Comparison of algorithms for incoming atmospheric long-wave radiation

While numerous algorithms exist for predicting incident atmospheric long-wave radiation under clear (Lclr) and cloudy skies, few comparisons have been published to assess the accuracy of the different algorithms. Virtually no comparisons have been made for both clear and cloudy skies across multiple sites. This study evaluates the accuracy of 13 algorithms for predicting incident long-wave radiation under clear skies, ten cloud correction algorithms, and four algorithms for all-sky conditions using data from 21 sites across North America and China. Data from five research sites were combined with publicly available data from nine sites in the AmeriFlux network for initial evaluation and optimization of cloud cover estimates; seven additional AmeriFlux sites were used as an independent test of the algorithms. Clear-sky algorithms that excelled in predicting Lclr were the Dilley, Prata, and Angström algorithms. Root mean square deviation (RMSD) between predicted and measured 30-minute or hourly Lclr averaged approximately 23 W m-2 for these three algorithms across all sites, while RMSD of daily estimates was as low as 14 W m-2. Cloud-correction algorithms of Kimball, Unsworth, and Crawford described the data best when combined with the Dilley clear-sky algorithm. Average RMSD across all sites for these three cloud corrections was approximately 24 to 25 W m -2 for 30-minute or hourly estimates and approximately 15 to 16 W m-2 for daily estimates. The Kimball and Unsworth cloud corrections require an estimate of cloud cover, while the Crawford algorithm corrects for cloud cover directly from measured solar radiation. Optimum limits in the clearness index, defined as the ratio of observed solar radiation to theoretical terrestrial solar radiation, for complete cloud cover and clear skies were suggested for the Kimball and Unsworth algorithms. Application of the optimized algorithms to seven independent sites yielded similar results. On the basis of the results, the recommended algorithms can be applied with reasonable accuracy for a wide range of climates, elevations, and latitudes. © 2009 by American Geophysical Union

Energy balance simulation of a wheat canopy using the RZ-SHAW (RZWQM-SHAW) model

RZ-SHAW is a new hybrid model coupling the Root Zone Water Quality Model (RZWQM) and the Simultaneous Heat and Water (SHAW) model to extend RZWQM applications to conditions of frozen soil and crop residue cover. RZ-SHAW offers the comprehensive land management options of RZWQM with the additional capability to simulate diurnal changes in energy balance needed for simulating the near-surface microclimate and leaf temperature. The objective of this study was to evaluate RZ-SHAW for simulations of radiation balance and sensible and latent heat fluxes over plant canopies. Canopy energy balance data were collected at various growing stages of winter wheat in the North China Plain (36° 57'N, 116° 6'E, 28 m above sea level). RZ-SHAW and SHAW simulations using hourly meteorological data were compared with measured net radiation, latent heat flux, sensible heat flux, and soil heat flux. RZ-SHAW provided similar goodness-of-prediction statistics as the original SHAW model for all the energy balance components when using observed plant growth input data. The root mean square error (RMSE) for simulated net radiation, latent heat, sensible heat, and soil heat fluxes was 29.7, 30.7, 29.9, and 25.9 W m -2 for SHAW and 30.6, 32.9, 34.2, and 30.6 W m -2 for RZ-SHAW, respectively. Nash-Sutcliffe R 2 ranged from 0.67 for sensible heat flux to 0.98 for net radiation. Subsequently, an analysis was performed using the plant growth component of RZ-SHAW instead of inputting LAI and plant height. The model simulation results agreed with measured plant height, yield, and LAI very well. As a result, RMSE for the energy balance components were very similar to the original RZ-SHAW simulation, and latent, sensible, and soil heat fluxes were actually simulated slightly better. RMSE for simulated net radiation, latent heat, sensible heat, and soil heat fluxes was 31.5, 30.4, 30.2, and 27.6 W m -2, respectively. Overall, the results demonstrated a successful coupling of RZWQM and SHAW in terms of canopy energy balance simulation, which has important implications for prediction of crop growth, crop water stress, and irrigation scheduling

An Improved ångström-type model for estimating solar radiation over the tibetan plateau

© 2017 by the authors. For estimating the annual mean of daily solar irradiation in plateau mountainous regions, observed data from 15 radiation stations were used to validate different empirical estimation methods over the Tibetan Plateau. Calibration indicates that sunshine-based site-dependent models perform better than temperature-based ones. Then, the highly rated sunshine-based Ångström model and temperature-based Bristow model were selected for regional application. The geographical models perform much better than the average models, but still not ideally. To achieve better performance, the Ångström-type model was improved using altitude and water vapor pressure as the leading factors. The improved model can accurately predict the coefficients at all the stations, and performs the best among all models with an average Nash-Sutcliffe Efficiency value of 0.856. Spatial distribution of the annual mean of daily solar irradiation was then estimated with the improved model. It is indicated that there is an increasing trend of radiation from east to west, with a great center of the annual mean of daily solar irradiation on southwest Tibetan Plateau ranging from 20 to 24 MJm2. The improved model should be further validated against observations before its applications in other plateau mountainous regions

Simplified expressions for radiation scattering in canopies with ellipsoidal leaf angle distributions

The ability to simulate the surface energy balance and microclimate within a plant canopy is contingent upon accurate simulation of radiation exchange within the canopy. Accurate radiation simulations require some assumption of leaf angle distribution to compute transmissivity, reflection and scattering of radiation. The ellipsoidal leaf angle density function can very closely approximate real plant canopies but requires complex integrations for different combinations of leaf area index, incident radiation angle, and density function. This paper presents close approximations (R2 > 0.99) to compute the transmissivity and scattering functions for elliptical leaf angle distributions that can be more easily implemented into simulation models. © 2007 Elsevier B.V. All rights reserved

Evaluation of the SHAW model in simulating the components of net all-wave radiation

Radiation exchange at the surface plays a critical role in the surface energy balance, plant microclimate, and plant growth. The ability to simulate the surface energy balance and the microclimate within the plant canopy is contingent upon accurate simulation of the surface radiation exchange. A validation exercise was conducted of the Simultaneous Heat and Water (SHAW) model for simulating the surface radiation exchange (including downward long-wave and upward short- and long-wave radiation) over a maize canopy surface using data collected at Yucheng in the North China Plain. The model simulated upward short-wave and net all-wave radiation well with model efficiencies (ME) equaling 0.97 and 0.98, respectively. Downward and upward long-wave radiation were overestimated by 12.1 and 8.3 W m -2 with ME equaling 0.68 and 0.89, respectively. Two modifications to the model were implemented and tested to improve the simulated long-wave radiation exchange. In one modification, alternative schemes were tested to simulate cloudy sky long-wave radiation, and the best algorithm was employed in the model. With this modification, both downward and upward long-wave radiation were simulated better, with ME rising to 0.88 and 0.91, respectively. A second modification was implemented to use leaf temperature rather than canopy air temperature to compute emitted long-wave radiation. Although more theoretically correct, this modification did not improve simulations compared to the original model because upward long-wave radiation was already overpredicted and midday leaf temperatures at this site were typically higher than canopy air temperatures. Thus, the modification resulted in even higher overprediction of upward midday long-wave radiation. However, this modification removed some of the bias in nighttime emitted long-wave radiation. While the SHAW model simulates the radiation balance and transfer processes within the canopy reasonably well, results point to areas for model improvement

Simulation of within-canopy radiation exchange

Radiation exchange at the surface plays a critical role in the surface energy balance, plant microclimate, and plant growth. The ability to simulate the surface energy balance and the microclimate within the plant canopy is contingent upon simulation of the surface radiation exchange. A validation and modification exercise of the Simultaneous Heat and Water (SHAW) model was conducted for simulating the surface short-wave and long-wave radiation exchange over and within wheat, maize and soya bean plant canopies using data collected at Yucheng in the North China Plain and near Ames, Iowa. Whereas model testing was limited to monocultures and mixed canopies of green and senesced leaves, methodologies were developed for simulating short-wave and long-wave radiation fluxes applicable to a multi-species, multi-layer plant canopy. Although the original SHAW model slightly underpredicted reflected solar radiation with a mean bias error (MBE) of -5 to -10 W m-2, one would conclude that the simulations were quite reasonable if within-canopy measurements were not available. However, within-canopy short-wave radiation was considerably underestimated (MBE of approximately -20 W m-2) by the original SHAW model. Additionally, leaf temperatures tended to be overpredicted (MBE = +0.76 °C) near the top of the canopy and underpredicted near the bottom (MBE = -1.12 °C). Modification to the SHAW model reduced MBE of above canopy reflected radiation to -1 to -6 W m-2 and within-canopy radiation simulations to approximately -6 W m-2; bias in leaf temperature was reduced to less than 0.4 °C. Model modifications resulted in essentially no change in simulated evapotranspiration for wheat, 4.5% lower for maize and 1% higher for soya bean. Alternative approaches for simulating canopy transmissivity to diffuse radiation were tested in the modified version and had a minor influence on simulated short-wave radiation, but made almost no difference in simulated long-wave radiation or evapotranspiration. Modifications to the model should lead to more accurate plant microclimate simulation; further work is needed to evaluate their influence. © 2009 Royal Netherlands Society for Agricultural Sciences

Evaluation of SHAW model in simulating energy balance, leaf temperature, and micrometeorological variables within a maize canopy

Understanding and simulating plant canopy conditions can assist in better acknowledgment of plant microclimate characteristics, its effect on plant processes, and the influence of management and climate scenarios. The ability of the Simultaneous Heat and Water (SHAW) model to simulate the surface energy balance and profiles of leaf temperature and micrometeorological variables within a maize canopy and the underlying soil temperatures was tested using data collected during 1999 and 2003 at Yucheng, in the North China Plain. The SHAW model simulates the near-surface heat and water movement driven by input meteorological variables and observed plant characteristic (leaf area index [LAI], height, and rooting depth). For 1999, the model accurately simulated air temperature and relative humidity in the upper one-third of the canopy, but overpredicted midday temperature in the lower canopy. For 2003, although the surface energy balance was simulated quite well, radiometric canopy surface temperature and midday leaf temperature in the upper portion of the canopy were overpredicted, by approximately 5°C. Model efficiency (the fraction of variation in observed values explained by the model) for leaf temperature in the lower two-thirds of the canopy ranged from 0.82 to 0.90, but fell to 0.38 for the uppermost canopy layer. Weaknesses in the model were identified and potentially include: the use of K-theory to simulate turbulent transfer within the canopy; and simplifying assumptions with regard to long-wave radiation transfer within the canopy. Model modifications are planned to address these weaknesses. © American Society of Agronomy

Surface fluxes and water balance of spatially varying vegetation within a small mountainous headwater catchment

Precipitation variability and complex topography often create a mosaic of vegetation communities in mountainous headwater catchments, creating a challenge for measuring and interpreting energy and mass fluxes. Understanding the role of these communities in modulating energy, water and carbon fluxes is critical to quantifying the variability in energy, carbon, and water balances across landscapes. The focus of this paper was: (1) to demonstrate the utility of eddy covariance (EC) systems in estimating the evapotranspiration component of the water balance of complex headwater mountain catchments; and (2) to compare and contrast the seasonal surface energy and carbon fluxes across a headwater catchment characterized by large variability in precipitation and vegetation cover. Eddy covariance systems were used to measure surface fluxes over sagebrush (Artemesia arbuscula and Artemesia tridentada vaseyana), aspen (Populus tremuloides) and the understory of grasses and forbs beneath the aspen canopy. Peak leaf area index of the sagebrush, aspen, and aspen understory was 0.77, 1.35, and 1.20, respectively. The sagebrush and aspen canopies were subject to similar meteorological forces, while the understory of the aspen was sheltered from the wind. Missing periods of measured data were common and made it necessary to extrapolate measured fluxes to the missing periods using a combination of measured and simulated data. Estimated cumulative evapotranspiratation from the sagebrush, aspen trees, and aspen understory were 384 mm, 314 mm and 185 mm. A water balance of the catchment indicated that of the 699 mm of areal average precipitation, 421 mm was lost to evapotranspiration, and 254 mm of streamflow was measured from the catchment; water balance closure for the catchment was within 22 mm. Fluxes of latent heat and carbon for all sites were minimal through the winter. Growing season fluxes of latent heat and carbon were consistently higher above the aspen canopy than from the other sites. While growing season carbon fluxes were very similar for the sagebrush and aspen understory, latent heat fluxes for the sagebrush were consistently higher, likely because it is more exposed to the wind. Sensible heat flux from the aspen tended to be slightly less than the sagebrush site during the growing season when the leaves were actively transpiring, but exceeded that from the sagebrush in May, September and October when the net radiation was not offset by evaporative cooling in the aspen. Results from this study demonstrate the utility of EC systems in closing the water balance of headwater mountain catchments and illustrate the influence of vegetation on the spatial variability of surface fluxes across mountainous rangeland landscapes. © Author(s) 2010

Modeling a wheat-maize double cropping system in China using two plant growth modules in RZWQM

Agricultural system models are potential tools for evaluating soil-water-nutrient management in intensive cropping systems. In this study, we calibrated and validated the Root Zone Water Quality Model (RZWQM) with both a generic plant growth module (RZWQM-G) and the CERES plant growth module (RZWQM-C) for simulating winter wheat (Triticum aestivum L.) and maize (Zea mays L.) double cropping systems in the Northern China Plain (NCP), China. Data were obtained from an experiment conducted at Yucheng Integrated Agricultural Experimental Station (36°57′N, 116°36′E, 28 m asl) in the North China Plain (NCP) from 1997 to 2001 (eight crop seasons) with field measurements of evapotranspiration, soil water, soil temperature, leaf area index (LAI), biomass and grain yield. Using the same soil water and nutrient modules, both plant modules were calibrated using the data from one crop sequence during 1998-1999 when detailed measurements of LAI and biomass growth were available. The calibrated models were then used to simulate maize and wheat production in other years. Overall simulation runs from 1997 to 2001 showed that the RZWQM-C model simulated grain yields with a RMSE of 0.94 Mg ha -1 in contrast to a RMSE of 1.23 Mg ha-1 with RZWQM-G. The RMSE for biomass simulation was 2.07 Mg ha-1 with RZWQM-G and 2.26 Mg ha-1 with RZWQM-C model. The RMSE values of simulated evapotranspiration, soil water, soil temperature and LAI were 1.4 mm, 0.046 m3 m-3, 1.75°C and 1.0 for RZWQM-G and 1.4 mm, 0.047 m3 m-3, 1.84°C and 1.1 for RZWQM-C, respectively. The study revealed that both plant models were able to simulate the intensive cropping systems once they were calibrated for the local weather and soil conditions. Sensitivity analysis also showed that a reduction of 25% of current water and N applications reduced N leaching by 24-77% with crop yield reduction of 1-9% only. © 2005 Elsevier Ltd. All rights reserved

Effect of precipitation change on water balance and WUE of the winter wheat-summer maize rotation in the North China Plain

Limited precipitation restricts crop yield in the North China Plain, where high level of production depends largely on irrigation. Establishing the optimal irrigation scheduling according to the crop water requirement (CWR) and precipitation is the key factor to achieve rational water use. Precipitation data collected for about 40 years were employed to analyze the long-term trend, and weather data from 1984 to 2005 were used to estimate the CWR and irrigation water requirements (IWR). Field experiments were performed at the Luancheng Station from 1997 to 2005 to calculate the soil water consumption and water use efficiency (WUE). The results showed the CWR for winter wheat and summer maize were similar and about 430 mm, while the IWR ranged from 247 to 370 mm and 0 to 336 mm at the 25% and 75% precipitation exceedance probabilities for winter wheat and summer maize, respectively. The irrigation applied varied in the different rainfall years and the optimal irrigation amount was about 186, 161 and 99 mm for winter wheat and 134, 88 and 0 mm for summer maize in the dry, normal and wet seasons, respectively. However, as precipitation reduces over time especially during the maize growing periods, development of water-saving management practices for sustainable agriculture into the future is imperative. © 2009 Elsevier B.V. All rights reserved