GOES multispectral rainfall algorithm (GMSRA)

A multispectral approach is used to optimize the identification of raining clouds located at a given altitude estimated from the cloud-top temperature . The approach combines information from five channels on the National Ocea nic and Atmospheric Administration Geostationary Operational Environmental Satellite (GOES): visible (0.65 mum), near infrared (3.9 mum), water vapor (6.7 mum), and window channels (11 and 12 mum). The screening of nonraining clouds includes the use of spatial gradient of cloud-top temperature for c irrus clouds (this screening is applied at all times) and the effective rad ius of cloud-top particles derived from the measurements at 3.9 mum during daytime. During nighttime, only clouds colder than 230 K are considered for the screening; during daytime, all clouds having a visible reflectance gre ater than 0.40 are considered for the screening, and a threshold of 15 mum in droplet effective radius is used as a low boundary of raining clouds. A GOES rain rate for each indicated raining cloud group referenced by its clo ud-top temperature is obtained by the product of probability of rain (P-b) and mean rain rate (RRmean) and is adjusted by a moisture factor that is de signed to modulate the evaporation effects on rain below cloud base for dif ferent moisture environments. The calibration of the algorithm for constant s P-b and RRmean is obtained using collocated instantaneous satellite and r adar data and hourly gauge-adjusted radar products collected during 17 days in June and July 1998. A comparison of the combined visible and a temperat ure threshold of 230 K (e.g., previous infrared/visible algorithms) with th e combined visible and a threshold of 15 mum demonstrates that the latter i mproves the detection of rain from warm clouds without lowering the skill o f the algorithm. The quantitative validation shows that the algorithm perfo rms well at daily and monthly scales. At monthly scales, a comparison with GOES Precipitation Index (GPI) shows that GOES Multispectral Rainfall Algor ithm's performance against gauges is much better for September and October 1999.