GHCN v4 Thermometer Inventory Over Time

In a prior posting I had graphs of GHCN v3 thermometers that were in the data set at different quasi random eras. Mostly about 50 years apart, but not consistently.

https://chiefio.wordpress.com/2019/03/11/thermometers-over-time/

This set of graphs will not be directly comparable for two reasons. First off, the year ranges are not exactly the same. Mostly this will not matter as the important cutoffs are the same or close enough. The second change is that instead of using “ranges” like “between 1850 and 1900” I’ve just gone with “Year FOO or before”. This ought to have nearly no impact as the older thermometers tend to persist into the following group OTHER THAN post the “baseline” period of about 1950 to 1990. To capture that effect I’ve included a “Now” graph of 2018 or newer (i.e. into the first few months of 2019).

In general, as expected, the years prior to about 1950 don’t change much. The reality of the few thermometers in the past “just is”. Then we get more in the “baseline” era and recently. I’m not seeing where comparing 27,000 thermometers “now” to 50 years ago tells us anything about climate in the context of known cycles of climate 60 to 200 years long (and longer) other than what part of the cycle one has chosen to measure. Certainly any comparisons to older data than the “baseline” are plagued by lack of data for comparison.

But take a look and see what you think.

GHCN v4 1800 and Before

GHCN v4 Coverage 1850 and Before

GHCN v4 Coverage 1900 and Before

GHCN v4 Coverage Before 1950

GHCN v4 Coverage 2000 and Before

GHCN v4 Coverage “Now” (2018 and newer)

Tech Talk

Here’s the MariaDB / MySQL schemas and the Python that made the above graphs:

CREATE TABLE invent4 (
    stnID      CHAR(11) NOT NULL,
    country    CHAR(3) NOT NULL,
    f1         CHAR(1),
    f2         CHAR(1),
    f3         CHAR(1),
    f4         CHAR(1),
    wmo        CHAR(5) NOT NULL,
    wnl        CHAR(6) NOT NULL,
    latitude   CHAR(8),
    longitude  CHAR(9),
    stn_elev   CHAR(6),
    name       CHAR(30) NOT NULL,
    version    CHAR(5) NOT NULL,
    ascension  CHAR(10),
    type       CHAR(4),
    coslong    CHAR(9),
    PRIMARY KEY (stnID)
    ) ;

CREATE TABLE temps4 (
    stnID CHAR(11) NOT NULL,
    abrev CHAR(2) NOT NULL,
    F1    CHAR(1),
    F2    CHAR(1),
    F3    CHAR(1),
    F4    CHAR(1),
    wmo   CHAR(5),
    year CHAR(4) NOT NULL,
    type CHAR(4) NOT NULL,
    version  CHAR(5) NOT NULL,
    ascension CHAR(10),
    month CHAR(4),
    deg_c DECIMAL(5,2),
    missing  CHAR(1),
    qc       CHAR(1),
    source   CHAR(1),
    PRIMARY KEY (stnID,year,month,type)
    ) ;

chiefio@PiM3Devuan2:~/Py3$ cat 4FiftyYr.py 
# -*- coding: utf-8 -*-
import datetime
import pandas as pd
import numpy as np
import matplotlib.pylab as plt
import math
import mysql.connector as MySQLdb

plt.title("Global Thermometer GHCN v4 1800 and Before")
plt.xlabel("Longitude")
plt.ylabel("Latitude")
plt.xlim(-180,180)
plt.ylim(-90,90)

try:
    db=MySQLdb.connect(user="chiefio",password="LetMeIn!",database='temps')
    cursor=db.cursor()

    print("doing before 1801")

    sql="SELECT I.latitude, I.coslong FROM invent4 AS I INNER JOIN temps4 as T on I.stnID=T.stnID WHERE year<1801 GROUP BY I.stnID;"
 
    cursor.execute(sql)
    stn=cursor.fetchall()
    data = np.array(list(stn))
    xs = data.transpose()[0]   # or xs = data.T[0] or  xs = data[:,0]
    ys = data.transpose()[1]

    plt.scatter(ys,xs,s=0.5,color='blue',alpha=0.5)

    plt.show()
    
    plt.title("Global Thermometer GHCN v4 1850 and Before")
    plt.xlabel("Longitude")
    plt.ylabel("Latitude")
    plt.xlim(-180,180)
    plt.ylim(-90,90)
    
    print("doing before 1851")
    
    sql="SELECT I.latitude, I.coslong FROM invent4 AS I INNER JOIN temps4 as T on I.stnID=T.stnID WHERE year<1851 GROUP BY I.stnID;"
 
    cursor.execute(sql)
    stn=cursor.fetchall()
    data = np.array(list(stn))
    xs = data.transpose()[0]   # or xs = data.T[0] or  xs = data[:,0]
    ys = data.transpose()[1]

    plt.scatter(ys,xs,s=0.5,color='green',alpha=0.5)

    plt.show()
    
    plt.title("Global Thermometer GHCN v4 1900 and Before")
    plt.xlabel("Longitude")
    plt.ylabel("Latitude")
    plt.xlim(-180,180)
    plt.ylim(-90,90)
    
    print("doing before 1901")
    
    sql="SELECT I.latitude, I.coslong FROM invent4 AS I INNER JOIN temps4 as T on I.stnID=T.stnID WHERE year<1901 GROUP BY I.stnID;"
 
    cursor.execute(sql)
    stn=cursor.fetchall()
    data = np.array(list(stn))
    xs = data.transpose()[0]   # or xs = data.T[0] or  xs = data[:,0]
    ys = data.transpose()[1]

    plt.scatter(ys,xs,s=0.5,color='orange')
    
    plt.show()

    print("doing Before 1950")
    
    plt.title("Global Thermometer GHCN v4 Before 1950")
    plt.xlabel("Longitude")
    plt.ylabel("Latitude")
    plt.xlim(-180,180)
    plt.ylim(-90,90)
    sql="SELECT I.latitude, I.coslong FROM invent4 AS I INNER JOIN temps4 as T on I.stnID=T.stnID WHERE year<1950 GROUP BY I.stnID;"
 
    cursor.execute(sql)
    stn=cursor.fetchall()
    data = np.array(list(stn))
    xs = data.transpose()[0]   # or xs = data.T[0] or  xs = data[:,0]
    ys = data.transpose()[1]

    plt.scatter(ys,xs,s=0.5,color='purple')
    plt.show()
    
    print("doing Before 2001")
    
    plt.title("Global Thermometer GHCN v4 2000 and Before")
    plt.xlabel("Longitude")
    plt.ylabel("Latitude")
    plt.xlim(-180,180)
    plt.ylim(-90,90)

    sql="SELECT I.latitude, I.coslong FROM invent4 AS I INNER JOIN temps4 as T on I.stnID=T.stnID WHERE year2017 GROUP BY I.stnID;"
 
    cursor.execute(sql)
    stn=cursor.fetchall()
    data = np.array(list(stn))
    xs = data.transpose()[0]   # or xs = data.T[0] or  xs = data[:,0]
    ys = data.transpose()[1]

    plt.scatter(ys,xs,s=0.5,color='black',alpha=0.5)

    plt.show()


except:
    print ("This is the exception branch")

finally:
    print ("All Done")
    if db:
        db.close()

Subscribe to feed