Africa - Central Africa - Sahel Africa - South Asia - East Siberia Asia - Indonesia Asia - North Central Asia - South Central Asia and China Australia Europe Global - Land North America - Alaska and Northern Canada North America - Eastern United States North America - Southern Canada North America - Western United States South America - Amazon

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	139.
CFORCEERA5	[-]	151.		13.3	20.1	1.02		0.367	0.434	0.933	0.542
CRUJRA2024	[-]	132.		16.3	25.9	1.02		0.225	0.345	0.933	0.462
GSWP3V1	[-]	169.		30.7	35.9	0.983		0.00	0.358	0.937	0.413
RAWERA5	[-]	157.		14.3	21.6	0.00		0.322	0.405	1.00	0.533

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	153.
CFORCEERA5	[-]	183.		32.8	37.4	0.00		0.00	0.221	1.00	0.360
CRUJRA2024	[-]	179.		47.4	60.1	5.10		0.00	0.00	0.0631	0.0158
GSWP3V1	[-]	175.		21.8	34.9	1.02		0.00	0.00	0.933	0.233
RAWERA5	[-]	188.		40.5	44.0	1.02		0.00	0.228	0.933	0.347

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	200.
CFORCEERA5	[-]	206.		6.25	9.97	6.05		0.703	0.639	7.41e-05	0.495
CRUJRA2024	[-]	206.		6.37	32.5	2.98		0.698	0.00	0.515	0.303
GSWP3V1	[-]	209.		9.05	18.9	5.10		0.570	0.438	0.0631	0.378
RAWERA5	[-]	207.		6.80	16.4	6.05		0.677	0.412	7.41e-05	0.375

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	74.5
CFORCEERA5	[-]	65.9		-8.63	17.7	0.00		0.427	0.203	1.00	0.458
CRUJRA2024	[-]	61.2		-13.4	13.7	0.00		0.440	0.247	1.00	0.484
GSWP3V1	[-]	61.3		-13.2	19.1	0.508		0.403	0.175	0.966	0.430
RAWERA5	[-]	61.7		-12.8	13.4	0.00		0.478	0.255	1.00	0.497

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	176.
CFORCEERA5	[-]	161.		-14.4	17.7	0.00		0.314	0.645	1.00	0.651
CRUJRA2024	[-]	156.		-19.4	29.8	0.00		0.0776	0.246	1.00	0.392
GSWP3V1	[-]	162.		-13.6	19.2	0.00		0.356	0.517	1.00	0.597
RAWERA5	[-]	165.		-10.3	15.1	1.02		0.510	0.619	0.933	0.670

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	112.
CFORCEERA5	[-]	93.8		-19.8	18.1	0.00		0.00	0.266	1.00	0.383
CRUJRA2024	[-]	101.		-8.00	16.9	0.00		0.459	0.154	1.00	0.442
GSWP3V1	[-]	96.5		-16.4	20.6	0.00		0.00	0.135	1.00	0.317
RAWERA5	[-]	95.7		-21.5	19.3	0.00		0.00	0.266	1.00	0.383

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	129.
CFORCEERA5	[-]	136.		1.08	12.2	1.27		0.628	0.522	0.840	0.628
CRUJRA2024	[-]	145.		9.00	19.6	1.53		0.436	0.255	0.823	0.442
GSWP3V1	[-]	142.		6.87	16.3	1.27		0.549	0.407	0.840	0.551
RAWERA5	[-]	147.		13.0	18.4	1.28		0.231	0.412	0.840	0.473

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	193.
CFORCEERA5	[-]	192.		-0.592	13.0	0.490		0.479	0.538	0.946	0.625
CRUJRA2024	[-]	198.		4.55	21.6	0.445		0.419	0.318	0.949	0.501
GSWP3V1	[-]	188.		-5.22	17.7	0.489		0.425	0.410	0.954	0.550
RAWERA5	[-]	189.		-3.93	13.9	0.667		0.472	0.501	0.924	0.600

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	118.
CFORCEERA5	[-]	115.		-6.88	14.9	0.313		0.427	0.478	0.979	0.591
CRUJRA2024	[-]	127.		6.22	21.7	0.411		0.355	0.267	0.971	0.465
GSWP3V1	[-]	116.		-5.37	19.3	0.293		0.410	0.316	0.981	0.506
RAWERA5	[-]	118.		-3.12	15.0	0.332		0.482	0.463	0.978	0.597

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	140.
CFORCEERA5	[-]	136.		-4.58	14.1	0.495		0.481	0.495	0.954	0.606
CRUJRA2024	[-]	142.		1.13	21.4	0.593		0.438	0.257	0.946	0.475
GSWP3V1	[-]	136.		-5.40	18.6	0.438		0.454	0.339	0.958	0.523
RAWERA5	[-]	140.		-1.82	15.0	0.580		0.493	0.468	0.946	0.594

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	63.7
CFORCEERA5	[-]	68.6		9.10	13.0	0.508		0.468	0.462	0.966	0.589
CRUJRA2024	[-]	67.1		7.22	13.7	0.508		0.583	0.435	0.966	0.605
GSWP3V1	[-]	72.4		11.5	15.5	0.508		0.326	0.399	0.966	0.523
RAWERA5	[-]	65.7		8.18	10.5	0.508		0.503	0.531	0.966	0.633

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	137.
CFORCEERA5	[-]	131.		-6.66	12.8	0.734		0.562	0.505	0.945	0.629
CRUJRA2024	[-]	138.		-1.05	19.3	0.565		0.622	0.234	0.963	0.513
GSWP3V1	[-]	131.		-7.24	17.5	0.508		0.547	0.314	0.960	0.534
RAWERA5	[-]	138.		1.14	14.3	0.734		0.598	0.483	0.951	0.629

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	113.
CFORCEERA5	[-]	108.		-4.74	10.4	0.363		0.649	0.601	0.968	0.704
CRUJRA2024	[-]	111.		-0.874	16.9	0.508		0.712	0.288	0.966	0.564
GSWP3V1	[-]	107.		-5.82	15.8	0.436		0.605	0.365	0.954	0.572
RAWERA5	[-]	107.		-5.23	11.0	0.581		0.607	0.569	0.937	0.670

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	181.
CFORCEERA5	[-]	173.		-5.47	12.9	0.428		0.433	0.512	0.972	0.607
CRUJRA2024	[-]	165.		-13.3	22.8	0.803		0.351	0.188	0.947	0.419
GSWP3V1	[-]	169.		-9.37	16.7	0.107		0.440	0.368	0.993	0.542
RAWERA5	[-]	178.		0.209	15.1	0.535		0.432	0.468	0.965	0.583

	Download Data	Period Mean (original grids) [W m-2]		Bias [W m-2]	RMSE [W m-2]	Phase Shift [months]		Bias Score [1]	RMSE Score [1]	Seasonal Cycle Score [1]	Overall Score [1]
Benchmark	[-]	175.
CFORCEERA5	[-]	170.		-1.78	11.9	0.00		0.781	0.571	1.00	0.731
CRUJRA2024	[-]	168.		-0.995	18.2	0.00		0.342	0.376	1.00	0.523
GSWP3V1	[-]	174.		1.29	15.1	0.00		0.907	0.473	1.00	0.713
RAWERA5	[-]	168.		-4.22	16.4	0.508		0.745	0.410	0.966	0.633

Africa - Central Africa - Sahel Africa - South Asia - East Siberia Asia - Indonesia Asia - North Central Asia - South Central Asia and China Asia - Southeast Asia and India Asia - West Siberia Australia Europe Global - Land Middle East and Sahara North America - Alaska and Northern Canada North America - Central America North America - Eastern United States North America - Southern Canada North America - Western United States South America - Amazon South America - Southeast South America - Southwest Temporally integrated period mean Temporally integrated period mean bias Temporally integrated period mean bias score Temporally integrated period mean max month Temporally integrated mean phase shift Temporally integrated mean phase shift score Temporally integrated period mean rmse Temporally integrated period mean rmse score Spatially integrated regional mean cycle Spatially integrated regional mean detrended cycle Spatially integrated regional mean

  Title:

Fluxnet2015

  Version:

2015

  Institutions:

The Fluxnet Community

  Source:

Data downloaded from the Fluxnet community data portal https://fluxnet.org/data/download-data/

  History:

2024-05-21: Data downloaded

2025-01-30: Converted to netcdf using https://github.com/rubisco-sfa/ILAMB-Data/blob/master/Fluxnet2015/convert.py

  References:

Pastorello, Gilberto and Trotta, Carlo and Canfora, Eleonora and Chu, Housen and Christianson, Danielle and Cheah, You-Wei and Poindexter, Cristina and Chen, Jiquan and Elbashandy, Abdelrahman and Humphrey, Marty and Isaac, Peter and Polidori, Diego and Ribeca, Alessio and van Ingen, Catharine and Zhang, Leiming and Amiro, Brian and Ammann, Christof and Arain, M. Altaf and Ardö, Jonas and Arkebauer, Timothy and Arndt, Stefan K. and Arriga, Nicola and Aubinet, Marc and Aurela, Mika and Baldocchi, Dennis and Barr, Alan and Beamesderfer, Eric and Marchesini, Luca Belelli and Bergeron, Onil and Beringer, Jason and Bernhofer, Christian and Berveiller, Daniel and Billesbach, Dave and Black, Thomas Andrew and Blanken, Peter D. and Bohrer, Gil and Boike, Julia and Bolstad, Paul V. and Bonal, Damien and Bonnefond, Jean-Marc and Bowling, David R. and Bracho, Rosvel and Brodeur, Jason and Brümmer, Christian and Buchmann, Nina and Burban, Benoit and Burns, Sean P. and Buysse, Pauline and Cale, Peter and Cavagna, Mauro and Cellier, Pierre and Chen, Shiping and Chini, Isaac and Christensen, Torben R. and Cleverly, James and Collalti, Alessio and Consalvo, Claudia and Cook, Bruce D. and Cook, David and Coursolle, Carole and Cremonese, Edoardo and Curtis, Peter S. and D’Andrea, Ettore and da Rocha, Humberto and Dai, Xiaoqin and Davis, Kenneth J. and De Cinti, Bruno and de Grandcourt, Agnes and De Ligne, Anne and De Oliveira, Raimundo C. and Delpierre, Nicolas and Desai, Ankur R. and Di Bella, Carlos Marcelo and di Tommasi, Paul and Dolman, Han and Domingo, Francisco and Dong, Gang and Dore, Sabina and Duce, Pierpaolo and Dufrêne, Eric and Dunn, Allison and Dušek, Jiří and Eamus, Derek and Eichelmann, Uwe and ElKhidir, Hatim Abdalla M. and Eugster, Werner and Ewenz, Cacilia M. and Ewers, Brent and Famulari, Daniela and Fares, Silvano and Feigenwinter, Iris and Feitz, Andrew and Fensholt, Rasmus and Filippa, Gianluca and Fischer, Marc and Frank, John and Galvagno, Marta and Gharun, Mana and Gianelle, Damiano and Gielen, Bert and Gioli, Beniamino and Gitelson, Anatoly and Goded, Ignacio and Goeckede, Mathias and Goldstein, Allen H. and Gough, Christopher M. and Goulden, Michael L. and Graf, Alexander and Griebel, Anne and Gruening, Carsten and Grünwald, Thomas and Hammerle, Albin and Han, Shijie and Han, Xingguo and Hansen, Birger Ulf and Hanson, Chad and Hatakka, Juha and He, Yongtao and Hehn, Markus and Heinesch, Bernard and Hinko-Najera, Nina and Hörtnagl, Lukas and Hutley, Lindsay and Ibrom, Andreas and Ikawa, Hiroki and Jackowicz-Korczynski, Marcin and Janouš, Dalibor and Jans, Wilma and Jassal, Rachhpal and Jiang, Shicheng and Kato, Tomomichi and Khomik, Myroslava and Klatt, Janina and Knohl, Alexander and Knox, Sara and Kobayashi, Hideki and Koerber, Georgia and Kolle, Olaf and Kosugi, Yoshiko and Kotani, Ayumi and Kowalski, Andrew and Kruijt, Bart and Kurbatova, Julia and Kutsch, Werner L. and Kwon, Hyojung and Launiainen, Samuli and Laurila, Tuomas and Law, Bev and Leuning, Ray and Li, Yingnian and Liddell, Michael and Limousin, Jean-Marc and Lion, Marryanna and Liska, Adam J. and Lohila, Annalea and López-Ballesteros, Ana and López-Blanco, Efrén and Loubet, Benjamin and Loustau, Denis and Lucas-Moffat, Antje and Lüers, Johannes and Ma, Siyan and Macfarlane, Craig and Magliulo, Vincenzo and Maier, Regine and Mammarella, Ivan and Manca, Giovanni and Marcolla, Barbara and Margolis, Hank A. and Marras, Serena and Massman, William and Mastepanov, Mikhail and Matamala, Roser and Matthes, Jaclyn Hatala and Mazzenga, Francesco and McCaughey, Harry and McHugh, Ian and McMillan, Andrew M. S. and Merbold, Lutz and Meyer, Wayne and Meyers, Tilden and Miller, Scott D. and Minerbi, Stefano and Moderow, Uta and Monson, Russell K. and Montagnani, Leonardo and Moore, Caitlin E. and Moors, Eddy and Moreaux, Virginie and Moureaux, Christine and Munger, J. William and Nakai, Taro and Neirynck, Johan and Nesic, Zoran and Nicolini, Giacomo and Noormets, Asko and Northwood, Matthew and Nosetto, Marcelo and Nouvellon, Yann and Novick, Kimberly and Oechel, Walter and Olesen, Jørgen Eivind and Ourcival, Jean-Marc and Papuga, Shirley A. and Parmentier, Frans-Jan and Paul-Limoges, Eugenie and Pavelka, Marian and Peichl, Matthias and Pendall, Elise and Phillips, Richard P. and Pilegaard, Kim and Pirk, Norbert and Posse, Gabriela and Powell, Thomas and Prasse, Heiko and Prober, Suzanne M. and Rambal, Serge and Rannik, Üllar and Raz-Yaseef, Naama and Reed, David and de Dios, Victor Resco and Restrepo-Coupe, Natalia and Reverter, Borja R. and Roland, Marilyn and Sabbatini, Simone and Sachs, Torsten and Saleska, Scott R. and Sánchez-Cañete, Enrique P. and Sanchez-Mejia, Zulia M. and Schmid, Hans Peter and Schmidt, Marius and Schneider, Karl and Schrader, Frederik and Schroder, Ivan and Scott, Russell L. and Sedlák, Pavel and Serrano-Ortíz, Penélope and Shao, Changliang and Shi, Peili and Shironya, Ivan and Siebicke, Lukas and Šigut, Ladislav and Silberstein, Richard and Sirca, Costantino and Spano, Donatella and Steinbrecher, Rainer and Stevens, Robert M. and Sturtevant, Cove and Suyker, Andy and Tagesson, Torbern and Takanashi, Satoru and Tang, Yanhong and Tapper, Nigel and Thom, Jonathan and Tiedemann, Frank and Tomassucci, Michele and Tuovinen, Juha-Pekka and Urbanski, Shawn and Valentini, Riccardo and van der Molen, Michiel and van Gorsel, Eva and van Huissteden, Ko and Varlagin, Andrej and Verfaillie, Joseph and Vesala, Timo and Vincke, Caroline and Vitale, Domenico and Vygodskaya, Natalia and Walker, Jeffrey P. and Walter-Shea, Elizabeth and Wang, Huimin and Weber, Robin and Westermann, Sebastian and Wille, Christian and Wofsy, Steven and Wohlfahrt, Georg and Wolf, Sebastian and Woodgate, William and Li, Yuelin and Zampedri, Roberto and Zhang, Junhui and Zhou, Guoyi and Zona, Donatella and Agarwal, Deb and Biraud, Sebastien and Torn, Margaret and Papale, Dario (2020), The {FLUXNET2015} dataset and the {ONEFlux} processing pipeline for eddy covariance data, Scientific Data, 1, 10.1038/s41597-020-0534-3