Accompany　with　the　development　of　information　service　and　rapid　expansion　of　cloud　computing,　scientific　workflow　system　is　facing　challenges　of　growing　size　of　heterogeneous　data,　complexity　of　scientific　computing　and　difficulty　of　task　integration.　In　this　paper,　a　cloud　scientific　workflow　system-CSWf,　which　based　on　Hadoop,　NoSQL　and　Web　Service　technology,　is　proposed　to　make　an　effective　integration　of　data　and　service　resources　in　the　loosely-coupled　cloud　service　environment.　To　implement　CSWf,　a　simple　but　effective　cloud　service　workflow　modeling　language　is　designed,　and　then　a　reliable　workflow　engine　is　developed　to　parse　and　schedule　the　workflow　processes,　also　a　distributed　execution　framework　is　built　to　encapsulate　workflow　jobs　and　execute　workflow　for　CSWf　in　the　cloud　environment.　CSWf　takes　benefits　of　massive　data　storage　capacity　and　distributed　parallel　computing　power　of　cloud　computing.　It　accommodates　well　on　the　requirement　of　modeling,　scheduling,　coordinating　and　executing　workflows　on　a　distributed　workflow　system.　At　the　end　of　this　paper,　an　urban　regional　air　pollution　workflow　with　different　size　input　data　on　the　cluster　is　run,　to　measure　the　performance　of　CSWf.　The　result　shows　that　CSWf　can　significantly　improve　the　efficiency　of　workflow　execution.　©　2013　IEEE.