A comparison of gap-filling algorithms for eddy covariance fluxes and their drivers
نویسندگان
چکیده
Abstract. The errors and uncertainties associated with gap-filling algorithms of water, carbon, energy fluxes data have always been one the main challenges global network microclimatological tower sites that use eddy covariance (EC) technique. To address these concerns find more efficient algorithms, we reviewed eight to estimate missing values environmental drivers nine for three major typically found in EC time series. We then examined algorithms' performance different scenarios utilising from five towers during 2013. This research's objectives were (a) evaluate impact gap lengths on each algorithm (b) compare traditional new techniques data, fluxes, separately their corresponding meteorological drivers. was evaluated by generating windows lengths, ranging a day 365 d. In scenario, period chosen randomly, removed dataset accordingly. After running variety statistical metrics used performance. showed levels sensitivity lengths; Prophet Forecast Model (FBP) revealed most sensitivity, whilst artificial neural networks (ANNs), instance, did not vary as much changing length. generally decreased increasing length, yet differences significant smaller than 30 No between recognised However, linear slight superiority over those machine learning (ML), except random forest (RF) estimating ground heat flux (root mean square – RMSEs 28.91 33.92 RF classic regression CLR, respectively). ML MDS other algorithms. Even though ANNs, (RF), eXtreme Gradient Boost (XGB) comparable provided consistent results slightly less bias against indicated no single outperforms all situations, but is potential alternative ANNs regards gap-filling.
منابع مشابه
Comprehensive comparison of gap-filling techniques for eddy covariance net carbon fluxes
We review 15 techniques for estimating missing values of net ecosystem CO2 exchange (NEE) in eddy covariance time series and evaluate their performance for different artificial gap scenarios based on a set of 10 benchmark datasets from six forested sites in Europe. The goal of gap filling is the reproduction of the NEE time series and hence this present work focuses on estimating missing NEE va...
متن کاملa comparison of linguistic and pragmatic knowledge: a case of iranian learners of english
در این تحقیق دانش زبانشناسی و کاربردشناسی زبان آموزان ایرانی در سطح بالای متوسط مقایسه شد. 50 دانش آموز با سابقه آموزشی مشابه از شش آموزشگاه زبان مختلف در دو آزمون دانش زبانشناسی و آزمون دانش گفتار شناسی زبان انگلیسی شرکت کردند که سوالات هر دو تست توسط محقق تهیه شده بود. همچنین در این تحقیق کارایی کتابهای آموزشی زبان در فراهم آوردن درون داد کافی برای زبان آموزان ایرانی به عنوان هدف جانبی تحقیق ...
15 صفحه اولMethane fluxes measured by eddy covariance and static chamber techniques
Introduction Conclusions References
متن کاملEddy covariance measurement of NOyi fluxes by TD-LIF
Application of thermal dissociation-laser induced fluorescence (TD-LIF) to measurement of HNO3, Σalkyl nitrates, Σperoxy nitrates, and NO2 fluxes using eddy covariance D. K. Farmer, P. J. Wooldridge, and R. C. Cohen Department of Chemistry; University of California, Berkeley, CA, 94720, USA Dept. of Earth and Planetary Science; University of California, Berkeley, CA, 94720, USA Received: 22 Dec...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Geoscientific instrumentation, methods and data systems
سال: 2021
ISSN: ['2193-0856', '2193-0864']
DOI: https://doi.org/10.5194/gi-10-123-2021