scholarly journals Ocean and atmosphere coupling, connection between sub-polar Atlantic air temperature, Icelandic minimum and temperature in Serbia

2009 ◽  
Vol 89 (3) ◽  
pp. 165-176 ◽  
Author(s):  
Bosko Milovanovic ◽  
Milan Radovanovic ◽  
Vladan Ducic
Keyword(s):  
Cluster Analysis ◽  
Atlantic Ocean ◽  
Air Temperature ◽  
Atmospheric Pressure ◽  
Southern Oscillation ◽  
Hierarchical Cluster ◽  
Sea Surface ◽  
Ocean Temperature ◽  
Grid Cells ◽  
Oscillation Mechanism

In the presented paper correlation between the northern part of the Atlantic ocean (belt between 50-65?N) and the atmospheric pressure is examined. Connection between the ocean temperature and atmospheric pressure is the most obvious in the El Nino southern oscillation mechanism. Thus, so far it is not known that such a mechanism exist in the Atlantic ocean. The main accent in the presented paper is focused on the connection between Iceland low and the sea surface temperature (SST) in the subpolar part of the Atlantic ocean (used data are in grid 5x5?). By hierarchical cluster analysis five relatively unified clusters of sea surface temperatures grid cells are defined. By multiple linear regression, we examined the correlation between each of the depicted clusters with position and intensity of Iceland low, and identified the most important grid cells inside every cluster. The analysis of the relation between Iceland low and air temperature in Serbia and Belgrade has shown the strongest correlation for the longitude of this centre of action. .

scholarly journals Linkage between water temperature of the subtropical Atlantic, the Azores maximum and air temperature in Serbia

2010 ◽  
Vol 90 (2) ◽  
pp. 69-84
Author(s):  
Bosko Milovanovic ◽  
Milan Radovanovic ◽  
Tamara Jojic-Glavonjic
Keyword(s):  
Linear Regression ◽  
Atlantic Ocean ◽  
Multiple Linear Regression ◽  
Water Temperature ◽  
Air Temperature ◽  
Atmospheric Pressure ◽  
Hierarchical Cluster ◽  
Geographical Latitude ◽  
Pressure Maximum ◽  
Hierarchical Cluster Analyses

The paper explores the link between water temperature of the subtropical part of the Atlantic Ocean (the belt of 25 to 40? N), atmospheric pressure and air temperature in Belgrade and Serbia. The main point of the research is to examine the linkage between the Azores air pressure maximum with the changes of water temperature in the subtropical belt of the Atlantic (given in the net 5x5?). Using the hierarchical cluster analyses, 10 clusters of water temperature of the subtropical part of the Atlantic Ocean were selected. Their linkage between the position and the intensity of the Azores maximum was examined by multiple-linear regression. It was established which of the clusters influenced most the geographical latitude, geographical longitude and the intensity of the Azores maximum, as well as which of the grid cells represented the most significant predictors within each of the clusters. Examining the relation between the position and the intensity of the Azores maximum with the air temperature in Belgrade, i.e. Serbia, it was established that the linkage with the geographical latitude of this action centre was the most significant. .

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.

Interdecadal Changes in the Relationship between Wintertime Surface Air Temperature over the Indo-China Peninsula and ENSO

2021 ◽  
pp. 1-45
Author(s):  
Juncong Li ◽  
Zhiping Wen ◽  
Xiuzhen Li ◽  
Yuanyuan Guo
Keyword(s):  
Air Temperature ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Seasonal Prediction ◽  
Atmospheric Model ◽  
Sea Surface ◽  
Warm Temperature ◽  
Southwesterly Wind ◽  
The Relationship ◽  
Sst Anomalies

AbstractInterdecadal variations of the relationship between El Niño-Southern Oscillation (ENSO) and the Indo-China Peninsula (ICP) surface air temperature (SAT) in winter are investigated in the study. Generally, there exists a positive correlation between them during 1958–2015 because the ENSO-induced anomalous western North Pacific anticyclone (WNPAC) is conducive to pronounced temperature advection anomalies over the ICP. However, such correlation is unstable in time, having experienced a high-to-low transition around the mid-1970s and a recovery since the early-1990s. This oscillating relationship is owing to the anomalous WNPAC intensity in different decades. During the epoch of high correlation, the anomalous WNPAC and associated southwesterly winds over the ICP are stronger, which brings amounts of warm temperature advections and markedly heats the ICP. Differently, a weaker WNPAC anomaly and insignificant ICP SAT anomalies are the circumstances for the epoch of low correlation. It is also found that substantial southwesterly wind anomalies over the ICP related to the anomalous WNPAC occur only when large sea surface temperature (SST) anomalies over the northwest Indian Ocean (NWIO) coincide with ENSO (namely when the ENSO-NWIO SST connection is strong). The NWIO SST anomalies are capable of driving favorable atmospheric circulation that effectively alters ICP SAT and efficiently modulates the ENSO-ICP SAT correlation, which is further supported by numerical simulations utilizing the Community Atmospheric Model, version 4 (CAM4). This paper emphasizes the non-stationarity of the ENSO-ICP SAT relationship and also uncovers the underlying modulation factors, which has important implications for the seasonal prediction of the ICP temperature.

scholarly journals How Much of Monthly Subsurface Temperature Variability in the Equatorial Pacific Can Be Recovered by the Specification of Sea Surface Temperatures?

2014 ◽  
Vol 27 (4) ◽  
pp. 1559-1577 ◽  
Author(s):  
Arun Kumar ◽  
Hui Wang ◽  
Yan Xue ◽  
Wanqiu Wang
Keyword(s):  
Initial Conditions ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Temperature Variability ◽  
Sea Surface ◽  
Model Integration ◽  
Ocean Temperature ◽  
Enso Prediction ◽  
Subsurface Ocean ◽  
Ocean Observing

Abstract The focus of the analysis is to investigate the question to what extent the specification of sea surface temperature (SST) in coupled model integration can impart realistic evolution of subsurface ocean temperature in the equatorial tropical Pacific. In the context of El Niño–Southern Oscillation (ENSO) prediction, the analysis is of importance from two aspects: such a system can be considered as a simple coupled ocean data assimilation system that can provide ocean initial conditions; and what additional components of the ocean observing system may be crucial for skillful ENSO prediction. The results indicate that coupled model integration where SST is continuously nudged toward the observed state can generate a realistic evolution of subsurface ocean temperature. The evolution of slow variability related to ENSO, in particular, has a good resemblance against the observational counterpart. The realism of subsurface ocean temperature variability is highest near the date line and least in the far eastern Pacific where the thermocline is shallowest. The results are also discussed in the context of ocean observing system requirements for ENSO prediction.

scholarly journals Technical Note: Is radiation important for the high amplitude variability of the MOC in the North Atlantic?

2007 ◽  
Vol 4 (5) ◽  
pp. 699-707
Author(s):  
D. Nof ◽  
L. Yu
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Air Temperature ◽  
North Atlantic ◽  
High Amplitude ◽  
Technical Note ◽  
Heat Fluxes ◽  
Sea Surface ◽  
Ocean Temperature ◽  
The Difference

Abstract. Radiation is of fundamental importance to climate modeling and it is customary to assume that it is also important for the variability of North Atlantic Deep Water (NADW) formation and the meridional overturning cell (MOC). Numerous articles follow this scenario and incorporate radiation into the calculation. Using relatively old heat-flux maps based on measurements taken in the nineteen sixties, Sandal and Nof (2007) recently suggested that, even though the radiation terms are of the same order as the other heat-flux terms, they are not important for the variability of the NADW and the MOC. They proposed that only sensible and latent heat fluxes are important for the long-term variability of the convection, i.e., for processes such as Heinrich events, which supposedly correspond to turning convection on-and-off in the Atlantic. Here, we place this suggestion on a firmer ground by presenting new and accurate up-to-date heat flux maps that also suggest that the radiation is of no major consequence to the NADW variability. Also, we attribute the relative importance of sensible and latent heat fluxes and the contrasting negligible role of radiation to the fact that the latent and sensible heat fluxes are primarily proportional to the difference between the sea surface and the air temperature whereas the radiation is primarily proportional to the sea surface temperature, i.e., radiation is approximately independent of the atmospheric temperature. Due the small heat capacity ratio of air/water (1/4), the difference between the ocean temperature and the air temperature varies dramatically between the state of active and inactive MOC, whereas the ocean temperature by itself varies very modestly between a state of active and inactive convection.

DRSA: a non-hierarchical clustering algorithm using k-NN graph and its application in vegetation classification

2015 ◽  
pp. 125-138 ◽  
Author(s):  
I. V. Goncharenko
Keyword(s):  
Cluster Analysis ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Clustering Algorithms ◽  
Protein Structures ◽  
Hierarchical Cluster ◽  
Vegetation Classification ◽  
K Nearest Neighbor ◽  
Neighbor Graph ◽  
Nearest Neighbor Graph

In this article we proposed a new method of non-hierarchical cluster analysis using k-nearest-neighbor graph and discussed it with respect to vegetation classification. The method of k-nearest neighbor (k-NN) classification was originally developed in 1951 (Fix, Hodges, 1951). Later a term “k-NN graph” and a few algorithms of k-NN clustering appeared (Cover, Hart, 1967; Brito et al., 1997). In biology k-NN is used in analysis of protein structures and genome sequences. Most of k-NN clustering algorithms build «excessive» graph firstly, so called hypergraph, and then truncate it to subgraphs, just partitioning and coarsening hypergraph. We developed other strategy, the “upward” clustering in forming (assembling consequentially) one cluster after the other. Until today graph-based cluster analysis has not been considered concerning classification of vegetation datasets.

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