Search Results

You are looking at 11 - 12 of 12 items for

  • Author or Editor: D. G. Wright x
  • Refine by Access: All Content x
Clear All Modify Search
J. W. Hurrell
,
M. Visbeck
,
A. Busalacchi
,
R. A. Clarke
,
T. L. Delworth
,
R. R. Dickson
,
W. E. Johns
,
K. P. Koltermann
,
Y. Kushnir
,
D. Marshall
,
C. Mauritzen
,
M. S. McCartney
,
A. Piola
,
C. Reason
,
G. Reverdin
,
F. Schott
,
R. Sutton
,
I. Wainer
, and
D. Wright

Abstract

Three interrelated climate phenomena are at the center of the Climate Variability and Predictability (CLIVAR) Atlantic research: tropical Atlantic variability (TAV), the North Atlantic Oscillation (NAO), and the Atlantic meridional overturning circulation (MOC). These phenomena produce a myriad of impacts on society and the environment on seasonal, interannual, and longer time scales through variability manifest as coherent fluctuations in ocean and land temperature, rainfall, and extreme events. Improved understanding of this variability is essential for assessing the likely range of future climate fluctuations and the extent to which they may be predictable, as well as understanding the potential impact of human-induced climate change. CLIVAR is addressing these issues through prioritized and integrated plans for short-term and sustained observations, basin-scale reanalysis, and modeling and theoretical investigations of the coupled Atlantic climate system and its links to remote regions. In this paper, a brief review of the state of understanding of Atlantic climate variability and achievements to date is provided. Considerable discussion is given to future challenges related to building and sustaining observing systems, developing synthesis strategies to support understanding and attribution of observed change, understanding sources of predictability, and developing prediction systems in order to meet the scientific objectives of the CLIVAR Atlantic program.

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