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Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haëntjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., Zona, D.
Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements …
Journal: Agricultural And Forest Meteorology, Volume 301-302: 108350 (2021), ISBN . DOI: 10.1016/j.agrformet.2021.108350 Sites: CA-ARB, CA-ARF, CA-Ca1, CA-Ca2, CA-Ca3, CA-Cbo, CA-DBB, CA-ER1, CA-Gro, CA-Let, CA-Man, CA-MR3, CA-MR5, CA-Na1, CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS5, CA-NS6, CA-NS7, CA-Oas, CA-Obs, CA-Ojp, CA-Qc2, CA-Qcu, CA-Qfo, CA-SCC, CA-SF1, CA-SF2, CA-SF3, CA-SJ2, CA-SJ3, CA-TP1, CA-TP3, CA-TP4, CA-TPD, CA-WP1, US-A03, US-A10, US-A32, US-A74, US-ADR, US-AR1, US-AR2, US-ARb, US-ARc, US-ARM, US-Aud, US-Bar, US-Bi1, US-Bi2, US-Bkg, US-Blk, US-Blo, US-Bn1, US-Bn2, US-Bn3, US-Bo1, US-Bo2, US-Br3, US-CaV, US-Ced, US-CF1, US-CF2, US-CF3, US-CF4, US-ChR, US-Cop, US-CPk, US-CRT, US-Ctn, US-Dia, US-Dix, US-Dk1, US-Dk2, US-Dk3, US-EDN, US-Elm, US-EML, US-Fmf, US-FPe, US-FR2, US-FR3, US-Fuf, US-Fwf, US-GLE, US-GMF, US-Goo, US-Ha1, US-Ha2, US-Hn2, US-Hn3, US-Ho1, US-Ho2, US-Ho3, US-IB1, US-IB2, US-Ivo, US-KFS, US-KLS, US-Kon, US-KS1, US-KS2, US-KUT, US-Lin, US-Los, US-LPH, US-LWW, US-Me1, US-Me2, US-Me3, US-Me4, US-Me5, US-Me6, US-MMS, US-MOz, US-Mpj, US-MRf, US-MtB, US-Myb, US-NC1, US-NC2, US-NC3, US-NC4, US-Ne1, US-Ne2, US-Ne3, US-NGB, US-NR1, US-Oho, US-ORv, US-PHM, US-Pon, US-Prr, US-RC1, US-RC2, US-RC3, US-RC4, US-RC5, US-Rls, US-Rms, US-Ro1, US-Ro2, US-Ro5, US-Ro6, US-Rpf, US-Rws, US-SdH, US-Seg, US-Ses, US-SFP, US-Shd, US-Skr, US-Slt, US-Snd, US-Sne, US-Snf, US-SO2, US-SO3, US-SO4, US-SP1, US-SP2, US-SP3, US-SRC, US-SRG, US-SRM, US-Srr, US-Sta, US-StJ, US-Syv, US-Ton, US-Tw1, US-Tw2, US-Tw3, US-Tw4, US-Tw5, US-Twt, US-Uaf, US-UMB, US-UMd, US-Var, US-Vcm, US-Vcp, US-Vcs, US-WBW, US-WCr, US-Wdn, US-Wgr, US-Whs, US-Wi0, US-Wi1, US-Wi3, US-Wi4, US-Wi5, US-Wi6, US-Wi7, US-Wi8, US-Wi9, US-Wjs, US-Wkg, US-Wlr, US-Wpp, US-WPT, US-Wrc, US-xBR, US-xCP, US-xDL, US-xHA, US-xKA, US-xKZ, US-xRM, US-xSR, US-xWD
Xu, B., Arain, M. A., Black, T. A., Law, B. E., Pastorello, G. Z., Chu, H.
Climate extremes such as heat waves and droughts are projected to occur more Frequently with increasing temperature and an intensified hydrological cycle. It is Important to understand and quantify how forest carbon fluxes respond to heat and drought stress. In this study, we developed a series of daily indices of sensitivity to …
Journal: Global Change Biology, Volume 26 (2): 901-918 (2020), ISBN . DOI: 10.1111/gcb.14843 Sites: CA-Ca1, CA-Ca2, CA-Ca3, CA-Gro, CA-Man, CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS5, CA-Oas, CA-Obs, CA-Qfo, CA-SF2, CA-TP1, CA-TP2, CA-TP3, CA-TP4, US-Bar, US-Blo, US-GLE, US-Ha1, US-Ho1, US-Me2, US-Me3, US-Me6, US-MMS, US-NR1, US-Oho, US-PFa, US-Prr, US-Syv, US-UMB, US-UMd, US-WCr
Chu, H., Baldocchi, D. D., Poindexter, C., Abraha, M., Desai, A. R., Bohrer, G., Arain, M. A., Griffis, T., Blanken, P. D., O'Halloran, T. L., Thomas, R. Q., Zhang, Q., Burns, S. P., Frank, J. M., Christian, D., Brown, S., Black, T. A., Gough, C. M., Law, B. E., Lee, X., Chen, J., Reed, D. E., Massman, W. J., Clark, K., Hatfield, J., Prueger, J., Bracho, R., Baker, J. M., Martin, T. A.
Aerodynamic canopy height (ha) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface‐atmosphere coupling. However, methods to estimate ha from data are limited. This synthesis evaluates the applicability and robustness of the calculation of ha from eddy covariance …
Journal: Geophysical Research Letters, Volume 45: 9275–9287 (2018), ISBN . DOI: 10.1029/2018GL079306 Sites: BR-Sa1, BR-Sa3, CA-Ca1, CA-Ca2, CA-Ca3, CA-Cbo, CA-ER1, CA-Gro, CA-Man, CA-NS1, CA-NS2, CA-NS3, CA-NS4, CA-NS5, CA-Oas, CA-Obs, CA-Ojp, CA-Qfo, CA-TP1, CA-TP3, CA-TP4, CA-TPD, US-Blo, US-Bn1, US-Bn2, US-Br1, US-Br3, US-Ced, US-CPk, US-CRT, US-Dix, US-Dk2, US-Dk3, US-Fmf, US-Fuf, US-GBT, US-GLE, US-GMF, US-Ha1, US-Ha2, US-Ho2, US-Ho3, US-IB1, US-IB2, US-KL1, US-KL2, US-KL3, US-KM1, US-KM2, US-KM3, US-KM4, US-Me2, US-Me3, US-Me4, US-Me5, US-Me6, US-MMS, US-MRf, US-NC1, US-NC2, US-Ne1, US-Ne2, US-Ne3, US-NR1, US-Oho, US-Prr, US-Ro1, US-Ro3, US-SB1, US-Shd, US-Skr, US-Slt, US-SP1, US-SP2, US-SP3, US-SRM, US-Srr, US-Syv, US-Ton, US-Tw3, US-Twt, US-UMB, US-UMd, US-Var, US-Vcm, US-WBW, US-Wi0, US-Wi1, US-Wi3, US-Wi4, US-Wi5, US-Wi8, US-Wi9, US-Wrc
Nagai, S., Akitsu, T., Saitoh, T. M., Busey, R. C., Fukuzawa, K., Honda, Y., Ichie, T., Ide, R., Ikawa, H., Iwasaki, A., Iwao, K., Kajiwara, K., Kang, S., Kim, Y., Khoon, K. L., Kononov, A. V., Kosugi, Y., Maeda, T., Mamiya, W., Matsuoka, M., Maximov, T. C., Menzel, A., Miura, T., Mizunuma, T., Morozumi, T., Motohka, T., Muraoka, H., Nagano, H., Nakai, T., Nakaji, T., Oguma, H., Ohta, T., Ono, K., Pungga, R. A., Petrov, R. E., Sakai, R., Schunk, C., Sekikawa, S., Shakhmatov, R., Son, Y., Sugimoto, A., Suzuki, R., Takagi, K., Takanashi, S., Tei, S., Tsuchida, S., Yamamoto, H., Yamasaki, E., Yamashita, M., Yoon, T. K., Yoshida, T., Yoshimura, M., Yoshitake, S., Wilkinson, M., Wingate, L., Nasahara, K. N.
We report long-term continuous phenological and sky images taken by time-lapse cameras through the Phenological Eyes Network (http://www.pheno-eye.org. Accessed 29 May 2018) in various ecosystems from the Arctic to the tropics. Phenological images are useful in recording the year-to-year variability in the timing of flowering, leaf-flush, …
Journal: Ecological Research, Volume : (2018), ISBN . DOI: 10.1007/s11284-018-1633-x Sites: US-Prr
Saito, K., Iwahana, G., Ikawa, H., Nagano, H., Busey, R. C.
A fibre-optic DTS (distributed temperature sensing) system using Raman-scattering optical time domain reflectometry was deployed to monitor a boreal forest research site in the interior of Alaska. Surface temperatures range between −40°C in winter and 30°C in summer at this site. In parallel experiments, a fibre-optic cable sensor …
Journal: Geoscientific Instrumentation, Methods And Data Systems, Volume 7 (3): 223-234 (2018), ISBN . DOI: 10.5194/gi-7-223-2018 Sites: US-Prr
Fischer, R., Walsh, J. E., Euskirchen, E. S., Bieniek, P. A.
The wetness of high-latitude land surfaces is strongly dependent on the dif- ference between precipitation (P) and evapotranspiration (ET). If climate models are to capture the trajectory of surface wetness in high latitudes, they must be able to simulate the seasonality and variations of the surface moisture fluxes, as well as the …
Journal: Atmospheric And Climate Sciences, Volume 08 (01): 29-54 (2018), ISBN . DOI: 10.4236/acs.2018.81003 Sites: US-Prr
Nagano, H., Ikawa, H., Nakai, T., Matsushima-Yashima, M., Kobayashi, H., Kim, Y., Suzuki, R.
Journal: Agricultural And Forest Meteorology, Volume 249: 297-309 (2018), ISBN . DOI: 10.1016/j.agrformet.2017.11.001 Sites: US-Prr
Kobayashi, H., Nagai, S., Kim, Y., Yang, W., Ikeda, K., Ikawa, H., Nagano, H., Suzuki, R.
Plant phenology timings, such as spring green-up and autumn senescence, are essential state information characterizing biological responses and terrestrial carbon cycles. Current efforts for the in situ reflectance measurements are not enough to obtain the exact interpretation of how seasonal spectral signature responds to phenological …
Journal: Remote Sensing, Volume 10 (7): 1071 (2018), ISBN . DOI: doi:10.3390/rs10071071 Sites: US-Prr
Xinchen Lu , Xiao Cheng, Xianglan Li Jiquan Chen, Minmin Sun, Ming Ji, Hong He, Siyu Wang, Sen Li, Jianwu Tang
Characterized by the noticeable seasonal patterns of canopy photosynthesis, mid-to-high latitude forests are sen- sitive to climate change and crucial for understanding the global carbon cycle. To monitor the seasonal cycle of the canopy photosynthesis from space, several remotely sensed indexes, such as normalized difference vegeta- …
Journal: Science of the Total Environment, Volume 644: 439-451 (2018), ISBN . DOI: org/10.1016/j.scitotenv.2018.06.269 Sites: US-Prr
Tripathi, B. M., Kim, M., Kim, Y., Byun, E., Yang, J., Ahn, J., Lee, Y. K.
Understating the microbial communities and ecological processes that influence their structure in permafrost soils is crucial for predicting the consequences of climate change. In this study we investigated the bacterial and archaeal communities along depth profiles of four soil cores collected across Alaska. The bacterial and archaeal …
Journal: Scientific Reports, Volume 8 (1): (2018), ISBN . DOI: 10.1038/s41598-017-18777-x Sites: US-Prr