Evaluation of Cloud Liquid Water Database Using Global CloudSystem Resolving Model for GPM/DPR Algorithms

This paper describes a cloud liquid water (CLW) database derived from a global cloud-system resolving model NICAM for precipitation retrievals of Dual-frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) core observatory. Furthermore, impacts of the CLW assumptions were evaluated by experiments using the operational DPR Level-2 algorithm that provides estimated precipitation rates. The CLW database was calculated using the 3.5km-mesh global atmospheric simulation data as a function of surface precipitation rate (SPR), precipitation type (convective or stratiform), temperature, latitude, and land surface type. By comparing the 1-month experiment of the CLW amount with 0 mg/m3, impacts of the current CLW assumptions to surface precipitation estimations were 1.8% for the Ku, 14.0% for the Ka, 8.0% for the Dual-frequency algorithms in global averages. The CLW database was calculated using the 3.5km-mesh global atmospheric simulation data as a function of surface precipitation rate (SPR), precipitation type (convective or stratiform), temperature, latitude, and land surface type. By comparing the 1-month experiment of the CLW amount with 0 mg/m3, impacts of the current CLW assumptions to surface precipitation estimations were 1.8% for the Ku, 14.0% for the Ka, 8.0% for the Dual-frequency algorithms in global averages. By comparing the 1-month experiment of the CLW amount with 0 mg/m3, impacts of the current CLW assumptions to surface precipitation estimations were 1.8% for the Ku, 14.0% for the Ka, 8.0% for the Dual-frequency algorithms in global averages.