TY  - JOUR
A1  - Totz, Sonja Juliana
A1  - Tziperman, Eli
A1  - Coumou, Dim
A1  - Pfeiffer, Karl
A1  - Cohen, Judah
T1  - Winter precipitation forecast in the European and mediterranean regions using cluster analysis
JF  - Geophysical research letters
N2  - The European climate is changing under global warming, and especially the Mediterranean region has been identified as a hot spot for climate change with climate models projecting a reduction in winter rainfall and a very pronounced increase in summertime heat waves. These trends are already detectable over the historic period. Hence, it is beneficial to forecast seasonal droughts well in advance so that water managers and stakeholders can prepare to mitigate deleterious impacts. We developed a new cluster-based empirical forecast method to predict precipitation anomalies in winter. This algorithm considers not only the strength but also the pattern of the precursors. We compare our algorithm with dynamic forecast models and a canonical correlation analysis-based prediction method demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.
KW  - precipitation anomaly
KW  - seasonal forecast
KW  - cluster analysis
Y1  - 2018
U6  - https://doi.org/10.1002/2017GL075674
SN  - 0094-8276
SN  - 1944-8007
VL  - 44
SP  - 12418
EP  - 12426
PB  - American Geophysical Union
CY  - Washington
ER  - 
TY  - JOUR
A1  - Paasche, Hendrik
A1  - Eberle, Detlef
T1  - Automated compilation of pseudo-lithology maps from geophysical data sets a comparison of Gustafson-Kessel and fuzzy c-means cluster algorithms
JF  - Exploration geophysics : the bulletin of the Australian Society of Exploration Geophysicists
N2  - The fuzzy partitioning Gustafson-Kessel cluster algorithm is employed for rapid and objective integration of multi-parameter Earth-science related databases. We begin by evaluating the Gustafson-Kessel algorithm using the example of a synthetic study and compare the results to those obtained from the more widely employed fuzzy c-means algorithm. Since the Gustafson-Kessel algorithm goes beyond the potential of the fuzzy c-means algorithm by adapting the shape of the clusters to be detected and enabling a manual control of the cluster volume, we believe the results obtained from Gustafson-Kessel algorithm to be superior. Accordingly, a field database comprising airborne and ground-based geophysical data sets is analysed, which has previously been classified by means of the fuzzy c-means algorithm. This database is integrated using the Gustafson-Kessel algorithm thus minimising the amount of empirical data processing required before and after fuzzy c-means clustering. The resultant zonal geophysical map is more evenly clustered matching regional geology information available from the survey area. Even additional information about linear structures, e. g. as typically caused by the presence of dolerite dykes or faults, is visible in the zonal map obtained from Gustafson-Kessel cluster analysis.
KW  - cluster analysis
KW  - data integration
KW  - airborne
KW  - South Africa
KW  - Gustafson-Kessel
KW  - fuzzy c-means
Y1  - 2011
U6  - https://doi.org/10.1071/EG11014
SN  - 0812-3985
VL  - 42
IS  - 4
SP  - 275
EP  - 285
PB  - CSIRO
CY  - Collingwood
ER  -