IPWG INVENTORY OF EXISTING OPERATIONAL ALGORITHMS

IMPORTANT
The following algorithms were listed as a result of a first IPWG inventory worldwide.
The list does not pretend to be exhaustive at the moment and the inventory will be a continuous process.
Therefore the list is under a constant revision process as new algorithms are identified.
Each algorithm is briefly described following a standard form issued by the IPWG.

You are encouraged to SUBMIT to IPWG the description of your algorithm. Please proceed as follows:

download the following FORM in WORD DOC and fill it;
send it as an e-mail attachment to the IPWG Co-chairs.

IR-based algorithms
Algorithm name	Institution	Developer/contact person
CMA	China Meteorological Agency (CMA), People Rep. of China	L. Naimeng
EURAINSAT/A 1.0	EURAINSAT project, EU	F. J. Tapiador
High resolution Precipitation Index (HPI)	EUMETSAT, EU	T. Heinemann
Hydro-Estimator for short term (1-6 hr) Extreme Precipitation	NOAA/NESDIS, USA	Bob Kuligowski
JMAMSC	Japan Meteorological Agency, Japan	N. Ohkawara

Multiple precipitation estimations blend
Algorithm name	Institution	Developer/contact person
GOES Multispectral Rainfall Algorithm (GMSRA)	NOAA/NESDIS, USA	M.Ba and A. Gruber
GPCP 1 Degree Daily	NASA/GSFC, USA	G. J. Huffman
GPCP Satellite-Gauge Combination	NASA/GSFC, USA	G. J. Huffman
TRMM var (3B41RT)	NASA/GSFC, USA	G. J. Huffman

MW-based algorithms
Algorithm name	Institution	Developer/contact person
AMSR-E L2 NOAA-NESDIS global rain rates	NOAA/NESDIS, USA	R. R. Ferraro
AMSU NOAA-NESDIS orbital, pentad and monthly global rain rates	NOAA/NESDIS, USA	R. R. Ferraro
SSM/I NOAA-NESDIS orbital, pentad and monthly global rain rates	NOAA/NESDIS, USA	R. R. Ferraro
TRMM HQ (3B40RT)	NASA/GSFC, USA	G. J. Huffman

Blended MW-IR algorithms
Algorithm name	Institution	Developer/contact person
CPC Morphing technique (CMORPH)	NOAA, USA	R. Joyce
EURAINSAT/B 1.0	EURAINSAT project, EU	C. Kidd
GSMaP	Osaka University, Japan	Tomoo Ushio and Ken'ichi Okamoto
Multi-sensor Precipitation Estimate (MPE)	EUMETSAT, Germany	T. Heinemann
NRL Blended Satellite Technique	Naval Research Laboratory, USA	F. J. Turk
Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN)	Univ. of California Irvine, USA	K.-L. Hsu
Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Cloud Classification System (PERSIANN-CCS)	Univ. of California Irvine, USA	Yang Hong
Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR)	NOAA-NESDIS-STAR, USA	Bob Kuligowski
TRMM HQ/VAR (3B42RT)	NASA/GSFC, USA	G. J. Huffman

WMO