Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
Irvin, J; Zhou, S; McNicol, G; Lu, F; Liu, V; Fluet-Chouinard, E; Ouyang, Z; Knox, S. H; Lucas-Moffat, A; Trotta, C; Papale, D; Vitale, D; Mammarella, I; Alekseychik, P; Aurela, M; Avati, A; Baldocchi, D; Bansal, S; Bohrer, G; Campbell, D. I; Chen, J; Chu, H; Dalmagro, H. J; Delwiche, K. B; Desai, A. R; Euskirchen, E; Feron, S; Goeckede, M; Heimann, M; Helbig, M; Helfter, C; Hemes, K. S; Hirano, T; Iwata, H; Jurasinski, G; Kalhori A; Kondrich A; Lai D YF; Lohila A; Malhotra A; Merbold L; Mitra B; Ng A; Nilsson MB; Noormets A; Peichl M; Rey-Sanchez AC; Richardson AD; Runkle B RK; Schafer K VR; Sonnentag O; Stuart-Haentjens E; Sturtevant C; Ueyama M; Valach R; Vargas R; Vourlitis G L; Ward EJ; Wong GX; Zona D; Alberto MCR; Billesbach DP; Celis G; Dolman H; Friborg T; Fuchs K; Gogo S; Gondwe MJ; Goodrich JP; Gottschalk P; Hortnagl L; Jacotot A; Koebsch F; Kasak K; Maier R; Morin TH; Nemitz E; Oechel WC; Oikawa PY; Ono K; Sachs T; Sakabe A; Schuur EA; Shortt R; Sullivan RC; Szutu DJ; Tuittila ES; Varlagin A; Verfaillie JG; Wille C; Windham-Myers L; Poulter B; Jackson RB
Agricultural and Forest Meteorology, 2021年07月, 査読有り