TY  - JOUR
A1  - Mauerberger, Stefan
A1  - Schanner, Maximilian Arthus
A1  - Korte, Monika
A1  - Holschneider, Matthias
T1  - Correlation based snapshot models of the archeomagnetic field
JF  - Geophysical journal international
N2  - For the time stationary global geomagnetic field, a new modelling concept is presented. A Bayesian non-parametric approach provides realistic location dependent uncertainty estimates. Modelling related variabilities are dealt with systematically by making little subjective apriori assumptions. Rather than parametrizing the model by Gauss coefficients, a functional analytic approach is applied. The geomagnetic potential is assumed a Gaussian process to describe a distribution over functions. Apriori correlations are given by an explicit kernel function with non-informative dipole contribution. A refined modelling strategy is proposed that accommodates non-linearities of archeomagnetic observables: First, a rough field estimate is obtained considering only sites that provide full field vector records. Subsequently, this estimate supports the linearization that incorporates the remaining incomplete records. The comparison of results for the archeomagnetic field over the past 1000 yr is in general agreement with previous models while improved model uncertainty estimates are provided.
KW  - geopotential theory
KW  - archaeomagnetism
KW  - magnetic field variations through
KW  - time
KW  - palaeomagnetism
KW  - inverse theory
KW  - statistical methods
Y1  - 2020
U6  - https://doi.org/10.1093/gji/ggaa336
SN  - 0956-540X
SN  - 1365-246X
VL  - 223
IS  - 1
SP  - 648
EP  - 665
PB  - Oxford Univ. Press
CY  - Oxford
ER  - 
TY  - JOUR
A1  - Bürger, Gerd
T1  - A counterexample to decomposing climate shifts and trends by weather types
JF  - International Journal of Climatology
N2  - The literature contains a sizable number of publications where weather types are used to decompose climate shifts or trends into contributions of frequency and mean of those types. They are all based on the product rule, that is, a transformation of a product of sums into a sum of products, the latter providing the decomposition. While there is nothing to argue about the transformation itself, its interpretation as a climate shift or trend decomposition is bound to fail. While the case of a climate shift may be viewed as an incomplete description of a more complex behaviour, trend decomposition indeed produces bogus trends, as demonstrated by a synthetic counterexample with well-defined trends in type frequency and mean. Consequently, decompositions based on that transformation, be it for climate shifts or trends, must not be used.
KW  - analysis
KW  - climate
KW  - statistical methods
Y1  - 2018
U6  - https://doi.org/10.1002/joc.5519
SN  - 0899-8418
SN  - 1097-0088
VL  - 38
IS  - 9
SP  - 3732
EP  - 3735
PB  - Wiley
CY  - Hoboken
ER  -