File:Suomen tammikuun keskilampotila 1.png
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Summary
[edit]DescriptionSuomen tammikuun keskilampotila 1.png |
Suomi: Suomen tammikuun keskilampotila |
Date | |
Source | Own work |
Author | Merikanto |
Source of data is WoldClim Historical climate data 2.1
https://www.worldclim.org/data/worldclim21.html
"This is WorldClim version 2.1 climate data for 1970-2000. This version was released in January 2020. "
Fick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315.
Code to cut raster
library(raster)
library(viridis)
inname1<-"./data1/wc2.1_30s_tavg_01.tif"
outname1="out1.nc"
plotname1="out.png"
- ext1 <- extent(-15,40,30 , 70)
x1=20
x2=32
y1=58
y2=72
pallength1=100
ext1 <- extent(x1,x2,y1,y2)
inras1<-raster(inname1)
inshape1 <- getData("GADM", country="FI", level=0)
selras1<-crop(inras1,ext1)
png(plotname1)
image(selras1, col=rev(viridis(pallength1) ) ,
xlim=c(x1,x2), ylim=c(y1,y2)
)
contour(selras1,add=TRUE)
plot(inshape1, add=TRUE)
dev.off()
crs(selras1) <- "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0"
writeRaster(selras1, filename=outname1, varname="z", format="CDF", overwrite=TRUE)
Code to draw pic
- plot netcdf mapped data with python
- 1.11.2021 0000.0000
- input must be cut netcdf area grid in many times!
-
- latitude, longitude, z
-
-
- -*- coding: utf-8 -*-
from mpl_toolkits.basemap import Basemap, cm
import matplotlib.pyplot as plt
from netCDF4 import Dataset as open_ncfile
import numpy as np
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
from matplotlib.pyplot import figure
plottitle="Tammikuun keskilämpötila"
- legtitle="T July avg.°C (LGM, CCSM4)"
legtitle="Tammikuun keskilämpötila °C"
- output
outsvg="out_python.svg"
outpng="out_python.png"
- contours and colormap min, max, step
zeta=-20 ## z min
zetb=10 ## z max
deltazd=1 ## z step, annotated contours
- a
deltazc=0.5 # z step, non-annotated contours
- lona=-15
- lonb=40
- lata=30
- latb=70
lona=20
lonb=32
lata=58
latb=72
- lon, lat lines in map
latdx=2
londy=2
- reso, figsize
dpi1 = 70
figux=1000
figuy=1600
figure(figsize=(10, 16), dpi=dpi1)
- palette
- cmap
- kolormap='jet'
- kolormap='jet'
- kolormap='Spectral_r'
kolormap='gist_rainbow_r'
- kolormap='BrBG'
- kolormap='rainbow'
- kolormap='viridis'
- kolormap = ListedColormap(parula_data2)
- netcdf infile name, variable names
- lon, lat, z vars
infilename='out1.nc'
zvarlabel='z'
latvarlabel='latitude'
lonvarlabel='longitude'
- load netcdf file
nc = open_ncfile(infilename)
var = nc.variables[zvarlabel][:,:]
var2=np.flipud(var)
lat = nc.variables[latvarlabel][:]
lon = nc.variables[lonvarlabel][:]
- plot
fig = plt.figure(figsize=(figux/dpi1, figuy/dpi1), dpi=dpi1)
ax = fig.add_axes([0.1,0.1,0.8,0.9])
map = Basemap(projection='cyl',llcrnrlat=lata,urcrnrlat= latb,\
resolution='h', llcrnrlon=lona,urcrnrlon=lonb)
map.drawcoastlines(color='black')
map.drawrivers(color='black')
map.drawcountries(linewidth=3.0, linestyle='dashed', color='red')
- map.drawstates()
kolorado=( (0.0, 0.0, 0.5),(0.0, 0.0, 0.5),(0.0, 0.0, 0.5),(0.0, 0.0, 0.5), (0.0, 0.0, 0.5),(0.0, 0.0, 0.5),(0.0, 0.0, 0.5),(0.0, 0.0, 0.5))
map.drawparallels(np.arange(lata, latb,latdx),labels=[1,0,0,0],fontsize=26)
map.drawmeridians(np.arange(lona,lonb,londy),labels=[0,0,0,1],fontsize=26)
x, y = map(*np.meshgrid(lon,lat))
clevs = np.arange(zeta,zetb,deltazc)
dlevs = np.arange(zeta,zetb,deltazd)
maplot1=map.imshow(var2, cmap=kolormap, vmin=zeta, vmax=zetb)
plt.rc('lines', linewidth=0.5, color='#000000')
cnplot2 = map.contour(x,y,var,clevs,colors='#4f004f', alpha=0.2)
cnplot = map.contour(x,y,var,dlevs,colors='#4f004f')
cbar = map.colorbar(maplot1,location='bottom',pad="10%", label=legtitle)
cbar.set_label(legtitle, fontsize=28)
cbar.ax.tick_params(labelsize=28)
plt.clabel(cnplot, fmt='%.0f',fontsize=34, inline=1)
plt.title(plottitle, fontsize=40)
- plt.show()
- plt.savefig(outsvg, bbox_inches='tight', dpi=dpi1)
plt.savefig(outpng, bbox_inches='tight', dpi=dpi1)
parula_data = [[0.2422, 0.1504, 0.6603],
[0.2444, 0.1534, 0.6728],
[0.2464, 0.1569, 0.6847],
[0.2484, 0.1607, 0.6961],
[0.2503, 0.1648, 0.7071],
[0.2522, 0.1689, 0.7179],
[0.254, 0.1732, 0.7286],
[0.2558, 0.1773, 0.7393],
[0.2576, 0.1814, 0.7501],
[0.2594, 0.1854, 0.761],
[0.2611, 0.1893, 0.7719],
[0.2628, 0.1932, 0.7828],
[0.2645, 0.1972, 0.7937],
[0.2661, 0.2011, 0.8043],
[0.2676, 0.2052, 0.8148],
[0.2691, 0.2094, 0.8249],
[0.2704, 0.2138, 0.8346],
[0.2717, 0.2184, 0.8439],
[0.2729, 0.2231, 0.8528],
[0.274, 0.228, 0.8612],
[0.2749, 0.233, 0.8692],
[0.2758, 0.2382, 0.8767],
[0.2766, 0.2435, 0.884],
[0.2774, 0.2489, 0.8908],
[0.2781, 0.2543, 0.8973],
[0.2788, 0.2598, 0.9035],
[0.2794, 0.2653, 0.9094],
[0.2798, 0.2708, 0.915],
[0.2802, 0.2764, 0.9204],
[0.2806, 0.2819, 0.9255],
[0.2809, 0.2875, 0.9305],
[0.2811, 0.293, 0.9352],
[0.2813, 0.2985, 0.9397],
[0.2814, 0.304, 0.9441],
[0.2814, 0.3095, 0.9483],
[0.2813, 0.315, 0.9524],
[0.2811, 0.3204, 0.9563],
[0.2809, 0.3259, 0.96],
[0.2807, 0.3313, 0.9636],
[0.2803, 0.3367, 0.967],
[0.2798, 0.3421, 0.9702],
[0.2791, 0.3475, 0.9733],
[0.2784, 0.3529, 0.9763],
[0.2776, 0.3583, 0.9791],
[0.2766, 0.3638, 0.9817],
[0.2754, 0.3693, 0.984],
[0.2741, 0.3748, 0.9862],
[0.2726, 0.3804, 0.9881],
[0.271, 0.386, 0.9898],
[0.2691, 0.3916, 0.9912],
[0.267, 0.3973, 0.9924],
[0.2647, 0.403, 0.9935],
[0.2621, 0.4088, 0.9946],
[0.2591, 0.4145, 0.9955],
[0.2556, 0.4203, 0.9965],
[0.2517, 0.4261, 0.9974],
[0.2473, 0.4319, 0.9983],
[0.2424, 0.4378, 0.9991],
[0.2369, 0.4437, 0.9996],
[0.2311, 0.4497, 0.9995],
[0.225, 0.4559, 0.9985],
[0.2189, 0.462, 0.9968],
[0.2128, 0.4682, 0.9948],
[0.2066, 0.4743, 0.9926],
[0.2006, 0.4803, 0.9906],
[0.195, 0.4861, 0.9887],
[0.1903, 0.4919, 0.9867],
[0.1869, 0.4975, 0.9844],
[0.1847, 0.503, 0.9819],
[0.1831, 0.5084, 0.9793],
[0.1818, 0.5138, 0.9766],
[0.1806, 0.5191, 0.9738],
[0.1795, 0.5244, 0.9709],
[0.1785, 0.5296, 0.9677],
[0.1778, 0.5349, 0.9641],
[0.1773, 0.5401, 0.9602],
[0.1768, 0.5452, 0.956],
[0.1764, 0.5504, 0.9516],
[0.1755, 0.5554, 0.9473],
[0.174, 0.5605, 0.9432],
[0.1716, 0.5655, 0.9393],
[0.1686, 0.5705, 0.9357],
[0.1649, 0.5755, 0.9323],
[0.161, 0.5805, 0.9289],
[0.1573, 0.5854, 0.9254],
[0.154, 0.5902, 0.9218],
[0.1513, 0.595, 0.9182],
[0.1492, 0.5997, 0.9147],
[0.1475, 0.6043, 0.9113],
[0.1461, 0.6089, 0.908],
[0.1446, 0.6135, 0.905],
[0.1429, 0.618, 0.9022],
[0.1408, 0.6226, 0.8998],
[0.1383, 0.6272, 0.8975],
[0.1354, 0.6317, 0.8953],
[0.1321, 0.6363, 0.8932],
[0.1288, 0.6408, 0.891],
[0.1253, 0.6453, 0.8887],
[0.1219, 0.6497, 0.8862],
[0.1185, 0.6541, 0.8834],
[0.1152, 0.6584, 0.8804],
[0.1119, 0.6627, 0.877],
[0.1085, 0.6669, 0.8734],
[0.1048, 0.671, 0.8695],
[0.1009, 0.675, 0.8653],
[0.0964, 0.6789, 0.8609],
[0.0914, 0.6828, 0.8562],
[0.0855, 0.6865, 0.8513],
[0.0789, 0.6902, 0.8462],
[0.0713, 0.6938, 0.8409],
[0.0628, 0.6972, 0.8355],
[0.0535, 0.7006, 0.8299],
[0.0433, 0.7039, 0.8242],
[0.0328, 0.7071, 0.8183],
[0.0234, 0.7103, 0.8124],
[0.0155, 0.7133, 0.8064],
[0.0091, 0.7163, 0.8003],
[0.0046, 0.7192, 0.7941],
[0.0019, 0.722, 0.7878],
[0.0009, 0.7248, 0.7815],
[0.0018, 0.7275, 0.7752],
[0.0046, 0.7301, 0.7688],
[0.0094, 0.7327, 0.7623],
[0.0162, 0.7352, 0.7558],
[0.0253, 0.7376, 0.7492],
[0.0369, 0.74, 0.7426],
[0.0504, 0.7423, 0.7359],
[0.0638, 0.7446, 0.7292],
[0.077, 0.7468, 0.7224],
[0.0899, 0.7489, 0.7156],
[0.1023, 0.751, 0.7088],
[0.1141, 0.7531, 0.7019],
[0.1252, 0.7552, 0.695],
[0.1354, 0.7572, 0.6881],
[0.1448, 0.7593, 0.6812],
[0.1532, 0.7614, 0.6741],
[0.1609, 0.7635, 0.6671],
[0.1678, 0.7656, 0.6599],
[0.1741, 0.7678, 0.6527],
[0.1799, 0.7699, 0.6454],
[0.1853, 0.7721, 0.6379],
[0.1905, 0.7743, 0.6303],
[0.1954, 0.7765, 0.6225],
[0.2003, 0.7787, 0.6146],
[0.2061, 0.7808, 0.6065],
[0.2118, 0.7828, 0.5983],
[0.2178, 0.7849, 0.5899],
[0.2244, 0.7869, 0.5813],
[0.2318, 0.7887, 0.5725],
[0.2401, 0.7905, 0.5636],
[0.2491, 0.7922, 0.5546],
[0.2589, 0.7937, 0.5454],
[0.2695, 0.7951, 0.536],
[0.2809, 0.7964, 0.5266],
[0.2929, 0.7975, 0.517],
[0.3052, 0.7985, 0.5074],
[0.3176, 0.7994, 0.4975],
[0.3301, 0.8002, 0.4876],
[0.3424, 0.8009, 0.4774],
[0.3548, 0.8016, 0.4669],
[0.3671, 0.8021, 0.4563],
[0.3795, 0.8026, 0.4454],
[0.3921, 0.8029, 0.4344],
[0.405, 0.8031, 0.4233],
[0.4184, 0.803, 0.4122],
[0.4322, 0.8028, 0.4013],
[0.4463, 0.8024, 0.3904],
[0.4608, 0.8018, 0.3797],
[0.4753, 0.8011, 0.3691],
[0.4899, 0.8002, 0.3586],
[0.5044, 0.7993, 0.348],
[0.5187, 0.7982, 0.3374],
[0.5329, 0.797, 0.3267],
[0.547, 0.7957, 0.3159],
[0.5609, 0.7943, 0.305],
[0.5748, 0.7929, 0.2941],
[0.5886, 0.7913, 0.2833],
[0.6024, 0.7896, 0.2726],
[0.6161, 0.7878, 0.2622],
[0.6297, 0.7859, 0.2521],
[0.6433, 0.7839, 0.2423],
[0.6567, 0.7818, 0.2329],
[0.6701, 0.7796, 0.2239],
[0.6833, 0.7773, 0.2155],
[0.6963, 0.775, 0.2075],
[0.7091, 0.7727, 0.1998],
[0.7218, 0.7703, 0.1924],
[0.7344, 0.7679, 0.1852],
[0.7468, 0.7654, 0.1782],
[0.759, 0.7629, 0.1717],
[0.771, 0.7604, 0.1658],
[0.7829, 0.7579, 0.1608],
[0.7945, 0.7554, 0.157],
[0.806, 0.7529, 0.1546],
[0.8172, 0.7505, 0.1535],
[0.8281, 0.7481, 0.1536],
[0.8389, 0.7457, 0.1546],
[0.8495, 0.7435, 0.1564],
[0.86, 0.7413, 0.1587],
[0.8703, 0.7392, 0.1615],
[0.8804, 0.7372, 0.165],
[0.8903, 0.7353, 0.1695],
[0.9, 0.7336, 0.1749],
[0.9093, 0.7321, 0.1815],
[0.9184, 0.7308, 0.189],
[0.9272, 0.7298, 0.1973],
[0.9357, 0.729, 0.2061],
[0.944, 0.7285, 0.2151],
[0.9523, 0.7284, 0.2237],
[0.9606, 0.7285, 0.2312],
[0.9689, 0.7292, 0.2373],
[0.977, 0.7304, 0.2418],
[0.9842, 0.733, 0.2446],
[0.99, 0.7365, 0.2429],
[0.9946, 0.7407, 0.2394],
[0.9966, 0.7458, 0.2351],
[0.9971, 0.7513, 0.2309],
[0.9972, 0.7569, 0.2267],
[0.9971, 0.7626, 0.2224],
[0.9969, 0.7683, 0.2181],
[0.9966, 0.774, 0.2138],
[0.9962, 0.7798, 0.2095],
[0.9957, 0.7856, 0.2053],
[0.9949, 0.7915, 0.2012],
[0.9938, 0.7974, 0.1974],
[0.9923, 0.8034, 0.1939],
[0.9906, 0.8095, 0.1906],
[0.9885, 0.8156, 0.1875],
[0.9861, 0.8218, 0.1846],
[0.9835, 0.828, 0.1817],
[0.9807, 0.8342, 0.1787],
[0.9778, 0.8404, 0.1757],
[0.9748, 0.8467, 0.1726],
[0.972, 0.8529, 0.1695],
[0.9694, 0.8591, 0.1665],
[0.9671, 0.8654, 0.1636],
[0.9651, 0.8716, 0.1608],
[0.9634, 0.8778, 0.1582],
[0.9619, 0.884, 0.1557],
[0.9608, 0.8902, 0.1532],
[0.9601, 0.8963, 0.1507],
[0.9596, 0.9023, 0.148],
[0.9595, 0.9084, 0.145],
[0.9597, 0.9143, 0.1418],
[0.9601, 0.9203, 0.1382],
[0.9608, 0.9262, 0.1344],
[0.9618, 0.932, 0.1304],
[0.9629, 0.9379, 0.1261],
[0.9642, 0.9437, 0.1216],
[0.9657, 0.9494, 0.1168],
[0.9674, 0.9552, 0.1116],
[0.9692, 0.9609, 0.1061],
[0.9711, 0.9667, 0.1001],
[0.973, 0.9724, 0.0938],
[0.9749, 0.9782, 0.0872],
[0.9769, 0.9839, 0.0805]]
parula_data2=parula_data[::-1]
Licensing
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- to share – to copy, distribute and transmit the work
- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
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