.


2014 ◽  
Vol 57 (5) ◽  
Author(s):  
Nazario Tartaglione ◽  
Rodrigo Caballero

<p>This article investigates the role of sea surface temperature (SST) as well as the effects of evaporation and moisture convergence on the evolution of cyclone Klaus, which occurred on January 23 and 24, 2009. To elucidate the role of sea surface temperature (SST) and air–sea fluxes in the dynamics of the cyclone, ten hydrostatic mesoscale simulations were performed by Bologna Limited Area Model (BOLAM). The first one was a control experiment with European Centre for Medium-Range Weather Forecasts (ECMWF) SST analysis. The nine following simulations are sensitivity experiments where the SST are obtained by adding a constant value by 1 to 9 K to the ECMWF field. Results show that a warmer sea increases the surface latent heat fluxes and the moisture convergence, favoring the development of convection in the storm. Convection is affected immediately by the increased SST. Later on, drop of mean sea level pressure (MSLP) occurs together with increasing of surface winds. The cyclone trajectory is not sensitive to change in SST differently from MSLP and convective precipitation.</p>


2011 ◽  
Vol 4 (2) ◽  
pp. 264
Author(s):  
Madson Tavares Silva ◽  
Stephany C. F. Do Egito Costa ◽  
Manoel Francisco Gomes Filho ◽  
Daisy B. Lucena

Apresenta-se neste estudo a avaliação da metodologia de Análises Multivariadas: Análises em Componente Principal (ACP) e de Agrupamento (AA), aos dados de Temperatura da Superfície do Mar (TSM) para os Oceanos Atlântico (Norte (NATL), Tropical (TROP) e Sul (SATL)) e Pacifico (NIÑO1+2, NIÑO3.4, NIÑO3 e NIÑO4). Foram utilizados dados mensais de janeiro de 1950 a dezembro de 2010 de TSM obtidos na NOAA (National Oceanic and Atmospheric Administration/Earth System Research Laboratory). As regiões TROP e NIÑO4 apresentam as maiores TSM para os meses entre dezembro-julho. A região NATL apresenta no período de agosto-outubro seu maiores valores de TSM. A região NIÑo1+2 apresentou os menores valores de TSM. Os resultados da Análise em Componente Principal (ACP) identificaram maiores pesos na variação total explicada pelas duas primeiras componentes, que representam cerca de 100% da variância total dos dados de TSM. A Análise de Agrupamento (AA), pelo método Ward, permitiu o agrupamento das estações em três grupos homogêneos. Palavras - chave: Análises Multivariadas, Mudanças climáticas, Aquecimento Global.   Study of Sea Surface Temperature for the Atlantic and Pacific Oceans Using the Technique of Principal Component Analysis and Cluster   ABSTRACT Presented in this study was to evaluate the methodology of Multivariate Analysis: Principal Component Analysis (PCA) and cluster analysis (CA), the data of sea surface temperature (SST) for the Atlantic (North (NATL), Tropical (TROP) and South (Satler)) and Pacific (+2 NIÑO1, NIÑO3.4, and NIÑO3 NIÑO4). We used monthly data from January 1950 to December 2010 SST obtained from NOAA (National Oceanic and Atmospheric Administration / Earth System Research Laboratory). TROP and NIÑO4 regions have the highest SST for the months from December to July. NATL The region has in the period August-October SST your highest values +2 NIÑo1 The region had the lowest values of TSM. Results on Principal Component Analysis (PCA) identified higher weights in the total variation explained by the first two components, which represent about 100% of the total variance of SST. The Cluster Analysis (AA), the Ward method, allowed the grouping of stations into three homogeneous groups. Keywords: Multivariate Analysis, Climate Change, Global Warming.


2016 ◽  
Vol 42 ◽  
pp. 73-81
Author(s):  
Miguel Tasambay-Salazar ◽  
María José OrtizBeviá ◽  
Antonio RuizdeElvira ◽  
Francisco José Alvarez-García

Abstract. The El Niño-Southern Oscillation (ENSO) phenomenon is the main source of the predictability skill in many regions of the world for seasonal and interannual timescales. Longer lead predictability experiments of Niño3.4 Index using simple statistical linear models have shown an important skill loss at longer lead times when the targeted season is summer or autumn. We develop different versions of the model substituting some its variables with others that contain tropical or extratropical information, produce a number of hindcasts with these models using two different predictions schemes and cross validate them. We have identified different sets of tropical or extratropical predictors, which can provide useful values of potential skill. We try to find out the sources of the predictability by comparing the sea surface temperature (SST) and heat content (HC) anomalous fields produced by the successful predictors for the 1980–2012 period. We observe that where tropical predictors are used the prediction reproduces only the equatorial characteristics of the warming (cooling). However, where extratropical predictors are included, the predictions are able to simulate the absorbed warming in the South Pacific Convergence Zone (SPCZ).


2014 ◽  
Vol 142 (5) ◽  
pp. 1771-1791 ◽  
Author(s):  
Mohamed Helmy Elsanabary ◽  
Thian Yew Gan

Abstract Rainfall is the primary driver of basin hydrologic processes. This article examines a recently developed rainfall predictive tool that combines wavelet principal component analysis (WPCA), an artificial neural networks-genetic algorithm (ANN-GA), and statistical disaggregation into an integrated framework useful for the management of water resources around the upper Blue Nile River basin (UBNB) in Ethiopia. From the correlation field between scale-average wavelet powers (SAWPs) of the February–May (FMAM) global sea surface temperature (SST) and the first wavelet principal component (WPC1) of June–September (JJAS) seasonal rainfall over the UBNB, sectors of the Indian, Atlantic, and Pacific Oceans where SSTs show a strong teleconnection with JJAS rainfall in the UBNB (r ≥ 0.4) were identified. An ANN-GA model was developed to forecast the UBNB seasonal rainfall using the selected SST sectors. Results show that ANN-GA forecasted seasonal rainfall amounts that agree well with the observed data for the UBNB [root-mean-square errors (RMSEs) between 0.72 and 0.82, correlation between 0.68 and 0.77, and Hanssen–Kuipers (HK) scores between 0.5 and 0.77], but the results in the foothills region of the Great Rift Valley (GRV) were poor, which is expected since the variability of WPC1 mainly comes from the highlands of Ethiopia. The Valencia and Schaake model was used to disaggregate the forecasted seasonal rainfall to weekly rainfall, which was found to reasonably capture the characteristics of the observed weekly rainfall over the UBNB. The ability to forecast the UBNB rainfall at a season-long lead time will be useful for an optimal allocation of water usage among various competing users in the river basin.


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