<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20230914</CreaDate>
<CreaTime>16180900</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idCitation>
<resTitle>2050 Annual Average Minimum Temperature</resTitle>
</idCitation>
<idAbs/>
<idCredit/>
<searchKeys>
<keyword>Cal-Adapt</keyword>
<keyword>Climate</keyword>
<keyword>Minimum Temperature</keyword>
<keyword>2050</keyword>
</searchKeys>
<idPurp>Cal-Adapt annual average minimum temperature model showing degrees fahrenheit under an RCP 8.5 scenario for 2050</idPurp>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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</Data>
</Thumbnail>
</Binary>
</metadata>
