File:Temperature of northern fennoscandia during time of teotihuacan collapse 1.svg

              World Data Center for Paleoclimatology, Boulder 
                                 and 
                    NOAA Paleoclimatology Program 

NOTE: Please cite original reference when using these data, plus the data file URL and date accessed.

NAME OF DATA SET: Fennoscandia 7500Yr Pollen-TreeRing July Temperature Reconstructions LAST UPDATE: 6/2012 (Original receipt by WDC Paleo) CONTRIBUTORS: Helama, S., H. Seppä, A.E. Bjune, and H.J.B. Birks IGBP PAGES/WDCA CONTRIBUTION SERIES NUMBER: 2012-106

WDC PALEO CONTRIBUTION SERIES CITATION: Helama, S., et al. 2012. Fennoscandia 7500Yr Pollen-TreeRing July Temperature Reconstructions. IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series # 2012-106. NOAA/NCDC Paleoclimatology Program, Boulder CO, USA.

ORIGINAL REFERENCE: Helama, S., H. Seppä, A.E. Bjune, and H.J.B. Birks. 2012. Fusing pollen-stratigraphic and dendroclimatic proxy data to reconstruct summer temperature variability during the past 7.5 ka in subarctic Fennoscandia. Journal of Paleolimnology, Vol. 48, No. 1, June 2012, pp. 275-286. DOI: 10.1007/s10933-012-9598-1

1. 3. drawing climate data diagram in python 3
   4. version 4000.0004
   5. 3.12.2022

import matplotlib.pyplot as plt import numpy as np import pandas as pd from scipy import interpolate from matplotlib.ticker import (MultipleLocator, AutoMinorLocator) import scipy.signal import matplotlib.colors as colors import math as math

1. datafilename="fennoscandia1a.csv"

datafilename="fennoscandia1a.csv" captioni="Temperature of July, Northern Fennoscandia: ~66°-70°N, ~14°-35°E" savename="fennoscandia_1.svg"

1. beginx=1800
2. endx=1950

1. beginx=50
2. endx=300

1. beginx=50
2. endx=1950

beginx=400 endx=900

1. beginx=1000
2. endx=1950

1. beginx=1800
2. endx=1950

beginy=19 endy=8

figsizex=19 figsizey=7

yearspan=int(math.fabs(endx-beginx))

dfin0=pd.read_csv(datafilename, sep=";")

s1='Year' s2='TJuly'

lst1=[s1, s2]

dfin1 = dfin0[dfin0.columns.intersection(lst1)]

x0=dfin1[s1] y0=dfin1[s2]

x=np.array(x0) y=np.array(y0)

1. print (y)
2. quit(-1)

size0=14 size1=16 size2=18 size3=22

x_sm = np.array(x) y_sm = np.array(y)

x_smooth = np.linspace(beginx,endx, yearspan*10) funk1 = interpolate.interp1d(x_sm, y_sm, kind="cubic") y_smooth = funk1(x_smooth) y_savgol1 = scipy.signal.savgol_filter(y_smooth,11, 3) y_savgol2 = scipy.signal.savgol_filter(y_smooth,501, 3)

1. a=np.outer(np.ones(2),y_smooth)

a=np.outer(np.ones(2),y_savgol2)

cmap1="RdBu" cmap1="hsv" cmap1="seismic" cmap1="bwr" clam1="coolwarm1"

print (type(cmap1))

1. fig=plt.gca()
2. plt.figure(figsize=(figsizex, figsizey))

plt.rcParams["figure.figsize"] = [figsizex, figsizey]

1. plt.imshow(a,aspect='auto', cmap=cmap1, extent=[beginx, endx,-50,-30], alpha=0.5)

plt.imshow(a,aspect='auto', cmap=cmap1, extent=[beginx, endx,endy,beginy], alpha=0.5)

1. 1. plt.imshow(a,aspect='auto', cmap=cmap1, vmin=endy-0, vmax=beginy+0, extent=[beginx, endx,endy,beginy], alpha=0.5)

1. plt.xlim(beginx, endx)
2. plt.ylim(endy, beginy)

plt.xlim([beginx, endx])

plt.plot(x, y, color="#ff0000", alpha=0.6, linewidth=5)

1. plt.plot(x_smooth, y_savgol1, color="#0000ff", alpha=0.33, linewidth=1)

1. plt.plot(x_smooth, y_savgol2, color="#0000ff", linewidth=2)

plt.title(captioni, fontsize=size3, color="#0000af") plt.xlabel('Year AD', color="darkgreen", fontsize=21) plt.ylabel('T July', color="darkgreen", fontsize=21)

plt.locator_params(axis='x', nbins=10)

plt.xticks(fontsize=17) plt.yticks(fontsize=17)

1. plt.gca().invert_xaxis()

1. mng = plt.get_current_fig_manager()
2. mng.window.state('zoomed')

plt.savefig('figure.svg')

plt.show()