Antarctic Seasonal Pressure Reconstructions 1905-2013

<div><h3>Overview:</h3><p>This project created seasonal reconstructions for many of the long-term Antarctic station records, in order to understand better the relative roles of natural variability and change during the 20th Century. Using midlatitude pressure records that were significantly correlated to the individual station being reconstructed, a principal component regression reconstruction technique was employed. The records were extended back to 1905 for all locations, and several different approaches were attempted:</p><li>Reconstructions based on groups of midlatitude predictor stations that were correlated at <i>p</i><0.05 and <i>p</i><0.10, termed the 5% and 10% networks, respectively;</li><li>Reconstructions based on detrended and original predictor and predictand seasonal pressure data;</li><li>Reconstructions with predictor and predictand data ending in 2011 vs. 2013;</li><li>Reconstructions calibrated over 1957-2011 (or 2013, whichever the ending year is), and validated using a leave-one-out cross validation procedure, termed the 'full period' reconstructions;</li><li>Reconstructions calibrated during the first 30 years (1957-1986) and validated over the last 25-27 years (1987-2011 or 1987-2013), termed the 'early' reconstructions;</li><li>Reconstructions calibrated during last 30-32 years (1982-2011 or 1982-2013) and validated over the first 25 years (1957-1981), termed the 'late' period reconstructions;</li><li>Reconstructions using all of the above mentioned methods with now incorporating in reanalysis data from HadSLP2 and NOAA 20CR, termed the 'pseudo' reconstructions.</li><br><b>NOTE:</b> Any reconstructions termed 'original' reconstructions are any reconstructions not using 'pseudo' data. Reconstructions using 'pseudo' data from reanalysis products are termed 'pseudo' reconstructions. <br><br>We provide here all the reconstruction data for each station (which can be accessed by downloading the data attached), including the best overall reconstructions for all stations.<p></p><b></b><p><b>Acknowledgments:</b> <br>This work is supported by funding from the National Science Foundation, through the <a href="http://www.nsf.gov/awardsearch/showAward?AWD_ID=1341621&HistoricalAwards=false" target="_blank">Antarctic Oceanic and Atmospheric Sciences award PLR-1341621</a></p><b><p>Relevant Publications:</p></b><p>For further information on the <b><u>reconstruction methodology</u></b>, please see the <a href="http://polarmet.osu.edu/ACD/sam/sam_recon.html" target="_blank">seasonal SAM index reconstructions</a>, or the following publications:</p><li>Jones, J. M., R. L. Fogt, M. Widmann, G. J. Marshall, P. D. Jones, and M. Visbeck, 2009: Historical SAM Variability. Part I: Century length seasonal reconstructions. <i>J. Climate</i>, <b>22</b>, 5319-5345, doi: 10.1175/2009JCLI2785.1</li><li>Fogt, R. L., J. Perlwitz, A. J. Monaghan, D. H. Bromwich, J. M. Jones, and G. J. Marshall, 2009: Historical SAM Variability. Part II: 20th century variability and trends from reconstructions, observations, and the IPCC AR4 Models. <i>J. Climate</i>, <b>22</b>, 5346-5365, doi: 10.1175/2009JCLI2786.1<br><br></li>For details on the <b><u>Antarctic station-based pressure reconstructions</u></b>, please see the following publications:<li>Fogt, R. L., C. A. Goergens, M. E. Jones, G. A. Witte, M. Y. Lee, and J. M. Jones, 2016: Antarctic station-based pressure reconstructions since 1905: 1. Reconstruction evaluation. <i>J. Geophysical Res.-Atmospheres</i>, <b>21</b>, 2814-2835, doi:10.1002/2015JD024564.  <a href="http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015JD024564/full" target="_blank">Access here from Wiley online library</a></li><li>Fogt, R. L., J. M. Jones, C. A. Goergens, M. E. Jones, G. A. Witte, and M. Y. Lee, 2016: Antarctic station-based pressure reconstructions since 1905: 2. Variability and trends during the twentieth century. <i>J. Geophysical Res.-Atmospheres</i>, <b>21</b>, 2836-2856, doi:10.1002/2015JD024565.  <a href="http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015JD024565/full" target="_blank">Access here from Wiley online library</a><p></p><b></b><p><b>Contacts:</b> <br>For additional information, please feel free to email <i>Dr. Ryan L. Fogt</i> (<a href="mailto:[email protected]">[email protected]</a>)</p><hr><p><b>RECONSTRUCTION PERFORMANCE</b><br>The evaluation statistics for the best performing original reconstructions for all the 'full period' reconstructions are summarized in the tables below. Full details on the length of the records (both for midlatitude and Antarctic stations reconstructed) and other skill measures can be found in <a href="http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015JD024564/full" target="_blank">Fogt et al. 2016</a>.</p><p><b></b></p><p><b>December-January-February (DJF)</b></p><p></p><table><tbody><tr><th>Stations</th><th>Calibration Correlation</th><th>Validation Correlation</th><th>Reduction of Error</th><th>Coefficient of Efficiency</th></tr><tr><td>Amundsen-Scott<br>Bellingshausen<br>Byrd<br>Casey<br>Davis<br>Dumont<br>Esperanza<br>Faraday<br>Halley<br>Marambio<br>Marsh / O'Higgins<br>Mawson<br>McMurdo / Scott Base<br>Mirny<br>Novolazarevskaya<br>Rothera<br>Syowa<br>Vostok<br></td><td>0.859<br>0.830<br>0.826<br>0.794<br>0.754<br>0.816<br>0.909<br>0.899<br>0.923<br>0.760<br>0.819<br>0.885<br>0.872<br>0.842<br>0.873<br>0.886<br>0.773<br>0.832<br></td><td>0.790<br>0.733<br>0.732<br>0.746<br>0.660<br>0.779<br>0.813<br>0.820<br>0.890<br>0.637<br>0.725<br>0.813<br>0.824<br>0.737<br>0.843<br>0.805<br>0.710<br>0.774<br></td><td>0.737<br>0.761<br>0.745<br>0.749<br>0.765<br>0.750<br>0.826<br>0.808<br>0.852<br>0.742<br>0.743<br>0.783<br>0.760<br>0.709<br>0.780<br>0.798<br>0.671<br>0.792<br></td><td>0.615<br>0.652<br>0.617<br>0.675<br>0.647<br>0.685<br>0.652<br>0.665<br>0.789<br>0.659<br>0.635<br>0.655<br>0.674<br>0.528<br>0.729<br>0.652<br>0.598<br>0.702<br></td></tr></tbody></table><b><p>March-April-May (MAM)</p></b><p></p><table><tbody><tr><th>Stations</th><th>Calibration Correlation</th><th>Validation Correlation</th><th>Reduction of Error</th><th>Coefficient of Efficiency</th></tr><tr><td>Amundsen-Scott<br>Bellingshausen<br>Byrd<br>Casey<br>Davis<br>Dumont<br>Esperanza<br>Faraday<br>Halley<br>Marambio<br>Marsh / O'Higgins<br>Mawson<br>McMurdo / Scott Base<br>Mirny<br>Novolazarevskaya<br>Rothera<br>Syowa<br>Vostok<br></td><td>0.721<br>0.853<br>0.668<br>0.559<br>0.738<br>0.660<br>0.785<br>0.819<br>0.608<br>0.725<br>0.719<br>0.742<br>0.678<br>0.717<br>0.779<br>0.699<br>0.719<br>0.660<br></td><td>0.678<br>0.818<br>0.603<br>0.486<br>0.660<br>0.606<br>0.748<br>0.778<br>0.529<br>0.670<br>0.770<br>0.671<br>0.635<br>0.677<br>0.732<br>0.635<br>0.638<br>0.609<br></td><td>0.520<br>0.739<br>0.473<br>0.313<br>0.554<br>0.441<br>0.615<br>0.672<br>0.369<br>0.637<br>0.565<br>0.551<br>0.459<br>0.514<br>0.627<br>0.503<br>0.545<br>0.464<br></td><td>0.456<br>0.682<br>0.385<br>0.222<br>0.438<br>0.353<br>0.557<br>0.601<br>0.269<br>0.586<br>0.559<br>0.438<br>0.401<br>0.456<br>0.570<br>0.411<br>0.430<br>0.409<br></td></tr></tbody></table><b><p>June-July-August (JJA)</p></b><p></p><table><tbody><tr><th>Stations</th><th>Calibration Correlation</th><th>Validation Correlation</th><th>Reduction of Error</th><th>Coefficient of Efficiency</th></tr><tr><td>Amundsen-Scott<br>Bellingshausen<br>Byrd<br>Casey<br>Davis<br>Dumont<br>Esperanza<br>Faraday<br>Halley<br>Marambio<br>Marsh / O'Higgins<br>Mawson<br>McMurdo / Scott Base<br>Mirny<br>Novolazarevskaya<br>Rothera<br>Syowa<br>Vostok<br></td><td>0.685<br>0.914<br>0.563<br>0.765<br>0.683<br>0.731<br>0.853<br>0.871<br>0.721<br>0.814<br>0.884<br>0.667<br>0.793<br>0.787<br>0.818<br>0.810<br>0.574<br>0.723<br></td><td>0.578<br>0.884<br>0.391<br>0.712<br>0.595<br>0.650<br>0.823<br>0.841<br>0.612<br>0.760<br>0.838<br>0.555<br>0.632<br>0.648<br>0.689<br>0.765<br>0.423<br>0.659<br></td><td>0.469<br>0.836<br>0.376<br>0.586<br>0.492<br>0.534<br>0.733<br>0.758<br>0.519<br>0.776<br>0.809<br>0.444<br>0.630<br>0.619<br>0.675<br>0.644<br>0.376<br>0.535<br></td><td>0.316<br>0.779<br>0.213<br>0.503<br>0.372<br>0.412<br>0.680<br>0.706<br>0.365<br>0.737<br>0.746<br>0.290<br>0.375<br>0.398<br>0.472<br>0.571<br>0.220<br>0.446<br></td></tr></tbody></table><b><p>September-October-November (SON)</p></b><p></p><table><tbody><tr><th>Stations</th><th>Calibration Correlation</th><th>Validation Correlation</th><th>Reduction of Error</th><th>Coefficient of Efficiency</th></tr><tr><td>Amundsen-Scott<br>Bellingshausen<br>Byrd<br>Casey<br>Davis<br>Dumont<br>Esperanza<br>Faraday<br>Halley<br>Marambio<br>Marsh / O'Higgins<br>Mawson<br>McMurdo / Scott Base<br>Mirny<br>Novolazarevskaya<br>Rothera<br>Syowa<br>Vostok<br></td><td>0.619<br>0.853<br>0.765<br>0.698<br>0.623<br>0.641<br>0.762<br>0.769<br>0.676<br>0.697<br>0.711<br>0.616<br>0.731<br>0.635<br>0.581<br>0.623<br>0.594<br>0.615<br></td><td>0.395<br>0.819<br>0.621<br>0.529<br>0.545<br>0.540<br>0.712<br>0.747<br>0.536<br>0.633<br>0.647<br>0.557<br>0.612<br>0.534<br>0.505<br>0.522<br>0.546<br>0.514<br></td><td>0.383<br>0.745<br>0.637<br>0.461<br>0.405<br>0.411<br>0.581<br>0.591<br>0.457<br>0.579<br>0.601<br>0.370<br>0.534<br>0.445<br>0.332<br>0.434<br>0.363<br>0.385<br></td><td>0.085<br>0.689<br>0.448<br>0.224<br>0.295<br>0.277<br>0.502<br>0.557<br>0.262<br>0.514<br>0.530<br>0.291<br>0.357<br>0.285<br>0.250<br>0.362<br>0.304<br>0.259<br></td></tr></tbody></table></li></div><div><p><b>DATA</b></p><p>Please <a href="http://www.scalialab.com/best_recons_all.xlsx"><b>click here</b></a> for access to all of the best performing reconstructions in an MS Excel spreadsheet. </p><p><br>To access more data pertaining to each station individually, please download individual station data provided above on this page. The attached .txt files for each individual station provide the overall best reconstructions by season. The .xlsx files provide all reconstructions for each station and method used.</p><p></p><hr><p>Last Revised: May 2016</p></div

DS Mice Undergo SUDEP.

<p>A. Kaplan-Meier survival curves for WT and DS mice (N = 75 for each group, p < 0.0001, Log-rank, Mantel-Cox, Survival Test). B. Percent survival in WT (N = 8) and DS (N = 13) mice implanted with radiotelemetry units. SUDEP or near-SUDEP in 3 DS mice (at P41, P45, and P51, respectively).</p

Altered Heart Rates Precede Death.

<p>A. DS mice exhibit significant QT prolongation (50 - 90%). B. Heart rates in DS mice decrease 100 min before death, followed by a sharp increase just prior to the terminal event, while the WT heart rates remains high and constant. (100 minutes = 10:16 PM in WT-1 and DS-1; 7:46 PM in WT-2 and DS-2). C. WT-3 and DS-3 HR cycling, followed by DS exhibiting sudden drops in heart rate in the 72 h preceding death. D and E. Increased R-R variability 60 min prior to SUDEP in DS-1 (blue) and DS-2 (red), respectively, with further increased variability immediately preceding the lethal arrhythmia, while 1 day prior at the same time the R-R interval was constant (black). F. Progressive bradycardia and increased R-R variability in DS-3 at several time points preceding an agonal state and euthanasia (denoted by colored arrows in C).</p

Dominant Frequency Analysis.

<p><i>A. Sinus</i> rhythm 1 day prior to SUDEP, which is consistent with heart rate (728 bpm) analysis. B. Muscle artifact embedded in the sinus ECG (same as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077843#pone-0077843-g009" target="_blank">Figure 9 C</a>) without any clear frequency peaks. C. High frequency electrical activity without any discernible sinus activity, consistent with VF (~25 Hz, same as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077843#pone-0077843-g009" target="_blank">Figure 9, D and E</a>). D. PTZ induced seizures lead to a lower frequency electrical signal (~10 - 20 Hz). <i>Inset</i>: Representative snapshots of the ECG signal included in the fast-fourier transformation.</p

Isolation of TTX-R and TTX-S I_Na Biophysical Properties.

<p>A. Boltzman curves for the voltage dependence of I_Na availability and conductance for the total cardiac I_Na (TTX-S + TTX-R I_Na; reproduction of the curve-fits from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077843#pone-0077843-g001" target="_blank">Figure 1C</a>). In both WT and DS myocytes the V_½ values of TTX-R I_Na (closed circles, following blockade of TTX-S I_Na with 100 nM TTX) and TTX-S I_Na (open circles, defined as total I_Na minus TTX-R I_Na) are plotted. Pharmacological separation of TTX-S and TTX-R I_Na was confirmed by the loss of difference in the V_½ values between WT vs DS, and the development of a significant difference between the TTX-S vs. TTX-R V ½ values for I_Na availability and conductance. B. Zoom-in of the boxed region in A.</p

mScn5a and Nav1.5 levels are unchanged in DS mutant hearts.

<p>A. Heart RNA from biological replicates (DS mice, n = 4; WT mice, n = 5) were used to generate two independent cDNAs per animal. The cDNAs were assayed using qPCR in quadruplicate with two independent <i>Scn5a</i> TaqMan primer sets and normalized to 18s RNA. B. Western blots of membrane proteins isolated from DS and WT ventricular CMs. 50 µg of protein was loaded in each lane, and probed with anti-Na_v1.5 (Mohler 1:1000), and anti-α-actin (Sigma 1:500), which served as the loading control. C. Quantification of Na_v1.5 expression normalized to α-actin expression.</p

Cardiac Arrhythmias Precede SUDEP in DS.

<p>Lead II ECG traces illustrating cardiac arrhythmias preceding death. A-C. In mouse DS-2, muscle artifact consistent with convulsive seizures was preceded by idioventricular rhythms, including premature ventricular complexes (PVCs), bundle branch block (BBB), altered QRS morphology, and R-R variability. D and E. Initiation of high frequency electrical activity without any discernible sinus activity, consistent with VF. F. Low amplitude wide complex focal bradycardia with a BBB morphology, and eventual asystole. </p

DS myocytes exhibit increased excitability and incidence of early after depolarizations (EADs).

<p>A. DS myocytes require significantly less injected current to fire APs. B. DS myocyte AP upstroke velocity is faster at all pacing cycle lengths (<i>p</i> = ns). C. Slight prolongation of the AP duration at 30%, 50%, and 75% repolarization at many pacing cycle lengths (<i>p</i> = ns). D. DS myocytes are significantly more susceptible to EADs, a substrate for arrhythmogenesis. <i>Inset</i>: Representative EADs from DS myocytes (red.) Panels A-C, unpaired t-test with Welch’s correction. Panel D χ² Test (WT, N = 9, n = 11, DS, N = 8, n = 17).</p

DS Mice Have Altered Cardiac I_Na Properties.

<p>A. Current-voltage (I-V) relationship of transient I_Na. Peak transient I_Na density is increased 2-fold in the DS (N = 6, n = 14) vs WT cardiac myocytes (N = 8, n = 20, <i>p</i> < 0.0001). <i>Inset</i>: Representative traces from each group. B. I-V relationship for persistent I_Na (pre- minus post-30 µM TTX) also shows a 2-fold increase in peak persistent I_Na in the DS vs. WT groups. To further confirm these results we employed the P/4 method to measure the persistent I_Na, yielding similar results (-60 mV, WT, -1.72 ± 0.50; DS, -3.88 ± 0.72, N = 2, n = 5-9, <i>p</i> = 0.02). C. Leftward shift (V_½ of Boltzman fit, <i>p</i> = 0.04) in the voltage dependence of I_Na availability and conductance in the DS group. D. Similar percent change in peak transient I_Na density upon administration of 100 nM TTX in the WT and DS groups. Unpaired t-test with Welch’s correction.</p

Decreased Threshold for PTZ Induced Seizures in DS Mice.

<p>WT and DS mice were administered incremental doses of pentylenetetrazole (PTZ), monitored for observable seizures, and classified on the Racine Scale.</p