Results 111 to 120 of about 7,780 (201)

Why April Stands Out: Monthly Impacts of Internal Variability on Arctic Amplification

Journal of Geophysical Research: Atmospheres, Volume 131, Issue 19, 16 October 2026.
Abstract Observed Arctic amplification (AA), defined as the ratio of Arctic‐mean to global‐mean surface air temperature (SAT) trends, peaks in April, a feature not captured by climate models. Here, we quantify the impact of internal variability on Arctic‐mean SAT trends in March, April, and May from 1980 to 2022 using multiple approaches, including ...
Skylar Gale, Qiang Fu, Hailong Wang, Edward Blanchard‐Wrigglesworth, Muyin Wang, Ash Gilbert, Aodhan Sweeney, Stephen Po‐Chedley   +7 more
wiley   +1 more source

Extreme temperature events reduced carbon uptake of a boreal forest ecosystem in Northeast China: Evidence from an 11-year eddy covariance observation. [PDF]

Front Plant Sci, 2023
Yan Y, Zhou L, Zhou G, Wang Y, Song J, Zhang S, Zhou M.   +6 more
europepmc   +1 more source

Long‐Term Ocular Outcomes of Dupilumab in Atopic Dermatitis: Results From the BioDay Registry

Clinical and Translational Allergy, Volume 16, Issue 10, October 2026.
ABSTRACT Background Dupilumab‐associated ocular surface disease (DAOSD) is the most reported side effect in dupilumab‐treated atopic dermatitis (AD) patients. We investigated the effect of long‐term dupilumab treatment on ocular surface disease (OSD), conjunctival goblet cells (GCs), and tear fluid dupilumab levels and proteins.
Nienke Veldhuis, Roselie E. Achten, Chantal M. van Luijk, Marlot M. van der Wal, Constance F. den Hartog Jager, Nicolaas P. A. Zuithoff, Mohsin El Amrani, Edward F. Knol, Femke van Wijk, Marlies de Graaf, Inge M. Haeck, Mor M. Dickman, Marjolein S. de Bruin‐Weller   +12 more
wiley   +1 more source

A decade of CO₂ flux measured by the eddy covariance method including the COVID-19 pandemic period in an urban center in Sakai, Japan. [PDF]

Environ Pollut, 2022
Ueyama M, Takano T.
europepmc   +1 more source

From Soil to Canopy: Using Moisture Data From Soil and Tree Sensors to Predict Live Fuel Moisture and Guide Forest Management in a Mediterranean Coastal Woodland

Ecohydrology, Volume 19, Issue 7, October/November 2026.
ABSTRACT Ecosystem response to forest management and disturbance is governed by many factors and their interactions. This has historically made it difficult for practitioners to reach consensus on ideal management prescriptions and restoration activities.
Michelle Stern, Ryan Ferrell, Lorraine Flint, James Thorne   +3 more
wiley   +1 more source

Eddy Covariance Theory: A Review. [PDF]

Glob Chang Biol
Wood JD, Gu L, Schreiner-McGraw AP.
europepmc   +1 more source

A 7‐Year Eddy Covariance Dataset of the Energy, Water Vapour and Carbon Dioxide Fluxes Observed in a Siberian Dwarf Pine Ecosystem

Geoscience Data Journal, Volume 13, Issue 4, October 2026.
To clarify the role of alpine ecosystems in water and carbon cycling, we measured eddy‐covariance fluxes in a Siberian dwarf pine ecosystem in the Japanese Alps. The quality of the flux data was assessed using micrometeorological criteria, and data gaps were filled using a random forest regression approach.
Hiroki Iwata, Ryo Sato, Naoki Makita, Hajime Kobayashi, Hiroyuki Oguma   +4 more
wiley   +1 more source

Spatial Decomposition of Eddy Covariance Fluxes: The FLUGS Framework. [PDF]

Glob Chang Biol
Schlutow M, Chew R, Göckede M.
europepmc   +1 more source

Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. [PDF]

Sci Data, 2021
Pastorello G, Trotta C, Canfora E, Chu H, Christianson D, Cheah YW, Poindexter C, Chen J, Elbashandy A, Humphrey M, Isaac P, Polidori D, Reichstein M, Ribeca A, van Ingen C, Vuichard N, Zhang L, Amiro B, Ammann C, Arain MA, Ardö J, Arkebauer T, Arndt SK, Arriga N, Aubinet M, Aurela M, Baldocchi D, Barr A, Beamesderfer E, Marchesini LB, Bergeron O, Beringer J, Bernhofer C, Berveiller D, Billesbach D, Black TA, Blanken PD, Bohrer G, Boike J, Bolstad PV, Bonal D, Bonnefond JM, Bowling DR, Bracho R, Brodeur J, Brümmer C, Buchmann N, Burban B, Burns SP, Buysse P, Cale P, Cavagna M, Cellier P, Chen S, Chini I, Christensen TR, Cleverly J, Collalti A, Consalvo C, Cook BD, Cook D, Coursolle C, Cremonese E, Curtis PS, D'Andrea E, da Rocha H, Dai X, Davis KJ, De Cinti B, de Grandcourt A, De Ligne A, De Oliveira RC, Delpierre N, Desai AR, Di Bella CM, di Tommasi P, Dolman H, Domingo F, Dong G, Dore S, Duce P, Dufrêne E, Dunn A, Dušek J, Eamus D, Eichelmann U, ElKhidir HAM, Eugster W, Ewenz CM, Ewers B, Famulari D, Fares S, Feigenwinter I, Feitz A, Fensholt R, Filippa G, Fischer M, Frank J, Galvagno M, Gharun M, Gianelle D, Gielen B, Gioli B, Gitelson A, Goded I, Goeckede M, Goldstein AH, Gough CM, Goulden ML, Graf A, Griebel A, Gruening C, Grünwald T, Hammerle A, Han S, Han X, Hansen BU, Hanson C, Hatakka J, He Y, Hehn M, Heinesch B, Hinko-Najera N, Hörtnagl L, Hutley L, Ibrom A, Ikawa H, Jackowicz-Korczynski M, Janouš D, Jans W, Jassal R, Jiang S, Kato T, Khomik M, Klatt J, Knohl A, Knox S, Kobayashi H, Koerber G, Kolle O, Kosugi Y, Kotani A, Kowalski A, Kruijt B, Kurbatova J, Kutsch WL, Kwon H, Launiainen S, Laurila T, Law B, Leuning R, Li Y, Liddell M, Limousin JM, Lion M, Liska AJ, Lohila A, López-Ballesteros A, López-Blanco E, Loubet B, Loustau D, Lucas-Moffat A, Lüers J, Ma S, Macfarlane C, Magliulo V, Maier R, Mammarella I, Manca G, Marcolla B, Margolis HA, Marras S, Massman W, Mastepanov M, Matamala R, Matthes JH, Mazzenga F, McCaughey H, McHugh I, McMillan AMS, Merbold L, Meyer W, Meyers T, Miller SD, Minerbi S, Moderow U, Monson RK, Montagnani L, Moore CE, Moors E, Moreaux V, Moureaux C, Munger JW, Nakai T, Neirynck J, Nesic Z, Nicolini G, Noormets A, Northwood M, Nosetto M, Nouvellon Y, Novick K, Oechel W, Olesen JE, Ourcival JM, Papuga SA, Parmentier FJ, Paul-Limoges E, Pavelka M, Peichl M, Pendall E, Phillips RP, Pilegaard K, Pirk N, Posse G, Powell T, Prasse H, Prober SM, Rambal S, Rannik Ü, Raz-Yaseef N, Rebmann C, Reed D, de Dios VR, Restrepo-Coupe N, Reverter BR, Roland M, Sabbatini S, Sachs T, Saleska SR, Sánchez-Cañete EP, Sanchez-Mejia ZM, Schmid HP, Schmidt M, Schneider K, Schrader F, Schroder I, Scott RL, Sedlák P, Serrano-Ortíz P, Shao C, Shi P, Shironya I, Siebicke L, Šigut L, Silberstein R, Sirca C, Spano D, Steinbrecher R, Stevens RM, Sturtevant C, Suyker A, Tagesson T, Takanashi S, Tang Y, Tapper N, Thom J, Tomassucci M, Tuovinen JP, Urbanski S, Valentini R, van der Molen M, van Gorsel E, van Huissteden K, Varlagin A, Verfaillie J, Vesala T, Vincke C, Vitale D, Vygodskaya N, Walker JP, Walter-Shea E, Wang H, Weber R, Westermann S, Wille C, Wofsy S, Wohlfahrt G, Wolf S, Woodgate W, Li Y, Zampedri R, Zhang J, Zhou G, Zona D, Agarwal D, Biraud S, Torn M, Papale D.   +288 more
europepmc   +1 more source

QG‐Python: A Reproducible 1.5‐Layer Quasi‐Geostrophic Modelling Service With Direct Sparse Solvers, Spectral Stability Diagnostics and Filter Sensitivity Data

Geoscience Data Journal, Volume 13, Issue 4, October 2026.
QG‐Python is an open, reproducible 1.5‐layer quasi‐geostrophic modelling service whose published diagnostics show that the classical von Neumann bound underestimates the true Leapfrog stability limit by a factor of 13.7, and that the Robert–Asselin–Williams filter reduces kinetic energy and enstrophy biases from ~21% and ~45% to under 4%.
Elias D. Nino‐Ruiz
wiley   +1 more source