Klimarealisterne slår til igen mod GISS/GHCN

Description of the pairwise algorithm
The pairwise algorithm is executed according to the
following six steps:

(i) Select a set of ''neighbors'' for each ''target'' series
in the network, and form pairwise difference series
between the target and its neighbors.
(ii) Identify the timing of shifts in all target-minus-
neighbor difference series using SNHT.
(iii) Verify each apparent shift identified by SNHT in
the pairwise differences (e.g., does the apparent
shift look more like a trend?).
(iv) Attribute the cause of shifts in the set of target-
minus-neighbor difference series to the various
''culprit'' series.
(v) Quantify the uncertainty in the timing of shifts
attributed to each culprit series.
(vi) Estimate the magnitude of the identified shifts for
use in adjusting the temperature series to reflect
the true background climate signal

Homogenization in climate research means the removal of non-climatic changes. Next to changes in the climate itself, raw climate records also contain non-climatic jumps and changes, for example due to relocations or changes in instrumentation. The most used principle to remove these inhomogeneities is the relative homogenization approach in which a candidate station is compared to a reference time series based on one or more neighboring stations. The candidate and reference station(s) experience about the same climate, non-climatic changes that happen only in one station can thus be identified and removed.

2. SOME PRACTICAL ASPECTS ON HOMOGENEITY TESTS
A time series of a climatological variable where the variations are caused by variations of weather and climate only is said to be homogeneous (Conrad and Pollack, 1962). However, long time series without artificial changes in their statistical characteristics are rare (e.g. Heino, 1994). Non-homogeneities may be abrupt, caused by relocations of instruments or changes of instruments, observers and observation practices, etc. Slow changes of the surroundings of the observation site may cause non-homogeneities to be gradual, e.g. in the case of urbanization. A common assumption is that non-homogeneities in a time series, the candidate, will become apparent when examining a ratio, or difference, between the candidate and a reference series developed from an
average of records from stations within the same climatic region. The likelihood that the candidate series is homogeneous can be determined by applying an appropriate statistical test to the ratio, or difference, series. The timing and size of significant non-homogeneities can also be estimated with statistical tests. Reviews of techniques for the construction of reference series and of statistical tests have been made recently by Peterson and Easterling (1994) and Easterling and Peterson (1995).

For de seneste 50 år har man satellitmålinger og dermed forholdsvis objektive data, der selvfølgeligt stadigvæk skal fortolkes.

Fig. 3 viser en tilsvarende justering for en flyveplads i New Zealand. Efter de oprindelige data at dømme, er der ingen stigning i temperaturen fra 1880 til 2018. Men efter justeringen er der en stigning på 1½ grad. Resultatet er opnået ved at sænke temperaturerne i starten af periode

Peder Kruse skrev:
Man homogeniserer ikke fortidens målinger. Man manipulerer ikke fortidens målinger uden at betale på troværdigheden.

Der er eksakte regler for at etablere en målerstation. Når målingen er udført og gemt, kan man tilføje tekstuelle bemærkninger til en serie målinger, men man ændrer ikke målingerne til et pc genereret horoskopisk gæt. Man kunne lige så godt smide data væk og være bedre stillet.

Hvis man ønsker ar tegne en hockeystav, er det bedre med papir og blyant.