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H. N. Lee
and
J. K. Shi

Abstract

A pseudospectral method and its numerical solution algorithm for application to boundary layer problems in the atmosphere are presented. The method introduces the evaluation of a polynomial function when the solution is expressed as the sum of a periodic function and a polynomial function. The periodic function is then treated by Fourier expansion. In the paper, the accuracy of method has been demonstrated. Numerical results for a system of time dependent equations, modeling the atmospheric planetary boundary layer flow and nocturnal flow over terrain are encouraging. The method offers a promising alternative to finite-difference techniques.

Full access
R. W. Higgins
,
J-K. E. Schemm
,
W. Shi
, and
A. Leetmaa

Abstract

Three-day accumulations of precipitation for 2.5° long × 2.0° lat areas along the west coast of the United States are used to rank precipitation events. Extreme precipitation events (those above the 90th percentile) occur at all phases of the El Niño–Southern Oscillation (ENSO) cycle, but the largest fraction of these events (for the West Coast as a whole) occur during neutral winters just prior to the onset of El Niño. In the tropical Pacific these winters are characterized by enhanced activity on intraseasonal (roughly 20–60 day) timescales and by relatively small sea surface temperature anomalies compared to ENSO winters. For these winters, lagged composites are used to document a coherent relationship between the location of extreme precipitation events along the West Coast and the location of enhanced tropical convection on intraseasonal timescales. The evolution of the atmospheric circulation patterns associated with the extreme precipitation events is described and a physical mechanism relating tropical intraseasonal oscillations, the “pineapple express,” and the extreme precipitation events is proposed and illustrated.

Full access
J. J. Shi
,
W-K. Tao
,
T. Matsui
,
R. Cifelli
,
A. Hou
,
S. Lang
,
A. Tokay
,
N-Y. Wang
,
C. Peters-Lidard
,
G. Skofronick-Jackson
,
S. Rutledge
, and
W. Petersen

Abstract

One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold-season precipitation measurements in mid- and high latitudes through the use of high-frequency passive microwave radiometry. For this purpose, the Weather Research and Forecasting model (WRF) with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF–SDSU) to facilitate snowfall retrieval algorithms over land by providing a virtual cloud library and corresponding microwave brightness temperature measurements consistent with the GPM Microwave Imager (GMI). When this study was initiated, there were no prior published results using WRF at cloud-resolving resolution (1 km or finer) for high-latitude snow events. This study tested the Goddard cloud microphysics scheme in WRF for two different snowstorm events (a lake-effect event and a synoptic event between 20 and 22 January 2007) that took place over the Canadian CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Validation Project (C3VP) site in Ontario, Canada. The 24-h-accumulated snowfall predicted by WRF with the Goddard microphysics was comparable to that observed by the ground-based radar for both events. The model correctly predicted the onset and termination of both snow events at the Centre for Atmospheric Research Experiments site. The WRF simulations captured the basic cloud patterns as seen by the ground-based radar and satellite [i.e., CloudSat and Advanced Microwave Sounding Unit B (AMSU-B)] observations, including the snowband featured in the lake event. The results reveal that WRF was able to capture the cloud macrostructure reasonably well. Sensitivity tests utilizing both the “2ICE” (ice and snow) and “3ICE” (ice, snow, and graupel) options in the Goddard microphysical scheme were also conducted. The domain- and time-averaged cloud species profiles from the WRF simulations with both microphysical options show identical results (due to weak vertical velocities and therefore the absence of large precipitating liquid or high-density ice particles like graupel). Both microphysics options produced an appreciable amount of liquid water, and the model cloud liquid water profiles compared well to the in situ C3VP aircraft measurements when only grid points in the vicinity of the flight paths were considered. However, statistical comparisons between observed and simulated radar echoes show that the model tended to have a high bias of several reflectivity decibels (dBZ), which shows that additional research is needed to improve the current cloud microphysics scheme for the extremely cold environment in high latitudes, despite the fact that the simulated ice/liquid water contents may have been reasonable for both events. Future aircraft observations are also needed to verify the existence of graupel in high-latitude continental snow events.

Full access
D. A. Knopf
,
K. R. Barry
,
T. A. Brubaker
,
L. G. Jahl
,
K. A. Jankowski
,
J. Li
,
Y. Lu
,
L. W. Monroe
,
K. A. Moore
,
F. A. Rivera-Adorno
,
K. A. Sauceda
,
Y. Shi
,
J. M. Tomlin
,
H. S. K. Vepuri
,
P. Wang
,
N. N. Lata
,
E. J. T. Levin
,
J. M. Creamean
,
T. C. J. Hill
,
S. China
,
P. A. Alpert
,
R. C. Moffet
,
N. Hiranuma
,
R. C. Sullivan
,
A. M. Fridlind
,
M. West
,
N. Riemer
,
A. Laskin
,
P. J. DeMott
, and
X. Liu

Abstract

Prediction of ice formation in clouds presents one of the grand challenges in the atmospheric sciences. Immersion freezing initiated by ice-nucleating particles (INPs) is the dominant pathway of primary ice crystal formation in mixed-phase clouds, where supercooled water droplets and ice crystals coexist, with important implications for the hydrological cycle and climate. However, derivation of INP number concentrations from an ambient aerosol population in cloud-resolving and climate models remains highly uncertain. We conducted an aerosol–ice formation closure pilot study using a field-observational approach to evaluate the predictive capability of immersion freezing INPs. The closure study relies on collocated measurements of the ambient size-resolved and single-particle composition and INP number concentrations. The acquired particle data serve as input in several immersion freezing parameterizations, which are employed in cloud-resolving and climate models, for prediction of INP number concentrations. We discuss in detail one closure case study in which a front passed through the measurement site, resulting in a change of ambient particle and INP populations. We achieved closure in some circumstances within uncertainties, but we emphasize the need for freezing parameterization of potentially missing INP types and evaluation of the choice of parameterization to be employed. Overall, this closure pilot study aims to assess the level of parameter details and measurement strategies needed to achieve aerosol–ice formation closure. The closure approach is designed to accurately guide immersion freezing schemes in models, and ultimately identify the leading causes for climate model bias in INP predictions.

Full access
Yunpeng Shan
,
Eric M. Wilcox
,
Lan Gao
,
Lin Lin
,
David L. Mitchell
,
Yan Yin
,
Tianliang Zhao
,
Lei Zhang
,
Hongrong Shi
, and
Meng Gao

Abstract

Significant uncertainty lies in representing the rain droplet size distribution (DSD) in bulk cloud microphysics schemes and in the derivation of parameters of the function fit to the spectrum from the varying moments of a DSD. Here we evaluate the suitability of gamma distribution functions (GDFs) for fitting rain DSDs against observed disdrometer data. Results illustrate that double-parameter GDFs with prescribed or diagnosed positive spectral shape parameters μ fit rain DSDs better than the Marshall–Palmer distribution function (with μ = 0). The relative errors of fitting the spectrum moments (especially high-order moments) decrease by an order of magnitude [from O(102) to O(101)]. Moreover, introduction of a triple-parameter GDF with mathematically solved μ decreases the relative errors to O(100). Based on further investigation of potential combinations of the three prognostic moments for triple-moment cloud microphysical schemes, it is found that the GDF with parameters determined from predictions of the zeroth, third, and fourth moments (the 034 GDF) exhibits the best fit to rain DSDs compared to other moment combinations. Therefore, we suggest that the 034 prognostic moment group should replace the widely accepted 036 group to represent rain DSDs in triple-moment cloud microphysics schemes. An evaluation of the capability of GDFs to represent rain DSDs demonstrates that 034 GDF exhibits accurate fits to all observed DSDs except for rarely occurring extremely wide spectra from heavy precipitation and extremely narrow spectra from drizzle. The knowledge gained from this assessment can also be used to improve cloud microphysics retrieval schemes and data assimilation.

Free access
Longhui Li
,
Yingping Wang
,
Vivek K. Arora
,
Derek Eamus
,
Hao Shi
,
Jing Li
,
Lei Cheng
,
James Cleverly
,
T. Hajima
,
Duoying Ji
,
C. Jones
,
M. Kawamiya
,
Weiping Li
,
J. Tjiputra
,
A. Wiltshire
,
Lu Zhang
, and
Qiang Yu

Abstract

Water and carbon fluxes simulated by 12 Earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) over several recent decades were evaluated using three functional constraints that are derived from both model simulations, or four global datasets, and 736 site-year measurements. Three functional constraints are ecosystem water-use efficiency (WUE), light-use efficiency (LUE), and the partitioning of precipitation P into evapotranspiration (ET) and runoff based on the Budyko framework. Although values of these three constraints varied significantly with time scale and should be quite conservative if being averaged over multiple decades, the results showed that both WUE and LUE simulated by the ensemble mean of 12 ESMs were generally lower than the site measurements. Simulations by the ESMs were generally consistent with the broad pattern of energy-controlled ET under wet conditions and soil water-controlled ET under dry conditions, as described by the Budyko framework. However, the value of the parameter in the Budyko framework ω, obtained from fitting the Budyko curve to the ensemble model simulation (1.74), was larger than the best-fit value of ω to the observed data (1.28). Globally, the ensemble mean of multiple models, although performing better than any individual model simulations, still underestimated the observed WUE and LUE, and overestimated the ratio of ET to P, as a result of overestimation in ET and underestimation in gross primary production (GPP). The results suggest that future model development should focus on improving the algorithms of the partitioning of precipitation into ecosystem ET and runoff, and the coupling of water and carbon cycles for different land-use types.

Open access
William L. Smith Jr.
,
Christy Hansen
,
Anthony Bucholtz
,
Bruce E. Anderson
,
Matthew Beckley
,
Joseph G. Corbett
,
Richard I. Cullather
,
Keith M. Hines
,
Michelle Hofton
,
Seiji Kato
,
Dan Lubin
,
Richard H. Moore
,
Michal Segal Rosenhaimer
,
Jens Redemann
,
Sebastian Schmidt
,
Ryan Scott
,
Shi Song
,
John D. Barrick
,
J. Bryan Blair
,
David H. Bromwich
,
Colleen Brooks
,
Gao Chen
,
Helen Cornejo
,
Chelsea A. Corr
,
Seung-Hee Ham
,
A. Scott Kittelman
,
Scott Knappmiller
,
Samuel LeBlanc
,
Norman G. Loeb
,
Colin Miller
,
Louis Nguyen
,
Rabindra Palikonda
,
David Rabine
,
Elizabeth A. Reid
,
Jacqueline A. Richter-Menge
,
Peter Pilewskie
,
Yohei Shinozuka
,
Douglas Spangenberg
,
Paul Stackhouse
,
Patrick Taylor
,
K. Lee Thornhill
,
David van Gilst
, and
Edward Winstead

Abstract

The National Aeronautics and Space Administration (NASA)’s Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) acquired unique aircraft data on atmospheric radiation and sea ice properties during the critical late summer to autumn sea ice minimum and commencement of refreezing. The C-130 aircraft flew 15 missions over the Beaufort Sea between 4 and 24 September 2014. ARISE deployed a shortwave and longwave broadband radiometer (BBR) system from the Naval Research Laboratory; a Solar Spectral Flux Radiometer (SSFR) from the University of Colorado Boulder; the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) from the NASA Ames Research Center; cloud microprobes from the NASA Langley Research Center; and the Land, Vegetation and Ice Sensor (LVIS) laser altimeter system from the NASA Goddard Space Flight Center. These instruments sampled the radiant energy exchange between clouds and a variety of sea ice scenarios, including prior to and after refreezing began. The most critical and unique aspect of ARISE mission planning was to coordinate the flight tracks with NASA Cloud and the Earth’s Radiant Energy System (CERES) satellite sensor observations in such a way that satellite sensor angular dependence models and derived top-of-atmosphere fluxes could be validated against the aircraft data over large gridbox domains of order 100–200 km. This was accomplished over open ocean, over the marginal ice zone (MIZ), and over a region of heavy sea ice concentration, in cloudy and clear skies. ARISE data will be valuable to the community for providing better interpretation of satellite energy budget measurements in the Arctic and for process studies involving ice–cloud–atmosphere energy exchange during the sea ice transition period.

Full access
Yongkang Xue
,
Ismaila Diallo
,
Aaron A. Boone
,
Tandong Yao
,
Yang Zhang
,
Xubin Zeng
,
J. David Neelin
,
William K. M. Lau
,
Yan Pan
,
Ye Liu
,
Xiaoduo Pan
,
Qi Tang
,
Peter J. van Oevelen
,
Tomonori Sato
,
Myung-Seo Koo
,
Stefano Materia
,
Chunxiang Shi
,
Jing Yang
,
Constantin Ardilouze
,
Zhaohui Lin
,
Xin Qi
,
Tetsu Nakamura
,
Subodh K. Saha
,
Retish Senan
,
Yuhei Takaya
,
Hailan Wang
,
Hongliang Zhang
,
Mei Zhao
,
Hara Prasad Nayak
,
Qiuyu Chen
,
Jinming Feng
,
Michael A. Brunke
,
Tianyi Fan
,
Songyou Hong
,
Paulo Nobre
,
Daniele Peano
,
Yi Qin
,
Frederic Vitart
,
Shaocheng Xie
,
Yanling Zhan
,
Daniel Klocke
,
Ruby Leung
,
Xin Li
,
Michael Ek
,
Weidong Guo
,
Gianpaolo Balsamo
,
Qing Bao
,
Sin Chan Chou
,
Patricia de Rosnay
,
Yanluan Lin
,
Yuejian Zhu
,
Yun Qian
,
Ping Zhao
,
Jianping Tang
,
Xin-Zhong Liang
,
Jinkyu Hong
,
Duoying Ji
,
Zhenming Ji
,
Yuan Qiu
,
Shiori Sugimoto
,
Weicai Wang
,
Kun Yang
, and
Miao Yu

Abstract

Subseasonal-to-seasonal (S2S) precipitation prediction in boreal spring and summer months, which contains a significant number of high-signal events, is scientifically challenging and prediction skill has remained poor for years. Tibetan Plateau (TP) spring observed surface ­temperatures show a lag correlation with summer precipitation in several remote regions, but current global land–atmosphere coupled models are unable to represent this behavior due to significant errors in producing observed TP surface temperatures. To address these issues, the Global Energy and Water Exchanges (GEWEX) program launched the “Impact of Initialized Land Temperature and Snowpack on Subseasonal-to-Seasonal Prediction” (LS4P) initiative as a community effort to test the impact of land temperature in high-mountain regions on S2S prediction by climate models: more than 40 institutions worldwide are participating in this project. After using an innovative new land state initialization approach based on observed surface 2-m temperature over the TP in the LS4P experiment, results from a multimodel ensemble provide evidence for a causal relationship in the observed association between the Plateau spring land temperature and summer precipitation over several regions across the world through teleconnections. The influence is underscored by an out-of-phase oscillation between the TP and Rocky Mountain surface temperatures. This study reveals for the first time that high-mountain land temperature could be a substantial source of S2S precipitation predictability, and its effect is probably as large as ocean surface temperature over global “hotspot” regions identified here; the ensemble means in some “hotspots” produce more than 40% of the observed anomalies. This LS4P approach should stimulate more follow-on explorations.

Free access
Robert J. H. Dunn
,
F. Aldred
,
Nadine Gobron
,
John B. Miller
,
Kate M. Willett
,
M. Ades
,
Robert Adler
,
Richard, P. Allan
,
Rob Allan
,
J. Anderson
,
Anthony Argüez
,
C. Arosio
,
John A. Augustine
,
C. Azorin-Molina
,
J. Barichivich
,
H. E. Beck
,
Andreas Becker
,
Nicolas Bellouin
,
Angela Benedetti
,
David I. Berry
,
Stephen Blenkinsop
,
Olivier Bock
,
X. Bodin
,
Michael G. Bosilovich
,
Olivier Boucher
,
S. A. Buehler
,
B. Calmettes
,
Laura Carrea
,
Laura Castia
,
Hanne H. Christiansen
,
John R. Christy
,
E.-S. Chung
,
Melanie Coldewey-Egbers
,
Owen R. Cooper
,
Richard C. Cornes
,
Curt Covey
,
J.-F. Cretaux
,
M. Crotwell
,
Sean M. Davis
,
Richard A. M. de Jeu
,
Doug Degenstein
,
R. Delaloye
,
Larry Di Girolamo
,
Markus G. Donat
,
Wouter A. Dorigo
,
Imke Durre
,
Geoff S. Dutton
,
Gregory Duveiller
,
James W. Elkins
,
Vitali E. Fioletov
,
Johannes Flemming
,
Michael J. Foster
,
Stacey M. Frith
,
Lucien Froidevaux
,
J. Garforth
,
Matthew Gentry
,
S. K. Gupta
,
S. Hahn
,
Leopold Haimberger
,
Brad D. Hall
,
Ian Harris
,
D. L. Hemming
,
M. Hirschi
,
Shu-pen (Ben) Ho
,
F. Hrbacek
,
Daan Hubert
,
Dale F. Hurst
,
Antje Inness
,
K. Isaksen
,
Viju O. John
,
Philip D. Jones
,
Robert Junod
,
J. W. Kaiser
,
V. Kaufmann
,
A. Kellerer-Pirklbauer
,
Elizabeth C. Kent
,
R. Kidd
,
Hyungjun Kim
,
Z. Kipling
,
A. Koppa
,
B. M. Kraemer
,
D. P. Kratz
,
Xin Lan
,
Kathleen O. Lantz
,
D. Lavers
,
Norman G. Loeb
,
Diego Loyola
,
R. Madelon
,
Michael Mayer
,
M. F. McCabe
,
Tim R. McVicar
,
Carl A. Mears
,
Christopher J. Merchant
,
Diego G. Miralles
,
L. Moesinger
,
Stephen A. Montzka
,
Colin Morice
,
L. Mösinger
,
Jens Mühle
,
Julien P. Nicolas
,
Jeannette Noetzli
,
Ben Noll
,
J. O’Keefe
,
Tim J. Osborn
,
T. Park
,
A. J. Pasik
,
C. Pellet
,
Maury S. Pelto
,
S. E. Perkins-Kirkpatrick
,
G. Petron
,
Coda Phillips
,
S. Po-Chedley
,
L. Polvani
,
W. Preimesberger
,
D. G. Rains
,
W. J. Randel
,
Nick A. Rayner
,
Samuel Rémy
,
L. Ricciardulli
,
A. D. Richardson
,
David A. Robinson
,
Matthew Rodell
,
N. J. Rodríguez-Fernández
,
K.H. Rosenlof
,
C. Roth
,
A. Rozanov
,
T. Rutishäuser
,
Ahira Sánchez-Lugo
,
P. Sawaengphokhai
,
T. Scanlon
,
Verena Schenzinger
,
R. W. Schlegel
,
S. Sharma
,
Lei Shi
,
Adrian J. Simmons
,
Carolina Siso
,
Sharon L. Smith
,
B. J. Soden
,
Viktoria Sofieva
,
T. H. Sparks
,
Paul W. Stackhouse Jr.
,
Wolfgang Steinbrecht
,
Martin Stengel
,
Dimitri A. Streletskiy
,
Sunny Sun-Mack
,
P. Tans
,
S. J. Thackeray
,
E. Thibert
,
D. Tokuda
,
Kleareti Tourpali
,
Mari R. Tye
,
Ronald van der A
,
Robin van der Schalie
,
Gerard van der Schrier
,
M. van der Vliet
,
Guido R. van der Werf
,
A. Vance
,
Jean-Paul Vernier
,
Isaac J. Vimont
,
Holger Vömel
,
Russell S. Vose
,
Ray Wang
,
Markus Weber
,
David Wiese
,
Anne C. Wilber
,
Jeanette D. Wild
,
Takmeng Wong
,
R. Iestyn Woolway
,
Xinjia Zhou
,
Xungang Yin
,
Guangyu Zhao
,
Lin Zhao
,
Jerry R. Ziemke
,
Markus Ziese
, and
R. M. Zotta
Free access
M. Ades
,
R. Adler
,
Rob Allan
,
R. P. Allan
,
J. Anderson
,
Anthony Argüez
,
C. Arosio
,
J. A. Augustine
,
C. Azorin-Molina
,
J. Barichivich
,
J. Barnes
,
H. E. Beck
,
Andreas Becker
,
Nicolas Bellouin
,
Angela Benedetti
,
David I. Berry
,
Stephen Blenkinsop
,
Olivier. Bock
,
Michael G. Bosilovich
,
Olivier. Boucher
,
S. A. Buehler
,
Laura. Carrea
,
Hanne H. Christiansen
,
F. Chouza
,
John R. Christy
,
E.-S. Chung
,
Melanie Coldewey-Egbers
,
Gil P. Compo
,
Owen R. Cooper
,
Curt Covey
,
A. Crotwell
,
Sean M. Davis
,
Elvira de Eyto
,
Richard A. M de Jeu
,
B.V. VanderSat
,
Curtis L. DeGasperi
,
Doug Degenstein
,
Larry Di Girolamo
,
Martin T. Dokulil
,
Markus G. Donat
,
Wouter A. Dorigo
,
Imke Durre
,
Geoff S. Dutton
,
G. Duveiller
,
James W. Elkins
,
Vitali E. Fioletov
,
Johannes Flemming
,
Michael J. Foster
,
Richard A. Frey
,
Stacey M. Frith
,
Lucien Froidevaux
,
J. Garforth
,
S. K. Gupta
,
Leopold Haimberger
,
Brad D. Hall
,
Ian Harris
,
Andrew K Heidinger
,
D. L. Hemming
,
Shu-peng (Ben) Ho
,
Daan Hubert
,
Dale F. Hurst
,
I. Hüser
,
Antje Inness
,
K. Isaksen
,
Viju John
,
Philip D. Jones
,
J. W. Kaiser
,
S. Kelly
,
S. Khaykin
,
R. Kidd
,
Hyungiun Kim
,
Z. Kipling
,
B. M. Kraemer
,
D. P. Kratz
,
R. S. La Fuente
,
Xin Lan
,
Kathleen O. Lantz
,
T. Leblanc
,
Bailing Li
,
Norman G Loeb
,
Craig S. Long
,
Diego Loyola
,
Wlodzimierz Marszelewski
,
B. Martens
,
Linda May
,
Michael Mayer
,
M. F. McCabe
,
Tim R. McVicar
,
Carl A. Mears
,
W. Paul Menzel
,
Christopher J. Merchant
,
Ben R. Miller
,
Diego G. Miralles
,
Stephen A. Montzka
,
Colin Morice
,
Jens Mühle
,
R. Myneni
,
Julien P. Nicolas
,
Jeannette Noetzli
,
Tim J. Osborn
,
T. Park
,
A. Pasik
,
Andrew M. Paterson
,
Mauri S. Pelto
,
S. Perkins-Kirkpatrick
,
G. Pétron
,
C. Phillips
,
Bernard Pinty
,
S. Po-Chedley
,
L. Polvani
,
W. Preimesberger
,
M. Pulkkanen
,
W. J. Randel
,
Samuel Rémy
,
L. Ricciardulli
,
A. D. Richardson
,
L. Rieger
,
David A. Robinson
,
Matthew Rodell
,
Karen H. Rosenlof
,
Chris Roth
,
A. Rozanov
,
James A. Rusak
,
O. Rusanovskaya
,
T. Rutishäuser
,
Ahira Sánchez-Lugo
,
P. Sawaengphokhai
,
T. Scanlon
,
Verena Schenzinger
,
S. Geoffey Schladow
,
R. W Schlegel
,
Eawag Schmid, Martin
,
H. B. Selkirk
,
S. Sharma
,
Lei Shi
,
S. V. Shimaraeva
,
E. A. Silow
,
Adrian J. Simmons
,
C. A. Smith
,
Sharon L Smith
,
B. J. Soden
,
Viktoria Sofieva
,
T. H. Sparks
,
Paul W. Stackhouse Jr.
,
Wolfgang Steinbrecht
,
Dimitri A. Streletskiy
,
G. Taha
,
Hagen Telg
,
S. J. Thackeray
,
M. A. Timofeyev
,
Kleareti Tourpali
,
Mari R. Tye
,
Ronald J. van der A
,
Robin, VanderSat B.V. van der Schalie
,
Gerard van der SchrierW. Paul
,
Guido R. van der Werf
,
Piet Verburg
,
Jean-Paul Vernier
,
Holger Vömel
,
Russell S. Vose
,
Ray Wang
,
Shohei G. Watanabe
,
Mark Weber
,
Gesa A. Weyhenmeyer
,
David Wiese
,
Anne C. Wilber
,
Jeanette D. Wild
,
Takmeng Wong
,
R. Iestyn Woolway
,
Xungang Yin
,
Lin Zhao
,
Guanguo Zhao
,
Xinjia Zhou
,
Jerry R. Ziemke
, and
Markus Ziese
Free access