Global precipitation measurements for validating climate models

The advent of global precipitation data sets with increasing temporal span has made it possible to use them for validating climate models. In order to fulfill the requirement of global coverage, existing products integrate satellite-derived retrievals from many sensors with direct ground observations (gauges, disdrometers, radars), which are used as reference for the satellites. While the resulting product can be deemed as the best-available source of quality validation data, awareness of the limitations of such data sets is important to avoid extracting wrong or unsubstantiated conclusions when assessing climate model abilities. This paper provides guidance on the use of precipitation data sets for climate research, including model validation and verification for improving physical parameterizations. The strengths and limitations of the data sets for climate modeling applications are presented, and a protocol for quality assurance of both observational databases and models is discussed. The http://dx.doi. org/10.1016/j.atmosres. 2017.06. 021 Received 7 April 2017; Received in revised form 21 May 2017; Accepted 19 June 2017 ⁎ Corresponding author. E-mail address: Francisco.Tapiador@uclm.es (F.J. Tapiador). Abbreviations: 4D, Four-dimensional; 1DD, GPCP One-Degree Daily; AIRS, Atmospheric Infrared Sounder; ANN, Artificial neural networks; APHRODITE, Asian Precipitation HighlyResolved Observational Data Integration Towards Evaluation; AR5, IPCC Fifth Assessment Report; ARM, Atmospheric Radiation Measurement; ATBD, Algorithm Theoretical Basis Document; BIAS, Bristol-NOAA InterActive Scheme; C3VP, Canadian CloudSat/CALIPSO Validation Program; CaPPM, Cloud and Precipitation Processes Mission; CDR, Climate Data Records; CESM, Community Earth System Model; CFAD, Contoured-Frequency-by-Altitude Diagram; CFSR, Climate Forecast System Reanalysis; CHIRPS, Climate Hazards group Infrared Precipitation with Station; CMAP, CPC Merged Analysis of Precipitation; CMORPH, CPC MORPHing technique; CORDEX, Coordinated Regional Climate Downscaling Experiment; COSMO, Consortium for Small-scale Modeling; CPC, Climate Prediction Center; CRM, Cloud Resolving Model; CRU, Climate Research Unit; CSH, Convective-Stratiform Heating; CST, Convective-Stratiform Technique; DPR, Dual-frequency Precipitation Radar; DSD, Drop Size Distribution; ECA, European Climate Assessment; ENSO, El Nino-Southern Oscillation; ERA-I, European Centre for Medium-Range Weather Forecast (ECMWF) interim reanalysis; GCE, Goddard Cumulus Ensemble; GCM, General Circulation Model/Global Climate Model; G-CRM, Global Cloud Resolving Model; GHCN, Global Historical Climatology Network; GMI, GPM Microwave Imager; GPCC, Global Precipitation Climatology Centre; GPCP, Global Precipitation Climatology Project; GPI, Global Precipitation Index; GPM, Global Precipitation Measurement mission; GPROF, Goddard profiling algorithm; G-SDSU, Goddard Satellite Data Simulator Unit; GSMAP, Global Satellite Map Product; GV, Ground validation; HH, Hydrometeor Heating; HR-GCM, High Resolution General Circulation Model; HRPP, High-Resolution Precipitation Products; iFloodS, Iowa Flood Studies; IMERG, Integrated Multi-satellitE Retrievals for GPM; IPCC, Intergovernmental Panel on Climate Change; ipHex, Integrated Precipitation and Hydrology Experiment; IPSL, Institut Pierre Simon Laplace; IR, Infrared radiation; ITCZ, Intertropical Convergence Zone; JCR, Journal Citation Reports; JRA25, Japanese 25-year Reanalysis; LH, Latent Heat; LMDZ, Laboratoire de Météorologie Dynamique Zoom; MERRA, Modern-Era Retrospective analysis for Research and Applications; MP, Microphysics; NRL, Naval Research Laboratory; NU-WRF, NASA-Unified Weather Research and Forecasting; OLYMPEX, Olympic Mountain Experiment; PBL, Planetary Boundary Layer; PDF, Probability distribution function; PERSIANN, Precipitation Estimation from Remote-Sensed Information using ANN; PMIR, Passive Microwave-InfraRed; PMW, Passive Microwave; PR, Precipitation Radar; PRESTORM, Preliminary Regional Experiment for STORM-Central; PRH, Precipitation Radar Heating; QA, Quality Assurance; QC, Quality Control; RAMS, Regional Atmospheric Modeling System; RCM, Regional Climate Model; REFAME, Rain Estimation using Forward Adjusted-advection of Microwave Estimates; RSS, Remote Sensing Systems; SBM, Spectral bin microphysics; SG, Satellite-Gauge; SLH, Spectral Latent Heating; SSM/I, Special Sensor Microwave Imager; SSMIS, Special Sensor Microwave Imager/Sounder; TAMSAT, Tropical Applications of Meteorology using SATellite data and ground-based observations; TMI, TRMMMicrowave Imager; TMPA, TRMMMulti-Satellite Precipitation Analysis; TMPI, Threshold-Matched Precipitation Index; TOVS, TIROS Operational Vertical Sounder; TRMM, Tropical Rainfall Measuring Mission; VIS, Visible; WRF-SBM, Weather Research and Forecasting – Spectral Bin Microphysics Atmospheric Research 197 (2017) 1–20 Available online 20 June 2017 0169-8095/ © 2017 Published by Elsevier B.V. MARK paper helps elaborating the recent IPCC AR5 acknowledgment of large observational uncertainties in precipitation observations for climate model validation.