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GISS Surface Temperature Analysis

Sources

GHCN = Global Historical Climate Network (NOAA) 

USHCN = US Historical Climate Network (NOAA) 

SCAR = Scientific Committee on Arctic Research 

Basic data set: GHCN - ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/v2 

 v2.mean.Z (data file) 

 v2.temperature.inv.Z (station information file) 

For US: USHCN - ftp://ftp.ncdc.noaa.gov/pub/data/ushcn/v2/monthly 

 9641C_yyyymm_F52.avg.gz where yyyy/mm is related to the date 

 that file was created 

 ushcn-v2-stations.txt 

For Antarctica: SCAR - http://www.antarctica.ac.uk/met/READER/surface/stationpt.html 

 http://www.antarctica.ac.uk/met/READER/temperature.html 

 http://www.antarctica.ac.uk/met/READER/aws/awspt.html 

For Hohenpeissenberg - http://members.lycos.nl/ErrenWijlens/co2/t_hohenpeissenberg_200306.txt 

 complete record for this rural station 

 (thanks to Hans Erren who reported it to GISS on July 16, 2003) 

USHCN stations are part of GHCN; but the data are adjusted for various recording 

and protocol errors and discontinuities; this set is particularly relevant if 

studies of US temperatures are made, whereas the corrections have little impact 

on the GLOBAL temperature trend, the US covering less than 2% of the globe. 

Step 0 : Merging of sources (do_comb_step0.sh) 

--------------------------- 

GHCN contains reports from several sources, so there often are multiple records 

for the same location. Occasionally, a single record was divided up by NOAA 

into several pieces, e.g. if suspicious discontinuities were discovered. 

USHCN and SCAR contain single source reports but in different formats/units 

and with different or no identification numbers. For USHCN, the table 

"ushcn2.tbl" gives a translation key, for SCAR we extended the WMO number if it 

existed or created a new ID if it did not (2 cases). SCAR stations are treated 

as new sources. 

Adding SCAR data to GHCN: 

The tables were reformatted and the data rescaled to fit the GHCN format; 

the new stations were added to the inventory file. The site temperature.html 

has not been updated for several years; we found and corrected a few typos 

in that file. (Any SCAR data marked "preliminary" are skipped) 

Replacing USHCN-unmodified by USHCN-corrected data:

The reports were converted from F to C and reformatted; data marked as being 

filled in using interpolation methods were removed. USHCN-IDs were replaced 

by the corresponding GHCN-ID. The latest common 10 years for each station 

were used to compare corrected and uncorrected data. The offset so obtained 

was subtracted from the corrected USHCN reports to match any new incoming 

GHCN reports for that station (GHCN reports are updated monthly; in the past, 

USHCN data used to lag by 1-5 years). 

Filling in missing data for Hohenpeissenberg: 

This is a version of a GHCN report with missing data filled in, so it is used 

to fill the gaps of the corresponding GHCN series. 

Result: v2.mean_comb 

Step 1 : Simplifications, elimination of dubious records, 2 adjustments (do_comb_step1.sh) 

----------------------------------------------------------------------- 

The various sources at a single location are combined into one record, if 

possible, using a version of the reference station method. The adjustments 

are determined in this case using series of estimated annual means. 

Non-overlapping records are viewed as a single record, unless this would 

result introducing a discontinuity; in the documented case of St.Helena 

Data @ NASA GISS: GISTEMP: Sources Documentation Page 1 of 3

http://data.giss.nasa.gov/gistemp/sources/gistemp.html 7/19/2010
the discontinuity is eliminated by adding 1C to the early part. 

After noticing an unusual warming trend in Hawaii, closer investigation 

showed its origin to be in the Lihue record; it had a discontinuity around 

1950 not present in any neighboring station. Based on those data, we added 

0.8C to the part before the discontinuity. 

Some unphysical looking segments were eliminated after manual inspection of 

unusual looking annual mean graphs and comparing them to the corresponding 

graphs of all neighboring stations. See CLEANING NOTES for further details. 

Result: Ts.txt 

Step 2 : Splitting into zonal sections and homogenization (do_comb_step2.sh) 

---------------------------------------------------------- 

To speed up processing, Ts.txt is converted to a binary file and split 

into 6 files, each covering a latitudinal zone of a width of 30 degrees. 

At the same time, stations with less than 20 years of data are dropped, since 

in the subsequent gridding step we require overlaps of at least 20 years 

to combine station records. 

The goal of the homogenization effort is to avoid any impact (warming 

or cooling) of the changing environment that some stations experienced 

by changing the long term trend of any non-rural station to match the 

long term trend of their rural neighbors, while retaining the short term 

monthly and annual variations. If no such neighbors exist or the overlap 

of the rural combination and the non-rural record is less than 20 years, the 

station is completely dropped; if the rural records are shorter, part of the 

non-rural record is dropped. 

Result: Ts.GHCN.CL.1-6 - before peri-urban adjustment 

 Ts.GHCN.CL.PA.1-6 - after peri-urban adjustment 

Step 3 : Gridding and computation of zonal means (do_comb_step3.sh) 

------------------------------------------------ 

A grid of 8000 grid boxes of equal area is used. Time series are changed 

to series of anomalies. For each grid box, the stations within that grid 

box and also any station within 1200km of the center of that box are 

combined using the reference station method. 

A similar method is also used to find a series of anomalies for 80 regions 

consisting of 100 boxes from the series for those boxes, and again to find 

the series for 6 latitudinal zones from those regional series, and finally 

to find the hemispheric and global series from the zonal series. 

WARNING: It should be noted that the base period for any of these anomalies 

 is not necessarily the same for each grid box, region, zone. This is 

 irrelevant when computing trend maps; however, when used to compute 

 anomalies, we always have to subtract the base period data from the 

 series of the selected time period to get a consistent anomaly map. 

Result: SBBX1880.Ts.GHCN.CL.PA.1200 and tables (GLB.Ts.GHCN.CL.PA.txt,...) 

Step 4 : Reformat sea surface temperature anomalies

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Sources: http://www.hadobs.org HadISST1: 1870-present 

 ftp.emc.ncep.noaa.gov cmb/sst/oimonth_v2 Reynolds 11/1981-present 

For both sources, we compute the anomalies with respect to 1982-1992, use 

the Hadley data for the period 1880-11/1981 and Reynolds data for 12/1981-present. 

Since these data sets are complete, creating 1982-92 climatologies is simple. 

These data are replicated on the 8000-box qual-area grid and stored in the same way 

as the surface data to be able to use the same utilities for surface and ocean data. 

Areas covered occasionally by sea ice are masked using a time-independent mask. 

The Reynolds climatology is included, since it also may be used to find that 

mask. Programs are included to show how to regrid these anomaly maps: 

do_comb_step4.sh adds a single or several successive months for the same year 

to an existing ocean file SBBX.HadR2; a program to add several years is also 

included. 

Result: update of SBBX.HadR2 

Step 5 : Computation of LOTI zonal means 

---------------------------------------- 

The same method as in step3 is used, except that for a particular grid box 

the anomaly or trend is computed twice, first based on surface data, then 

based on ocean data. Depending on the location of the grid box, one or 

the other is used with priority given to the surface data, if available. 

Result: tables (GLB.Tsho2.GHCN.CL.PA.txt,...) 

Data @ NASA GISS: GISTEMP: Sources Documentation Page 2 of 3

http://data.giss.nasa.gov/gistemp/sources/gistemp.html 7/19/2010
Final Notes 

----------- 

A program that can read the two basic files SBBX1880.Ts.GHCN.CL.PA.1200 and 

SBBX.HadR2 in order to compute anomaly and trend maps etc was available on our 

web site for many years and still is. 

For a better overview of the structure, the programs and files for the various 

steps are put into separate directories with their own input_files, 

work_files, temp_files directories. If used in this way, files created by 

step0 and put into the temp_files directory will have to be manually moved 

to the temp_files directory of the step1. To avoid that, you could 

consolidate all sources in a single directory and merge all input_files 

directories into a single subdirectory. 

The reason to call the first step "Step 0" is historical: For our 1999 paper 

"GISS analysis of surface temperature change", we started with "Step 1", i.e. 

we used GHCN's v2.mean as our only source for station temperature data. The 

USHCN data were used for the 2001 paper "A closer look at United States and 

global surface temperature change", the other parts of "Step 0" were added later. 

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GISS Website Curator: Robert B. Schmunk 

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Page updated: 2010-07-02

Data @ NASA GISS: GISTEMP: Sources Documentation Page 3 of 3

http://data.giss.nasa.gov/gistemp/sources/gistemp.html 7/19/2010