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James W. Hurrell
,
James J. Hack
,
Adam S. Phillips
,
Julie Caron
, and
Jeffrey Yin

Abstract

The dynamical simulation of the latest version of the Community Atmosphere Model (CAM3) is examined, including the seasonal variation of its mean state and its interannual variability. An ensemble of integrations forced with observed monthly varying sea surface temperatures and sea ice concentrations is compared to coexisting observations. The most significant differences from the previous version of the model [Community Climate Model version 3 (CCM3)] are associated with changes to the parameterized physics package. Results show that these changes have resulted in a modest improvement in the overall simulated climate; however, CAM3 continues to share many of the same biases exhibited by CCM3.

At sea level, CAM3 reproduces the basic observed patterns of the pressure field. Simulated surface pressures are higher than observed over the subtropics, however, an error consistent with an easterly bias in the simulated trade winds and low-latitude surface wind stress. The largest regional differences over the Northern Hemisphere (NH) occur where the simulated highs over the eastern Pacific and Atlantic Oceans are too strong during boreal winter, and erroneously low pressures at higher latitudes are most notable over Europe and Eurasia. Over the Southern Hemisphere (SH), the circumpolar Antarctic trough is too deep throughout the year.

The zonal wind structure in CAM3 is close to that observed, although the middle-latitude westerlies are too strong in both hemispheres throughout the year, consistent with errors in the simulated pressure field and the transient momentum fluxes. The observed patterns and magnitudes of upper-level divergent outflow are also well simulated by CAM3, a finding consistent with an improved and overall realistic simulation of tropical precipitation. There is, however, a tendency for the tropical precipitation maxima to remain in the NH throughout the year, while precipitation tends to be less than indicated by satellite estimates along the equator.

The CAM3 simulation of tropical intraseasonal variability is quite poor. In contrast, observed changes in tropical and subtropical precipitation and the atmospheric circulation changes associated with tropical interannual variability are well simulated. Similarly, principal modes of extratropical variability bear considerable resemblance to those observed, although biases in the mean state degrade the simulated structure of the leading mode of NH atmospheric variability.

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Clara Deser
,
Adam S. Phillips
,
Robert A. Tomas
,
Yuko M. Okumura
,
Michael A. Alexander
,
Antonietta Capotondi
,
James D. Scott
,
Young-Oh Kwon
, and
Masamichi Ohba

Abstract

This study presents an overview of the El Niño–Southern Oscillation (ENSO) phenomenon and Pacific decadal variability (PDV) simulated in a multicentury preindustrial control integration of the NCAR Community Climate System Model version 4 (CCSM4) at nominal 1° latitude–longitude resolution. Several aspects of ENSO are improved in CCSM4 compared to its predecessor CCSM3, including the lengthened period (3–6 yr), the larger range of amplitude and frequency of events, and the longer duration of La Niña compared to El Niño. However, the overall magnitude of ENSO in CCSM4 is overestimated by ~30%. The simulated ENSO exhibits characteristics consistent with the delayed/recharge oscillator paradigm, including correspondence between the lengthened period and increased latitudinal width of the anomalous equatorial zonal wind stress. Global seasonal atmospheric teleconnections with accompanying impacts on precipitation and temperature are generally well simulated, although the wintertime deepening of the Aleutian low erroneously persists into spring. The vertical structure of the upper-ocean temperature response to ENSO in the north and south Pacific displays a realistic seasonal evolution, with notable asymmetries between warm and cold events. The model shows evidence of atmospheric circulation precursors over the North Pacific associated with the “seasonal footprinting mechanism,” similar to observations. Simulated PDV exhibits a significant spectral peak around 15 yr, with generally realistic spatial pattern and magnitude. However, PDV linkages between the tropics and extratropics are weaker than observed.

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Gokhan Danabasoglu
,
Steve G. Yeager
,
Young-Oh Kwon
,
Joseph J. Tribbia
,
Adam S. Phillips
, and
James W. Hurrell

Abstract

Atlantic meridional overturning circulation (AMOC) variability is documented in the Community Climate System Model, version 4 (CCSM4) preindustrial control simulation that uses nominal 1° horizontal resolution in all its components. AMOC shows a broad spectrum of low-frequency variability covering the 50–200-yr range, contrasting sharply with the multidecadal variability seen in the T85 × 1 resolution CCSM3 present-day control simulation. Furthermore, the amplitude of variability is much reduced in CCSM4 compared to that of CCSM3. Similarities as well as differences in AMOC variability mechanisms between CCSM3 and CCSM4 are discussed. As in CCSM3, the CCSM4 AMOC variability is primarily driven by the positive density anomalies at the Labrador Sea (LS) deep-water formation site, peaking 2 yr prior to an AMOC maximum. All processes, including parameterized mesoscale and submesoscale eddies, play a role in the creation of salinity anomalies that dominate these density anomalies. High Nordic Sea densities do not necessarily lead to increased overflow transports because the overflow physics is governed by source and interior region density differences. Increased overflow transports do not lead to a higher AMOC either but instead appear to be a precursor to lower AMOC transports through enhanced stratification in LS. This has important implications for decadal prediction studies. The North Atlantic Oscillation (NAO) is significantly correlated with the positive boundary layer depth and density anomalies prior to an AMOC maximum. This suggests a role for NAO through setting the surface flux anomalies in LS and affecting the subpolar gyre circulation strength.

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Barry H. Lynn
,
Seth Cohen
,
Leonard Druyan
,
Adam S. Phillips
,
Dennis Shea
,
Haim-Zvi Krugliak
, and
Alexander P. Khain

Abstract

A large set of deterministic and ensemble forecasts was produced to identify the optimal spacing for forecasting U.S. East Coast snowstorms. WRF forecasts were produced on cloud-allowing (~1-km grid spacing) and convection-allowing (3–4 km) grids, and compared against forecasts with parameterized convection (>~10 km). Performance diagrams were used to evaluate 19 deterministic forecasts from the winter of 2013–14. Ensemble forecasts of five disruptive snowstorms spanning the years 2015–18 were evaluated using various methods to evaluate probabilistic forecasts. While deterministic forecasts using cloud-allowing grids were not better than convection-allowing forecasts, both had lower bias and higher success ratios than forecasts with parameterized convection. All forecasts were underdispersive. Nevertheless, forecasts on the higher-resolution grids were more reliable than those with parameterized convection. Forecasts on the cloud-allowing grid were best able to discriminate areas that received heavy snow and those that did not, while the forecasts with parameterized convection were least able to do so. It is recommended to use convection-resolving and (if computationally possible) to use cloud-allowing forecast grids when predicting East Coast winter storms.

Free access
Clara Deser
,
Adam S. Phillips
,
Michael. A. Alexander
,
Dillon J. Amaya
,
Antonietta Capotondi
,
Michael G. Jacox
, and
James D. Scott

Abstract

The future evolution of sea surface temperature (SST) extremes is of great concern, not only for the health of marine ecosystems and sustainability of commercial fisheries, but also for precipitation extremes fueled by moisture evaporated from the ocean. This study examines the projected influence of anthropogenic climate change on the intensity and duration of monthly SST extremes, hereafter termed marine heat waves (MHWs) and marine cold waves (MCWs), based on initial-condition large ensembles with seven Earth system models. The large number of simulations (30–100) with each model allows for robust quantification of future changes in both the mean state and variability in each model. In general, models indicate that future changes in variability will cause MHW and MCW events to intensify in the northern extratropics and weaken in the tropics and Southern Ocean, and to shorten in duration in many areas. These changes are generally symmetric between MHWs and MCWs, except for the longitude of duration change in the tropical Pacific and sign of duration change in the Arctic. Projected changes in ENSO account for a large fraction of the variability-induced changes in MHW and MCW characteristics in each model and are responsible for much of the intermodel spread as a result of differences in future ENSO behavior. The variability-related changes in MHW and MCW characteristics noted above are superimposed upon large mean-state changes. Indeed, their contribution to the total change in SST during MHW and MCW events is generally <10% except in polar regions where they contribute upward of 50%.

Open access
Simone Tilmes
,
Jadwiga H. Richter
,
Ben Kravitz
,
Douglas G. MacMartin
,
Michael J. Mills
,
Isla R. Simpson
,
Anne S. Glanville
,
John T. Fasullo
,
Adam S. Phillips
,
Jean-Francois Lamarque
,
Joseph Tribbia
,
Jim Edwards
,
Sheri Mickelson
, and
Siddhartha Ghosh

Abstract

This paper describes the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) project, which promotes the use of a unique model dataset, performed with the Community Earth System Model, with the Whole Atmosphere Community Climate Model as its atmospheric component [CESM1(WACCM)], to investigate global and regional impacts of geoengineering. The performed simulations were designed to achieve multiple simultaneous climate goals, by strategically placing sulfur injections at four different locations in the stratosphere, unlike many earlier studies that targeted globally averaged surface temperature by placing injections in regions at or around the equator. This advanced approach reduces some of the previously found adverse effects of stratospheric aerosol geoengineering, including uneven cooling between the poles and the equator and shifts in tropical precipitation. The 20-member ensemble increases the ability to distinguish between forced changes and changes due to climate variability in global and regional climate variables in the coupled atmosphere, land, sea ice, and ocean system. We invite the broader community to perform in-depth analyses of climate-related impacts and to identify processes that lead to changes in the climate system as the result of a strategic application of stratospheric aerosol geoengineering.

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Matthew Newman
,
Michael A. Alexander
,
Toby R. Ault
,
Kim M. Cobb
,
Clara Deser
,
Emanuele Di Lorenzo
,
Nathan J. Mantua
,
Arthur J. Miller
,
Shoshiro Minobe
,
Hisashi Nakamura
,
Niklas Schneider
,
Daniel J. Vimont
,
Adam S. Phillips
,
James D. Scott
, and
Catherine A. Smith

Abstract

The Pacific decadal oscillation (PDO), the dominant year-round pattern of monthly North Pacific sea surface temperature (SST) variability, is an important target of ongoing research within the meteorological and climate dynamics communities and is central to the work of many geologists, ecologists, natural resource managers, and social scientists. Research over the last 15 years has led to an emerging consensus: the PDO is not a single phenomenon, but is instead the result of a combination of different physical processes, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns. How these processes combine to generate the observed PDO evolution, including apparent regime shifts, is shown using simple autoregressive models of increasing spatial complexity. Simulations of recent climate in coupled GCMs are able to capture many aspects of the PDO, but do so based on a balance of processes often more independent of the tropics than is observed. Finally, it is suggested that the assessment of PDO-related regional climate impacts, reconstruction of PDO-related variability into the past with proxy records, and diagnosis of Pacific variability within coupled GCMs should all account for the effects of these different processes, which only partly represent the direct forcing of the atmosphere by North Pacific Ocean SSTs.

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Gijs de Boer
,
Brian J. Butterworth
,
Jack S. Elston
,
Adam Houston
,
Elizabeth Pillar-Little
,
Brian Argrow
,
Tyler M. Bell
,
Phillip Chilson
,
Christopher Choate
,
Brian R. Greene
,
Ashraful Islam
,
Ryan Martz
,
Michael Rhodes
,
Daniel Rico
,
Maciej Stachura
,
Francesca M. Lappin
,
Antonio R. Segales
,
Seabrooke Whyte
, and
Matthew Wilson

Abstract

Small uncrewed aircraft systems (sUAS) are regularly being used to conduct atmospheric research and are starting to be used as a data source for informing weather models through data assimilation. However, only a limited number of studies have been conducted to evaluate the performance of these systems and assess their ability to replicate measurements from more traditional sensors such as radiosondes and towers. In the current work, we use data collected in central Oklahoma over a 2-week period to offer insight into the performance of five different sUAS platforms and associated sensors in measuring key weather data. This includes data from three rotary-wing and two fixed-wing sUAS and included two commercially available systems and three university-developed research systems. Flight data were compared to regular radiosondes launched at the flight location, tower observations, and intercompared with data from other sUAS platforms. All platforms were shown to measure atmospheric state with reasonable accuracy, though there were some consistent biases detected for individual platforms. This information can be used to inform future studies using these platforms and is currently being used to provide estimated error covariances as required in support of assimilation of sUAS data into weather forecasting systems.

Open access
Stephen W. Nesbitt
,
Paola V. Salio
,
Eldo Ávila
,
Phillip Bitzer
,
Lawrence Carey
,
V. Chandrasekar
,
Wiebke Deierling
,
Francina Dominguez
,
Maria Eugenia Dillon
,
C. Marcelo Garcia
,
David Gochis
,
Steven Goodman
,
Deanna A. Hence
,
Karen A. Kosiba
,
Matthew R. Kumjian
,
Timothy Lang
,
Lorena Medina Luna
,
James Marquis
,
Robert Marshall
,
Lynn A. McMurdie
,
Ernani de Lima Nascimento
,
Kristen L. Rasmussen
,
Rita Roberts
,
Angela K. Rowe
,
Juan José Ruiz
,
Eliah F.M.T. São Sabbas
,
A. Celeste Saulo
,
Russ S. Schumacher
,
Yanina Garcia Skabar
,
Luiz Augusto Toledo Machado
,
Robert J. Trapp
,
Adam C. Varble
,
James Wilson
,
Joshua Wurman
,
Edward J. Zipser
,
Ivan Arias
,
Hernán Bechis
, and
Maxwell A. Grover

Abstract

This article provides an overview of the experimental design, execution, education and public outreach, data collection, and initial scientific results from the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. RELAMPAGO was a major field campaign conducted in the Córdoba and Mendoza provinces in Argentina and western Rio Grande do Sul State in Brazil in 2018–19 that involved more than 200 scientists and students from the United States, Argentina, and Brazil. This campaign was motivated by the physical processes and societal impacts of deep convection that frequently initiates in this region, often along the complex terrain of the Sierras de Córdoba and Andes, and often grows rapidly upscale into dangerous storms that impact society. Observed storms during the experiment produced copious hail, intense flash flooding, extreme lightning flash rates, and other unusual lightning phenomena, but few tornadoes. The five distinct scientific foci of RELAMPAGO—convection initiation, severe weather, upscale growth, hydrometeorology, and lightning and electrification—are described, as are the deployment strategies to observe physical processes relevant to these foci. The campaign’s international cooperation, forecasting efforts, and mission planning strategies enabled a successful data collection effort. In addition, the legacy of RELAMPAGO in South America, including extensive multinational education, public outreach, and social media data gathering associated with the campaign, is summarized.

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