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Title: An Intercomparison of Microphysical Retrieval Algorithms for Upper-Tropospheric Ice Clouds

Abstract

The large horizontal extent, location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the earth’s radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud scale processes in large-scale models and for accurately predicting the earth’s future climate. A number of passive and active remote sensing retrievals exist for estimating the microphysical properties of upper tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement program (ARM) Cloud Properties Working Group are involved in an intercomparison of optical depth (tau), ice water path, and characteristic particle size in ice clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for improvement. Currently, there is significant scatter in the algorithms for difficult clouds with very small optical depths (tau<0.3) and thick ice clouds (tau>1).more » The good news is that for thin cirrus (0.3« less

Authors:
; ; ; ; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
985043
Report Number(s):
PNNL-SA-48156
Journal ID: ISSN 0003-0007; ISSN 1520-0477; KP1205010; TRN: US201016%%1657
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Bulletin of the American Meteorological Society, 88(2):191-204; Journal Volume: 88; Journal Issue: 2
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 97 MATHEMATICAL METHODS AND COMPUTING; ALGORITHMS; ICE; CLOUDS; PARTICLE SIZE; REMOTE SENSING; SATELLITES; TROPOSPHERE; WATER; PHYSICAL PROPERTIES; AIRCRAFT; COMPARATIVE EVALUATIONS

Citation Formats

Comstock, Jennifer M., d'Entremont, Robert, DeSlover, Daniel, Mace, Gerald G., Matrosov, S. Y., McFarlane, Sally A., Minnis, Patrick, Mitchell, David, Sassen, Kenneth, Shupe, Matthew D., Turner, David D., and Wang, Zhien. An Intercomparison of Microphysical Retrieval Algorithms for Upper-Tropospheric Ice Clouds. United States: N. p., 2007. Web. doi:10.1175/BAMS-88-2-191.
Comstock, Jennifer M., d'Entremont, Robert, DeSlover, Daniel, Mace, Gerald G., Matrosov, S. Y., McFarlane, Sally A., Minnis, Patrick, Mitchell, David, Sassen, Kenneth, Shupe, Matthew D., Turner, David D., & Wang, Zhien. An Intercomparison of Microphysical Retrieval Algorithms for Upper-Tropospheric Ice Clouds. United States. doi:10.1175/BAMS-88-2-191.
Comstock, Jennifer M., d'Entremont, Robert, DeSlover, Daniel, Mace, Gerald G., Matrosov, S. Y., McFarlane, Sally A., Minnis, Patrick, Mitchell, David, Sassen, Kenneth, Shupe, Matthew D., Turner, David D., and Wang, Zhien. Thu . "An Intercomparison of Microphysical Retrieval Algorithms for Upper-Tropospheric Ice Clouds". United States. doi:10.1175/BAMS-88-2-191.
@article{osti_985043,
title = {An Intercomparison of Microphysical Retrieval Algorithms for Upper-Tropospheric Ice Clouds},
author = {Comstock, Jennifer M. and d'Entremont, Robert and DeSlover, Daniel and Mace, Gerald G. and Matrosov, S. Y. and McFarlane, Sally A. and Minnis, Patrick and Mitchell, David and Sassen, Kenneth and Shupe, Matthew D. and Turner, David D. and Wang, Zhien},
abstractNote = {The large horizontal extent, location in the cold upper troposphere, and ice composition make cirrus clouds important modulators of the earth’s radiation budget and climate. Cirrus cloud microphysical properties are difficult to measure and model because they are inhomogeneous in nature and their ice crystal size distribution and habit are not well characterized. Accurate retrievals of cloud properties are crucial for improving the representation of cloud scale processes in large-scale models and for accurately predicting the earth’s future climate. A number of passive and active remote sensing retrievals exist for estimating the microphysical properties of upper tropospheric clouds. We believe significant progress has been made in the evolution of these retrieval algorithms in the last decade; however, there is room for improvement. Members of the Atmospheric Radiation Measurement program (ARM) Cloud Properties Working Group are involved in an intercomparison of optical depth (tau), ice water path, and characteristic particle size in ice clouds retrieved using ground-based instruments. The goals of this intercomparison are to evaluate the accuracy of state-of-the-art algorithms, quantify the uncertainties, and make recommendations for improvement. Currently, there is significant scatter in the algorithms for difficult clouds with very small optical depths (tau<0.3) and thick ice clouds (tau>1). The good news is that for thin cirrus (0.3},
doi = {10.1175/BAMS-88-2-191},
journal = {Bulletin of the American Meteorological Society, 88(2):191-204},
number = 2,
volume = 88,
place = {United States},
year = {Thu Feb 01 00:00:00 EST 2007},
month = {Thu Feb 01 00:00:00 EST 2007}
}
  • This study presents new algorithms for retrieving ice cloud microphysical properties (ice water content (IWC) and median mass diameter (Dm)) for the stratiform and thick anvil regions of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and recently developed empirical relationships from aircraft in situ measurements during the Midlatitude Continental Convective Clouds Experiment (MC3E). A classic DCS case on 20 May 2011 is used to compare the retrieved IWC profiles with other retrieval and cloud-resolving model simulations. The mean values of each retrieved and simulated IWC fall within one standard derivation of the other two. The statistical results frommore » six selected cases during MC3E show that the aircraft in situ derived IWC and Dm are 0.47 ± 0.29 g m-3 and 2.02 ± 1.3 mm, while the mean values of retrievals have a positive bias of 0.16 g m-3 (34%) and a negative bias of 0.39 mm (19%). To validate the newly developed retrieval algorithms from this study, IWC and Dm are performed with other DCS cases during Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) field campaign using composite gridded NEXRAD reflectivity and compared with in situ IWC and Dm from aircraft. A total of 64 1-min collocated aircraft and radar samples are available for comparisons, and the averages of radar retrieved and aircraft in situ measured IWCs are 1.22 g m-3 and 1.26 g m-3 with a correlation of 0.5, and their averaged Dm values are 2.15 and 1.80 mm. These comparisons have shown that the retrieval algorithms 45 developed during MC3E can retrieve similar ice cloud microphysical properties of DCS to aircraft in situ measurements during BAMEX with median errors of ~40% and ~25% for IWC and Dm retrievals, respectively. This is indicating our retrieval algorithms are suitable for other midlatitude continental DCS ice clouds, especially at stratiform rain and thick anvil regions. In addition, based on the averaged IWC and Dm values during MC3E and BAMEX, the DCS IWC values over midlatitude are significantly different, while their Dm values are close to each other. On the other hand, these DCS IWC and Dm values are 1-2 orders of magnitude larger than those of single-layered cirrus clouds over midlatitudes.« less
  • (A260/OAK) Ice cloud microphysical parameters are estimated from the ground using combined radar and radiometer techniques. The remote sensing method for retrieving vertical profiles of microphysical parameters in ice clouds from ground-based measurements taken by the Doppler radar and IR radiometer was applied to several cloud cases observed during different field experiments including FIRE-II, ASTEX, and the Arizona Program. The measurements were performed with the NOAA Environmental Technology Laboratory instrumentation. The observed ice clouds were mostly cirrus clouds located in the upper troposphere above 5.6 km. Their geometrical thicknesses varied from a few hundred meters to 3 km. Characteristic cloudmore » particle sizes expressed in median mass diameters of equal-volume spheres varied from about 25 {micro}m to more than 400 {micro}m. Typically, characteristic particle sizes were increasing toward the cloud base, with the exception of the lowest range gates where particles were quickly sublimating. Highest particle concentrations were usually observed near the cloud tops. The vertical variability of particle sizes inside an individual cloud could reach one order of magnitude. The standard deviation of the mean profile for a typical cloud is usually factor of 2 or 3 smaller than mean values of particle characteristic size. Typical values of retrieved cloud ice water content varied from 1 to 100 mg m{sup -3}; however, individual variations were as high as four orders of magnitude. There was no consistent pattern in the vertical distribution of ice water content except for the rapid decrease in the vicinity of the cloud base. The relationships between retrieved cloud parameters and measured radar reflectivities were considered. The uncertainty of estimating cloud parameters from the power-law regressions is discussed. The parameters of these regressions varied from cloud to cloud and were comparable to the parameters in corresponding regressions obtained from direct particle sampling in other experiments. Relationships between cloud microphysical parameters and reflectivity can vary even for the same observational case. The variability diminishes if stronger reflectivities are considered. A procedure of ''tuning'' cloud microphysics--reflectivity regressions for individual profiles is suggested. Such a procedure can simplify the radar--radiometer method and make it applicable for a broader range of clouds.« less
  • (A260/OAK) Ice cloud microphysical parameters are estimated from the ground using combined radar and radiometer techniques.
  • Mixed-phase stratiform clouds can persist even with steady ice precipitation fluxes, and the origin and microphysical properties of the ice crystals are of interest. Vapor deposition growth and sedimentation of ice particles along with a uniform volume source of ice nucleation, leads to a power law relation between ice water content wi and ice number concentration ni with exponent 2.5. The result is independent of assumptions about the vertical velocity structure of the cloud and is therefore more general than the related expression of Yang et al. [2013]. The sensitivity of the wi-ni relationship to the spatial distribution of icemore » nucleation is confirmed by Lagrangian tracking and ice growth with cloud-volume, cloud-top, and cloud-base sources of ice particles through a time-dependent cloud field. Based on observed wi and ni from ISDAC, a lower bound of 0.006 m^3/s is obtained for the ice crystal formation rate.« less
  • Measurement of ice number concentration in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving ice number concentration from remote sensing measurements. The simple ice generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer ice number concentration quantitatively. To understand the strong temperature dependency of ice habit and growth rate quantitatively, we develop a 1-D ice growth model to calculate the ice diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of ice crystals calculatedmore » from the 1-D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D ice growth model simulations, we develop a method to retrieve the ice number concentrations in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved ice concentrations in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved ice number concentrations are within an uncertainty of a factor of 2, statistically.« less