Diffuse Photosynthetically Active Radiation Research Articles

Effects of Biophysical Factors on Light Use Efficiency at Multiple Time Scales in a Chinese Cork Oak Plantation Ecosystem

Light use efficiency (LUE) characterizes the efficiency of vegetation in converting photosynthetically active radiation (PAR) into biomass energy through photosynthesis and is a critical parameter for gross primary productivity (GPP) in terrestrial ecosystems. Based on the eddy covariance measurements of a Chinese cork oak plantation ecosystem in northern China, the temporal variations in LUE were investigated, and biophysical factors were examined at time scales ranging from hours to years. Our results show that diurnal LUE first increased sharply before 8:30 and then decreased gradually until 12:00, thereafter increasing gradually and reaching the maximum value at sunset during the growing season. The daily and monthly LUE first increased and then decreased within a year and showed a substantial drop around June. The annual LUE ranged from 0.09 to 0.17 g C mol photon−1, and the multiyear mean maximal LUE was 0.30 g C mol photon−1 during 2006–2019. Only GPP (positive) and clearness index (CI) (negative) had consistent effects on LUE at different time scales, and the effects of the remaining biophysical factors on LUE were different as the time scale changed. The effects of air temperature, vapor pressure deficit, precipitation, evaporative fraction, and normalized difference vegetation index on LUE were mainly indirect (via PAR and/or GPP). When CI decreased, an increased ratio of diffuse PAR to PAR produced a more uniform irradiance in the canopy, which ultimately resulted in a higher LUE. Due to climate change in our study area, the annual LUE may decrease in the future but improving management practices may slow or even reverse this trend in the annual LUE in the studied Chinese cork oak plantation.

Quantifying the effects of diffuse photosynthetically active radiation on water use efficiency in different ecosystems

Compared with direct radiation, diffuse radiation could be more efficiently used for photosynthesis because of the diffuse fertilization effect (DFE). Because carbon uptake and water loss are coupled through leaf stomata, DFE probably increases gross primary productivity (GPP) and evapotranspiration (ET) simultaneously. Multi-year eddy covariance flux observation data and simulated diffuse fraction of photosynthetically active radiation (PAR) for nine ecosystems across China (containing forest, grassland, wetland, and cropland) were used to quantify the impact of DFE on water use efficiency (WUE). The results showed that GPP firstly increased and then decreased with increasing diffuse fraction of PAR (kd-PAR = diffuse PAR/PAR) for each ecosystems. The kd-PAR values at which maximum GPP occurred varied between 0.34 and 0.76 across nine ecosystems. ET decreased with increasing kd-PAR in most ecosystems mainly because high kd-PAR (indicating low PAR) could reduce evaporation in most ecosystems. The relationships between WUE and kd-PAR were significantly linear with averaged slopes of forest, grassland, wetland, and cropland of 1.64, 0.96, 1.19, and 4.51 g C kg−1 H2O, respectively. A multiple linear regression method was used to analyze the effect of diffuse PAR (PARdif) and direct PAR (PARdir) on GPP and ET. The conversion efficiencies for PARdif were greater than for PARdir, and the relative differences were 178.35% and 23.77% for GPP and ET, respectively. The intensity of DFE for GPP and ET were greater for forest and cropland than for grassland and wetland. The intensity of DFE was 3.05 to 236.96 times higher for GPP than for ET. The mathematical analysis results demonstrated that the promoting effect of PARdif was greater for GPP than for ET, thereby inducing an increase in WUE with increasing kd-PAR. These results will be helpful for improving modeling accuracy of carbon and water cycles under the conditions accompanying global climate change.

Shedding light on the increased carbon uptake by a boreal forest under diffuse solar radiation across multiple scales.

Solar radiation is scattered by cloud cover, aerosols and other particles in the atmosphere, all of which are affected by global changes. Furthermore, the diffuse fraction of solar radiation is increased by more frequent forest fires and likewise would be if climate interventions such as stratospheric aerosol injection were adopted. Forest ecosystem studies predict that an increase in diffuse radiation would result in higher productivity, but ecophysiological data are required to identify the processes responsible within the forest canopy. In our study, the response of a boreal forest to direct, diffuse and heterogeneous solar radiation conditions was examined during the daytime in the growing season to determine how carbon uptake is affected by radiation conditions at different scales. A 10-year data set of ecosystem, shoot and forest floor vegetation carbon and water-flux data was examined. Ecosystem-level carbon assimilation was higher under diffuse radiation conditions in comparison with direct radiation conditions at equivalent total photosynthetically active radiation (PAR). This was driven by both an increase in shoot and forest floor vegetation photosynthetic rate. Most notably, ecosystem-scale productivity was strongly related to the absolute amount of diffuse PAR, since it integrates both changes in total PAR and diffuse fraction. This finding provides a gateway to explore the processes by which absolute diffuse PAR enhances productivity, and the long-term persistence of this effect under scenarios of higher global diffuse radiation.

Light blocking film in a glasshouse impacts Capsicum annuum L. yield differentially across planting season.

High energy costs are a barrier to producing high-quality produce at protected cropping facilities. A potential solution to mitigate high energy costs is film technology, which blocks heat-producing radiation; however, the alteration of the light environment by these films may impact crop yield and quality. Previous studies have assessed the impact of ULR 80 [i.e., light-blocking film (LBF)] on crop yield and photosynthetically active radiation (PAR); however, an assessment of the spectral environment over different seasons is important to understand potential crop impacts through different developmental phases. In this study, two varieties (red and orange) of Capsicum annuum were grown across two crop cycles: one cycle with primary crop growth in the autumn (i.e., autumn experiment [AE]) and the other with primary crop growth in the summer (i.e., summer experiment [SE]). LBF reduced PAR (roof level: 26%-30%, plant canopy level: 8%-25%) and net radiation (36%-66%). LBF also reduced total diffuse PAR (AE: 8%, SE: 15%), but the diffuse fraction of PAR increased by 7% and 9% for AE and SE, respectively, potentially resulting in differential light penetration throughout the canopy across treatments. LBF reduced near-infrared radiation (700 nm-2,500 nm), including far-red (700 nm-780 nm) at mid- and lower-canopy levels. LBF significantly altered light quantity and quality, which determined the amount of time that the crop grew under light-limited (<12mol m-2 d-1) versus sufficient light conditions. In AE, crops were established and grown under light-limited conditions for 57% of the growing season, whereas in SE, crops were established and grown under sufficient light conditions for 66% of the growing season. Overall, LBF significantly reduced the yield in SE for both varieties (red: 29%; orange: 16%), but not in AE. The light changes in different seasons in response to LBF suggest that planting time is crucial for maximizing fruit yield when grown under a film that reduces light quantity. LBF may be unsuitable for year-round production of capsicum, and additional development of LBF is required for the film to be beneficial for saving energy during production and sustaining good crop yields in protected cropping.

Impact of radiation variations on temporal upscaling of instantaneous Solar-Induced Chlorophyll Fluorescence

Solar-Induced Chlorophyll Fluorescence (SIF) has been increasingly used as a novel proxy for vegetation productivity. Several space-borne instruments can retrieve SIF at varying overpass time, which complicates the interpretation as SIF is driven by absorbed Photosynthetically Active Radiation (PAR) at the acquisition time. To facilitate comparisons across sensors, satellite-based SIF is upscaled to daily averages with a length-of-day correction factor (DC). In conventional DC calculations, the light intensity over a day is approximated geometrically by the cosine of the Solar Zenith Angle (SZA), neglecting changes in atmospheric extinction and topographic effects. Here, we use reanalysis PAR data for DC calculations to evaluate the impact of atmospheric extinction and diffuse radiation individually. We find that the simple SZA approach is a reliable approximation for flat surfaces, where the overall atmospheric impact on DC is less than 10% as large individual effects on direct and diffuse PAR partially compensate each other. At longer time-scales, a sampling (clear sky) bias might exist due to cloud-filtering of satellite data. We find that in the Amazon the true monthly mean PAR can be 25% lower than the one for cloud-filtered days, potentially inducing seasonal SIF biases on the same order. An additional factor impacting PAR during a day is topography. For complex terrain, direct light in the DC expression requires a correction for surface slopes. For example in the San Gabriel Mountains, California, USA, the modified DC is changed by as much as 500% for strongly tilted surfaces. This modification is especially important for satellite instruments with fine spatial resolutions, where surface slopes are not averaged out and can have a substantial impact on reflectance and SIF. Overall, our refined DC-corrections and averaging strategy can help satellite SIF interpretation as well as intercomparisons over a wide range of spatio-temporal scales and overpass times.

Photosynthetically active radiation decomposition models for agrivoltaic systems applications

Decomposition models of solar irradiance estimate the magnitude of diffuse horizontal irradiance from global horizontal irradiance. These two radiation components are well known to be essential for predicting the performance of solar photovoltaic systems. In open-field agrivoltaic systems (i.e., the dual use of land for both agricultural activities and solar power conversion), cultivated crops receive unequal amounts of direct, diffuse, and reflected photosynthetically active radiation (PAR). These uneven amounts depend on where the crops are growing due to the non-homogenous shadings caused by the presence of the installed solar panels (above the crops or vertically mounted). It is known that, per unit of total PAR, diffuse PAR is more efficient for canopy photosynthesis than is direct PAR. For this reason, it is essential to estimate the diffuse PAR component when agrivoltaic systems are being assessed, in order to properly predict the crop yield. Since PAR is the electromagnetic radiation in the 400–700 nm waveband that can be used for photosynthesis by the crops, several stand-alone decomposition models typically used to split global horizontal irradiance are selected in this study to decompose PAR into direct and diffuse. These models are applied and validated in three locations in Sweden (Lanna, Hyltemossa and Norunda) using the coefficients stated on the models’ original publications and locally fitted coefficients. The results showed weaker performances in all stand-alone models for non-locally fitted coefficients (nRMSE ranging from 27% to 43%). However, performances improve with re-parameterization, with a highest nRMSE of 35.24% in Lanna. The Yang2 decomposition model is the best-performing one, with the lowest nRMSE of 23.75% in Norunda when applying re-estimated coefficients. Country level sets of coefficients for the best-performing models (Yang2 and Starke) are given after parameterization using combined data for all three locations in Sweden. These Sweden-fitted models are tested and show an nRMSE of 25.08% (Yang2) and 28.60% (Starke). These results can be used to perform estimations of the PAR diffuse component in Sweden wherever ground measurements are not available. The overall methodology can be similarly applied to other countries.

The Effect of Diffuse Radiation on Ecosystem Carbon Fluxes Across China From FLUXNET Forest Observations

Aerosol loading and cloud cover can alter the composition of radiation reaching the Earth’s surface and affect the ecosystem’s carbon cycle. In this study, we established an empirical model of the diffuse radiation fraction (Kd) based on a clearness index (Kt) to obtain the Kd of four FLUXNET forest sites in China. We focused on the relationships among the Kd, photosynthetically active radiation (PAR), light-use efficiency (LUE) and gross primary productivity (GPP) through mechanistic analysis. The relationships between carbon fluxes [including GPP, ecosystem respiration (ER), and net ecosystem exchange (NEE)] and the Kd were explored. Furthermore, we investigated the influence of environmental factors on carbon fluxes. The results showed that the Kd models were accurate in estimating Kd (R2= 0.88–0.93). Overall, the GPP first increased and then decreased with increasing Kd. When Kd&amp;lt; Ko (Ko, the diffuse radiation fraction corresponding to the maximum value of GPP), the direct PAR decreased as Kd increased, while the diffuse PAR increased rapidly. At this stage, the diffuse fertilization effect led to an increase in GPP. When Ko&amp;lt;Kd&amp;lt;Kdiff-max (Kdiff-max, the diffuse radiation fraction corresponding to the maximum value of diffuse PAR), as Kd increased the direct PAR still decreased and the diffuse PAR still increased, but the GPP declined. When Kd&amp;gt;Kdiff-max, the diffuse PAR began to decrease, and the reduction in the superimposed direct PAR caused the GPP of the canopy to drop rapidly. The LUE of the vegetation canopy was higher under diffuse light conditions than under direct light. Furthermore, with an increase in the Kd, the negative value change of the NEE was consistent with the GPP, but the ER was less affected by the Kd. Finally, the impact of temperature (TA) and vapor pressure deficit (VPD) on the GPP was unimodal, and the impact on the NEE was U-shaped. In addition, latent heat (LE) had a significant positive effect on GPP and NEE. Our study emphasized the relationship between the change in PAR composition and the Kd, as well as its impact on the carbon fluxes change, which is highly important to the study of carbon neutralization.

Identifying the dominant climate-driven uncertainties in modeling gross primary productivity

Accurate simulation of gross primary productivity (GPP) is essential for estimating the global carbon budget. However, GPP modeling is subject to various sources of uncertainties, among which the impacts of biases in climate forcing data have not been well quantified. Here, using a well-validated vegetation model, we compare site-level simulations using either ground-based meteorology or assimilated reanalyses to identify climate-driven uncertainties in the predicted GPP at 91 FLUXNET sites. Simulations yield the lowest root mean square errors (RMSE) in GPP relative to observations when all site-level meteorology and CO2 concentrations are used. Sensitivity tests conducted with Modern-Era Retrospective Analysis (MERRA) reanalyses increase GPP RMSE by 30%. Replacement of site-level CO2 with global annual average values provides limited contributions to these changes. In contrast, GPP uncertainties increase almost linearly with the biases in meteorology. Among all factors, photosynthetically active radiation (PAR), especially diffuse PAR, plays dominant roles in modulating GPP uncertainties. Simulations using all MERRA forcings but with site-level diffuse PAR help reduce over 50% of the climate-driven biases in GPP. Our study reveals that biases in meteorological forcings, especially the variabilities at diurnal to seasonal time scales, can induce significant uncertainties in the simulated GPP at FLUXET sites. We suggest cautions in simulating global GPP using climate reanalyses for dynamic global vegetation models and urgent improvements in climatic variability in reanalyses data, especially for diffuse radiation.

Atmospheric aerosols elevated ecosystem productivity of a poplar plantation in Beijing, China

Atmospheric aerosols can influence energy allocation, environmental factors, and thus, canopy photosynthesis. However, the regulations of aerosols on ecosystem productivity are not well understood. Here, we applied the optical properties of aerosols to quantify the effects of aerosol type and concentration on the environmental factors and associated gross primary productivity (GPP) of a poplar (Populus euramericana) plantation during the months of June to August from 2014 to 2016 in Beijing, China. As aerosol optical depth (AOD) increased from 0 to 2.5, total photosynthetically active radiation (PAR) decreased by 29%, while the diffuse PAR increased by 39%. Although there was no significant impact of aerosols on air temperature (p &gt; 0.05), aerosols decreased vapor pressure deficit by more than 40%. We found that the plantation GPP changed exponentially with AOD, indicating that aerosols elevated GPP by about 37% under severe aerosol pollution (AOD ≥ 1) compared with background aerosol (AOD &lt; 0.4). Aerosols type also had a significant effect on GPP. We concluded that aerosols could increase the GPP of the poplar plantation, and the promotion effect of aerosols on poplar plantation would not be significantly reduced until AOD was &lt;1 under the projected decrease in aerosol loading in the future.

The Response of the Amazon Ecosystem to the Photosynthetically Active Radiation Fields: Integrating Impacts of Biomass Burning Aerosol and Clouds in the NASA GEOS ESM

Abstract. The Amazon experiences fires every year, and the resulting biomass burning aerosols, together with cloud particles, influence the penetration of sunlight through the atmosphere, increasing the ratio of diffuse to direct photosynthetically active radiation (PAR) reaching the vegetation canopy and thereby potentially increasing ecosystem productivity. In this study, we use the NASA Goddard Earth Observing System (GEOS) model running with coupled aerosol, cloud, radiation, and ecosystem modules to investigate the impact of Amazon biomass burning aerosols on ecosystem productivity, as well as the role of the Amazon’s clouds in tempering the impact. The study focuses on a seven-year period (2010–2016) during which the Amazon experienced a variety of dynamic environments (e.g., La Nina, normal years, and El Nino). The radiative impacts of biomass burning aerosols on ecosystem productivity – call here the aerosol light fertilizer effect – are found to increase Amazonian Gross Primary Production (GPP) by 2.6 % via a 3.8 % increase in diffuse PAR (DFPAR) despite a 5.4 % decrease in direct PAR (DRPAR) on multiyear average. On a monthly basis, this increase in GPP can be as large as 9.9 % (occurring in August 2010). Consequently, the net primary production (NPP) in the Amazon is increased by 1.5 %, or ~92 TgCyr−1– equivalent to ~37 % of the carbon lost due to Amazon fires over the seven years considered. Clouds, however, strongly regulate the effectiveness of the aerosol light fertilizer effect. The efficiency of the fertilizer effect is highest for cloud-free conditions and linearly decreases with increasing cloud amount until the cloud fraction reaches ~0.8, at which point the aerosol-influenced light changes from being a stimulator to an inhibitor of plant growth. Nevertheless, interannual changes in the overall strength of the aerosol light fertilizer effect are primarily controlled by the large interannual changes in biomass burning aerosols rather than by changes in cloudiness during the studied period.

Characterizing the three-dimensional spatiotemporal variation of forest photosynthetically active radiation using terrestrial laser scanning data

The three-dimensional (3-D) spatiotemporal distribution of forest canopy photosynthetically active radiation (PAR) is a major determinant of within-crown variations of leaf photosynthesis and transpiration. However, it remains challenging to map the 3-D spatiotemporal distribution of PAR within and under the forest canopy due to the limited ability to capture the detailed 3-D structures of forest canopies.This study proposes a simple approach to estimate the 3-D spatiotemporal distribution of forest canopy PAR at a fine spatial resolution based on terrestrial laser scanner (TLS) data by characterizing difference in transfer of incident solar direct PAR and diffuse PAR and by considering the effect of the orientation angles of foliage elements on the 3-D distribution of direct PAR. Estimated PAR was validated using 10-minute PAR measurements from pyranometers at different locations within four forest plots, at which effective leaf area index (LAIe) ranged from 0.83–4.25. It showed that the proposed method captured 85% (N=2831, p<0.001) of the variations in the field pyranometer measurements. Furthermore, the proposed method was also applicable for estimating the vertical distribution of PAR (R2=0.95, N=15, p<0.001). Direct, diffuse, and total PAR exhibited similar vertical distributions changing with LAIe. It was shown that without differentiation of direct and diffuse PAR or ignoring effects of orientation angles of foliage elements may cause errors of about 20% in the estimated 3-D PAR distribution. Furthermore, the results indicated that the proposed method can be used to estimate the vertical distribution of PAR when the average neighbor point distance (NPD) is ≤20 cm. This proposed method will be usable for accurate separation of sunlit and shaded leaves and estimation of vertical distribution of PAR, which will benefit to reduce uncertainties in the estimation of terrestrial carbon fluxes and retrieval of vegetation structural and biochemical parameters.

Changes of Light Components and Impacts on Interannual Variations of Photosynthesis in China Over 2000–2017 by Using a Two‐Leaf Light Use Efficiency Model

AbstractDiffuse radiation produces a higher light use efficiency (LUE) than does direct radiation. However, light components and their impacts on interannual variations of photosynthesis in China have not been intensively studied. We estimated gross primary production (GPP) from a two‐leaf LUE model that incorporates a diffuse radiation effect and compared it with a big‐leaf LUE model that ignores the diffuse radiation impact. The results show that a dimming occurred in China—the estimated annual photosynthetically active radiation (PAR) declined by −1.79 MJ m−2 yr−1. However, the diffuse fraction and diffuse PAR increased over this interval. Both GPP models simulated an increasing trend of GPP in China from 2000 to 2017. The big‐leaf GPP model underestimated the increasing trend of GPP from the two‐leaf GPP model by 6.4%. The diffuse fraction change during the dimming exerted an embedded positive impact relative to the big‐leaf GPP trend in China.To evaluate the impact of total PAR versus its components on GPP, annual anomaly percentage (Ap) of GPP shows that the big‐leaf GPP model had a positive correlation between Ap of GPP and PAR across China. Considering the diffuse radiation impact, Ap of two‐leaf GPP was negatively correlated with PAR in southern China, which had a higher leaf area index (2.02) and a greater diffuse fraction (0.63). Strong diffuse radiation effects in southern China produced GPP anomalies in opposition to the direction of the PAR changes. These findings highlight the distinctive impact of light components on interannual variations of plant photosynthesis.

Responses of gross primary productivity to diffuse radiation at global FLUXNET sites

Diffuse radiation can promote ecosystem gross primary productivity (GPP) and strengthen land carbon sink. However, measurements of diffuse radiation at carbon flux sites are rare, limiting the explorations of diffuse fertilization efficiency (DFE), the percentage changes of GPP per unit diffuse photosynthetically active radiation (PAR). Here, we derive diffuse radiative fraction (Kd) at >200 FLUXNET sites based on an artificial neural network (ANN) and estimate DFE at individual sites around the world. Evaluations show that the ANN on average increases modeling-to-observation correlation coefficients and the Willmott index of Kd by 8% and reduces root-mean-square error by 14.7% compared to 11 empirical models. High Kd of 0.6–0.82 is located at mid-high latitudes and relatively low Kd of 0.46–0.58 is found at subtropical regions. The optimal Kd leading to maximum GPP is estimated to be 0.46 averaged for all FLUXNET sites. In response to 1 W m−2 enhancement of diffuse PAR, daytime GPP increases by 0.44–1.01% for tree species and 0.16–0.94% for non-tree species. Such GPP enhancement by diffuse radiation is on average 2.5 times of that by the same amount of direct radiation.

Spatio-Temporal Variation in AOD and Correlation Analysis with PAR and NPP in China from 2001 to 2017

Atmospheric aerosols can elicit variations in how much solar radiation reaches the ground surface due to scattering and absorption, which may affect plant photosynthesis and carbon uptake in terrestrial ecosystems. In this study, the spatio-temporal variations in aerosol optical depth (AOD) are compared with that in photosynthetically active radiation (PAR) and net primary productivity (NPP) during 2001–2017 in China using multiple remote sensing data. The correlations between them are analyzed at different scales. Overall, the AOD exhibited a northeast-to-southwest decreasing pattern in space. A national increasing trend of 0.004 year−1 and a declining trend of −0.007 year−1 of AOD are observed during 2001–2008 and 2009–2017. The direct PAR (PARdir) and diffuse PAR (PARdif) present consistent and opposite tendency with AOD during two periods, respectively. The total PAR (PARtotal) shows a similar variation pattern with PARdir. In terms of annual variation, the peaks of AOD coincide with the peaks of PARdif and the troughs of PARdir, indicating that aerosols have a significant positive impact on PARdir and a negative impact on PARdif. Furthermore, the PARdir has a stronger negative association with AOD than the positive correlation between PARdif and AOD at national and regional scales, indicating that PARdir is more sensitive to aerosol changes. The NPP has higher values in the east than in the west and exhibits a significant increasing trend of 0.035 gCm−2day−1 after 2008. The NPP has a negative correlation (−0.4–0) with AOD and PARdif and a positive correlation (0–0.4) with PARdir in most areas of China. The area covered by forests has the highest NPP-PAR correlation, indicating that NPP in forests is more sensitive to the PAR than is the NPP in grasslands and croplands. This study is beneficial for interpreting the aerosol-induced PAR impact on plant growth and for predicting plant production on haze days.

Modelling Three-Dimensional Spatiotemporal Distributions of Forest Photosynthetically Active Radiation Using UAV-Based Lidar Data

The three dimensional (3-D) spatiotemporal variations of forest photosynthetically active radiation (PAR) dictate the exchange rates of matter and energy in the carbon and water cycle processes between the plant-soil system and the atmosphere. It is still challenging to explicitly simulate spatial PAR values at any specific position within or under a discontinuous forest canopy. In this study, we propose a novel lidar-based approach to estimate both direct and diffuse forest PAR components from a 3-D perspective. An improved path length-based direct PAR estimation method was developed by incorporating the point density along a light transmission path, and we also obtained the diffuse PAR components using a point-based sky view analysis by assuming the anisotropic sky diffuse distribution. We compared the total PAR modelled using three light path length-based parameters with reference data measured by radiometers on a five-minute time scale during a daily solar course. Our results show that, in a discontinuous forest canopy, the effective path length is a feasible and powerful (R2 = 0.92, p &lt; 0.01) parameter to capture the spatiotemporal variations of total PAR along a light transmission path with a mean bias of −53.04 μmol·m−2·s−1(−6.8%). Furthermore, incorporating point density and spatial distribution factors will further improve the final estimation accuracy (R2 = 0.97, p &lt; 0.01). In the meantime, diffuse PAR tends to be overestimated by 17% at noon and underestimated by about 10% at sunrise and sunset periods by assuming the isotropic sky diffuse distribution. The proposed lidar-based 3-D PAR model will provide a solid foundation to various process-based eco-hydrological models for simulating plant physiological processes such as photosynthesis and evapotranspiration, intra-species competition and succession, and snowmelt dynamics purposes.

Global radiation, photosynthetically active radiation, and the diffuse component dataset of China, 1981–2010

Abstract. Solar radiation, especially photosynthetically active radiation (PAR), is the main energy source of plant photosynthesis, and the diffuse component can enhance canopy light use efficiency, thus increasing ecosystem productivity. In order to predict the terrestrial ecosystem productivity precisely, we not only need global radiation and PAR as driving variables, but also need to treat diffuse radiation and diffuse PAR explicitly in ecosystem models. Therefore, we generated a series of radiation datasets, including global radiation, diffuse radiation, PAR, and diffuse PAR of China from 1981 to 2010, based on the observations of the China Meteorology Administration (CMA) and the Chinese Ecosystem Research Network (CERN). The dataset should be useful for the analysis of the spatiotemporal variations of solar radiation in China and the impact of diffuse radiation on terrestrial ecosystem productivity based on ecosystem models. The dataset is freely available from Zenodo on the following website: https://zenodo.org/record/1198894#.Wx6–C_MwWo (https://doi.org/10.11922/sciencedb.555, Ren et al., 2018).

A long-term time series of global and diffuse photosynthetically active radiation in the Mediterranean: interannual variability and cloud effects

Abstract. Measurements of global and diffuse photosynthetically active radiation (PAR) have been carried out on the island of Lampedusa, in the central Mediterranean Sea, since 2002. PAR is derived from observations made with multi-filter rotating shadowband radiometers (MFRSRs) by comparison with a freshly calibrated PAR sensor and by relying on the on-site Langley plots. In this way, a long-term calibrated record covering the period 2002–2016 is obtained and is presented in this work. The monthly mean global PAR peaks in June, with about 160 W m−2, while the diffuse PAR reaches 60 W m−2 in spring or summer. The global PAR displays a clear annual cycle with a semi amplitude of about 52 W m−2. The diffuse PAR annual cycle has a semi amplitude of about 12 W m−2. A simple method to retrieve the cloud-free PAR global and diffuse irradiances in days characterized by partly cloudy conditions has been implemented and applied to the dataset. This method allows retrieval of the cloud-free evolution of PAR and calculation of the cloud radiative effect, CRE, for downwelling PAR. The cloud-free monthly mean global PAR reaches 175 W m−2 in summer, while the diffuse PAR peaks at about 40 W m−2. The cloud radiative effect, CRE, on global and diffuse PAR is calculated as the difference between all-sky and cloud-free measurements. The annual average CRE is about −14.7 W m−2 for the global PAR and +8.1 W m−2 for the diffuse PAR. The smallest CRE is observed in July, due to the high cloud-free condition frequency. Maxima (negative for the global, and positive for the diffuse component) occur in March–April and in October, due to the combination of elevated PAR irradiances and high occurrence of cloudy conditions. Summer clouds appear to be characterized by a low frequency of occurrence, low altitude, and low optical thickness, possibly linked to the peculiar marine boundary layer structure. These properties also contribute to produce small radiative effects on PAR in summer. The cloud radiative effect has been deseasonalized to remove the influence of annual irradiance variations. The monthly mean normalized CRE for global PAR can be well represented by a multi-linear regression with respect to monthly cloud fraction, cloud top pressure, and cloud optical thickness, as determined from satellite MODIS observations. The behaviour of the normalized CRE for diffuse PAR can not be satisfactorily described by a simple multi-linear model with respect to the cloud properties, due to its non-linear dependency, in particular on the cloud optical depth. The analysis suggests that about 77 % of the global PAR interannual variability may be ascribed to cloud variability in winter.

MODIS-derived global land products of shortwave radiation and diffuse and total photosynthetically active radiation at 5 km resolution from 2000

Incident shortwave radiation (SW), photosynthetically active radiation (PAR), and diffuse PAR (PARdif) at the land surface drive a multitude of processes related to biosphere-atmosphere interactions and play a critical role in the Earth climate system. Previous global solar radiation products were spatially coarse (>50-km resolution) or temporally short (a few years), which hindered scaling-up ground based observations of the land surface processes into regional, continental, and global scales across multiple time scales. Here, we report Breathing Earth System Simulator (BESS) SW, PAR, and PARdif products over the global land surface at a 5km resolution with 4day intervals between 2000 and 2016. We combined an atmospheric radiative transfer model with an artificial neural network (ANN) to compute SW, PAR, and PARdif. A series of MODerate Resolution Imaging Spectroradiometer (MODIS) atmosphere and land products were used as inputs to run the ANN. We test the performance of the products using data from 158 (SW), 77 (PAR), and 22 (PARdif) stations collected in the Baseline Surface Radiation Network (BSRN) and flux tower networks, which covered a range of climatic zones from polar to tropical zones. BESS had strong linear relationships with in-situ SW data (R2=0.95, relative bias=−2.3%), PAR (R2=0.94, relative bias=1.7%), and PARdif (R2=0.84, relative bias=0.2%). BESS captured the interannual variability of SW at both the site (a majority of long-term BSRN sites) and continental levels. Over the study period, global annual SW, PAR, and PARdif values did not show any dimming or brightening trends, although these trends appeared at regional levels, e.g. dimming in India. Mean annual SW over the global land surface was 184.8Wm−2 (875ZJyr−1, zetta=1021); 46% of SW was partitioned to PAR, which was further split into direct (59%) and diffuse (41%) components. The developed products will be useful in solar energy harvesting research and will improve water, carbon, and energy flux estimates of terrestrial ecosystems from local to the global scales.

Mapping diffuse photosynthetically active radiation from satellite data in Thailand

In this paper, calculation of monthly average hourly diffuse photosynthetically active radiation (PAR) using satellite data is proposed. Diffuse PAR was analyzed at four stations in Thailand. A radiative transfer model was used for calculating the diffuse PAR for cloudless sky conditions. Differences between the diffuse PAR under all sky conditions obtained from the ground-based measurements and those from the model are representative of cloud effects. Two models are developed, one describing diffuse PAR only asa function of solar zenith angle, and the second one asa multiple linear regression with solar zenith angle and satellite reflectivity acting linearly and aerosol optical depth acting in logarithmic functions. When tested with an independent data set, the multiple regression model performed best with a higher coefficient of variance R2 (0.78 vs. 0.70), lower root mean square difference (RMSD) (12.92% vs. 13.05%) and the same mean bias difference (MBD) of −2.20%. Results from the multiple regression model are used to map diffuse PAR throughout the country as monthly averages of hourly data.

Border row effects on light interception in wheat/maize strip intercropping systems

In strip intercropping systems, different crop rows in a complete strip usually behave differently in growth dynamics and have distinct contribution to the final yield of the system, so resources capture and utilization processes of different crop rows should be treated separately in the performance evaluation of the whole system. This study was conducted to investigate the differences in light capture among different crop rows in wheat/maize strip intercropping systems. The field experiment comprised four planting patterns: monoculture wheat, monoculture maize, six rows of wheat alternated with two rows of maize (I62), and twelve rows of wheat alternated with four rows of maize (I124). A geometrical radiation transmission model was modified to estimate instantaneous light capture by different intercropped rows, which was tested with photosynthetically active radiation (PAR) measured above and beneath the intercrop canopy. The results demonstrated that the model accurately predicted PAR transmitted through the canopy with mean absolute error, root mean square error (RMSE) and normalized RMSE of 60.2μmolm−2s−1, 82.6μmolm−2s−1 and 5.2% respectively for I62 and of 65.9μmolm−2s−1, 95.3μmolm−2s−1 and 5.7% respectively for I124. With assistance of the model, we found that border rows in wheat strip intercepted far greater amount of both direct and diffuse PAR than the inner rows, whereas maize border rows showed no advantage in PAR absorption due to its canopy development was constrained by the competition from wheat strip. Canopy structure character showed positive effects on radiation interception in wheat border rows and all maize rows, and plant phenotypic plasticity showed positive effects on wheat border rows but negative effects on maize border rows. The radiation transmission model presented in this work was proved to be a useful tool for calculating spatial and temporal variability of radiation in strip intercropping systems and it can be further served as a base for modeling the plant growth dynamics in strip intercrops.