Principal Component Analysis of Winter 2013-2014 - Finding the Predominant Modes

Using the predominant signals of the Winter 13-14 (defined by NDJF), Extremely Warm Mean NPAC SST's, Very High Bering Sea/Alaskan Mean 500mb Heights, Very Low S.E. Canada/Hudson Bay Mean 500mb Heights, and High Pressure dominant Sea Level Pressure over the North Central Plains. These 4 Datasets since 1948 were put through Rotated Principle Components Analysis.

Two Principal Components had significant Eigenvalues of 1 or above and explained 79% of the Winter (NDJF) Pattern. The 1st Principle component explained 43.4% and was determined to be the predominant boreal mode of the East Pacific Oscillation (EPO). The 2nd Principle component explained 35.6% and was determined to be the Tropical/Northern Hemiphere (TNH) teleconnection.

 



NEW: Global Wind Oscillation Analog Model OUTPUT, March Still likely to be colder then normal. Atmospheric Base State: +Torque / Ninoesque

I just ran the Global Wind Oscillation analog model. The atmospheric base stateh at the end of February was that of  + Frictional/Mountain Torque, very close to El-Nino-like. I thought maybe you, the reader would like to see some of the process. Hence, here is the FORTRAN Output along with an info graphic. CLICK ON INFOGRAPHIC FOR FULL SIZE or Click: Infographic

Fortran Output:

  AAM-Y  TEND-X  -ANGLE-  -MAG-  Q  Year  M DI-DE #D ATMENSO PHS
  0.548  -0.653  140.022  0.853  2  1958  2 20-28  9 -Torque 7.5
 -0.731   0.363  296.426  0.816  4  1959  2 20-28  9 La Nina 3.5
 -0.536   0.713  323.102  0.892  4  1960  2 20-28  9 +Torque 3.5
 -0.287   0.734  338.678  0.788  4  1961  2 20-28  9 +Torque 4.5
 -1.053   0.222  281.913  1.077  4  1962  2 20-28  9 La Nina 2.5
 -2.507  -0.494  258.842  2.555  3  1963  2 20-28  9 La Nina 2.5
 -0.284   0.550  332.653  0.619  4  1964  2 20-28  9 +Torque 3.5
 -1.268   0.604  295.491  1.404  4  1965  2 20-28  9 La Nina 3.5
 -1.374  -0.141  264.138  1.382  3  1966  2 20-28  9 La Nina 2.5
 -1.399   0.073  273.001  1.401  4  1967  2 20-28  9 La Nina 2.5
 -0.239  -1.663  188.173  1.680  3  1968  2 20-28  9 -Torque 0.5
  1.258   0.588   64.953  1.388  1  1969  2 20-28  9 El Nino 5.5
  1.189   0.277   76.900  1.221  1  1970  2 20-28  9 El Nino 6.5
 -1.819   0.117  273.670  1.823  4  1971  2 20-28  9 La Nina 2.5
 -0.424   0.852  333.525  0.952  4  1972  2 20-28  9 +Torque 3.5
 -0.140  -0.572  193.748  0.589  3  1973  2 20-28  9 -Torque 0.5
 -1.790   0.467  284.612  1.850  4  1974  2 20-28  9 La Nina 2.5
 -1.217  -0.833  235.592  1.475  3  1975  2 20-28  9 La Nina 1.5
 -1.268   0.753  300.719  1.475  4  1976  2 20-28  9 La Nina 3.5
 -1.452  -0.176  263.107  1.463  3  1977  2 20-28  9 La Nina 2.5
  2.571  -0.299   96.631  2.588  2  1978  2 20-28  9 El Nino 6.5
  0.246  -0.053  102.254  0.251  2  1979  2 20-28  9 El Nino 6.5
  0.720  -0.624  130.935  0.953  2  1980  2 20-28  9 El Nino 7.5
  0.149   1.530    5.558  1.537  1  1981  2 20-28  9 +Torque 4.5
  0.101   0.204   26.315  0.228  1  1982  2 20-28  9 +Torque 5.5
  3.389   0.641   79.287  3.449  1  1983  2 20-28  9 El Nino 6.5
 -2.448  -0.474  259.031  2.493  3  1984  2 20-28  9 La Nina 2.5
 -0.561  -0.114  258.472  0.573  3  1985  2 20-28  9 La Nina 2.5
 -0.748  -0.637  229.589  0.982  3  1986  2 20-28  9 La Nina 1.5
  0.993   1.073   42.783  1.462  1  1987  2 20-28  9 +Torque 5.5
  2.002   0.337   80.455  2.030  1  1988  2 20-28  9 El Nino 6.5
 -2.013   0.289  278.166  2.034  4  1989  2 20-28  9 La Nina 2.5
  0.543  -1.457  159.545  1.555  2  1990  2 20-28  9 -Torque 0.5
  0.470   0.908   27.373  1.022  1  1991  2 20-28  9 +Torque 5.5
  0.411  -0.301  126.220  0.510  2  1992  2 20-28  9 El Nino 7.5
  1.183  -0.802  124.135  1.430  2  1993  2 20-28  9 El Nino 7.5
  0.570   1.206   25.305  1.334  1  1994  2 20-28  9 +Torque 5.5
  0.793   0.126   81.007  0.803  1  1995  2 20-28  9 El Nino 6.5
 -0.973   0.203  281.800  0.994  4  1996  2 20-28  9 La Nina 2.5
  0.009   0.646    0.789  0.646  1  1997  2 20-28  9 +Torque 4.5
  2.006   0.517   75.554  2.071  1  1998  2 20-28  9 El Nino 6.5
 -0.853  -1.033  219.550  1.340  3  1999  2 20-28  9 -Torque 1.5
 -1.366  -0.181  262.445  1.378  3  2000  2 20-28  9 La Nina 2.5
  0.524   0.466   48.404  0.701  1  2001  2 20-28  9 El Nino 5.5
  0.958  -0.100   95.961  0.963  2  2002  2 20-28  9 El Nino 6.5
  0.122  -0.409  163.358  0.427  2  2003  2 20-28  9 -Torque 0.5
  1.030  -0.361  109.320  1.091  2  2004  2 20-28  9 El Nino 6.5
  3.264   0.480   81.635  3.300  1  2005  2 20-28  9 El Nino 6.5
  0.429   0.839   27.079  0.942  1  2006  2 20-28  9 +Torque 5.5
 -1.592   0.253  279.040  1.612  4  2007  2 20-28  9 La Nina 2.5
 -1.602  -0.659  247.646  1.732  3  2008  2 20-28  9 La Nina 2.5
 -1.661   0.876  297.793  1.878  4  2009  2 20-28  9 La Nina 3.5
  1.582  -0.692  113.629  1.727  2  2010  2 20-28  9 El Nino 7.5
 -0.471  -0.631  216.741  0.788  3  2011  2 20-28  9 -Torque 1.5
 -1.900  -1.000  242.241  2.147  3  2012  2 20-28  9 La Nina 1.5
  0.400   1.300   17.103  1.360  1  2013  2 20-28  9 +Torque 4.5
  0.643   0.971   33.523  1.165  1  2014  2 20-28  9 +Torque 5.5
                                                                                         
(===================================Process Complete!======================================)       
          _____                            _____                            _____                  
         /\    \                          /\    \                          /\    \                 
        /::\    \                        /::\    \                        /::\____\                
       /::::\    \                       \:::\    \                      /::::|   |                
      /::::::\    \                       \:::\    \                    /:::::|   |                
     /:::/\:::\    \                       \:::\    \                  /::::::|   |                
    /:::/__\:::\    \                       \:::\    \                /:::/|::|   |                
   /::::\   \:::\    \                      /::::\    \              /:::/ |::|   |                
  /::::::\   \:::\    \            _____   /::::::\    \            /:::/  |::|___|______          
 /:::/\:::\   \:::\    \          /\    \ /:::/\:::\    \          /:::/   |::::::::\    \         
/:::/  \:::\   \:::\____\        /::\    /:::/  \:::\____\        /:::/    |:::::::::\____\        
\::/    \:::\  /:::/    /        \:::\  /:::/    \::/    /        \::/    / ~~~~~/:::/    /        
 \/____/ \:::\/:::/    /          \:::\/:::/    / \/____/          \/____/      /:::/    /         
          \::::::/    /            \::::::/    /                               /:::/    /          
           \::::/    /              \::::/    /                               /:::/    /           
           /:::/    /                \::/    /                               /:::/    /            
          /:::/    /                  \/____/                               /:::/    /             
         /:::/    /                                                        /:::/    /              
        /:::/    /                                                        /:::/    /               
        \::/    /                                                         \::/    /                
         \/____/                                                           \/____/                 
                                                                                                   
(BY: Alan Marinaro - Northern Illinois University - Meteorology Graduate Teachers Assistant)       
                                                                                                   
(             Program: Global Wind Oscillation Monthly & Periodic Analog Model             )       
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      =MMMMM=?+MMMMMMMMMM . ?MMMMMM  ..===========MM$~MMMMM=.                                      
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 +=MMDDDDDDDNMMMMMMMMMMMMMMNDDDNNDDMDDDDDDNMNDDDDDDDMMMMMMMMMNDDDDDDNMMN=...                       
 .=NMM7.$$$Z$$DMMMMMMMMMMMMMZ.$$$$MMZ?:$$$ZMMZ.Z$$$MMMMMMMMMMMZ.7$$$MMM==                          
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   ..=+MMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMMM++..                            
  ..,=================================================================.                            
  ..,=================================================================.                            



                         

Rockford,Ill Seasonal Snowfall - The Winter of 2013-2014 Ranks 13th Overall w/ 52.1 Inches.

The Current Seasonal Snowfall Rankings for KRFD: It wouldn't take much snow to push Rockford into the Top 5 Seasons.



ENSO Prediction: The Summer (JJA) Oceanic Nino Index used as a harbinger for El Niño and La Nina Events.

The JJA or Summer Oceanic Nino Index seems to be a predictor for later in the year La Nina's and El Niño's. The JJA ONI at certain thresholds in the negative (La Nina) and the positive (El Niño) can act as a predictor for the definition of ENSO events where the ONI is +/-0.5 consecutively for 5 trimonthly periods or more.

The El Niño Indicator: 100% of the time since 1950 , if the JJA ONI is +0.4 or higher while excluding the years that already have El Niño's occurring through the year (1958, 1969, 1987), then an El Niño will have started by MAM to ASO. Half of the years end up having Strong El Niño Status.

 

 

The La Nina Indicator: 100% of the time since 1950, If an El Niño ends at the beginning of the year, and the ONI for the trimonthly period of JJA is -0.4 or less, then a La Nina will have already started by AMJ to JAS. 5 out of 7 of the La Nina's end up Strong.

 

 

The Biannual Arctic Oscillation and it's association with Influenza Outbreaks since 1950.

The negative mode of the Arctic Oscillation seems to be associated with flu outbreaks. The reason speculated is a -AO allows the polar jet to slow down and allow cold air to flow meridionally south into the mid-latitudes. This cold air effects the population and the Influenza Virus in a way that's favorable for infection.

1. People are more likely to stay in buildings and domisciles, spreading the virus between each other.

2. Your body needs to use energy to heat your body depleting energy away from your immune system.

3. The flu virus is very hardy in the winter cold, it's external shell becomes a barrier to allow it to live in the cold better. Therefore, it stays around in the cold to infect the population.

The literature also equates Influenza with PDO and ENSO modes, but I figured I'd try the AO which fit rather well. The 4 main Flu Outbreaks since 1950 are denoted by the more negative biannual values of the Arctic Oscillation where the most negative value ranks 1st and the most positive value ranks last. The four Influenza Outbreaks rank one, two, four, and sixteen since 1950. It's rather telling that the clustering toward the top of the rank in mainly denoted by Hong Kong, H1N1, & Asian Flu (1,2, and 4 ranked respectively). As for the 16th ranked Russian Flu (which happened to be a late 70's winter), I speculate it may have been dictated by Scandinavian or East Asian/West Russian blocking mechanism versus the Arctic Oscillation, maybe even the TNH teleconnection.

Here is the graphic:

Experimental: An Indicator for March Rockford,ILL / KRFD Snowfall Within The February U.S. Meridional Wind Anomaly Distribution

This is kind of an experiment to see if these type of correlating indicators work as shown by the map. If so, maybe forecasts like this can be used for snowfall, precipitation, and temperature for different cities across the world. This is an example of using the previous months V-Wind across the United States as a harbinger for KRFD Snowfall. Other indicators could be anything from sea-level pressure, SST's, or even stream function on a sigma level. This begs the question about the typical "Correlation With Causation Argument". The March Snowfall Average was calculated using March 1951-2012 Snowfall, which averaged out to 5.5 inches. We'll come back to this to see if it worked or not.......

Research: Constructing a Composite of Teleconnection Indices to Better Forecast Temperature over the Eastern United States

Here is a research paper I did during my Senior Year, it attempts to to combine teleconnections mathematically as a tool for Eastern U.S. Temperature Prediction.

 

Download The PDF: http://www.docdroid.net/file/download/9ftd/constructing-a-composite-of-teleconnection-indices-to-better-forecast-temperature-over-the-eastern-united-states-marinaro-2012.pdf

 

 

Constructing a Composite of Teleconnection Indices to Better Forecast Temperature over the Eastern United States

 

Alan Marinaro 

Department of Geography

Northern Illinois University

DeKalb, IL 60115

  

ABSTRACT: 

The agricultural, industrial, and financial sectors east of the 100W longitude line to the I-95 corridor of the United States, are directly or indirectly susceptible to the affects of surface air temperature. A new modeling regime to improve temperature forecasts would help curb weather risks, crop yields, and energy consumption within the most economically active part of the country. A new index is constructed to better describe the temperature over the eastern half of the country. Northern Hemispheric teleconnections are known to have direct effects on temperatures and 500mb geopotential heights over the United States. Three teleconnections that best describe atmospheric blocking over the eastern U.S. include the East Pacific Oscillation (EPO), North Atlantic Oscillation (NAO), and the Arctic Oscillation (AO). The EPO, NAO, and AO have a direct correlation with 500mb geopotential heights and surface air temperature east of the Rocky Mountains to the I-95 Corridor. Creating a composited & weighted time series from these three teleconnections using multiple regression created a more comprehensive tool to describe, forecast, and model surface temperatures for the eastern U.S. This is known as the Composite Blocking Index (CBI). Comparing the CBI composite time series with its components (EPO, NAO, and AO) individually, it shows a higher correlation with surface temperatures over the eastern U.S. The variance that describes the average surface temperature is increased 11.5% to 18.8% higher annually using the CBI in comparison to the NAO, AO, and EPO individually.

Keywords: Atmospheric Blocking, Teleconnections, North Atlantic Oscillation, & United States Temperatures.