In　our　previous　study,　a　prediction　method　of　indoor　temperature　distribution　based　on　the　Contribution　Ratio　of　Indoor　Climate　(CRI)　and　finite　air　temperature　collected　by　one　mobile　sensor　has　been　proposed.　However,　the　CRI　fixed　value　hypothesis　limits　its　application　in　practical　situations.　In　this　regard,　this　study　proposes　to　introduce　interpolation　POD　(proper　orthogonal　decomposition)　method　to　obtain　the　dynamic　distribution　of　CRI,　so　as　to　improve　the　prediction　accuracy.　As　a　case　study,　in　a　simplified　CFD　model　with　identified　heat　source　conditions,　based　on　the　interpolation　POD　method,　the　reconstruction　of　each　sub　temperature　field　dominated　by　only　one　heat　source　under　any　air　supply　parameters　was　realized,　and　thus　its　CRI　distribution　could　be　calculated.　Then,　by　combining　the　finite　air　temperature　collected　by　the　mobile　sensor,　the　indoor　temperature　distribution　was　predicted.　The　results　showed　that　the　introduction　of　interpolation　POD　method　is　effective,　which　breaks　the　application　limitations　of　CRI　fixed　value　hypothesis　on　the　proposed　method,　and　further　promotes　its　development　potential　in　the　direction　of　＂real-time　prediction　and　dynamic　regulation＂　in　practical　application.　©　The　Authors,　published　by　EDP　Sciences.　This　is　an　open　access　article　distributed　under　the　terms　of　the　Creative　Commons　Attribution　License　4.0　(http://creativecommons.org/licenses/by/4.0/)