Detection of homogeneous precipitation regions at
seasonal and annual time scales, northwest Iran
Mohammad Arab Amiri, Mohammad Saadi Mesgari
and Christian Conoscenti
ABSTRACT
Detection of homogeneous climate areas is a challenging issue, which can be affected by different
criteria. One of the most prominent factors is choosing the time scale, which can lead to different
spatial and temporal patterns. Total precipitation is a key factor in climatological studies, and
studying its distribution is of utmost importance. The combination of principal components analysis
and cluster analysis is used for homogeneous precipitation areas’ detection. Hence, the spatial
pattern of total precipitation was investigated in northwestern Iran during the past two decades
(1991–2010) on seasonal and annual time scales. The results of clustering on each time scale were
validated, and well-defined clusters were investigated and compared with each other. Two
homogeneous sub-regions were recognized in spring, the best period for depicting homogeneous
precipitation clusters at seasonal resolution. The annual pattern of precipitation delineated three
clusters in the study region. Finally, the characteristics of the well-clustered maps reveal the
importance of time scale in detection of homogeneous precipitation sub-zones.
Mohammad Arab Amiri (corresponding author)
Department of Geographic Information System,
Faculty of Geodesy and Geomatics Eng.,
K. N. Toosi University of Technology,
Tehran, Iran
E-mail: mohamadamiri89@yahoo.com
Mohammad Saadi Mesgari
Department of Geographic Information System,
Faculty of Geodesy and Geomatics Eng., and
Center of Excellence in Geospatial Information
Technology (CEGIT),
K. N. Toosi University of Technology,
Tehran,
Iran
Christian Conoscenti
Department of Earth and Marine Sciences,
University of Palermo,
Palermo,
Italy
Key words | cluster analysis, GIS, principal component analysis, time scale, total precipitation
INTRODUCTION
Regional studies on spatial and temporal climate variability
are as vital as those of global studies, especially in large
countries with different climate regimes (Türkeş et al.
). Moreover, the changing spatio-temporal patterns of
the individual climatic variables are region specific, and
vary from one region to another (Qian & Qin ) because
climate variables vary in time and space, and their spatio-
temporal behavior depends on spatial and temporal scales.
Some researchers have incorporated spatial and temporal
information, and have found that trends for different climate
variables differ significantly from region to region (Ada-
mowski et al. ). Therefore, studying the spatial and
temporal variability of climate variables at regional scale is
of utmost importance.
Temporal trend analysis and spatial interpolation
methods have been widely used in spatio-temporal climate
variability studies (Shahid ; Santos et al. ; Martins
et al. ). The majority of the previously performed
researches in climate trend analysis focused on long-term
trend detection of the main climate variables such as pre-
cipitation and temperature (Haylock & Nicholls ;
Griffiths et al. ; Qian & Qin ; Shahid ; Martins
et al. ; Taxak et al. ; Arab Amiri et al. ). Regard-
ing spatial variability, a set of possible local and regional
factors can contribute to the delineation of homogeneous
climatic sub-zones (Adamowski et al. ). Moreover,
homogeneous regions with similar behavior in terms of cli-
matological variables can play an important role in
decision-making procedures. This is because identification
of homogeneous climate areas at regional scale can be con-
sidered an important issue in spatial and temporal analysis
of climate time series, and have been proved to be extremely
701 © IWA Publishing 2017 Journal of Water and Climate Change | 08.4 | 2017
doi: 10.2166/wcc.2017.088
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