A5068660254- Hydrology and Watershed Management Studies
- Climate variability and models
- Plant Water Relations and Carbon Dynamics
- Meteorological Phenomena and Simulations
- Atmospheric and Environmental Gas Dynamics
- Climate change and permafrost
- Cryospheric studies and observations
- Hydrology and Drought Analysis
- Atomic and Subatomic Physics Research
- Text Readability and Simplification
- Landslides and related hazards
- Seismology and Earthquake Studies
- Soil Geostatistics and Mapping
- Groundwater flow and contamination studies
UNSW Sydney
2014-2018
ARC Centre of Excellence for Climate System Science
2016-2017
Land surface models (LSMs) must accurately simulate observed energy and water fluxes during droughts in order to provide reliable estimates of future resources. We evaluated 8 different LSMs (14 model versions) for simulating evapotranspiration (ET) periods evaporative drought (Edrought) across six flux tower sites. Using an empirically defined Edrought threshold (a decline ET below the 15th percentile), we show that simulated 58 days per year, on average, sites, ∼3 times as many 20 d. The...
The PALS Land sUrface Model Benchmarking Evaluation pRoject (PLUMBER) illustrated the value of prescribing a priori performance targets in model intercomparisons. It showed that turbulent energy flux predictions from different land surface models, at broad range tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all models were outperformed by linear regression against downward shortwave radiation. latent flux,...
Abstract. The FLUXNET dataset contains eddy covariance measurements from across the globe and represents an invaluable estimate of fluxes energy, water, carbon between land surface atmosphere. While there is expectation that broad range site characteristics in result a diversity flux behaviour, has been little exploration how predictable behaviour network. Here, 155 datasets with 30 min temporal resolution Tier 1 2015 were analysed first attempt to assess individual predictability. We...
Abstract. Previous research has shown that land surface models (LSMs) are performing poorly when compared with relatively simple empirical over a wide range of metrics and environments. Atmospheric driving data appear to provide information about fluxes LSMs not fully utilising. Here, we further quantify the available in meteorological forcing used by for predicting fluxes, interrogating FLUXNET data, extending benchmarking methodology previous experiments. We show substantial performance...
Abstract. Flux towers measure ecosystem-scale surface–atmosphere exchanges of energy, carbon dioxide and water vapour. The network flux now encompasses ∼ 900 sites, spread across every continent. Consequently, these data have become an essential benchmarking tool for land surface models (LSMs). However, as released are not immediately usable driving, evaluating LSMs. tower must first be transformed into a LSM-readable file format, process which involves changing units, screening missing...
Abstract. Flux towers measure ecosystem-scale surface-atmosphere exchanges of energy, carbon dioxide and water vapour. The network flux now encompasses ~ 900 sites, spread across every continent. Consequently, these data have become an essential benchmarking tool for land surface models (LSMs). However, as released are not immediately usable driving, evaluating LSMs. tower must first be transformed into a LSM-readable file format, process which involves changing units, screening missing...
Abstract. The FLUXNET dataset contains eddy covariance measurements from across the globe, and represents an invaluable estimate of fluxes energy, water carbon between land surface atmosphere. While there is expectation that broad range site characteristics in result a diversity flux behaviour, has been little exploration how predictable behaviour network. Aside intrinsic interest this fundamental question, understanding predictability would be useful for model (LSM) evaluation setting...
Abstract. Previous research has shown that Land Surface Models (LSMs) are performing poorly when compared with rela- tively simple empirical models over a wide range of metrics and environments. Atmospheric driving data appears to provide information about land surface fluxes LSMs not fully utilising. Here, we further quantify the available in meteorological forcing is used by for predicting fluxes, interrogating Fluxnet data, extending benchmarking methodology previous experiments. We show...
Uncertainty in Cluster-plus-regression modelsThe models used this paper include some uncertainty their results.This stems from the fact that there is no "correct" initialisation for K-means clustering (we use common "random selection of samples" method), and guarantee convergence algorithm.This means each time model trained, it slightly different -cluster centres are different, so samples included linear regressions node, also all different.This problem unavoidable with kind (indeed, nearly...
How unique are fluxes from different FLUXNET sites? Extended Budyko AnalysisThe following 2 plots show predictability metrics for Potential and Actual evapotranspiration. 1 0.2 0.0 0.4 0.6 0.