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Richard Essery
,
Nick Rutter
,
John Pomeroy
,
Robert Baxter
,
Manfred Stähli
,
David Gustafsson
,
Alan Barr
,
Paul Bartlett
, and
Kelly Elder

The Northern Hemisphere has large areas that are forested and seasonally snow covered. Compared with open areas, forest canopies strongly influence interactions between the atmosphere and snow on the ground by sheltering the snow from wind and solar radiation and by intercepting falling snow; these influences have important consequences for the meteorology, hydrology, and ecology of forests. Many of the land surface models used in meteorological and hydrological forecasting now include representations of canopy snow processes, but these have not been widely tested in comparison with observations. Phase 2 of the Snow Model Intercomparison Project (SnowMIP2) was therefore designed as an intercomparison of surface mass and energy balance simulations for snow in forested areas. Model forcing and calibration data for sites with paired forested and open plots were supplied to modeling groups. Participants in 11 countries contributed output from 33 models, and the results are published here for sites in Canada, the United States, and Switzerland. On average, the models perform fairly well in simulating snow accumulation and ablation, although there is a wide intermodal spread and a tendency to underestimate differences in snow mass between open and forested areas. Most models capture the large differences in surface albedos and temperatures between forest canopies and open snow well. There is, however, a strong tendency for models to underestimate soil temperature under snow, particularly for forest sites, and this would have large consequences for simulations of runoff and biological processes in the soil.

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Julie M. Thériault
,
Nicolas R. Leroux
,
Ronald E. Stewart
,
André Bertoncini
,
Stephen J. Déry
,
John W. Pomeroy
,
Hadleigh D. Thompson
,
Hilary Smith
,
Zen Mariani
,
Aurélie Desroches-Lapointe
,
Selina Mitchell
, and
Juris Almonte

Abstract

The Canadian Rockies are a triple-continental divide, whose high mountains are drained by major snow-fed and rain-fed rivers flowing to the Pacific, Atlantic, and Arctic Oceans. The objective of the April–June 2019 Storms and Precipitation Across the continental Divide Experiment (SPADE) was to determine the atmospheric processes producing precipitation on the eastern and western sides of the Canadian Rockies during springtime, a period when upslope events of variable phase dominate precipitation on the eastern slopes. To do so, three observing sites across the divide were instrumented with advanced meteorological sensors. During the 13 observed events, the western side recorded only 25% of the eastern side’s precipitation accumulation, rainfall occurred rather than snowfall, and skies were mainly clear. Moisture sources and amounts varied markedly between events. An atmospheric river landfall in California led to moisture flowing persistently northward and producing the longest duration of precipitation on both sides of the divide. Moisture from the continental interior always produced precipitation on the eastern side but only in specific conditions on the western side. Mainly slow-falling ice crystals, sometimes rimed, formed at higher elevations on the eastern side (>3 km MSL), were lifted, and subsequently drifted westward over the divide during nonconvective storms to produce rain at the surface on the western side. Overall, precipitation generally crossed the divide in the Canadian Rockies during specific spring-storm atmospheric conditions although amounts at the surface varied with elevation, condensate type, and local and large-scale flow fields.

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Cecile B. Menard
,
Richard Essery
,
Gerhard Krinner
,
Gabriele Arduini
,
Paul Bartlett
,
Aaron Boone
,
Claire Brutel-Vuilmet
,
Eleanor Burke
,
Matthias Cuntz
,
Yongjiu Dai
,
Bertrand Decharme
,
Emanuel Dutra
,
Xing Fang
,
Charles Fierz
,
Yeugeniy Gusev
,
Stefan Hagemann
,
Vanessa Haverd
,
Hyungjun Kim
,
Matthieu Lafaysse
,
Thomas Marke
,
Olga Nasonova
,
Tomoko Nitta
,
Masashi Niwano
,
John Pomeroy
,
Gerd Schädler
,
Vladimir A. Semenov
,
Tatiana Smirnova
,
Ulrich Strasser
,
Sean Swenson
,
Dmitry Turkov
,
Nander Wever
, and
Hua Yuan

Abstract

Twenty-seven models participated in the Earth System Model–Snow Model Intercomparison Project (ESM-SnowMIP), the most data-rich MIP dedicated to snow modeling. Our findings do not support the hypothesis advanced by previous snow MIPs: evaluating models against more variables and providing evaluation datasets extended temporally and spatially does not facilitate identification of key new processes requiring improvement to model snow mass and energy budgets, even at point scales. In fact, the same modeling issues identified by previous snow MIPs arose: albedo is a major source of uncertainty, surface exchange parameterizations are problematic, and individual model performance is inconsistent. This lack of progress is attributed partly to the large number of human errors that led to anomalous model behavior and to numerous resubmissions. It is unclear how widespread such errors are in our field and others; dedicated time and resources will be needed to tackle this issue to prevent highly sophisticated models and their research outputs from being vulnerable because of avoidable human mistakes. The design of and the data available to successive snow MIPs were also questioned. Evaluation of models against bulk snow properties was found to be sufficient for some but inappropriate for more complex snow models whose skills at simulating internal snow properties remained untested. Discussions between the authors of this paper on the purpose of MIPs revealed varied, and sometimes contradictory, motivations behind their participation. These findings started a collaborative effort to adapt future snow MIPs to respond to the diverse needs of the community.

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Diana Greenslade
,
Mark Hemer
,
Alex Babanin
,
Ryan Lowe
,
Ian Turner
,
Hannah Power
,
Ian Young
,
Daniel Ierodiaconou
,
Greg Hibbert
,
Greg Williams
,
Saima Aijaz
,
João Albuquerque
,
Stewart Allen
,
Michael Banner
,
Paul Branson
,
Steve Buchan
,
Andrew Burton
,
John Bye
,
Nick Cartwright
,
Amin Chabchoub
,
Frank Colberg
,
Stephanie Contardo
,
Francois Dufois
,
Craig Earl-Spurr
,
David Farr
,
Ian Goodwin
,
Jim Gunson
,
Jeff Hansen
,
David Hanslow
,
Mitchell Harley
,
Yasha Hetzel
,
Ron Hoeke
,
Nicole Jones
,
Michael Kinsela
,
Qingxiang Liu
,
Oleg Makarynskyy
,
Hayden Marcollo
,
Said Mazaheri
,
Jason McConochie
,
Grant Millar
,
Tim Moltmann
,
Neal Moodie
,
Joao Morim
,
Russel Morison
,
Jana Orszaghova
,
Charitha Pattiaratchi
,
Andrew Pomeroy
,
Roger Proctor
,
David Provis
,
Ruth Reef
,
Dirk Rijnsdorp
,
Martin Rutherford
,
Eric Schulz
,
Jake Shayer
,
Kristen Splinter
,
Craig Steinberg
,
Darrell Strauss
,
Greg Stuart
,
Graham Symonds
,
Karina Tarbath
,
Daniel Taylor
,
James Taylor
,
Darshani Thotagamuwage
,
Alessandro Toffoli
,
Alireza Valizadeh
,
Jonathan van Hazel
,
Guilherme Vieira da Silva
,
Moritz Wandres
,
Colin Whittaker
,
David Williams
,
Gundula Winter
,
Jiangtao Xu
,
Aihong Zhong
, and
Stefan Zieger
Full access
Diana Greenslade
,
Mark Hemer
,
Alex Babanin
,
Ryan Lowe
,
Ian Turner
,
Hannah Power
,
Ian Young
,
Daniel Ierodiaconou
,
Greg Hibbert
,
Greg Williams
,
Saima Aijaz
,
João Albuquerque
,
Stewart Allen
,
Michael Banner
,
Paul Branson
,
Steve Buchan
,
Andrew Burton
,
John Bye
,
Nick Cartwright
,
Amin Chabchoub
,
Frank Colberg
,
Stephanie Contardo
,
Francois Dufois
,
Craig Earl-Spurr
,
David Farr
,
Ian Goodwin
,
Jim Gunson
,
Jeff Hansen
,
David Hanslow
,
Mitchell Harley
,
Yasha Hetzel
,
Ron Hoeke
,
Nicole Jones
,
Michael Kinsela
,
Qingxiang Liu
,
Oleg Makarynskyy
,
Hayden Marcollo
,
Said Mazaheri
,
Jason McConochie
,
Grant Millar
,
Tim Moltmann
,
Neal Moodie
,
Joao Morim
,
Russel Morison
,
Jana Orszaghova
,
Charitha Pattiaratchi
,
Andrew Pomeroy
,
Roger Proctor
,
David Provis
,
Ruth Reef
,
Dirk Rijnsdorp
,
Martin Rutherford
,
Eric Schulz
,
Jake Shayer
,
Kristen Splinter
,
Craig Steinberg
,
Darrell Strauss
,
Greg Stuart
,
Graham Symonds
,
Karina Tarbath
,
Daniel Taylor
,
James Taylor
,
Darshani Thotagamuwage
,
Alessandro Toffoli
,
Alireza Valizadeh
,
Jonathan van Hazel
,
Guilherme Vieira da Silva
,
Moritz Wandres
,
Colin Whittaker
,
David Williams
,
Gundula Winter
,
Jiangtao Xu
,
Aihong Zhong
, and
Stefan Zieger

Abstract

The Australian marine research, industry, and stakeholder community has recently undertaken an extensive collaborative process to identify the highest national priorities for wind-waves research. This was undertaken under the auspices of the Forum for Operational Oceanography Surface Waves Working Group. The main steps in the process were first, soliciting possible research questions from the community via an online survey; second, reviewing the questions at a face-to-face workshop; and third, online ranking of the research questions by individuals. This process resulted in 15 identified priorities, covering research activities and the development of infrastructure. The top five priorities are 1) enhanced and updated nearshore and coastal bathymetry; 2) improved understanding of extreme sea states; 3) maintain and enhance the in situ buoy network; 4) improved data access and sharing; and 5) ensemble and probabilistic wave modeling and forecasting. In this paper, each of the 15 priorities is discussed in detail, providing insight into why each priority is important, and the current state of the art, both nationally and internationally, where relevant. While this process has been driven by Australian needs, it is likely that the results will be relevant to other marine-focused nations.

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