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  • Author or Editor: G. G. Mace x
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Kenneth Sassen
,
Jennifer M. Comstock
,
Zhien Wang
, and
Gerald G. Mace

Since October 1987, the University of Utah Facility for Atmospheric Remote Sensing (FARS) has been applied to the probing of the atmosphere, concentrating on the study of high-level clouds. Regular FARS measurements, which currently total ~3000 h of ruby lidar polarization data, have been directed toward basic cloud research, remote sensing techniques development, and to improving satellite cloud property retrieval methods and GCM predictions by providing climatologically representative cloud datasets and parameterizations. Although the initial studies involved mainly the ruby lidar, the facility has steadily evolved to include a range of visible, infrared, and microwave passive remote sensors, and state-of-the-art, high-resolution dual-wavelength scanning lidar and W-band Doppler radar systems. All three active systems display polarization diversity. In this paper are reviewed the specifications of FARS instrumentation and the research programs to which they have been applied. Four multiple remote sensor case studies of various cloud systems are presented to illustrate the research capabilities. Like a handful of similar sites elsewhere, such research centers dedicated to extended time observation programs have great potential for contributing to atmospheric monitoring and climate research.

Full access
C. N. Long
,
S. A. McFarlane
,
A. Del Genio
,
P. Minnis
,
T. P. Ackerman
,
J. Mather
,
J. Comstock
,
G. G. Mace
,
M. Jensen
, and
C. Jakob

The tropical western Pacific (TWP) is an important climatic region. Strong solar heating, warm sea surface temperatures, and the annual progression of the intertropical convergence zone (ITCZ) across this region generate abundant convective systems, which through their effects on the heat and water budgets have a profound impact on global climate and precipitation. In order to accurately evaluate tropical cloud systems in models, measurements of tropical clouds, the environment in which they reside, and their impact on the radiation and water budgets are needed. Because of the remote location, ground-based datasets of cloud, atmosphere, and radiation properties from the TWP region have come primarily from shortterm field experiments. While providing extremely useful information on physical processes, these short-term datasets are limited in statistical and climatological information. To provide longterm measurements of the surface radiation budget in the tropics and the atmospheric properties that affect it, the Atmospheric Radiation Measurement program established a measurement site on Manus Island, Papua New Guinea, in 1996 and on the island republic of Nauru in late 1998. These sites provide unique datasets now available for more than 10 years on Manus and Nauru. This article presents examples of the scientific use of these datasets including characterization of cloud properties, analysis of cloud radiative forcing, model studies of tropical clouds and processes, and validation of satellite algorithms. New instrumentation recently installed at the Manus site will provide expanded opportunities for tropical atmospheric science.

Full access
Maximilian Maahn
,
David D. Turner
,
Ulrich Löhnert
,
Derek J. Posselt
,
Kerstin Ebell
,
Gerald G. Mace
, and
Jennifer M. Comstock
Full access
Maximilian Maahn
,
David D. Turner
,
Ulrich Löhnert
,
Derek J. Posselt
,
Kerstin Ebell
,
Gerald G. Mace
, and
Jennifer M. Comstock

Abstract

Remote sensing instruments are heavily used to provide observations for both the operational and research communities. These sensors do not provide direct observations of the desired atmospheric variables, but instead, retrieval algorithms are necessary to convert the indirect observations into the variable of interest. It is critical to be aware of the underlying assumptions made by many retrieval algorithms, including that the retrieval problem is often ill posed and that there are various sources of uncertainty that need to be treated properly. In short, the retrieval challenge is to invert a set of noisy observations to obtain estimates of atmospheric quantities. The problem is often complicated by imperfect forward models, by imperfect prior knowledge, and by the existence of nonunique solutions. Optimal estimation (OE) is a widely used physical retrieval method that combines measurements, prior information, and the corresponding uncertainties based on Bayes’s theorem to find an optimal solution for the atmospheric state. Furthermore, OE also allows the relative contributions of the different sources of error to the uncertainty in the final retrieved atmospheric state to be understood. Here, we provide a novel Python library to illustrate the use of OE for inverse problems in the atmospheric sciences. We introduce two example problems: how to retrieve drop size distribution parameters from radar observations and how to retrieve the temperature profile from ground-based microwave sensors. Using these examples, we discuss common pitfalls, how the various error sources impact the retrieval, and how the quality of the retrieval results can be quantified.

Free access
Peter T. May
,
James H. Mather
,
Geraint Vaughan
,
Christian Jakob
,
Greg M. McFarquhar
,
Keith N. Bower
, and
Gerald G. Mace

A comprehensive dataset describing tropical cloud systems and their environmental setting and impacts has been collected during the Tropical Warm Pool International Cloud Experiment (TWPICE) and Aerosol and Chemical Transport in Tropical Convection (ACTIVE) campaign in the area around Darwin, Northern Australia, in January and February 2006. The aim of the experiment was to observe the evolution of tropical cloud systems and their interaction with the environment within an observational framework optimized for a range of modeling activities with the goal of improving the representation of cloud and aerosol process in a range of models. The experiment design utilized permanent observational facilities in Darwin, including a polarimetric weather radar and a suite of cloud remote-sensing instruments. This was augmented by a dense network of soundings, together with radiation, flux, lightning, and remote-sensing measurements, as well as oceanographic observations. A fleet of five research aircraft, including two high-altitude aircraft, were taking measurements of fluxes, cloud microphysics, and chemistry; cloud radar and lidar were carried on a third aircraft. Highlights of the experiment include an intense mesoscale convective system (MCS) developed within the network, observations used to analyze the impacts of aerosol on convective systems, and observations used to relate cirrus properties to the parent storm properties.

Full access
Peter T. May
,
James H. Mather
,
Geraint Vaughan
,
Keith N. Bower
,
Christian Jakob
,
Greg M. McFarquhar
, and
Gerald G. Mace
Full access

THE CLOUDSAT MISSION AND THE A-TRAIN

A New Dimension of Space-Based Observations of Clouds and Precipitation

Graeme L. Stephens
,
Deborah G. Vane
,
Ronald J. Boain
,
Gerald G. Mace
,
Kenneth Sassen
,
Zhien Wang
,
Anthony J. Illingworth
,
Ewan J. O'connor
,
William B. Rossow
,
Stephen L. Durden
,
Steven D. Miller
,
Richard T. Austin
,
Angela Benedetti
,
Cristian Mitrescu
, and
the CloudSat Science Team

CloudSat is a satellite experiment designed to measure the vertical structure of clouds from space. The expected launch of CloudSat is planned for 2004, and once launched, CloudSat will orbit in formation as part of a constellation of satellites (the A-Train) that includes NASA's Aqua and Aura satellites, a NASA–CNES lidar satellite (CALIPSO), and a CNES satellite carrying a polarimeter (PARASOL). A unique feature that CloudSat brings to this constellation is the ability to fly a precise orbit enabling the fields of view of the CloudSat radar to be overlapped with the CALIPSO lidar footprint and the other measurements of the constellation. The precision and near simultaneity of this overlap creates a unique multisatellite observing system for studying the atmospheric processes essential to the hydrological cycle.

The vertical profiles of cloud properties provided by CloudSat on the global scale fill a critical gap in the investigation of feedback mechanisms linking clouds to climate. Measuring these profiles requires a combination of active and passive instruments, and this will be achieved by combining the radar data of CloudSat with data from other active and passive sensors of the constellation. This paper describes the underpinning science and general overview of the mission, provides some idea of the expected products and anticipated application of these products, and the potential capability of the A-Train for cloud observations. Notably, the CloudSat mission is expected to stimulate new areas of research on clouds. The mission also provides an important opportunity to demonstrate active sensor technology for future scientific and tactical applications. The CloudSat mission is a partnership between NASA's JPL, the Canadian Space Agency, Colorado State University, the U.S. Air Force, and the U.S. Department of Energy.

Full access
Jennifer M. Comstock
,
Robert d'Entremont
,
Daniel DeSlover
,
Gerald G. Mace
,
Sergey Y. Matrosov
,
Sally A . McFarlane
,
Patrick Minnis
,
David Mitchell
,
Kenneth Sassen
,
Matthew D. Shupe
,
David D. Turner
, and
Zhien Wang

The large horizontal extent, with its 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 largescale models and for accurately predicting the Earth's future climate. A number of passive and active remote sensing retrieval algorithms 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 (ARM) program Cloud Properties Working Group are involved in an intercomparison of optical depth τ and ice water path 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 their improvement.

Currently, there are significant discrepancies among the algorithms for ice clouds with very small optical depths (τ < 0.3) and those with 1 < τ < 5. The good news is that for thin clouds (0.3 < τ < 1), the algorithms tend to converge. In this first stage of the intercomparison, we present results from a representative case study, compare the retrieved cloud properties with aircraft and satellite measurements, and perform a radiative closure experiment to begin gauging the accuracy of these retrieval algorithms.

Full access
Robert A. Houze Jr.
,
Lynn A. McMurdie
,
Walter A. Petersen
,
Mathew R. Schwaller
,
William Baccus
,
Jessica D. Lundquist
,
Clifford F. Mass
,
Bart Nijssen
,
Steven A. Rutledge
,
David R. Hudak
,
Simone Tanelli
,
Gerald G. Mace
,
Michael R. Poellot
,
Dennis P. Lettenmaier
,
Joseph P. Zagrodnik
,
Angela K. Rowe
,
Jennifer C. DeHart
,
Luke E. Madaus
,
Hannah C. Barnes
, and
V. Chandrasekar

Abstract

The Olympic Mountains Experiment (OLYMPEX) took place during the 2015/16 fall–winter season in the vicinity of the mountainous Olympic Peninsula of Washington State. The goals of OLYMPEX were to provide physical and hydrologic ground validation for the U.S.–Japan Global Precipitation Measurement (GPM) satellite mission and, more specifically, to study how precipitation in Pacific frontal systems is modified by passage over coastal mountains. Four transportable scanning dual-polarization Doppler radars of various wavelengths were installed. Surface stations were placed at various altitudes to measure precipitation rates, particle size distributions, and fall velocities. Autonomous recording cameras monitored and recorded snow accumulation. Four research aircraft supplied by NASA investigated precipitation processes and snow cover, and supplemental rawinsondes and dropsondes were deployed during precipitation events. Numerous Pacific frontal systems were sampled, including several reaching “atmospheric river” status, warm- and cold-frontal systems, and postfrontal convection.

Open access
J. S. Reid
,
H. B. Maring
,
G. T. Narisma
,
S. van den Heever
,
L. Di Girolamo
,
R. Ferrare
,
P. Lawson
,
G. G. Mace
,
J. B. Simpas
,
S. Tanelli
,
L. Ziemba
,
B. van Diedenhoven
,
R. Bruintjes
,
A. Bucholtz
,
B. Cairns
,
M. O. Cambaliza
,
G. Chen
,
G. S. Diskin
,
J. H. Flynn
,
C. A. Hostetler
,
R. E. Holz
,
T. J. Lang
,
K. S. Schmidt
,
G. Smith
,
A. Sorooshian
,
E. J. Thompson
,
K. L. Thornhill
,
C. Trepte
,
J. Wang
,
S. Woods
,
S. Yoon
,
M. Alexandrov
,
S. Alvarez
,
C. G. Amiot
,
J. R. Bennett
,
M. Brooks
,
S. P. Burton
,
E. Cayanan
,
H. Chen
,
A. Collow
,
E. Crosbie
,
A. DaSilva
,
J. P. DiGangi
,
D. D. Flagg
,
S. W. Freeman
,
D. Fu
,
E. Fukada
,
M. R. A. Hilario
,
Y. Hong
,
S. M. Hristova-Veleva
,
R. Kuehn
,
R. S. Kowch
,
G. R. Leung
,
J. Loveridge
,
K. Meyer
,
R. M. Miller
,
M. J. Montes
,
J. N. Moum
,
A. Nenes
,
S. W. Nesbitt
,
M. Norgren
,
E. P. Nowottnick
,
R. M. Rauber
,
E. A. Reid
,
S. Rutledge
,
J. S. Schlosser
,
T. T. Sekiyama
,
M. A. Shook
,
G. A. Sokolowsky
,
S. A. Stamnes
,
T. Y. Tanaka
,
A. Wasilewski
,
P. Xian
,
Q. Xiao
,
Zhuocan Xu
, and
J. Zavaleta

Abstract

The NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) employed the NASA P-3, Stratton Park Engineering Company (SPEC) Learjet 35, and a host of satellites and surface sensors to characterize the coupling of aerosol processes, cloud physics, and atmospheric radiation within the Maritime Continent’s complex southwest monsoonal environment. Conducted in the late summer of 2019 from Luzon, Philippines, in conjunction with the Office of Naval Research Propagation of Intraseasonal Tropical Oscillations (PISTON) experiment with its R/V Sally Ride stationed in the northwestern tropical Pacific, CAMP2Ex documented diverse biomass burning, industrial and natural aerosol populations, and their interactions with small to congestus convection. The 2019 season exhibited El Niño conditions and associated drought, high biomass burning emissions, and an early monsoon transition allowing for observation of pristine to massively polluted environments as they advected through intricate diurnal mesoscale and radiative environments into the monsoonal trough. CAMP2Ex’s preliminary results indicate 1) increasing aerosol loadings tend to invigorate congestus convection in height and increase liquid water paths; 2) lidar, polarimetry, and geostationary Advanced Himawari Imager remote sensing sensors have skill in quantifying diverse aerosol and cloud properties and their interaction; and 3) high-resolution remote sensing technologies are able to greatly improve our ability to evaluate the radiation budget in complex cloud systems. Through the development of innovative informatics technologies, CAMP2Ex provides a benchmark dataset of an environment of extremes for the study of aerosol, cloud, and radiation processes as well as a crucible for the design of future observing systems.

Open access