Search Results

You are looking at 11 - 20 of 21 items for

  • Author or Editor: F. K. Li x
  • Refine by Access: All Content x
Clear All Modify Search
Gerhard Theurich
,
C. DeLuca
,
T. Campbell
,
F. Liu
,
K. Saint
,
M. Vertenstein
,
J. Chen
,
R. Oehmke
,
J. Doyle
,
T. Whitcomb
,
A. Wallcraft
,
M. Iredell
,
T. Black
,
A. M. Da Silva
,
T. Clune
,
R. Ferraro
,
P. Li
,
M. Kelley
,
I. Aleinov
,
V. Balaji
,
N. Zadeh
,
R. Jacob
,
B. Kirtman
,
F. Giraldo
,
D. McCarren
,
S. Sandgathe
,
S. Peckham
, and
R. Dunlap IV

Abstract

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open-source terms or to credentialed users.

The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the United States. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multiagency development of coupled modeling systems; controlled experimentation and testing; and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NAVGEM), the Hybrid Coordinate Ocean Model (HYCOM), and the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model.

Full access
H. W. Barker
,
G. L. Stephens
,
P. T. Partain
,
J. W. Bergman
,
B. Bonnel
,
K. Campana
,
E. E. Clothiaux
,
S. Clough
,
S. Cusack
,
J. Delamere
,
J. Edwards
,
K. F. Evans
,
Y. Fouquart
,
S. Freidenreich
,
V. Galin
,
Y. Hou
,
S. Kato
,
J. Li
,
E. Mlawer
,
J.-J. Morcrette
,
W. O'Hirok
,
P. Räisänen
,
V. Ramaswamy
,
B. Ritter
,
E. Rozanov
,
M. Schlesinger
,
K. Shibata
,
P. Sporyshev
,
Z. Sun
,
M. Wendisch
,
N. Wood
, and
F. Yang

Abstract

The primary purpose of this study is to assess the performance of 1D solar radiative transfer codes that are used currently both for research and in weather and climate models. Emphasis is on interpretation and handling of unresolved clouds. Answers are sought to the following questions: (i) How well do 1D solar codes interpret and handle columns of information pertaining to partly cloudy atmospheres? (ii) Regardless of the adequacy of their assumptions about unresolved clouds, do 1D solar codes perform as intended?

One clear-sky and two plane-parallel, homogeneous (PPH) overcast cloud cases serve to elucidate 1D model differences due to varying treatments of gaseous transmittances, cloud optical properties, and basic radiative transfer. The remaining four cases involve 3D distributions of cloud water and water vapor as simulated by cloud-resolving models. Results for 25 1D codes, which included two line-by-line (LBL) models (clear and overcast only) and four 3D Monte Carlo (MC) photon transport algorithms, were submitted by 22 groups. Benchmark, domain-averaged irradiance profiles were computed by the MC codes. For the clear and overcast cases, all MC estimates of top-of-atmosphere albedo, atmospheric absorptance, and surface absorptance agree with one of the LBL codes to within ±2%. Most 1D codes underestimate atmospheric absorptance by typically 15–25 W m–2 at overhead sun for the standard tropical atmosphere regardless of clouds.

Depending on assumptions about unresolved clouds, the 1D codes were partitioned into four genres: (i) horizontal variability, (ii) exact overlap of PPH clouds, (iii) maximum/random overlap of PPH clouds, and (iv) random overlap of PPH clouds. A single MC code was used to establish conditional benchmarks applicable to each genre, and all MC codes were used to establish the full 3D benchmarks. There is a tendency for 1D codes to cluster near their respective conditional benchmarks, though intragenre variances typically exceed those for the clear and overcast cases. The majority of 1D codes fall into the extreme category of maximum/random overlap of PPH clouds and thus generally disagree with full 3D benchmark values. Given the fairly limited scope of these tests and the inability of any one code to perform extremely well for all cases begs the question that a paradigm shift is due for modeling 1D solar fluxes for cloudy atmospheres.

Full access
Chidong Zhang
,
Aaron F. Levine
,
Muyin Wang
,
Chelle Gentemann
,
Calvin W. Mordy
,
Edward D. Cokelet
,
Philip A. Browne
,
Qiong Yang
,
Noah Lawrence-Slavas
,
Christian Meinig
,
Gregory Smith
,
Andy Chiodi
,
Dongxiao Zhang
,
Phyllis Stabeno
,
Wanqiu Wang
,
Hong-Li Ren
,
K. Andrew Peterson
,
Silvio N. Figueroa
,
Michael Steele
,
Neil P. Barton
,
Andrew Huang
, and
Hyun-Cheol Shin

Abstract

Observations from uncrewed surface vehicles (saildrones) in the Bering, Chukchi, and Beaufort Seas during June–September 2019 were used to evaluate initial conditions and forecasts with lead times up to 10 days produced by eight operational numerical weather prediction centers. Prediction error behaviors in pressure and wind are found to be different from those in temperature and humidity. For example, errors in surface pressure were small in short-range (<6 days) forecasts, but they grew rapidly with increasing lead time beyond 6 days. Non-weighted multimodel means outperformed all individual models approaching a 10-day forecast lead time. In contrast, errors in surface air temperature and relative humidity could be large in initial conditions and remained large through 10-day forecasts without much growth, and non-weighted multimodel means did not outperform all individual models. These results following the tracks of the mobile platforms are consistent with those at a fixed location. Large errors in initial condition of sea surface temperature (SST) resulted in part from the unusual Arctic surface warming in 2019 not captured by data assimilation systems used for model initialization. These errors in SST led to large initial and prediction errors in surface air temperature. Our results suggest that improving predictions of surface conditions over the Arctic Ocean requires enhanced in situ observations and better data assimilation capability for more accurate initial conditions as well as better model physics. Numerical predictions of Arctic atmospheric conditions may continue to suffer from large errors if they do not fully capture the large SST anomalies related to Arctic warming.

Full access
S. Pawson
,
K. Kodera
,
K. Hamilton
,
T. G. Shepherd
,
S. R. Beagley
,
B. A. Boville
,
J. D. Farrara
,
T. D. A. Fairlie
,
A. Kitoh
,
W. A. Lahoz
,
U. Langematz
,
E. Manzini
,
D. H. Rind
,
A. A. Scaife
,
K. Shibata
,
P. Simon
,
R. Swinbank
,
L. Takacs
,
R. J. Wilson
,
J. A. Al-Saadi
,
M. Amodei
,
M. Chiba
,
L. Coy
,
J. de Grandpré
,
R. S. Eckman
,
M. Fiorino
,
W. L. Grose
,
H. Koide
,
J. N. Koshyk
,
D. Li
,
J. Lerner
,
J. D. Mahlman
,
N. A. McFarlane
,
C. R. Mechoso
,
A. Molod
,
A. O'Neill
,
R. B. Pierce
,
W. J. Randel
,
R. B. Rood
, and
F. Wu

To investigate the effects of the middle atmosphere on climate, the World Climate Research Programme is supporting the project “Stratospheric Processes and their Role in Climate” (SPARC). A central theme of SPARC, to examine model simulations of the coupled troposphere–middle atmosphere system, is being performed through the initiative called GRIPS (GCM-Reality Intercomparison Project for SPARC). In this paper, an overview of the objectives of GRIPS is given. Initial activities include an assessment of the performance of middle atmosphere climate models, and preliminary results from this evaluation are presented here. It is shown that although all 13 models evaluated represent most major features of the mean atmospheric state, there are deficiencies in the magnitude and location of the features, which cannot easily be traced to the formulation (resolution or the parameterizations included) of the models. Most models show a cold bias in all locations, apart from the tropical tropopause region where they can be either too warm or too cold. The strengths and locations of the major jets are often misrepresented in the models. Looking at three-dimensional fields reveals, for some models, more severe deficiencies in the magnitude and positioning of the dominant structures (such as the Aleutian high in the stratosphere), although undersampling might explain some of these differences from observations. All the models have shortcomings in their simulations of the present-day climate, which might limit the accuracy of predictions of the climate response to ozone change and other anomalous forcing.

Full access
Neal Butchart
,
I. Cionni
,
V. Eyring
,
T. G. Shepherd
,
D. W. Waugh
,
H. Akiyoshi
,
J. Austin
,
C. Brühl
,
M. P. Chipperfield
,
E. Cordero
,
M. Dameris
,
R. Deckert
,
S. Dhomse
,
S. M. Frith
,
R. R. Garcia
,
A. Gettelman
,
M. A. Giorgetta
,
D. E. Kinnison
,
F. Li
,
E. Mancini
,
C. McLandress
,
S. Pawson
,
G. Pitari
,
D. A. Plummer
,
E. Rozanov
,
F. Sassi
,
J. F. Scinocca
,
K. Shibata
,
B. Steil
, and
W. Tian

Abstract

The response of stratospheric climate and circulation to increasing amounts of greenhouse gases (GHGs) and ozone recovery in the twenty-first century is analyzed in simulations of 11 chemistry–climate models using near-identical forcings and experimental setup. In addition to an overall global cooling of the stratosphere in the simulations (0.59 ± 0.07 K decade−1 at 10 hPa), ozone recovery causes a warming of the Southern Hemisphere polar lower stratosphere in summer with enhanced cooling above. The rate of warming correlates with the rate of ozone recovery projected by the models and, on average, changes from 0.8 to 0.48 K decade−1 at 100 hPa as the rate of recovery declines from the first to the second half of the century. In the winter northern polar lower stratosphere the increased radiative cooling from the growing abundance of GHGs is, in most models, balanced by adiabatic warming from stronger polar downwelling. In the Antarctic lower stratosphere the models simulate an increase in low temperature extremes required for polar stratospheric cloud (PSC) formation, but the positive trend is decreasing over the twenty-first century in all models. In the Arctic, none of the models simulates a statistically significant increase in Arctic PSCs throughout the twenty-first century. The subtropical jets accelerate in response to climate change and the ozone recovery produces a westward acceleration of the lower-stratospheric wind over the Antarctic during summer, though this response is sensitive to the rate of recovery projected by the models. There is a strengthening of the Brewer–Dobson circulation throughout the depth of the stratosphere, which reduces the mean age of air nearly everywhere at a rate of about 0.05 yr decade−1 in those models with this diagnostic. On average, the annual mean tropical upwelling in the lower stratosphere (∼70 hPa) increases by almost 2% decade−1, with 59% of this trend forced by the parameterized orographic gravity wave drag in the models. This is a consequence of the eastward acceleration of the subtropical jets, which increases the upward flux of (parameterized) momentum reaching the lower stratosphere in these latitudes.

Full access
Ben P. Kirtman
,
Dughong Min
,
Johnna M. Infanti
,
James L. Kinter III
,
Daniel A. Paolino
,
Qin Zhang
,
Huug van den Dool
,
Suranjana Saha
,
Malaquias Pena Mendez
,
Emily Becker
,
Peitao Peng
,
Patrick Tripp
,
Jin Huang
,
David G. DeWitt
,
Michael K. Tippett
,
Anthony G. Barnston
,
Shuhua Li
,
Anthony Rosati
,
Siegfried D. Schubert
,
Michele Rienecker
,
Max Suarez
,
Zhao E. Li
,
Jelena Marshak
,
Young-Kwon Lim
,
Joseph Tribbia
,
Kathleen Pegion
,
William J. Merryfield
,
Bertrand Denis
, and
Eric F. Wood

The recent U.S. National Academies report, Assessment of Intraseasonal to Interannual Climate Prediction and Predictability, was unequivocal in recommending the need for the development of a North American Multimodel Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users.

The multimodel ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation and has proven to produce better prediction quality (on average) than any single model ensemble. This multimodel approach is the basis for several international collaborative prediction research efforts and an operational European system, and there are numerous examples of how this multimodel ensemble approach yields superior forecasts compared to any single model.

Based on two NOAA Climate Test bed (CTB) NMME workshops (18 February and 8 April 2011), a collaborative and coordinated implementation strategy for a NMME prediction system has been developed and is currently delivering real-time seasonal-to-interannual predictions on the NOAA Climate Prediction Center (CPC) operational schedule. The hindcast and real-time prediction data are readily available (e.g., http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/) and in graphical format from CPC (www.cpc.ncep.noaa.gov/products/NMME/). Moreover, the NMME forecast is already currently being used as guidance for operational forecasters. This paper describes the new NMME effort, and presents an overview of the multimodel forecast quality and the complementary skill associated with individual models.

Full access
P. M. Ruti
,
S. Somot
,
F. Giorgi
,
C. Dubois
,
E. Flaounas
,
A. Obermann
,
A. Dell’Aquila
,
G. Pisacane
,
A. Harzallah
,
E. Lombardi
,
B. Ahrens
,
N. Akhtar
,
A. Alias
,
T. Arsouze
,
R. Aznar
,
S. Bastin
,
J. Bartholy
,
K. Béranger
,
J. Beuvier
,
S. Bouffies-Cloché
,
J. Brauch
,
W. Cabos
,
S. Calmanti
,
J.-C. Calvet
,
A. Carillo
,
D. Conte
,
E. Coppola
,
V. Djurdjevic
,
P. Drobinski
,
A. Elizalde-Arellano
,
M. Gaertner
,
P. Galàn
,
C. Gallardo
,
S. Gualdi
,
M. Goncalves
,
O. Jorba
,
G. Jordà
,
B. L’Heveder
,
C. Lebeaupin-Brossier
,
L. Li
,
G. Liguori
,
P. Lionello
,
D. Maciàs
,
P. Nabat
,
B. Önol
,
B. Raikovic
,
K. Ramage
,
F. Sevault
,
G. Sannino
,
M. V. Struglia
,
A. Sanna
,
C. Torma
, and
V. Vervatis

Abstract

The Mediterranean is expected to be one of the most prominent and vulnerable climate change “hotspots” of the twenty-first century, and the physical mechanisms underlying this finding are still not clear. Furthermore, complex interactions and feedbacks involving ocean–atmosphere–land–biogeochemical processes play a prominent role in modulating the climate and environment of the Mediterranean region on a range of spatial and temporal scales. Therefore, it is critical to provide robust climate change information for use in vulnerability–impact–adaptation assessment studies considering the Mediterranean as a fully coupled environmental system. The Mediterranean Coordinated Regional Downscaling Experiment (Med-CORDEX) initiative aims at coordinating the Mediterranean climate modeling community toward the development of fully coupled regional climate simulations, improving all relevant components of the system from atmosphere and ocean dynamics to land surface, hydrology, and biogeochemical processes. The primary goals of Med-CORDEX are to improve understanding of past climate variability and trends and to provide more accurate and reliable future projections, assessing in a quantitative and robust way the added value of using high-resolution and coupled regional climate models. The coordination activities and the scientific outcomes of Med-CORDEX can produce an important framework to foster the development of regional Earth system models in several key regions worldwide.

Full access
G. C Johnson
,
R Lumpkin
,
C Atkinson
,
Tiago Biló
,
Tim Boyer
,
Francis Bringas
,
Brendan R. Carter
,
Ivona Cetinić
,
Don P. Chambers
,
Duo Chan
,
Lijing Cheng
,
Leah Chomiak
,
Meghan F. Cronin
,
Shenfu Dong
,
Richard A. Feely
,
Bryan A. Franz
,
Meng Gao
,
Jay Garg
,
John Gilson
,
Gustavo Goni
,
Benjamin D. Hamlington
,
W. Hobbs
,
Zeng-Zhen Hu
,
Boyin Huang
,
Masayoshi Ishii
,
Svetlana Jevrejeva
,
W. Johns
,
Peter Landschützer
,
Matthias Lankhorst
,
Eric Leuliette
,
Ricardo Locarnini
,
John M. Lyman
,
Michael J. McPhaden
,
Mark A. Merrifield
,
Alexey Mishonov
,
Gary T. Mitchum
,
Ben I. Moat
,
Ivan Mrekaj
,
R. Steven Nerem
,
Sarah G. Purkey
,
Bo Qiu
,
James Reagan
,
Katsunari Sato
,
Claudia Schmid
,
Jonathan D. Sharp
,
David A. Siegel
,
David A. Smeed
,
Paul W. Stackhouse Jr.
,
William Sweet
,
Philip R. Thompson
,
Joaquin A. Triñanes
,
Denis L. Volkov
,
Rik Wanninkhof
,
Caihong Wen
,
Toby K. Westberry
,
Matthew J. Widlansky
,
J. Willis
,
Ping-Ping Xie
,
Xungang Yin
,
Huai-min Zhang
,
Li Zhang
,
Jessicca Allen
,
Amy V. Camper
,
Bridgette O. Haley
,
Gregory Hammer
,
S. Elizabeth Love-Brotak
,
Laura Ohlmann
,
Lukas Noguchi
,
Deborah B. Riddle
, and
Sara W. Veasey
Open access
Peter Bissolli
,
Catherine Ganter
,
Tim Li
,
Ademe Mekonnen
,
Ahira Sánchez-Lugo
,
Eric J. Alfaro
,
Lincoln M. Alves
,
Jorge A. Amador
,
B. Andrade
,
Francisco Argeñalso
,
P. Asgarzadeh
,
Julian Baez
,
Reuben Barakiza
,
M. Yu. Bardin
,
Mikhail Bardin
,
Oliver Bochníček
,
Brandon Bukunt
,
Blanca Calderón
,
Jayaka D. Campbell
,
Elise Chandler
,
Ladislaus Chang’a
,
Vincent Y. S. Cheng
,
Leonardo A. Clarke
,
Kris Correa
,
Catalina Cortés
,
Felipe Costa
,
A.P.M.A. Cunha
,
Mesut Demircan
,
K. R. Dhurmea
,
A. Diawara
,
Sarah Diouf
,
Dashkhuu Dulamsuren
,
M. ElKharrim
,
Jhan-Carlo Espinoza
,
A. Fazl-Kazem
,
Chris Fenimore
,
Steven Fuhrman
,
Karin Gleason
,
Charles “Chip” P. Guard
,
Samson Hagos
,
Mizuki Hanafusa
,
H. R. Hasannezhad
,
Richard R. Heim Jr.
,
Hugo G. Hidalgo
,
J. A. Ijampy
,
Gyo Soon Im
,
Annie C. Joseph
,
G. Jumaux
,
K. R. Kabidi
,
P-H. Kamsu-Tamo
,
John Kennedy
,
Valentina Khan
,
Mai Van Khiem
,
Philemon King’uza
,
Natalia N. Korshunova
,
A. C. Kruger
,
Hoang Phuc Lam
,
Mark A. Lander
,
Waldo Lavado-Casimiro
,
Tsz-Cheung Lee
,
Kinson H. Y. Leung
,
Gregor Macara
,
Jostein Mamen
,
José A. Marengo
,
Charlotte McBride
,
Noelia Misevicius
,
Aurel Moise
,
Jorge Molina-Carpio
,
Natali Mora
,
Awatif E. Mostafa
,
Habiba Mtongori
,
Charles Mutai
,
O. Ndiaye
,
Juan José Nieto
,
Latifa Nyembo
,
Patricia Nying’uro
,
Xiao Pan
,
Reynaldo Pascual Ramírez
,
David Phillips
,
Brad Pugh
,
Madhavan Rajeevan
,
M. L. Rakotonirina
,
Andrea M. Ramos
,
M. Robjhon
,
Camino Rodriguez
,
Guisado Rodriguez
,
Josyane Ronchail
,
Benjamin Rösner
,
Roberto Salinas
,
Hirotaka Sato
,
Hitoshi Sato
,
Amal Sayouri
,
Joseph Sebaziga
,
Serhat Sensoy
,
Sandra Spillane
,
Katja Trachte
,
Gerard van der Schrier
,
F. Sima
,
Adam Smith
,
Jacqueline M. Spence
,
O. P. Sreejith
,
A. K. Srivastava
,
José L. Stella
,
Kimberly A. Stephenson
,
Tannecia S. Stephenson
,
S. Supari
,
Sahar Tajbakhsh-Mosalman
,
Gerard Tamar
,
Michael A. Taylor
,
Asaminew Teshome
,
Wassila M. Thiaw
,
Skie Tobin
,
Adrian R. Trotman
,
Cedric J. Van Meerbeeck
,
A. Vazifeh
,
Shunya Wakamatsu
,
Wei Wang
,
Fei Xin
,
F. Zeng
,
Peiqun Zhang
, and
Zhiwei Zhu
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