[Effects of radiation changes on net ecosystem exchange of carbon dioxide in a middle subtropical Chinese fir plantation]. / 辐射变化对中亚热带杉木人工林净CO2交换的影响.

Total solar radiation is an important factor affecting carbon exchange in forest ecosystem. In order to understand the effects of radiation change on carbon exchange in Chinese fir plantation, long-term monitoring data of carbon dioxide flux and meteorological factors measured by open eddy covariance system and meteorological gradient observation system were used in this study. The clearness index (kt) was used to represent the condition of solar radiation. We analyzed the effects of kt on net ecosystem exchange of carbon dioxide (NEE) in the central subtropical Chinese fir plantation during the growing season (from April to October). The results showed that total solar radiation in clear sky was usually higher in the morning than that in the afternoon, and that NEE was lower in the morning than in the afternoon. Such difference in NEE reached the maximum when the solar elevation angle was about 50°. At the medium kt(0.42-0.52), carbon absorption of Chinese fir plantation was the strongest. The ave-rage maximum relative change of NEE in 10 years in different solar elevation angles ranged from 11.0% to 29.4%, while the minimum and maximum critical values appeared at 35°-40° and 45°-50°, respectively. When kt was at the moderate degree due to the existence of clouds, carbon absorption and diffuse photosynthetically active radiation of Chinese fir plantation reached the maximum, and the latter might be the main reason for the former. Moderate radiation condition with the presence of cloud clould promote NEE of Chinese fir plantation and lead to largest carbon absorption.

Hourly global horizontal irradiance data of three stations in Punjab, Pakistan.

This paper presents hourly Global Horizontal Irradiance (GHI) measured data at three stations (Lahore, Multan, Bahawalpur) in Punjab, Pakistan. The estimated GHI data from three reanalysis datasets have also been presented. Clearness index (KT ), Solar zenith angle (θsza) and Periodicity factor (Pf) were calculated and used to develop bias correction models. The estimated corrected GHI data using best model M20 for years 2015 and 2016 is also presented.

Prediction of site-specific solar diffuse horizontal irradiance from two input variables in Colombia.

Accurate measurements of diffuse irradiance are essential to design a solar photovoltaic system. However, in-situ radiation measurements in Colombia, South America, can be limited by the costs of the implementation of meteorological stations equipped with a pyranometer mounted on a sun tracker with a shading device, which is required to measure diffuse irradiance. Furthermore, the databases found in Colombia contain missing data, which raises the need for implementing models that are trained with very few features. In this paper, we introduce a methodology based on simple angle calculations and a regression model to predict half-hourly diffuse horizontal solar irradiance from only the measure of global horizontal irradiance and a geographic coordinate as inputs. Using measurements taken from the national solar radiation database for 6 different sites in Colombia and state-of-the-art machine learning models for regression, we validated the accuracy prediction of the proposed methodology. The results showed a prediction error ranging from 5.86 to 9.36 [W/m 2], and a coefficient of determination ranging from 0.9974 to 0.9983. The data-set used along with the feature engineering process and the deep neural network model created can be found in a Github repository referenced in the paper.

Integrating SIF and Clearness Index to Improve Maize GPP Estimation Using Continuous Tower-Based Observations.

Solar-induced chlorophyll fluorescence (SIF) has been proven to be well correlated with vegetation photosynthesis. Although multiple studies have found that SIF demonstrates a strong correlation with gross primary production (GPP), SIF-based GPP estimation at different temporal scales has not been well explored. In this study, we aimed to investigate the quality of GPP estimates produced using the far-red SIF retrieved at 760 nm (SIF760) based on continuous tower-based observations of a maize field made during 2017 and 2018, and to explore the responses of GPP and SIF to different meteorological conditions, such as the amount of photosynthetically active radiation (PAR), the clearness index (CI, representing the weather condition), the air temperature (AT), and the vapor pressure deficit (VPD). Firstly, our results showed that the SIF760 tracked GPP well at both diurnal and seasonal scales, and that SIF760 was more linearly correlated to PAR than GPP was. Therefore, the SIF760-GPP relationship was clearly a hyperbolic relationship. For instantaneous observations made within a period of half an hour, the R2 value was 0.66 in 2017 and 2018. Based on daily mean observations, the R2 value was 0.82 and 0.76 in 2017 and 2018, respectively. and had an R2 value of 0.66 (2017) and 0.66 (2018) for instantaneous observations made within a period of half an hour and 0.82 (2017) and 0.76 (2018) for daily mean observations. Secondly, it was found that the SIF760-GPP relationship varied with the environmental conditions, with the CI being the dominant factor. At both diurnal and seasonal scales, the ratio of GPP to SIF760 decreased noticeably as the CI increased. Finally, the SIF760-based GPP models with and without the inclusion of CI were trained using 70% of daily observations from 2017 and 2018 and the models were validated using the remaining 30% of the dataset. For both linear and non-linear models, the inclusion of the CI greatly improved the SIF760-based GPP estimates based on daily mean observations: the value of R2 increased from 0.71 to 0.82 for the linear model and from 0.82 to 0.87 for the non-linear model. The validation results confirmed that the SIF760-based GPP estimation was improved greatly by including the CI, giving a higher R2 and a lower RMSE. These values improved from R2 = 0.66 and RMSE = 7.02 mw/m2/nm/sr to R2 = 0.76 and RMSE = 6.36 mw/m2/nm/sr for the linear model, and from R2 = 0.71 and RMSE = 4.76 mw/m2/nm/sr to R2 = 0.78 and RMSE = 3.50 mw/m2/nm/sr for the non-linear model. Therefore, our results demonstrated that SIF760 is a reliable proxy for GPP and that SIF760-based GPP estimation can be greatly improved by integrating the CI with SIF760. These findings will be useful in the remote sensing of vegetation GPP using satellite, airborne, and tower-based SIF data because the CI is usually an easily accessible meteorological variable.

Linking diffuse radiation and ecosystem productivity of a desert steppe ecosystem.

Radiation components have distinct effects on photosynthesis. In the desert steppe ecosystem, the influence of diffuse radiation on carbon fixation has not been thoroughly explored. We examined this diffusion and its effect on ecosystem productivity was examined during the growing season from 2014 to 2015 on the basis of eddy covariance measurements of CO2 exchange in a desert steppe ecosystem in northwest China. Our results indicated that the gross ecosystem production (GEP) and diffuse photosynthetically active radiation (PARdif) peaked when the clearness index (CI) was around 0.5. The maximum canopy photosynthesis (Pmax) under cloudy skies (CI < 0.7) was 23.7% greater than under clear skies (CI ≥ 0.7). When the skies became cloudy in the desert steppe ecosystem, PARdif had a greater effect on GEP. Additionally, lower vapor pressure deficits (VPD ≤ 1 kPa), lower air temperatures (Ta ≤ 20 °C), and non-stressed water conditions (REW ≥ 0.4) were more conducive for enhanced ecosystem photosynthesis under cloudy skies than under clear skies. This may be due to the comprehensive effects of VPD and Ta on stomatal conductance. We concluded that cloudiness can influence diffuse radiation components and that diffuse radiation can increase the ecosystem production of desert steppe ecosystems in northwest China.

[Responses of net ecosystem carbon exchange to diffuse radiation in an alpine meadow on the Qinghai-Tibetan Plateau, China.] / 青藏高原高寒草甸净生态系统碳交换对散射辐射变化的响应.

Qinghai-Tibetan Plateau, one of the regions on the earth that receives the most solar radiation, is the world's highest alpine meadow ecosystem, with significance to regional and global carbon cycles. To examine the effects of solar radiation on ecosystem carbon dynamics in an alpine meadow, the net ecosystem CO2 exchange (NEE), solar radiation, diffuse radiation, and related environmental variables were measured using eddy-covariance technique and micro-meteorological system. Sky conditions were divided into three categories of clear days (CI≥0.7), cloudy days (0.315 ℃. Under clear sky day conditions, Re increased with increasing CI due to the increases of air temperature, with negative effects on NEE. NEE increased with the increases of VPD up to 0.6 kPa, then slowly decreased when VPD>0.6 kPa, illustrating that NEE was reduced due to the relatively high VPD. Our results suggested that strong solar radiation on clear days would not increase carbon uptake capacity of alpine meadow, while cloudy days with clearness index of 0.6-0.7 would help increase carbon sequestration on the Qinghai-Tibetan Plateau.

Light use efficiency of a warm-temperate mixed plantation in north China.

Light use efficiency (LUE) is one of the important parameters on calculating terrestrial gross primary productivity (GPP) and net primary productivity (NPP). Based on 5-year (2006-2010) carbon flux and climatic variable data of a mixed plantation in north China, the seasonal and interannual variation of LUE was investigated and the biophysical controls were examined. Our results show that LUE had a distinct seasonal course, and peaked in the vigorous growing season with a value of 0.92-1.27 g C MJ-1. During the period of 2006-2010, annual mean LUE ranged between 0.54 and 0.62 g C MJ-1, and it was linearly correlated with annual GPP. In the growing season, LUE was significantly linked with the water availability variables (including monthly mean vapor pressure deficit (VPD), precipitation, evaporative fraction (EF), and the ratio of precipitation to evapotranspiration (P/ET)) and canopy conductance (g c). However, EF was a better estimator of LUE compared with other biophysical variables. LUE decreased with an increase of the clearness index (CI), indicating that LUE was higher under cloudy sky conditions than that under sunny sky conditions in the mixed plantation.

Hourly photosynthetically active radiation estimation in Midwestern United States from artificial neural networks and conventional regressions models.

The relationship between hourly photosynthetically active radiation (PAR) and the global solar radiation (R s ) was analyzed from data gathered over 3 years at Bondville, IL, and Sioux Falls, SD, Midwestern USA. These data were used to determine temporal variability of the PAR fraction and its dependence on different sky conditions, which were defined by the clearness index. Meanwhile, models based on artificial neural networks (ANNs) were established for predicting hourly PAR. The performance of the proposed models was compared with four existing conventional regression models in terms of the normalized root mean square error (NRMSE), the coefficient of determination (r (2)), the mean percentage error (MPE), and the relative standard error (RSE). From the overall analysis, it shows that the ANN model can predict PAR accurately, especially for overcast sky and clear sky conditions. Meanwhile, the parameters related to water vapor do not improve the prediction result significantly.

[Monitoring temporal dynamics in leaf area index of the temperate broadleaved deciduous forest in Maoershan region, Northeast China with tower-based radiation measurements.] / 基于塔载辐射监测帽儿山落叶阔叶林.

Broadband vegetation indices (BVIs) derived from routine radiation measurements on eddy flux towers have the advantage of high temporal resolutions, and thus have the potential to obtain detailed information of dynamics in canopy leaf area index (LAI). Taking the temperate broadleaved deciduous forest around the Maoershan flux tower in Northeast China as a case, we investigated the controlling factors and smoothing method of four BVI time-series, i.e., broadband norma-lized difference vegetation index (NDVIB), broadband enhanced vegetation index (EVIB), the ratio of the near-infrared radiation reflectance to photosynthetically active radiation reflectance (SRNP), and the ratio of the shortwave radiation reflectance to photosynthetically active radiation reflectance (SRSP). We compared the seasonal courses of the BVIs with the LAI based on litterfall collection method. The values for each BVI were slightly different among the three calculation methods by Huemmrich, Wilson, and Jenkins, but showed similar seasonal patterns. The diurnal variations in BVIs were mainly influenced by the solar elevation and the angle between the solar elevation and slope, but the BVIs were relatively stable around 12:30. The noise of daily BVI time-series could be effectively smoothed by a threshold of clearness index (K). The seasonal courses of BVIs for each time of day around the noon had similar patterns, but their thresholds of K and the percen-tages of remaining data were different. Therefore, the daily values of BVIs might be optimized based on the smoothing and the proportion of remaining data. The NDVIB was closely correlated linearly with the LAI derived from the litterfall collection method, while the EVIB, SRNP, and SRSP had a logarithmic relationship with the LAI. The NDVIB had the advantage in tracking the seasonal dyna-mics in LAI and extrapolating LAI to a broader scale. Given that most eddy flux towers had equipped with energy balance measurements, a network of monitoring canopy LAI could be readily achieved if the reflectance of photosynthetically active radiation was measured synchronously.

Effect of the relative optical air mass and the clearness index on solar erythemal UV irradiance.

This paper analyses the effects of the clearness index (Kt) and the relative optical air mass (mr) on erythemal UV irradiance (UVER). The UVER measurements were made in Valencia (Spain) from 6:00 am to 6:00 pm between June 2003 and December 2012 and (140,000 data points). Firstly, two models were used to calculate values for the erythemal ultraviolet irradiance clearness index (KtUVER) as a function of the global irradiance clearness index (Kt). Secondly, a potential regression model to measure the KtUVER as a function of the relative optical air mass was studied. The coefficients of this regression were evaluated for clear and cloudy days, as well as for days with high and low ozone levels. Thirdly, an analysis was made of the relationship between the two effects in the experimental database, with it being found that the highest degree of agreement, or the joint highest frequencies, are located in the optical mass range mr∈[1.0, 1.2] and the clearness index range of Kt∈[0.8, 1.0]. This is useful for establishing the ranges of parameters where models are more efficient. Simple equations have been tested that can provide additional information for the engineering projects concerning thermal installations. Fourthly, a high dispersion of radiation data was observed for intermediate values of the clearness for UV and UVER.