SCOPE 2.0: a Model to Simulate Vegetated Land Surface Fluxes and Satellite Signals
Total Page：16
File Type：pdf, Size：1020Kb
Geosci. Model Dev., 14, 4697–4712, 2021 https://doi.org/10.5194/gmd-14-4697-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. SCOPE 2.0: a model to simulate vegetated land surface fluxes and satellite signals Peiqi Yang, Egor Prikaziuk, Wout Verhoef, and Christiaan van der Tol University of Twente, Faculty ITC, P.O. Box 217, 7500 AE Enschede, the Netherlands Correspondence: Christiaan van der Tol ([email protected]) Received: 31 July 2020 – Discussion started: 28 October 2020 Revised: 23 May 2021 – Accepted: 27 June 2021 – Published: 29 July 2021 Abstract. The Soil Canopy Observation of Photosynthesis 1 Introduction and Energy fluxes (SCOPE) model aims at linking satellite observations in the visible, infrared, and thermal domains Vegetation, as a dynamic component of the Earth system, with land surface processes in a physically based manner, affects the climate via its influence on the exchange of en- and quantifying the microclimate in vegetation canopies. It ergy and matter between the land surface and the atmosphere. simulates radiative transfer in the soil, leaves, and vegetation Quantification of this exchange is relevant for a wide range canopies, as well as photosynthesis and non-radiative heat of applications including weather prediction, climate projec- dissipation through convection and mechanical turbulence. tions, agriculture, and ecological and hydrological studies. Since the first publication 12 years ago, SCOPE has been ap- Process-based terrestrial ecosystem models describe the plied in remote sensing studies of solar-induced chlorophyll exchange of water, carbon, energy among soil, vegetation, fluorescence (SIF), energy balance fluxes, gross primary pro- and atmosphere in a mechanistic way. A number of models duction (GPP), and directional thermal signals. Here, we have been developed since 1970s, such as the comprehensive present a thoroughly revised version, SCOPE 2.0, which fea- plant–environment model Cupid (Norman, 1979), the Sim- tures a number of new elements: (1) it enables the definition ple Biosphere model (SiB, Sellers et al., 1986), the Boreal of layers consisting of leaves with different properties, thus Ecosystem Productivity Simulator (BEPS, Liu et al., 1997), enabling the simulation of vegetation with an understorey the Biosphere Energy Transfer Hydrology model (BETHY, or with a vertical gradient in leaf chlorophyll concentration; Rayner et al., 2005), and the models in the Trends in (2) it enables the simulation of soil reflectance; (3) it in- Net Land-Atmosphere Carbon Exchange project (TRENDY, cludes the simulation of leaf and canopy reflectance changes Sitch et al., 2008). Proper representation of the land surface induced by the xanthophyll cycle; and (4) the computation and the response of net CO2 exchange to changes in envi- speed has been reduced by 90 % compared to earlier ver- ronmental conditions (e.g. temperature and precipitation) is sions due to a fundamental optimization of the model. These crucial for accurately modelling future climate and climate– new features improve the capability of the model to repre- carbon cycle feedbacks. Terrestrial ecosystem models con- sent complex canopies and to explore the response of remote sider vegetation layers either as one big leaf (e.g. SiB), two sensing signals to vegetation physiology. The improvements big leaves (e.g. BEPS), or a cluster of leaves (e.g. BETHY). in computational efficiency make it possible to use SCOPE They generally include a photosynthesis submodel for esti- 2.0 routinely for the simulation of satellite data and land sur- mation of ecosystem production and an energy balance sub- face fluxes. It also strengthens the operability for the numer- model for the partition of net radiant energy into sensible and ical retrieval of land surface products from satellite or air- latent flux, and use remotely sensed data (e.g. leaf area in- borne data. dex, LAI) as temporally variant input data to capture spatial and temporal variations in terrestrial vegetation (Xiao et al., 2019). Earth observation with satellites can be used to monitor key characteristics of vegetation that are responsible for the Published by Copernicus Publications on behalf of the European Geosciences Union. 4698 P. Yang et al.: SCOPE 2.0 surface–atmosphere exchange and identify changes therein. SCOPE has been applied in a wide range of studies. The most commonly used remote sensing indicator of vege- Thanks to the coupling of photosynthesis and radiative trans- tation biophysical and biochemical properties is reflectance fer of fluorescence in the SCOPE model, it has been used (Ollinger, 2011). For example, the MODIS (Moderate Res- as a convenient tool for in-depth process-based studies to olution Imaging Spectroradiometer) normalized vegetation unravel the relationship between fluorescence and photosyn- reflectance index (NDVI), and the Envisat MERIS Terres- thesis (Damm et al., 2015; Verrelst et al., 2016; Migliavacca trial Chlorophyll Index (MTCI) have been empirically corre- et al., 2017). Besides, it has also been used for simulating lated with canopy LAI and leaf chlorophyll content, respec- directional anisotropy of satellite-measured surface tempera- tively (Huete et al., 2002). For the past 10 years, remotely tures (Duffour et al., 2015), for predicting evapotranspiration sensed solar-induced chlorophyll fluorescence (SIF) has of- (Galleguillos et al., 2011), and as a benchmark for other sim- fered an additional way to monitor vegetation (Mohammed pler radiative transfer models (Bian et al., 2020). Contem- et al., 2019). SIF has been successfully used to estimate gross porary simulations of satellite observations and plant physio- primary production (GPP) (Guanter et al., 2014; Ryu et al., logical processes make SCOPE a useful tool to monitor vege- 2019) and stress detection (Acˇ et al., 2015; Rossini et al., tation dynamic response to environmental conditions (Zhang 2015). In addition to reflectance and SIF, thermal signals pro- et al., 2014; Pacheco-Labrador et al., 2019). vide insights in the physical processes of surface energy and Since the original publication, SCOPE been extended with water balance, such as demonstrated by the mapping of evap- new features: otranspiration globally with satellite thermal radiance (Ne- 1. The Brightness–Shape–Moisture (BSM) soil re- mani and Running, 1989; Allen et al., 2007). flectance model (Verhoef et al., 2018; Yang et al., Combined radiative transfer and plant physiological mod- 2020b) has been introduced. elling is a promising way to investigate the exchange of en- ergy, water, and carbon among soil, vegetation, and atmo- 2. The radiative transfer of fluorescence has been im- sphere, and to develop remote sensing techniques for mon- proved (Van der Tol et al., 2019). itoring of vegetation functioning. Many factors affect the signals observed from remote sensing, including the Sun– 3. Changes in reflectance due to dynamic xanthophyll pig- observation geometry and the structure and composition of ment changes have been included (Vilfan et al., 2018). the Earth’s surface and atmosphere. A physically consis- 4. The RTMs in the SCOPE have been adapted for multi- tent exploitation of remote sensing data therefore requires layer canopies (Yang et al., 2017). the modelling of radiative transfer in the soil–vegetation– atmosphere system. Radiative transfer models (RTMs) de- These new features have not been described together. In scribe the relationship between vegetation characteristics and the new version of SCOPE (SCOPE 2.0) presented here, remote sensing observations obtained under varying Sun– these improvements are coherently incorporated. Moreover, observer geometry. However, for a complete understanding the model has been optimized in many ways to improve the of the role of vegetation in the energy budget of the Earth’s computational efficiency and stability, and the options to pro- surface, radiative transfer modelling is not sufficient. One vide data input formats have been extended. We present a also needs to model non-radiative processes of energy dis- description of basic functionality of the model followed by sipation via photosynthesis, phase transitions of water, heat several recent developments. storage, and turbulent heat exchange between the surface and the atmosphere. This enables investigations beyond the mon- 2 General description of SCOPE itoring of vegetation biophysical and biochemical properties, towards monitoring of fluxes. 2.1 Starting points The Soil Canopy Observation of Photosynthesis and En- ergy fluxes (SCOPE) model simulates the radiative transfer SCOPE is designed to simulate photosynthetic, hydrological, of incident light and thermal and fluorescence radiation emit- and radiative transfer processes at the vegetated land surface. ted by soil and plants, component temperatures, photosyn- For these purposes, it combines several RTMs with a leaf thesis, and turbulent heat exchange (van der Tol et al., 2009). biochemical model and an aerodynamic resistance scheme. In SCOPE, the radiative transfer and the non-radiative en- These models provide simulations of emanating hyperspec- ergy fluxes are computed in an assemblage of leaves and tral radiance and net radiation Rn (via radiative transfer pro- soil. The energy balance is maintained at all levels of spa- cesses), photosynthesis rates (via photosynthetic processes), tial aggregation. Maintaining an energy budget is necessary and sensible heat flux H, latent heat flux λE, and ground heat for the simulation