Defining climate zone of Borneo based on cluster analysis
Although Borneo Island is one of the most vulnerable tropical regions to climate change, maps depicting the local climate conditions employing climate classification are still not well defined. The present study attempted regional climate classification to divide the Borneo region into several homog...
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Veröffentlicht in: | Theoretical and applied climatology 2021-08, Vol.145 (3-4), p.1467-1484 |
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description | Although Borneo Island is one of the most vulnerable tropical regions to climate change, maps depicting the local climate conditions employing climate classification are still not well defined. The present study attempted regional climate classification to divide the Borneo region into several homogenous groups based on long-term average climate behavior. Daily gridded rainfall and temperature (Tavg, Tmax, and Tmin) data at 0.25° resolution spanning 56 years (1960–2016) was used. The classification was done using non-hierarchical
k-mean
and several hierarchical methods, namely,
Single
,
Complete
,
McQuitty
,
Average
,
Centroid
,
Median
, and two algorithms of Ward’s method,
wardD
, and
wardD2
. The results showed that
k-mean
,
wardD
, and
wardD2
were able to classify the climate of Borneo into four zones, namely ‘dry and hot’ (DH), ‘wet and hot’ (WH), ‘wet’ (W), and ‘wet and cold’ (WC) with a considerable difference at the boundaries. Spatial relevancy, stability, and variability of the clusters based on correlation and compromise programming showed that the
wardD
method was the most likely to yield acceptable results with optimum 4-cluster to partition the area into four principal climate zones. The constructed cluster plot, centroid plot, and probability distribution function (PDF) showed a distinct climatic characteristic between the climate zones in terms of rainfall, temperature, and seasonality. The proposed climate zonation for Borneo can help in better understanding climate regionality and climate-related development planning. |
doi_str_mv | 10.1007/s00704-021-03701-1 |
format | Article |
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k-mean
and several hierarchical methods, namely,
Single
,
Complete
,
McQuitty
,
Average
,
Centroid
,
Median
, and two algorithms of Ward’s method,
wardD
, and
wardD2
. The results showed that
k-mean
,
wardD
, and
wardD2
were able to classify the climate of Borneo into four zones, namely ‘dry and hot’ (DH), ‘wet and hot’ (WH), ‘wet’ (W), and ‘wet and cold’ (WC) with a considerable difference at the boundaries. Spatial relevancy, stability, and variability of the clusters based on correlation and compromise programming showed that the
wardD
method was the most likely to yield acceptable results with optimum 4-cluster to partition the area into four principal climate zones. The constructed cluster plot, centroid plot, and probability distribution function (PDF) showed a distinct climatic characteristic between the climate zones in terms of rainfall, temperature, and seasonality. The proposed climate zonation for Borneo can help in better understanding climate regionality and climate-related development planning.</description><identifier>ISSN: 0177-798X</identifier><identifier>EISSN: 1434-4483</identifier><identifier>DOI: 10.1007/s00704-021-03701-1</identifier><language>eng</language><publisher>Vienna: Springer Vienna</publisher><subject>Algorithms ; Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; Atmospheric Sciences ; Centroids ; Classification ; Climate change ; Climate science ; Climatic changes ; Climatic classifications ; Climatic conditions ; Climatology ; Cluster analysis ; Daily rainfall ; Distribution functions ; Earth and Environmental Science ; Earth Sciences ; Local climates ; Mean ; Original Paper ; Probability distribution ; Probability distribution functions ; Probability theory ; Rain ; Rain and rainfall ; Rainfall ; Regional climates ; Seasonal variations ; Seasonality ; Stability ; Temperature ; Tropical climate ; Tropical climates ; Tropical environment ; Tropical environments ; Waste Water Technology ; Water Management ; Water Pollution Control ; Zonation</subject><ispartof>Theoretical and applied climatology, 2021-08, Vol.145 (3-4), p.1467-1484</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2021</rights><rights>COPYRIGHT 2021 Springer</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c436t-6844a265c051d1af357d53fc5c57404e1c08a667a10a524b1c7b2bbdc7d913483</citedby><cites>FETCH-LOGICAL-c436t-6844a265c051d1af357d53fc5c57404e1c08a667a10a524b1c7b2bbdc7d913483</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00704-021-03701-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00704-021-03701-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Sa’adi, Zulfaqar</creatorcontrib><creatorcontrib>Shahid, Shamsuddin</creatorcontrib><creatorcontrib>Shiru, Mohammed Sanusi</creatorcontrib><title>Defining climate zone of Borneo based on cluster analysis</title><title>Theoretical and applied climatology</title><addtitle>Theor Appl Climatol</addtitle><description>Although Borneo Island is one of the most vulnerable tropical regions to climate change, maps depicting the local climate conditions employing climate classification are still not well defined. The present study attempted regional climate classification to divide the Borneo region into several homogenous groups based on long-term average climate behavior. Daily gridded rainfall and temperature (Tavg, Tmax, and Tmin) data at 0.25° resolution spanning 56 years (1960–2016) was used. The classification was done using non-hierarchical
k-mean
and several hierarchical methods, namely,
Single
,
Complete
,
McQuitty
,
Average
,
Centroid
,
Median
, and two algorithms of Ward’s method,
wardD
, and
wardD2
. The results showed that
k-mean
,
wardD
, and
wardD2
were able to classify the climate of Borneo into four zones, namely ‘dry and hot’ (DH), ‘wet and hot’ (WH), ‘wet’ (W), and ‘wet and cold’ (WC) with a considerable difference at the boundaries. Spatial relevancy, stability, and variability of the clusters based on correlation and compromise programming showed that the
wardD
method was the most likely to yield acceptable results with optimum 4-cluster to partition the area into four principal climate zones. The constructed cluster plot, centroid plot, and probability distribution function (PDF) showed a distinct climatic characteristic between the climate zones in terms of rainfall, temperature, and seasonality. The proposed climate zonation for Borneo can help in better understanding climate regionality and climate-related development planning.</description><subject>Algorithms</subject><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Atmospheric Sciences</subject><subject>Centroids</subject><subject>Classification</subject><subject>Climate change</subject><subject>Climate science</subject><subject>Climatic changes</subject><subject>Climatic classifications</subject><subject>Climatic conditions</subject><subject>Climatology</subject><subject>Cluster analysis</subject><subject>Daily rainfall</subject><subject>Distribution functions</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Local climates</subject><subject>Mean</subject><subject>Original Paper</subject><subject>Probability distribution</subject><subject>Probability distribution functions</subject><subject>Probability theory</subject><subject>Rain</subject><subject>Rain and rainfall</subject><subject>Rainfall</subject><subject>Regional climates</subject><subject>Seasonal variations</subject><subject>Seasonality</subject><subject>Stability</subject><subject>Temperature</subject><subject>Tropical climate</subject><subject>Tropical climates</subject><subject>Tropical environment</subject><subject>Tropical environments</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution 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Borneo based on cluster analysis</title><author>Sa’adi, Zulfaqar ; Shahid, Shamsuddin ; Shiru, Mohammed Sanusi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c436t-6844a265c051d1af357d53fc5c57404e1c08a667a10a524b1c7b2bbdc7d913483</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Aquatic Pollution</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>Atmospheric Sciences</topic><topic>Centroids</topic><topic>Classification</topic><topic>Climate change</topic><topic>Climate science</topic><topic>Climatic changes</topic><topic>Climatic classifications</topic><topic>Climatic conditions</topic><topic>Climatology</topic><topic>Cluster analysis</topic><topic>Daily rainfall</topic><topic>Distribution functions</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Local 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analysis</atitle><jtitle>Theoretical and applied climatology</jtitle><stitle>Theor Appl Climatol</stitle><date>2021-08-01</date><risdate>2021</risdate><volume>145</volume><issue>3-4</issue><spage>1467</spage><epage>1484</epage><pages>1467-1484</pages><issn>0177-798X</issn><eissn>1434-4483</eissn><abstract>Although Borneo Island is one of the most vulnerable tropical regions to climate change, maps depicting the local climate conditions employing climate classification are still not well defined. The present study attempted regional climate classification to divide the Borneo region into several homogenous groups based on long-term average climate behavior. Daily gridded rainfall and temperature (Tavg, Tmax, and Tmin) data at 0.25° resolution spanning 56 years (1960–2016) was used. The classification was done using non-hierarchical
k-mean
and several hierarchical methods, namely,
Single
,
Complete
,
McQuitty
,
Average
,
Centroid
,
Median
, and two algorithms of Ward’s method,
wardD
, and
wardD2
. The results showed that
k-mean
,
wardD
, and
wardD2
were able to classify the climate of Borneo into four zones, namely ‘dry and hot’ (DH), ‘wet and hot’ (WH), ‘wet’ (W), and ‘wet and cold’ (WC) with a considerable difference at the boundaries. Spatial relevancy, stability, and variability of the clusters based on correlation and compromise programming showed that the
wardD
method was the most likely to yield acceptable results with optimum 4-cluster to partition the area into four principal climate zones. The constructed cluster plot, centroid plot, and probability distribution function (PDF) showed a distinct climatic characteristic between the climate zones in terms of rainfall, temperature, and seasonality. The proposed climate zonation for Borneo can help in better understanding climate regionality and climate-related development planning.</abstract><cop>Vienna</cop><pub>Springer Vienna</pub><doi>10.1007/s00704-021-03701-1</doi><tpages>18</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Centroids Classification Climate change Climate science Climatic changes Climatic classifications Climatic conditions Climatology Cluster analysis Daily rainfall Distribution functions Earth and Environmental Science Earth Sciences Local climates Mean Original Paper Probability distribution Probability distribution functions Probability theory Rain Rain and rainfall Rainfall Regional climates Seasonal variations Seasonality Stability Temperature Tropical climate Tropical climates Tropical environment Tropical environments Waste Water Technology Water Management Water Pollution Control Zonation |
title | Defining climate zone of Borneo based on cluster analysis |
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