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D. D. Turner
,
A. M. Vogelmann
,
R. T. Austin
,
J. C. Barnard
,
K. Cady-Pereira
,
J. C. Chiu
,
S. A. Clough
,
C. Flynn
,
M. M. Khaiyer
,
J. Liljegren
,
K. Johnson
,
B. Lin
,
C. Long
,
A. Marshak
,
S. Y. Matrosov
,
S. A. McFarlane
,
M. Miller
,
Q. Min
,
P. Minimis
,
W. O'Hirok
,
Z. Wang
, and
W. Wiscombe

Many of the clouds important to the Earth's energy balance, from the Tropics to the Arctic, contain small amounts of liquid water. Longwave and shortwave radiative fluxes are very sensitive to small perturbations of the cloud liquid water path (LWP), when the LWP is small (i.e., < 100 g m−2; clouds with LWP less than this threshold will be referred to as “thin”). Thus, the radiative properties of these thin liquid water clouds must be well understood to capture them correctly in climate models. We review the importance of these thin clouds to the Earth's energy balance, and explain the difficulties in observing them. In particular, because these clouds are thin, potentially mixed phase, and often broken (i.e., have large 3D variability), it is challenging to retrieve their microphysical properties accurately. We describe a retrieval algorithm intercomparison that was conducted to evaluate the issues involved. The intercomparison used data collected at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site and included 18 different algorithms to evaluate their retrieved LWP, optical depth, and effective radii. Surprisingly, evaluation of the simplest case, a single-layer overcast stratocumulus, revealed that huge discrepancies exist among the various techniques, even among different algorithms that are in the same general classification. This suggests that, despite considerable advances that have occurred in the field, much more work must be done, and we discuss potential avenues for future research.)

Full access
Chidong Zhang
,
Aaron F. Levine
,
Muyin Wang
,
Chelle Gentemann
,
Calvin W. Mordy
,
Edward D. Cokelet
,
Philip A. Browne
,
Qiong Yang
,
Noah Lawrence-Slavas
,
Christian Meinig
,
Gregory Smith
,
Andy Chiodi
,
Dongxiao Zhang
,
Phyllis Stabeno
,
Wanqiu Wang
,
Hong-Li Ren
,
K. Andrew Peterson
,
Silvio N. Figueroa
,
Michael Steele
,
Neil P. Barton
,
Andrew Huang
, and
Hyun-Cheol Shin

Abstract

Observations from uncrewed surface vehicles (saildrones) in the Bering, Chukchi, and Beaufort Seas during June–September 2019 were used to evaluate initial conditions and forecasts with lead times up to 10 days produced by eight operational numerical weather prediction centers. Prediction error behaviors in pressure and wind are found to be different from those in temperature and humidity. For example, errors in surface pressure were small in short-range (<6 days) forecasts, but they grew rapidly with increasing lead time beyond 6 days. Non-weighted multimodel means outperformed all individual models approaching a 10-day forecast lead time. In contrast, errors in surface air temperature and relative humidity could be large in initial conditions and remained large through 10-day forecasts without much growth, and non-weighted multimodel means did not outperform all individual models. These results following the tracks of the mobile platforms are consistent with those at a fixed location. Large errors in initial condition of sea surface temperature (SST) resulted in part from the unusual Arctic surface warming in 2019 not captured by data assimilation systems used for model initialization. These errors in SST led to large initial and prediction errors in surface air temperature. Our results suggest that improving predictions of surface conditions over the Arctic Ocean requires enhanced in situ observations and better data assimilation capability for more accurate initial conditions as well as better model physics. Numerical predictions of Arctic atmospheric conditions may continue to suffer from large errors if they do not fully capture the large SST anomalies related to Arctic warming.

Full access
Michael J. DeFlorio
,
Agniv Sengupta
,
Christopher M. Castellano
,
Jiabao Wang
,
Zhenhai Zhang
,
Alexander Gershunov
,
Kristen Guirguis
,
Rosa Luna Niño
,
Rachel E. S. Clemesha
,
Ming Pan
,
Mu Xiao
,
Brian Kawzenuk
,
Peter B. Gibson
,
William Scheftic
,
Patrick D. Broxton
,
Matthew B. Switanek
,
Jing Yuan
,
Michael D. Dettinger
,
Chad W. Hecht
,
Daniel R. Cayan
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Bruce D. Cornuelle
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Arthur J. Miller
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Julie Kalansky
,
Luca Delle Monache
,
F. Martin Ralph
,
Duane E. Waliser
,
Andrew W. Robertson
,
Xubin Zeng
,
David G. DeWitt
,
Jeanine Jones
, and
Michael L. Anderson

Abstract

California experienced a historic run of nine consecutive landfalling atmospheric rivers (ARs) in three weeks’ time during winter 2022/23. Following three years of drought from 2020 to 2022, intense landfalling ARs across California in December 2022–January 2023 were responsible for bringing reservoirs back to historical averages and producing damaging floods and debris flows. In recent years, the Center for Western Weather and Water Extremes and collaborating institutions have developed and routinely provided to end users peer-reviewed experimental seasonal (1–6 month lead time) and subseasonal (2–6 week lead time) prediction tools for western U.S. ARs, circulation regimes, and precipitation. Here, we evaluate the performance of experimental seasonal precipitation forecasts for winter 2022/23, along with experimental subseasonal AR activity and circulation forecasts during the December 2022 regime shift from dry conditions to persistent troughing and record AR-driven wetness over the western United States. Experimental seasonal precipitation forecasts were too dry across Southern California (likely due to their overreliance on La Niña), and the observed above-normal precipitation across Northern and Central California was underpredicted. However, experimental subseasonal forecasts skillfully captured the regime shift from dry to wet conditions in late December 2022 at 2–3 week lead time. During this time, an active MJO shift from phases 4 and 5 to 6 and 7 occurred, which historically tilts the odds toward increased AR activity over California. New experimental seasonal and subseasonal synthesis forecast products, designed to aggregate information across institutions and methods, are introduced in the context of this historic winter to provide situational awareness guidance to western U.S. water managers.

Open access
P. Joe
,
S. Belair
,
N.B. Bernier
,
V. Bouchet
,
J. R. Brook
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D. Brunet
,
W. Burrows
,
J.-P. Charland
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A. Dehghan
,
N. Driedger
,
C. Duhaime
,
G. Evans
,
A.-B. Filion
,
R. Frenette
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J. de Grandpré
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I. Gultepe
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D. Henderson
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A. Herdt
,
N. Hilker
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L. Huang
,
E. Hung
,
G. Isaac
,
C.-H. Jeong
,
D. Johnston
,
J. Klaassen
,
S. Leroyer
,
H. Lin
,
M. MacDonald
,
J. MacPhee
,
Z. Mariani
,
T. Munoz
,
J. Reid
,
A. Robichaud
,
Y. Rochon
,
K. Shairsingh
,
D. Sills
,
L. Spacek
,
C. Stroud
,
Y. Su
,
N. Taylor
,
J. Vanos
,
J. Voogt
,
J. M. Wang
,
T. Wiechers
,
S. Wren
,
H. Yang
, and
T. Yip

Abstract

The Pan and Parapan American Games (PA15) are the third largest sporting event in the world and were held in Toronto in the summer of 2015 (10–26 July and 7–15 August). This was used as an opportunity to coordinate and showcase existing innovative research and development activities related to weather, air quality (AQ), and health at Environment and Climate Change Canada. New observational technologies included weather stations based on compact sensors that were augmented with black globe thermometers, two Doppler lidars, two wave buoys, a 3D lightning mapping array, two new AQ stations, and low-cost AQ and ultraviolet sensors. These were supplemented by observations from other agencies, four mobile vehicles, two mobile AQ laboratories, and two supersites with enhanced vertical profiling. High-resolution modeling for weather (250 m and 1 km), AQ (2.5 km), lake circulation (2 km), and wave models (250-m, 1-km, and 2.5-km ensembles) were run. The focus of the science, which guided the design of the observation network, was to characterize and investigate the lake breeze, which affects thunderstorm initiation, air pollutant transport, and heat stress. Experimental forecasts and nowcasts were provided by research support desks. Web portals provided access to the experimental products for other government departments, public health authorities, and PA15 decision-makers. The data have been released through the government of Canada’s Open Data Portal and as a World Meteorological Organization’s Global Atmospheric Watch Urban Research Meteorology and Environment dataset.

Full access
Stephen Baxter
,
Gerald D Bell
,
Eric S Blake
,
Francis G Bringas
,
Suzana J Camargo
,
Lin Chen
,
Caio A. S Coelho
,
Ricardo Domingues
,
Stanley B Goldenberg
,
Gustavo Goni
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Nicolas Fauchereau
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Michael S Halpert
,
Qiong He
,
Philip J Klotzbach
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John A Knaff
,
Michelle L'Heureux
,
Chris W Landsea
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I.-I Lin
,
Andrew M Lorrey
,
Jing-Jia Luo
,
Andrew D Magee
,
Richard J Pasch
,
Petra R Pearce
,
Alexandre B Pezza
,
Matthew Rosencrans
,
Blair C Trewin
,
Ryan E Truchelut
,
Bin Wang
,
H Wang
,
Kimberly M Wood
, and
John-Mark Woolley
Free access
D. B. Parsons
,
M. Beland
,
D. Burridge
,
P. Bougeault
,
G. Brunet
,
J. Caughey
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S. M. Cavallo
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M. Charron
,
H. C. Davies
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A. Diongue Niang
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V. Ducrocq
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P. Gauthier
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T. M. Hamill
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P. A. Harr
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S. C. Jones
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R. H. Langland
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S. J. Majumdar
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B. N. Mills
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M. Moncrieff
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T. Nakazawa
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T. Paccagnella
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F. Rabier
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J.-L. Redelsperger
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C. Riedel
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R. W. Saunders
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M. A. Shapiro
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R. Swinbank
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I. Szunyogh
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C. Thorncroft
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A. J. Thorpe
,
X. Wang
,
D. Waliser
,
H. Wernli
, and
Z. Toth

Abstract

The Observing System Research and Predictability Experiment (THORPEX) was a 10-yr, international research program organized by the World Meteorological Organization’s World Weather Research Program. THORPEX was motivated by the need to accelerate the rate of improvement in the accuracy of 1-day to 2-week forecasts of high-impact weather for the benefit of society, the economy, and the environment. THORPEX, which took place from 2005 to 2014, was the first major international program focusing on the advancement of global numerical weather prediction systems since the Global Atmospheric Research Program, which took place almost 40 years earlier, from 1967 through 1982. The scientific achievements of THORPEX were accomplished through bringing together scientists from operational centers, research laboratories, and the academic community to collaborate on research that would ultimately advance operational predictive skill. THORPEX included an unprecedented effort to make operational products readily accessible to the broader academic research community, with community efforts focused on problems where challenging science intersected with the potential to accelerate improvements in predictive skill. THORPEX also collaborated with other major programs to identify research areas of mutual interest, such as topics at the intersection of weather and climate. THORPEX research has 1) increased our knowledge of the global-to-regional influences on the initiation, evolution, and predictability of high-impact weather; 2) provided insight into how predictive skill depends on observing strategies and observing systems; 3) improved data assimilation and ensemble forecast systems; 4) advanced knowledge of high-impact weather associated with tropical and polar circulations and their interactions with midlatitude flows; and 5) expanded society’s use of weather information through applied and social science research.

Full access
H. J. S. Fernando
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J. Mann
,
J. M. L. M. Palma
,
J. K. Lundquist
,
R. J. Barthelmie
,
M. Belo-Pereira
,
W. O. J. Brown
,
F. K. Chow
,
T. Gerz
,
C. M. Hocut
,
P. M. Klein
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L. S. Leo
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J. C. Matos
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S. P. Oncley
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S. C. Pryor
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L. Bariteau
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T. M. Bell
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N. Bodini
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M. B. Carney
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M. S. Courtney
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E. D. Creegan
,
R. Dimitrova
,
S. Gomes
,
M. Hagen
,
J. O. Hyde
,
S. Kigle
,
R. Krishnamurthy
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J. C. Lopes
,
L. Mazzaro
,
J. M. T. Neher
,
R. Menke
,
P. Murphy
,
L. Oswald
,
S. Otarola-Bustos
,
A. K. Pattantyus
,
C. Veiga Rodrigues
,
A. Schady
,
N. Sirin
,
S. Spuler
,
E. Svensson
,
J. Tomaszewski
,
D. D. Turner
,
L. van Veen
,
N. Vasiljević
,
D. Vassallo
,
S. Voss
,
N. Wildmann
, and
Y. Wang

Abstract

A grand challenge from the wind energy industry is to provide reliable forecasts on mountain winds several hours in advance at microscale (∼100 m) resolution. This requires better microscale wind-energy physics included in forecasting tools, for which field observations are imperative. While mesoscale (∼1 km) measurements abound, microscale processes are not monitored in practice nor do plentiful measurements exist at this scale. After a decade of preparation, a group of European and U.S. collaborators conducted a field campaign during 1 May–15 June 2017 in Vale Cobrão in central Portugal to delve into microscale processes in complex terrain. This valley is nestled within a parallel double ridge near the town of Perdigão with dominant wind climatology normal to the ridges, offering a nominally simple yet natural setting for fundamental studies. The dense instrument ensemble deployed covered a ∼4 km × 4 km swath horizontally and ∼10 km vertically, with measurement resolutions of tens of meters and seconds. Meteorological data were collected continuously, capturing multiscale flow interactions from synoptic to microscales, diurnal variability, thermal circulation, turbine wake and acoustics, waves, and turbulence. Particularly noteworthy are the extensiveness of the instrument array, space–time scales covered, use of leading-edge multiple-lidar technology alongside conventional tower and remote sensors, fruitful cross-Atlantic partnership, and adaptive management of the campaign. Preliminary data analysis uncovered interesting new phenomena. All data are being archived for public use.

Full access
Brian J. Butterworth
,
Ankur R. Desai
,
Stefan Metzger
,
Philip A. Townsend
,
Mark D. Schwartz
,
Grant W. Petty
,
Matthias Mauder
,
Hannes Vogelmann
,
Christian G. Andresen
,
Travis J. Augustine
,
Timothy H. Bertram
,
William O.J. Brown
,
Michael Buban
,
Patricia Cleary
,
David J. Durden
,
Christopher R. Florian
,
Trevor J. Iglinski
,
Eric L. Kruger
,
Kathleen Lantz
,
Temple R. Lee
,
Tilden P. Meyers
,
James K. Mineau
,
Erik R. Olson
,
Steven P. Oncley
,
Sreenath Paleri
,
Rosalyn A. Pertzborn
,
Claire Pettersen
,
David M. Plummer
,
Laura D. Riihimaki
,
Eliceo Ruiz Guzman
,
Joseph Sedlar
,
Elizabeth N. Smith
,
Johannes Speidel
,
Paul C. Stoy
,
Matthias Sühring
,
Jonathan E. Thom
,
David D. Turner
,
Michael P. Vermeuel
,
Timothy J. Wagner
,
Zhien Wang
,
Luise Wanner
,
Loren D. White
,
James M. Wilczak
,
Daniel B. Wright
, and
Ting Zheng
Full access
Brian J. Butterworth
,
Ankur R. Desai
,
Philip A. Townsend
,
Grant W. Petty
,
Christian G. Andresen
,
Timothy H. Bertram
,
Eric L. Kruger
,
James K. Mineau
,
Erik R. Olson
,
Sreenath Paleri
,
Rosalyn A. Pertzborn
,
Claire Pettersen
,
Paul C. Stoy
,
Jonathan E. Thom
,
Michael P. Vermeuel
,
Timothy J. Wagner
,
Daniel B. Wright
,
Ting Zheng
,
Stefan Metzger
,
Mark D. Schwartz
,
Trevor J. Iglinski
,
Matthias Mauder
,
Johannes Speidel
,
Hannes Vogelmann
,
Luise Wanner
,
Travis J. Augustine
,
William O. J. Brown
,
Steven P. Oncley
,
Michael Buban
,
Temple R. Lee
,
Patricia Cleary
,
David J. Durden
,
Christopher R. Florian
,
Kathleen Lantz
,
Laura D. Riihimaki
,
Joseph Sedlar
,
Tilden P. Meyers
,
David M. Plummer
,
Eliceo Ruiz Guzman
,
Elizabeth N. Smith
,
Matthias Sühring
,
David D. Turner
,
Zhien Wang
,
Loren D. White
, and
James M. Wilczak

Abstract

The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve model–data comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km × 10 km domain of a heterogeneous forest ecosystem in the Chequamegon–Nicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the world’s highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models.

Open access
Howard J. Diamond
,
Carl J. Schreck III
,
Adam Allgood
,
Emily J. Becker
,
Eric S. Blake
,
Francis G. Bringas
,
Suzana J. Camargo
,
Lin Chen
,
Caio A. S. Coelho
,
Nicolas Fauchereau
,
Stanley B. Goldenberg
,
Gustavo Goni
,
Michael S. Halpert
,
Qiong He
,
Zeng-Zhen Hu
,
Philip J. Klotzbach
,
John A. Knaff
,
Arun Kumar
,
Chris W. Landsea
,
Michelle L’Heureux
,
I.-I. Lin
,
Andrew M. Lorrey
,
Jing-Jia Luo
,
Andrew D. Magee
,
Richard J. Pasch
,
Alexandre B. Pezza
,
Matthew Rosencrans
,
Blair C. Trewin
,
Ryan E. Truchelut
,
Bin Wang
,
Hui Wang
,
Kimberly M. Wood
, and
John-Mark Woolley
Free access