Spatial and temporal patterns of solar radiation based on topography and air temperature

Incident solar radiation is a driving force for many ecological and hydrological processes. For this study, we developed TopoRad, a new radiation model, to describe spatial and temporal patterns of daily radiation based on topog- raphy and daily temperature regimes. The model was applied to the Mount Jumbong Forest, located in the mid-eastern area of the Korean peninsula; and the model calculations were evaluated by varying the spatial scales of the digital ele - vation models (DEMs). In the TopoRad, a clearness index was used to calculate global radiation on a horizontal sur- face and to partition direct and diffuse radiation. Topographic corrections were separately calculated for each direct and diffuse radiation, using daily topographic modifiers calculated from a DEM. TopoRad predicted daily global radiation of five weather stations with a mean absolute error of 3.1 MJ·m -2 ·day -1 and a mean bias of -0.3 MJ·m -2 ·day -1 .I n the spatial application for Mount Jumbong Forest, distinctively different patterns between direct and diffuse radiations were found where direct radiation (5.2 MJ·m -2 ·day -1 ) had more influence than diffuse radiation (4.6 MJ·m -2 ·day -1 ) on annual mean daily radiation. When the scaling effect was inspected across different spatial resolutions, the predicted global ra - diation was nonlinearly related to spatial resolutions. As the spatial resolution became more coarse, the predicted radia - tion decreased for south-facing slopes and increased for north-facing slopes, indicating that the predictions from the models cannot be generalized for gradients. TopoRad is better suited to predict daily radiation in rugged landscapes where fine-scale prediction is required. Resume : Le rayonnement solaire incident est la source d'energie de plusieurs processus ecologiques et hydrologiques. Dans le cadre de cette etude, nous avons developpe un nouveau modele de rayonnement, TopoRad, pour decrire les va- riations spatiale et temporelle du rayonnement journalier sur la base de la topographie et du regime journalier de tem- perature. Le modele a ete utilise a la foret du mont Jumbong qui est situee dans le centre-est de la peninsule coreenne. Les calculs effectues par le modele ont ete evalues en faisant varier l'echelle spatiale des modeles numeriques d'altitude. TopoRad utilise un indice de clarte pour estimer le rayonnement global sur une surface horizontale et sepa- rer les rayonnements direct et diffus. Les corrections topographiques ont ete calculees separement pour les rayonne- ments direct et diffus, en utilisant des modificateurs topographiques journaliers estimes au moyen d'un modele numerique d'altitude. TopoRad a predit le rayonnement global journalier pour cinq stations meteorologiques avec une erreur absolue moyenne de 3,1 MJ·m -2 ·jour -1 et un biais moyen de -0,3 MJ·m -2 ·jour -1 . Des patrons nettement differents ont ete observes pour les rayonnements direct et diffus suite a l'application spatiale du modele a la foret du mont Jum - bong. Le rayonnement direct (5,2 MJ·m -2 ·jour -1 ) avait plus d'influence sur la moyenne annuelle du rayonnement jour- nalier que le rayonnement diffus (4,6 MJ·m -2 ·jour -1 ). Lorsque l'effet d'echelle a ete examine en ayant recours a differentes resolutions spatiales, le rayonnement journalier calcule etait non lineairement relie a la resolution spatiale. A mesure que la resolution spatiale devient plus grossiere, le rayonnement calcule diminue sur les pentes orientees au sud et augmente sur les pentes orientees au nord, indiquant que les predictions des modeles ne peuvent pas etre generali - sees pour les gradients. TopoRad est mieux adapte pour predire le rayonnement journalier pour les paysages accidentes ou il est necessaire d'obtenir une prediction a petite echelle. (Traduit par la Redaction) Kang et al. 497

[1]  J. Dozier,et al.  A faster solution to the horizon problem , 1981 .

[2]  Ralph Dubayah,et al.  Topographic Solar Radiation Models for GIS , 1995, Int. J. Geogr. Inf. Sci..

[3]  S. Running,et al.  A general model of forest ecosystem processes for regional applications I. Hydrologic balance, canopy gas exchange and primary production processes , 1988 .

[4]  P. Rich,et al.  Modeling topographic influences on solar radiation: A manual for the SOLARFLUX Model , 1995 .

[5]  Oleg Antonić,et al.  Modelling daily topographic solar radiation without site-specific hourly radiation data , 1998 .

[6]  T. O. Aro,et al.  The Diffuse Fraction of Global Solar Irradianceat a Tropical Location , 1998 .

[7]  J. Monteith,et al.  Principles of Environmental Physics , 2014 .

[8]  J. Duffie,et al.  Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation , 1982 .

[9]  F. J. Barnes,et al.  Hetrick, W.A., P.M. Rich, F.J. Barnes, and S.B. Weiss. 1993. GIS-based solar radiation flux models. American Society for Photogrammetry and Remote Sensing Technical Papers. Vol 3, GIS. Photogrammetry, and Modeling. pp 132-143. GIS-BASED SOLAR RADIATION FLUX MODELS , 1993 .

[10]  R. Dubayah.  Estimating net solar radiation using Landsat Thematic Mapper and digital elevation data , 1992 .

[11]  S. Running,et al.  An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation , 1999 .

[12]  L. Swift,et al.  Algorithm for solar radiation on mountain slopes , 1976 .

[13]  Sinkyu Kang,et al.  Significance of aspect and understory type to leaf litter redistribution in a temperate hardwood forest , 1999 .

[14]  J. Orgill,et al.  Correlation equation for hourly diffuse radiation on a horizontal surface , 1976 .

[15]  Peter E. Thornton,et al.  Generating surfaces of daily meteorological variables over large regions of complex terrain , 1997 .

[16]  H. Wackernagel,et al.  Mapping temperature using kriging with external drift: Theory and an example from scotland , 1994 .

[17]  R. Dubayah,et al.  Modeling Topographic Solar Radiation Using GOES Data , 1997 .

[18]  F. Vignola,et al.  Diffuse-global correlation: Seasonal variations , 1984 .

[19]  M. Iqbal.  An introduction to solar radiation , 1983 .

[20]  J. Aber,et al.  A generalized, lumped-parameter model of photosynthesis, evapotranspiration and net primary production in temperate and boreal forest ecosystems , 1992, Oecologia.

[21]  L. Hadjioannou,et al.  On the diffuse fraction of daily and monthly global radiation for the island of Cyprus , 1996 .

[22]  J. Kimball,et al.  Topographic and climatic controls on soil respiration in six temperate mixed‐hardwood forest slopes, Korea , 2003 .

[23]  R. Dubayah.  Modeling a solar radiation topoclimatology for the Rio Grande River Basin , 1994 .

[24]  K.G.T. Hollands,et al.  A derivation of the diffuse fraction's dependence on the clearness index , 1985 .

[25]  Ramakrishna R. Nemani,et al.  MTCLIM: a mountain microclimate simulation model , 1989 .

[26]  G. Campbell,et al.  On the relationship between incoming solar radiation and daily maximum and minimum temperature , 1984 .

[27]  A. Flint,et al.  Calculation of solar radiation in mountainous terrain , 1987 .

[28]  S. Jose,et al.  Leaf Area-Productivity Relationships Among Mixed-Species Hardwood Forest Communities of the Central Hardwood Region , 1997 .

[29]  W. Beckman,et al.  Solar Engineering of Thermal Processes , 1985 .

[30]  H. Gholz.  Applications of Physiological Ecology to Forest Management , 1997 .

[31]  Peter E. Thornton,et al.  Simultaneous estimation of daily solar radiation and humidity from observed temperature and precipitation: an application over complex terrain in Austria. , 2000 .

[32]  Ramakrishna R. Nemani,et al.  Extrapolation of synoptic meteorological data in mountainous terrain and its use for simulating forest evapotranspiration and photosynthesis , 1987 .

[33]  J. Dozier,et al.  Rapid calculation of terrain parameters for radiation modeling from digital elevation data , 1990 .

[34]  R. Waring,et al.  A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning , 1997 .

[35]  Sinkyu Kang,et al.  Predicting spatial and temporal patterns of soil temperature based on topography, surface cover and air temperature , 2000 .

[36]  Clayton V. Deutsch,et al.  GSLIB: Geostatistical Software Library and User's Guide , 1993 .