What is similarity pattern between ocean currents of Pacific and Atlantic?
Answers
Answer: pacaific is larger than Atlantic
Explanation:
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Abstract
[1] An evaluation of Pacific and Atlantic Ocean sea surface temperatures (SSTs) and continental U.S. streamflow was performed to identify coupled regions of SST and continental U.S. streamflow variability. Both SSTs and streamflow displayed temporal variability when applying the singular value decomposition (SVD) statistical method. Initially, an extended temporal evaluation was performed using the entire period of record (i.e., all years from 1951 to 2002). This was followed by an interdecadal-temporal evaluation for the Pacific (Atlantic) Ocean based on the phase of the Pacific Decadal Oscillation (PDO) (Atlantic Multidecadal Oscillation (AMO)). Finally, an extended temporal evaluation was performed using detrended SST and streamflow data. A lead time approach was assessed in which the previous year's spring-summer season Pacific Ocean (Atlantic Ocean) SSTs were evaluated with the current water year continental U.S. streamflow. During the cold phase of the PDO, Pacific Ocean SSTs influenced streamflow regions (southeast, northwest, southwest, and northeast United States) most often associated with El Niño–Southern Oscillation (ENSO), while during the warm phase of the PDO, Pacific Ocean SSTs influenced non-ENSO streamflow regions (Upper Colorado River basin and middle Atlantic United States). ENSO and the PDO were identified by the Pacific Ocean SST SVD first temporal expansion series as climatic influences for the PDO cold phase, PDO warm phase, and the all years analysis. Additionally, the phase of the AMO resulted in continental U.S. streamflow variability when evaluating Atlantic Ocean SSTs. During the cold phase of the AMO, Atlantic Ocean SSTs influenced middle Atlantic and central U.S. streamflow, while during the warm phase of the AMO, Atlantic Ocean SSTs influenced upper Mississippi River basin, peninsular Florida, and northwest U.S. streamflow. The AMO signal was identified in the Atlantic Ocean SST SVD first temporal expansion series. Applying SVD, first temporal expansions series were developed for Pacific and Atlantic Ocean SSTs and continental U.S. streamflow. The first temporal expansion series of SSTs and streamflow were strongly correlated, which could result in improved streamflow predictability.
1. Introduction
[2] Sea surface temperature (SST) variability can provide important predictive information about hydrologic variability in regions around the world. While coupled SST variability and continental U.S. precipitation (and drought) variability has been examined, water managers could benefit from an evaluation of coupled SST variability and continental U.S. streamflow variability, focusing on improving long lead time forecasts of streamflow. Continental U.S. streamflow regions have been identified that respond to oceanic/atmospheric phenomena such as the El Niño–Southern Oscillation (ENSO) [e.g., Cayan and Peterson, 1989; Cayan and Webb, 1992; Kahya and Dracup, 1993, 1994a, 1994b; Maurer et al., 2004], the Pacific Decadal Oscillation (PDO) [e.g., Maurer et al., 2004], and the Atlantic Multidecadal Oscillation (AMO) [e.g., Enfield et al., 2001; Rogers and Coleman, 2003]. While the interannual ENSO experiences a 2–7 year periodicity [Philander, 1990], the interdecadal PDO [Mantua et al., 1997; Mantua and Hare, 2002] and AMO [Kerr, 2000; Gray et al., 2004] exhibit long-term (e.g., 25–30 year) periodicity of warm and cold phases. Although each of these oceanic/atmospheric phenomena represent SST variability, the SST variability represented is for a specific, spatially predetermined region (e.g., tropical Pacific Ocean, northern Pacific Ocean, northern Atlantic Ocean). The utilization of SSTs for entire regions (Pacific and Atlantic Oceans) eliminates any spatial bias as to which oceanic SST region (or regions) impact continental U.S. streamflow. This could result in new SST (and continental U.S. streamflow) regions being identified as having coupled impacts. Additionally, when evaluating SSTs for extended time series, both interdecadal and interannual SST oscillations can be considered.
[3] Various methods, including canonical correlation analysis, combined principal component analysis and singular value decomposition (SVD) are available to determine coupled relationships between two, spatial-temporal fields such as SSTs and climatic variables. Bretherton et al. [1992] evaluated several statistical methods designed to determine coupled relationships between two, spatial-temporal fields and concluded SVD was simple to perform and preferable for general use. Wallace et al. [1992] evaluated the interannual coupling of wintertime Pacific SSTs and atmospheric 500-mbar height and determined that, when compared to other techniques, SVD isolates the most important modes of variability.
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