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O. Coddington
,
J. L. Lean
,
P. Pilewskie
,
M. Snow
, and
D. Lindholm

Abstract

We present a new climate data record for total solar irradiance and solar spectral irradiance between 1610 and the present day with associated wavelength and time-dependent uncertainties and quarterly updates. The data record, which is part of the National Oceanic and Atmospheric Administration’s (NOAA) Climate Data Record (CDR) program, provides a robust, sustainable, and scientifically defensible record of solar irradiance that is of sufficient length, consistency, and continuity for use in studies of climate variability and climate change on multiple time scales and for user groups spanning climate modeling, remote sensing, and natural resource and renewable energy industries. The data record, jointly developed by the University of Colorado’s Laboratory for Atmospheric and Space Physics (LASP) and the Naval Research Laboratory (NRL), is constructed from solar irradiance models that determine the changes with respect to quiet sun conditions when facular brightening and sunspot darkening features are present on the solar disk where the magnitude of the changes in irradiance are determined from the linear regression of a proxy magnesium (Mg) II index and sunspot area indices against the approximately decade-long solar irradiance measurements of the Solar Radiation and Climate Experiment (SORCE). To promote long-term data usage and sharing for a broad range of users, the source code, the dataset itself, and supporting documentation are archived at NOAA’s National Centers for Environmental Information (NCEI). In the future, the dataset will also be available through the LASP Interactive Solar Irradiance Data Center (LISIRD) for user-specified time periods and spectral ranges of interest.

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Thorwald H. M. Stein
,
Robin J. Hogan
,
Peter A. Clark
,
Carol E. Halliwell
,
Kirsty E. Hanley
,
Humphrey W. Lean
,
John C. Nicol
, and
Robert S. Plant

Abstract

A new frontier in weather forecasting is emerging by operational forecast models now being run at convection-permitting resolutions at many national weather services. However, this is not a panacea; significant systematic errors remain in the character of convective storms and rainfall distributions. The Dynamical and Microphysical Evolution of Convective Storms (DYMECS) project is taking a fundamentally new approach to evaluate and improve such models: rather than relying on a limited number of cases, which may not be representative, the authors have gathered a large database of 3D storm structures on 40 convective days using the Chilbolton radar in southern England. They have related these structures to storm life cycles derived by tracking features in the rainfall from the U.K. radar network and compared them statistically to storm structures in the Met Office model, which they ran at horizontal grid length between 1.5 km and 100 m, including simulations with different subgrid mixing length. The authors also evaluated the scale and intensity of convective updrafts using a new radar technique. They find that the horizontal size of simulated convective storms and the updrafts within them is much too large at 1.5-km resolution, such that the convective mass flux of individual updrafts can be too large by an order of magnitude. The scale of precipitation cores and updrafts decreases steadily with decreasing grid lengths, as does the typical storm lifetime. The 200-m grid-length simulation with standard mixing length performs best over all diagnostics, although a greater mixing length improves the representation of deep convective storms.

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John S. Kain
,
Steve Willington
,
Adam J. Clark
,
Steven J. Weiss
,
Mark Weeks
,
Israel L. Jirak
,
Michael C. Coniglio
,
Nigel M. Roberts
,
Christopher D. Karstens
,
Jonathan M. Wilkinson
,
Kent H. Knopfmeier
,
Humphrey W. Lean
,
Laura Ellam
,
Kirsty Hanley
,
Rachel North
, and
Dan Suri

Abstract

In recent years, a growing partnership has emerged between the Met Office and the designated U.S. national centers for expertise in severe weather research and forecasting, that is, the National Oceanic and Atmospheric Administration (NOAA) National Severe Storms Laboratory (NSSL) and the NOAA Storm Prediction Center (SPC). The driving force behind this partnership is a compelling set of mutual interests related to predicting and understanding high-impact weather and using high-resolution numerical weather prediction models as foundational tools to explore these interests.

The forum for this collaborative activity is the NOAA Hazardous Weather Testbed, where annual Spring Forecasting Experiments (SFEs) are conducted by NSSL and SPC. For the last decade, NSSL and SPC have used these experiments to find ways that high-resolution models can help achieve greater success in the prediction of tornadoes, large hail, and damaging winds. Beginning in 2012, the Met Office became a contributing partner in annual SFEs, bringing complementary expertise in the use of convection-allowing models, derived in their case from a parallel decadelong effort to use these models to advance prediction of flash floods associated with heavy thunderstorms.

The collaboration between NSSL, SPC, and the Met Office has been enthusiastic and productive, driven by strong mutual interests at a grassroots level and generous institutional support from the parent government agencies. In this article, a historical background is provided, motivations for collaborative activities are emphasized, and preliminary results are highlighted.

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A. J. Illingworth
,
A. Battaglia
,
J. Bradford
,
M. Forsythe
,
P. Joe
,
P. Kollias
,
K. Lean
,
M. Lori
,
J.-F. Mahfouf
,
S. Melo
,
R Midthassel
,
Y. Munro
,
J. Nicol
,
R. Potthast
,
M. Rennie
,
T. H. M. Stein
,
S. Tanelli
,
F. Tridon
,
C. J. Walden
, and
M. Wolde

Abstract

This paper presents a conically scanning spaceborne Dopplerized 94-GHz radar Earth science mission concept: Wind Velocity Radar Nephoscope (WIVERN). WIVERN aims to provide global measurements of in-cloud winds using the Doppler-shifted radar returns from hydrometeors. The conically scanning radar could provide wind data with daily revisits poleward of 50°, 50-km horizontal resolution, and approximately 1-km vertical resolution. The measured winds, when assimilated into weather forecasts and provided they are representative of the larger-scale mean flow, should lead to further improvements in the accuracy and effectiveness of forecasts of severe weather and better focusing of activities to limit damage and loss of life. It should also be possible to characterize the more variable winds associated with local convection. Polarization diversity would be used to enable high wind speeds to be unambiguously observed; analysis indicates that artifacts associated with polarization diversity are rare and can be identified. Winds should be measurable down to 1 km above the ocean surface and 2 km over land. The potential impact of the WIVERN winds on reducing forecast errors is estimated by comparison with the known positive impact of cloud motion and aircraft winds. The main thrust of WIVERN is observing in-cloud winds, but WIVERN should also provide global estimates of ice water content, cloud cover, and vertical distribution, continuing the data series started by CloudSat with the conical scan giving increased coverage. As with CloudSat, estimates of rainfall and snowfall rates should be possible. These nonwind products may also have a positive impact when assimilated into weather forecasts.

Open access
G. Vaughan
,
J. Methven
,
D. Anderson
,
B. Antonescu
,
L. Baker
,
T. P. Baker
,
S. P. Ballard
,
K. N. Bower
,
P. R. A. Brown
,
J. Chagnon
,
T. W. Choularton
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J. Chylik
,
P. J. Connolly
,
P. A. Cook
,
R. J. Cotton
,
J. Crosier
,
C. Dearden
,
J. R. Dorsey
,
T. H. A. Frame
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M. W. Gallagher
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M. Goodliff
,
S. L. Gray
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B. J. Harvey
,
P. Knippertz
,
H. W. Lean
,
D. Li
,
G. Lloyd
,
O. Martínez–Alvarado
,
J. Nicol
,
J. Norris
,
E. Öström
,
J. Owen
,
D. J. Parker
,
R. S. Plant
,
I. A. Renfrew
,
N. M. Roberts
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P. Rosenberg
,
A. C. Rudd
,
D. M. Schultz
,
J. P. Taylor
,
T. Trzeciak
,
R. Tubbs
,
A. K. Vance
,
P. J. van Leeuwen
,
A. Wellpott
, and
A. Woolley

Abstract

The Diabatic Influences on Mesoscale Structures in Extratropical Storms (DIAMET) project aims to improve forecasts of high-impact weather in extratropical cyclones through field measurements, high-resolution numerical modeling, and improved design of ensemble forecasting and data assimilation systems. This article introduces DIAMET and presents some of the first results. Four field campaigns were conducted by the project, one of which, in late 2011, coincided with an exceptionally stormy period marked by an unusually strong, zonal North Atlantic jet stream and a succession of severe windstorms in northwest Europe. As a result, December 2011 had the highest monthly North Atlantic Oscillation index (2.52) of any December in the last 60 years. Detailed observations of several of these storms were gathered using the U.K.’s BAe 146 research aircraft and extensive ground-based measurements. As an example of the results obtained during the campaign, observations are presented of Extratropical Cyclone Friedhelm on 8 December 2011, when surface winds with gusts exceeding 30 m s–1 crossed central Scotland, leading to widespread disruption to transportation and electricity supply. Friedhelm deepened 44 hPa in 24 h and developed a pronounced bent-back front wrapping around the storm center. The strongest winds at 850 hPa and the surface occurred in the southern quadrant of the storm, and detailed measurements showed these to be most intense in clear air between bands of showers. High-resolution ensemble forecasts from the Met Office showed similar features, with the strongest winds aligned in linear swaths between the bands, suggesting that there is potential for improved skill in forecasts of damaging winds.

Open access
David C. Leon
,
Jeffrey R. French
,
Sonia Lasher-Trapp
,
Alan M. Blyth
,
Steven J. Abel
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Susan Ballard
,
Andrew Barrett
,
Lindsay J. Bennett
,
Keith Bower
,
Barbara Brooks
,
Phil Brown
,
Cristina Charlton-Perez
,
Thomas Choularton
,
Peter Clark
,
Chris Collier
,
Jonathan Crosier
,
Zhiqiang Cui
,
Seonaid Dey
,
David Dufton
,
Chloe Eagle
,
Michael J. Flynn
,
Martin Gallagher
,
Carol Halliwell
,
Kirsty Hanley
,
Lee Hawkness-Smith
,
Yahui Huang
,
Graeme Kelly
,
Malcolm Kitchen
,
Alexei Korolev
,
Humphrey Lean
,
Zixia Liu
,
John Marsham
,
Daniel Moser
,
John Nicol
,
Emily G. Norton
,
David Plummer
,
Jeremy Price
,
Hugo Ricketts
,
Nigel Roberts
,
Phil D. Rosenberg
,
David Simonin
,
Jonathan W. Taylor
,
Robert Warren
,
Paul I. Williams
, and
Gillian Young

Abstract

The Convective Precipitation Experiment (COPE) was a joint U.K.–U.S. field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly as a result of the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the United States. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve numerical weather prediction (NWP) model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the U.K. BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360° volume scans over 10 elevation angles approximately every 5 min and was augmented by two Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper i) provides an overview of the COPE field campaign and the resulting dataset, ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone, and iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.

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Keith A. Browning
,
Alan M. Blyth
,
Peter A. Clark
,
Ulrich Corsmeier
,
Cyril J. Morcrette
,
Judith L. Agnew
,
Sue P. Ballard
,
Dave Bamber
,
Christian Barthlott
,
Lindsay J. Bennett
,
Karl M. Beswick
,
Mark Bitter
,
Karen E. Bozier
,
Barbara J. Brooks
,
Chris G. Collier
,
Fay Davies
,
Bernhard Deny
,
Mark A. Dixon
,
Thomas Feuerle
,
Richard M. Forbes
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Catherine Gaffard
,
Malcolm D. Gray
,
Rolf Hankers
,
Tim J. Hewison
,
Norbert Kalthoff
,
Samiro Khodayar
,
Martin Kohler
,
Christoph Kottmeier
,
Stephan Kraut
,
Michael Kunz
,
Darcy N. Ladd
,
Humphrey W. Lean
,
Jürgen Lenfant
,
Zhihong Li
,
John Marsham
,
James McGregor
,
Stephan D. Mobbs
,
John Nicol
,
Emily Norton
,
Douglas J. Parker
,
Felicity Perry
,
Markus Ramatschi
,
Hugo M. A. Ricketts
,
Nigel M. Roberts
,
Andrew Russell
,
Helmut Schulz
,
Elizabeth C. Slack
,
Geraint Vaughan
,
Joe Waight
,
David P. Wareing
,
Robert J. Watson
,
Ann R. Webb
, and
Andreas Wieser

The Convective Storm Initiation Project (CSIP) is an international project to understand precisely where, when, and how convective clouds form and develop into showers in the mainly maritime environment of southern England. A major aim of CSIP is to compare the results of the very high resolution Met Office weather forecasting model with detailed observations of the early stages of convective clouds and to use the newly gained understanding to improve the predictions of the model.

A large array of ground-based instruments plus two instrumented aircraft, from the U.K. National Centre for Atmospheric Science (NCAS) and the German Institute for Meteorology and Climate Research (IMK), Karlsruhe, were deployed in southern England, over an area centered on the meteorological radars at Chilbolton, during the summers of 2004 and 2005. In addition to a variety of ground-based remote-sensing instruments, numerous rawinsondes were released at one- to two-hourly intervals from six closely spaced sites. The Met Office weather radar network and Meteosat satellite imagery were used to provide context for the observations made by the instruments deployed during CSIP.

This article presents an overview of the CSIP field campaign and examples from CSIP of the types of convective initiation phenomena that are typical in the United Kingdom. It shows the way in which certain kinds of observational data are able to reveal these phenomena and gives an explanation of how the analyses of data from the field campaign will be used in the development of an improved very high resolution NWP model for operational use.

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Leon Hermanson
,
Doug Smith
,
Melissa Seabrook
,
Roberto Bilbao
,
Francisco Doblas-Reyes
,
Etienne Tourigny
,
Vladimir Lapin
,
Viatcheslav V. Kharin
,
William J. Merryfield
,
Reinel Sospedra-Alfonso
,
Panos Athanasiadis
,
Dario Nicoli
,
Silvio Gualdi
,
Nick Dunstone
,
Rosie Eade
,
Adam Scaife
,
Mark Collier
,
Terence O’Kane
,
Vassili Kitsios
,
Paul Sandery
,
Klaus Pankatz
,
Barbara Früh
,
Holger Pohlmann
,
Wolfgang Müller
,
Takahito Kataoka
,
Hiroaki Tatebe
,
Masayoshi Ishii
,
Yukiko Imada
,
Tim Kruschke
,
Torben Koenigk
,
Mehdi Pasha Karami
,
Shuting Yang
,
Tian Tian
,
Liping Zhang
,
Tom Delworth
,
Xiaosong Yang
,
Fanrong Zeng
,
Yiguo Wang
,
François Counillon
,
Noel Keenlyside
,
Ingo Bethke
,
Judith Lean
,
Jürg Luterbacher
,
Rupa Kumar Kolli
, and
Arun Kumar

Abstract

As climate change accelerates, societies and climate-sensitive socioeconomic sectors cannot continue to rely on the past as a guide to possible future climate hazards. Operational decadal predictions offer the potential to inform current adaptation and increase resilience by filling the important gap between seasonal forecasts and climate projections. The World Meteorological Organization (WMO) has recognized this and in 2017 established the WMO Lead Centre for Annual to Decadal Climate Predictions (shortened to “Lead Centre” below), which annually provides a large multimodel ensemble of predictions covering the next 5 years. This international collaboration produces a prediction that is more skillful and useful than any single center can achieve. One of the main outputs of the Lead Centre is the Global Annual to Decadal Climate Update (GADCU), a consensus forecast based on these predictions. This update includes maps showing key variables, discussion on forecast skill, and predictions of climate indices such as the global mean near-surface temperature and Atlantic multidecadal variability. it also estimates the probability of the global mean temperature exceeding 1.5°C above preindustrial levels for at least 1 year in the next 5 years, which helps policy-makers understand how closely the world is approaching this goal of the Paris Agreement. This paper, written by the authors of the GADCU, introduces the GADCU, presents its key outputs, and briefly discusses its role in providing vital climate information for society now and in the future.

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