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  • Author or Editor: M. C. Wu x
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K.-M. Lau
,
V. Ramanathan
,
G.-X. Wu
,
Z. Li
,
S. C. Tsay
,
C. Hsu
,
R. Sikka
,
B. Holben
,
D. Lu
,
G. Tartari
,
M. Chin
,
P. Koudelova
,
H. Chen
,
Y. Ma
,
J. Huang
,
K. Taniguchi
, and
R. Zhang

Aerosol- and moonsoon-related droughts and floods are two of the most serious environmental hazards confronting more than 60% of the population of the world living in the Asian monsoon countries. In recent years, thanks to improved satellite and in situ observations, and better models, great strides have been made in aerosol and monsoon research, respectively. There is now a growing body of evidence suggesting that interaction of aerosol forcing with monsoon dynamics may alter the redistribution of energy in the atmosphere and at the Earth s surface, thereby influencing monsoon water cycle and climate. In this article, the authors describe the scientific rationale and challenges for an integrated approach to study the interactions between aerosol and monsoon water cycle dynamics. A Joint Aerosol-Monsoon Experiment (JAMEX) is proposed for 2007–11, with enhanced observations of the physical and chemical properties, sources and sinks, and long-range transport of aerosols, in conjunction with meteorological and oceanographic observations in the Indo-Pacific continental and oceanic regions. JAMEX will leverage on coordination among many ongoing and planned national research programs on aerosols and monsoons in China, India, Japan, Nepal, Italy, and the United States, as well as international research programs of the World Climate Research Program (WCRP) and the World Meteorological Organization (WMO).

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F. Vitart
,
C. Ardilouze
,
A. Bonet
,
A. Brookshaw
,
M. Chen
,
C. Codorean
,
M. Déqué
,
L. Ferranti
,
E. Fucile
,
M. Fuentes
,
H. Hendon
,
J. Hodgson
,
H.-S. Kang
,
A. Kumar
,
H. Lin
,
G. Liu
,
X. Liu
,
P. Malguzzi
,
I. Mallas
,
M. Manoussakis
,
D. Mastrangelo
,
C. MacLachlan
,
P. McLean
,
A. Minami
,
R. Mladek
,
T. Nakazawa
,
S. Najm
,
Y. Nie
,
M. Rixen
,
A. W. Robertson
,
P. Ruti
,
C. Sun
,
Y. Takaya
,
M. Tolstykh
,
F. Venuti
,
D. Waliser
,
S. Woolnough
,
T. Wu
,
D.-J. Won
,
H. Xiao
,
R. Zaripov
, and
L. Zhang

Abstract

Demands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between medium-range weather and long-range or seasonal forecasts. Based on the potential for improved forecast skill at the subseasonal to seasonal time range, the Subseasonal to Seasonal (S2S) Prediction research project has been established by the World Weather Research Programme/World Climate Research Programme. A main deliverable of this project is the establishment of an extensive database containing subseasonal (up to 60 days) forecasts, 3 weeks behind real time, and reforecasts from 11 operational centers, modeled in part on the The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database for medium-range forecasts (up to 15 days).

The S2S database, available to the research community since May 2015, represents an important tool to advance our understanding of the subseasonal to seasonal time range that has been considered for a long time as a “desert of predictability.” In particular, this database will help identify common successes and shortcomings in the model simulation and prediction of sources of subseasonal to seasonal predictability. For instance, a preliminary study suggests that the S2S models significantly underestimate the amplitude of the Madden–Julian oscillation (MJO) teleconnections over the Euro-Atlantic sector. The S2S database also represents an important tool for case studies of extreme events. For instance, a multimodel combination of S2S models displays higher probability of a landfall over the islands of Vanuatu 2–3 weeks before Tropical Cyclone Pam devastated the islands in March 2015.

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M. Goldberg
,
G. Ohring
,
J. Butler
,
C. Cao
,
R. Datla
,
D. Doelling
,
V. Gärtner
,
T. Hewison
,
B. Iacovazzi
,
D. Kim
,
T. Kurino
,
J. Lafeuille
,
P. Minnis
,
D. Renaut
,
J. Schmetz
,
D. Tobin
,
L. Wang
,
F. Weng
,
X. Wu
,
F. Yu
,
P. Zhang
, and
T. Zhu

The Global Space-based Inter-Calibration System (GSICS) is a new international program to assure the comparability of satellite measurements taken at different times and locations by different instruments operated by different satellite agencies. Sponsored by the World Meteorological Organization and the Coordination Group for Meteorological Satellites, GSICS will intercalibrate the instruments of the international constellation of operational low-earth-orbiting (LEO) and geostationary earth-orbiting (GEO) environmental satellites and tie these to common reference standards. The intercomparability of the observations will result in more accurate measurements for assimilation in numerical weather prediction models, construction of more reliable climate data records, and progress toward achieving the societal goals of the Global Earth Observation System of Systems. GSICS includes globally coordinated activities for prelaunch instrument characterization, onboard routine calibration, sensor intercomparison of near-simultaneous observations of individual scenes or overlapping time series, vicarious calibration using Earth-based or celestial references, and field campaigns. An initial strategy uses high-accuracy satellite instruments, such as the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)'s Centre National d'Études Spatiales (CNES) Infrared Atmospheric Sounding Interferometer (IASI), as space-based reference standards for intercalibrating the operational satellite sensors. Examples of initial intercalibration results and future plans are presented. Agencies participating in the program include the Centre National d'Études Spatiales, China Meteorological Administration, EUMETSAT, Japan Meteorological Agency, Korea Meteorological Administration, NASA, National Institute of Standards and Technology, and NOAA.

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Xin-Zhong Liang
,
Drew Gower
,
Jennifer A. Kennedy
,
Melissa Kenney
,
Michael C. Maddox
,
Michael Gerst
,
Guillermo Balboa
,
Talon Becker
,
Ximing Cai
,
Roger Elmore
,
Wei Gao
,
Yufeng He
,
Kang Liang
,
Shane Lotton
,
Leena Malayil
,
Megan L. Matthews
,
Alison M. Meadow
,
Christopher M. U. Neale
,
Greg Newman
,
Amy Rebecca Sapkota
,
Sanghoon Shin
,
Jonathan Straube
,
Chao Sun
,
You Wu
,
Yun Yang
, and
Xuesong Zhang

Abstract

Climate change presents huge challenges to the already-complex decisions faced by U.S. agricultural producers, as seasonal weather patterns increasingly deviate from historical tendencies. Under USDA funding, a transdisciplinary team of researchers, extension experts, educators, and stakeholders is developing a climate decision support Dashboard for Agricultural Water use and Nutrient management (DAWN) to provide Corn Belt farmers with better predictive information. DAWN’s goal is to provide credible, usable information to support decisions by creating infrastructure to make subseasonal-to-seasonal forecasts accessible. DAWN uses an integrated approach to 1) engage stakeholders to coproduce a decision support and information delivery system; 2) build a coupled modeling system to represent and transfer holistic systems knowledge into effective tools; 3) produce reliable forecasts to help stakeholders optimize crop productivity and environmental quality; and 4) integrate research and extension into experiential, transdisciplinary education. This article presents DAWN’s framework for integrating climate–agriculture research, extension, and education to bridge science and service. We also present key challenges to the creation and delivery of decision support, specifically in infrastructure development, coproduction and trust building with stakeholders, product design, effective communication, and moving tools toward use.

Open access
C. P. Weaver
,
X.-Z. Liang
,
J. Zhu
,
P. J. Adams
,
P. Amar
,
J. Avise
,
M. Caughey
,
J. Chen
,
R. C. Cohen
,
E. Cooter
,
J. P. Dawson
,
R. Gilliam
,
A. Gilliland
,
A. H. Goldstein
,
A. Grambsch
,
D. Grano
,
A. Guenther
,
W. I. Gustafson
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R. A. Harley
,
S. He
,
B. Hemming
,
C. Hogrefe
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H.-C. Huang
,
S. W. Hunt
,
D.J. Jacob
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P. L. Kinney
,
K. Kunkel
,
J.-F. Lamarque
,
B. Lamb
,
N. K. Larkin
,
L. R. Leung
,
K.-J. Liao
,
J.-T. Lin
,
B. H. Lynn
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K. Manomaiphiboon
,
C. Mass
,
D. McKenzie
,
L. J. Mickley
,
S. M. O'neill
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C. Nolte
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S. N. Pandis
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P. N. Racherla
,
C. Rosenzweig
,
A. G. Russell
,
E. Salathé
,
A. L. Steiner
,
E. Tagaris
,
Z. Tao
,
S. Tonse
,
C. Wiedinmyer
,
A. Williams
,
D. A. Winner
,
J.-H. Woo
,
S. WU
, and
D. J. Wuebbles

This paper provides a synthesis of results that have emerged from recent modeling studies of the potential sensitivity of U.S. regional ozone (O3) concentrations to global climate change (ca. 2050). This research has been carried out under the auspices of an ongoing U.S. Environmental Protection Agency (EPA) assessment effort to increase scientific understanding of the multiple complex interactions among climate, emissions, atmospheric chemistry, and air quality. The ultimate goal is to enhance the ability of air quality managers to consider global change in their decisions through improved characterization of the potential effects of global change on air quality, including O3 The results discussed here are interim, representing the first phase of the EPA assessment. The aim in this first phase was to consider the effects of climate change alone on air quality, without accompanying changes in anthropogenic emissions of precursor pollutants. Across all of the modeling experiments carried out by the different groups, simulated global climate change causes increases of a few to several parts per billion (ppb) in summertime mean maximum daily 8-h average O3 concentrations over substantial regions of the country. The different modeling experiments in general do not, however, simulate the same regional patterns of change. These differences seem to result largely from variations in the simulated patterns of changes in key meteorological drivers, such as temperature and surface insolation. How isoprene nitrate chemistry is represented in the different modeling systems is an additional critical factor in the simulated O3 response to climate change.

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S. Pawson
,
K. Kodera
,
K. Hamilton
,
T. G. Shepherd
,
S. R. Beagley
,
B. A. Boville
,
J. D. Farrara
,
T. D. A. Fairlie
,
A. Kitoh
,
W. A. Lahoz
,
U. Langematz
,
E. Manzini
,
D. H. Rind
,
A. A. Scaife
,
K. Shibata
,
P. Simon
,
R. Swinbank
,
L. Takacs
,
R. J. Wilson
,
J. A. Al-Saadi
,
M. Amodei
,
M. Chiba
,
L. Coy
,
J. de Grandpré
,
R. S. Eckman
,
M. Fiorino
,
W. L. Grose
,
H. Koide
,
J. N. Koshyk
,
D. Li
,
J. Lerner
,
J. D. Mahlman
,
N. A. McFarlane
,
C. R. Mechoso
,
A. Molod
,
A. O'Neill
,
R. B. Pierce
,
W. J. Randel
,
R. B. Rood
, and
F. Wu

To investigate the effects of the middle atmosphere on climate, the World Climate Research Programme is supporting the project “Stratospheric Processes and their Role in Climate” (SPARC). A central theme of SPARC, to examine model simulations of the coupled troposphere–middle atmosphere system, is being performed through the initiative called GRIPS (GCM-Reality Intercomparison Project for SPARC). In this paper, an overview of the objectives of GRIPS is given. Initial activities include an assessment of the performance of middle atmosphere climate models, and preliminary results from this evaluation are presented here. It is shown that although all 13 models evaluated represent most major features of the mean atmospheric state, there are deficiencies in the magnitude and location of the features, which cannot easily be traced to the formulation (resolution or the parameterizations included) of the models. Most models show a cold bias in all locations, apart from the tropical tropopause region where they can be either too warm or too cold. The strengths and locations of the major jets are often misrepresented in the models. Looking at three-dimensional fields reveals, for some models, more severe deficiencies in the magnitude and positioning of the dominant structures (such as the Aleutian high in the stratosphere), although undersampling might explain some of these differences from observations. All the models have shortcomings in their simulations of the present-day climate, which might limit the accuracy of predictions of the climate response to ozone change and other anomalous forcing.

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Greg M. McFarquhar
,
Christopher S. Bretherton
,
Roger Marchand
,
Alain Protat
,
Paul J. DeMott
,
Simon P. Alexander
,
Greg C. Roberts
,
Cynthia H. Twohy
,
Darin Toohey
,
Steve Siems
,
Yi Huang
,
Robert Wood
,
Robert M. Rauber
,
Sonia Lasher-Trapp
,
Jorgen Jensen
,
Jeffrey L. Stith
,
Jay Mace
,
Junshik Um
,
Emma Järvinen
,
Martin Schnaiter
,
Andrew Gettelman
,
Kevin J. Sanchez
,
Christina S. McCluskey
,
Lynn M. Russell
,
Isabel L. McCoy
,
Rachel L. Atlas
,
Charles G. Bardeen
,
Kathryn A. Moore
,
Thomas C. J. Hill
,
Ruhi S. Humphries
,
Melita D. Keywood
,
Zoran Ristovski
,
Luke Cravigan
,
Robyn Schofield
,
Chris Fairall
,
Marc D. Mallet
,
Sonia M. Kreidenweis
,
Bryan Rainwater
,
John D’Alessandro
,
Yang Wang
,
Wei Wu
,
Georges Saliba
,
Ezra J. T. Levin
,
Saisai Ding
,
Francisco Lang
,
Son C. H. Truong
,
Cory Wolff
,
Julie Haggerty
,
Mike J. Harvey
,
Andrew R. Klekociuk
, and
Adrian McDonald

Abstract

Weather and climate models are challenged by uncertainties and biases in simulating Southern Ocean (SO) radiative fluxes that trace to a poor understanding of cloud, aerosol, precipitation, and radiative processes, and their interactions. Projects between 2016 and 2018 used in situ probes, radar, lidar, and other instruments to make comprehensive measurements of thermodynamics, surface radiation, cloud, precipitation, aerosol, cloud condensation nuclei (CCN), and ice nucleating particles over the SO cold waters, and in ubiquitous liquid and mixed-phase clouds common to this pristine environment. Data including soundings were collected from the NSF–NCAR G-V aircraft flying north–south gradients south of Tasmania, at Macquarie Island, and on the R/V Investigator and RSV Aurora Australis. Synergistically these data characterize boundary layer and free troposphere environmental properties, and represent the most comprehensive data of this type available south of the oceanic polar front, in the cold sector of SO cyclones, and across seasons. Results show largely pristine environments with numerous small and few large aerosols above cloud, suggesting new particle formation and limited long-range transport from continents, high variability in CCN and cloud droplet concentrations, and ubiquitous supercooled water in thin, multilayered clouds, often with small-scale generating cells near cloud top. These observations demonstrate how cloud properties depend on aerosols while highlighting the importance of dynamics and turbulence that likely drive heterogeneity of cloud phase. Satellite retrievals confirmed low clouds were responsible for radiation biases. The combination of models and observations is examining how aerosols and meteorology couple to control SO water and energy budgets.

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Bart Geerts
,
Scott E. Giangrande
,
Greg M. McFarquhar
,
Lulin Xue
,
Steven J. Abel
,
Jennifer M. Comstock
,
Susanne Crewell
,
Paul J. DeMott
,
Kerstin Ebell
,
Paul Field
,
Thomas C. J. Hill
,
Alexis Hunzinger
,
Michael P. Jensen
,
Karen L. Johnson
,
Timothy W. Juliano
,
Pavlos Kollias
,
Branko Kosovic
,
Christian Lackner
,
Ed Luke
,
Christof Lüpkes
,
Alyssa A. Matthews
,
Roel Neggers
,
Mikhail Ovchinnikov
,
Heath Powers
,
Matthew D. Shupe
,
Thomas Spengler
,
Benjamin E. Swanson
,
Michael Tjernström
,
Adam K. Theisen
,
Nathan A. Wales
,
Yonggang Wang
,
Manfred Wendisch
, and
Peng Wu

Abstract

One of the most intense air mass transformations on Earth happens when cold air flows from frozen surfaces to much warmer open water in cold-air outbreaks (CAOs), a process captured beautifully in satellite imagery. Despite the ubiquity of the CAO cloud regime over high-latitude oceans, we have a rather poor understanding of its properties, its role in energy and water cycles, and its treatment in weather and climate models. The Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) was conducted to better understand this regime and its representation in models. COMBLE aimed to examine the relations between surface fluxes, boundary layer structure, aerosol, cloud, and precipitation properties, and mesoscale circulations in marine CAOs. Processes affecting these properties largely fall in a range of scales where boundary layer processes, convection, and precipitation are tightly coupled, which makes accurate representation of the CAO cloud regime in numerical weather prediction and global climate models most challenging. COMBLE deployed an Atmospheric Radiation Measurement Mobile Facility at a coastal site in northern Scandinavia (69°N), with additional instruments on Bear Island (75°N), from December 2019 to May 2020. CAO conditions were experienced 19% (21%) of the time at the main site (on Bear Island). A comprehensive suite of continuous in situ and remote sensing observations of atmospheric conditions, clouds, precipitation, and aerosol were collected. Because of the clouds’ well-defined origin, their shallow depth, and the broad range of observed temperature and aerosol concentrations, the COMBLE dataset provides a powerful modeling testbed for improving the representation of mixed-phase cloud processes in large-eddy simulations and large-scale models.

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Guy P. Brasseur
,
Mohan Gupta
,
Bruce E. Anderson
,
Sathya Balasubramanian
,
Steven Barrett
,
David Duda
,
Gregg Fleming
,
Piers M. Forster
,
Jan Fuglestvedt
,
Andrew Gettelman
,
Rangasayi N. Halthore
,
S. Daniel Jacob
,
Mark Z. Jacobson
,
Arezoo Khodayari
,
Kuo-Nan Liou
,
Marianne T. Lund
,
Richard C. Miake-Lye
,
Patrick Minnis
,
Seth Olsen
,
Joyce E. Penner
,
Ronald Prinn
,
Ulrich Schumann
,
Henry B. Selkirk
,
Andrei Sokolov
,
Nadine Unger
,
Philip Wolfe
,
Hsi-Wu Wong
,
Donald W. Wuebbles
,
Bingqi Yi
,
Ping Yang
, and
Cheng Zhou

Abstract

Under the Federal Aviation Administration’s (FAA) Aviation Climate Change Research Initiative (ACCRI), non-CO2 climatic impacts of commercial aviation are assessed for current (2006) and for future (2050) baseline and mitigation scenarios. The effects of the non-CO2 aircraft emissions are examined using a number of advanced climate and atmospheric chemistry transport models. Radiative forcing (RF) estimates for individual forcing effects are provided as a range for comparison against those published in the literature. Preliminary results for selected RF components for 2050 scenarios indicate that a 2% increase in fuel efficiency and a decrease in NOx emissions due to advanced aircraft technologies and operational procedures, as well as the introduction of renewable alternative fuels, will significantly decrease future aviation climate impacts. In particular, the use of renewable fuels will further decrease RF associated with sulfate aerosol and black carbon. While this focused ACCRI program effort has yielded significant new knowledge, fundamental uncertainties remain in our understanding of aviation climate impacts. These include several chemical and physical processes associated with NOx–O3–CH4 interactions and the formation of aviation-produced contrails and the effects of aviation soot aerosols on cirrus clouds as well as on deriving a measure of change in temperature from RF for aviation non-CO2 climate impacts—an important metric that informs decision-making.

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