PI Product : Combined Retrieval, Microphysical Retrievals & Heating Rates

[ research data - ASR funded ]

The PNNL Combined Remote Sensor retrieval algorithm (CombRet) is designed to retrieve cloud and precipitation properties for all sky conditions. The retrieval is based on a combination of several previously published retrievals, with new additions related to the retrieval of cloud microphysical properties when only one instrument is able to detect cloud (i.e. radar only or lidar only). The CombRet has been evaluated against other algorithms in Zhao et al. (2012) and Comstock et al. (2013).

Purpose

The purpose of the dataset is to provide best estimate total hydrometeor profiles from non-precipitating clouds to precipitating deep convection in a single dataset, to retrieve cloud microphysics and broadband radiative heating rate profiles for all-sky conditions, to help understanding of the cloud radiative impacts in the warm tropical oceanic environment, and to evaluate and improve numerical weather prediction model and climate model simulations.

Data Details

Developed by Zhe Feng
Contact
Zhe Feng
zhe.feng@pnnl.gov
(509)372-4052
PO Box 999 MSIN: K9-24
Richland, WA  99352
Resource(s) Data Directory, ReadMe
Data Format netcdf
Data Usage There are several sets of files provided and are explained below: 1) Merged KAZR/S-Pol/MPL moments files, containing basic radar moments, cloud mask, precipitation, etc.: gan2kazrspolcombineM1 2) CombRet cloud microphysics files, containing water content, effective particle size, cloud phase, etc.: gan2combret7fengM1 3) CombRet radiative heating rate files, containing shortwave/longwave broadband radiative heating rate profiles, surface/TOA fluxes, etc.: gan2combret7feng_hr1M1 4) 1-hourly averaged radiative heating rate files on constant pressure grid for entire AMIE period, containing all relevant variables in 3): gan2combret7feng_hr_20111010_20120208.nc 5) Quick look images for each day: combrethr_quicklooks
Content Time Range 2011.10.10 — 2012.02.08
Scientific Measurements
Measurement Variables
Cloud droplet size

reff_liquid

Ice effective size

dge_ice

Liquid water content

lwc

Ice water content

iwc

Cloud top height

cloud_layer_top_height

Cloud base height

vceil_cloudbase
cloud_base_best_estimate

Hydrometeor phase

cloud_phase

Precipitation

rainrate

Broadband shortwave heating rate

swhr

Broadband longwave heating rate

lwhr

Broadband shortwave upwelling flux

swfluxuptoa
swfluxupsfc

Broadband shortwave downwelling flux

swfluxdownsfc

Broadband longwave upwelling flux

lwfluxuptoa
lwfluxupsfc

Broadband longwave downwelling flux

lwfluxdownsfc

Cloud optical depth

liqtau
icetau
raintau
fu_icetau
fu_ir_icetau

Instruments Active Remote Sensing of CLouds (ARSCL) product using Ka-band ARM Zenith Radars
NCAR S-PolKa dual-polarimetric radar (10 cm)
Micropulse Lidar
Surface Meteorological Instrumentation
Microwave Radiometer
Merged Sounding
Attribute Accuracy No formal attribute accuracy tests were conducted
Positional Accuracy N/A
Data Consistency and Completeness Yes, dataset may contain some bad values, although some basic Quality Control of removing out-of-range values have been applied. Users are advised to read the provided detail documentation carefully for additional details.
Factor Affecting the Research N/A
Access Restriction No access constraints are associated with this data.
Use Restriction No use constraints are associated with this data.
File Naming Convention SiteName + DataSetName + Version + Author + FacilityID: e.g. gan2combret7fengM1
Directory Organization Merged KAZR/S-Pol moment profiles: gan2kazrspolcombineM1; Cloud microphysics retrieval: gan2combret7fengM1; Cloud radiative heating rate retrieval: gan2combret7feng_hr1M1
Citations Feng, Z., S. A. McFarlane, C. Schumacher, S. Ellis, J. Comstock, and N. Bharadwaj, 2014: Constructing a Merged Cloud-Precipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll. J. Atmos. Oceanic Technol., 31, 1021-1042. doi: http://dx.doi.org/10.1175/JTECH-D-13-00132.1

Comstock, J. M., A. Protat, S. A. McFarlane, J. Delanoe, and M. Deng, (2013): Assessment of Uncertainty in Cloud Radiative Effects and Heating Rates through Retrieval Algorithm Differences: Analysis using 3-years of ARM data at Darwin, Australia. J. Geophys. Res., 118, 4549-4571, doi:10.1002/jgrd.50404.

Zhao, C., et al. (2012), Toward understanding of differences in current cloud retrievals of ARM ground-based measurements, J. Geophys. Res., 117, D10206, doi:10.1029/2011JD016792.