Mean monthly net longwave radiation modelled using the 1" DEM-S - 1" tiles

Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as 1x1 degree tiles in ESRI float grid format. 813 tiles make up the extent of Australia. The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18611 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18612\nLineage: Source data\n1. 1 arcsecond SRTM-derived Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016)\n2. Aspect derived from the 1 arcsecond SRTM DEM-S\n3. Slope derived from the 1 arcsecond SRTM DEM-S\n4. Monthly cloud cover fraction (Jovanovic et al., 2011)\n5. Monthly albedo derived from AVHRR (Donohue et al., 2010)\n6. Monthly minimum and maximum air temperature (Bureau of Meteorology)\n7. Monthly vapour pressure (Bureau of Meteorology)\n8. Monthly fractional cover (Donohue et al., 2010)\n9. Monthly black-sky and white-sky albedo from MODIS (MCD43A3, B3) (Paget and King, 2008; NASA LP DAAC, 2013)\n10. Measurements of daily sunshine hours, 9 am and 3pm cloud cover, and daily solar radiation from meteorological stations around Australia (Bureau of Meteorology)\n\nSolar radiation model\nSolar radiation was calculated using the SRAD model (Wilson and Gallant, 2000), which accounts for:\n\tAnnual variations in sun-earth distance\n\tSolar geometry based on latitude and time of year\n\tThe orientation of the land surface relative to the sun\n\tShadowing by surrounding topography\n\tClear-sky and cloud transmittance\n\tSunshine fraction (cloud-free fraction of the day) in morning and afternoon\n\tSurface albedo\n\tThe effects of surface temperature on outgoing long-wave radiation, which is modulated by incoming radiation and moderated by vegetation cover\n\tAtmospheric emissivity based on vapour pressure\n\nAll input parameters were long-term averages for each month, i.e., monthly climatologies of cloud cover, air temperature, vapour pressure, fractional cover, AVHRR albedo and MODIS albedo.\n\nCircumsolar coefficient was fixed both spatially and temporally at 0.25, while clear sky atmospheric transmissivity and cloud transmittance were varied. Transmittance measures the fraction of radiation passing through a material (air or clouds in this case), while transmissivity measures that fraction for a specified amount of material. SRAD uses a transmittance parameter for cloud, representing an average of all cloud types during cloudy periods, and a transmissivity parameter for clear sky so that the transmittance can vary with the position of the sun in the sky and hence the thickness of atmosphere that radiation passes through on its way to the ground. The clear sky transmissivity τ and cloud transmittance β were calibrated using observed daily radiation and sunshine hours. \n\nReferences\nDonohue R. J., McVicar T. R. and Roderick M. L. (2010a). Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. Journal of Hydrology, 386, 186-197, doi:10.1016/j.jhydrol.2010.03.020.\n\nDonohue, R. J., T. R. McVicar, L. Lingtao, and M. L. Roderick (2010b). A data resource for analysing dynamics in Australian ecohydrological conditions, Austral Ecol, 35, 593–594, doi: 10.1111/j.1442-9993.2010.02144.x.\n\nErbs, D. G., S. A. Klein, and J. A. Duffie (1982), Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation, Solar Energy, 28(4), 293-302.\n\nJovanovic, B., Collins, D., Braganza, K., Jakob, D. and Jones, D.A. (2011). A high-quality monthly total cloud amount dataset for Australia. Climatic Change, 108, 485-517.\n\nNASA Land Processes Distributed Active Archive Center (LP DAAC) (2013). MCD43A3, B3. USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota\n\nPaget, M.J. and King, E.A. (2008). MODIS Land data sets for the Australian region. CSIRO Marine and Atmospheric Research Internal Report No. 004. https://remote-sensing.nci.org.au/u39/public/html/modis/lpdaac-mosaics-cmar\n\nWilson, J.P. and Gallant, J.C. (2000) Secondary topographic attributes, chapter 4 in Wilson, J.P. and Gallant, J.C. Terrain Analysis: Principles and Applications, John Wiley and Sons, New York.

本数据集依托1弧秒分辨率SRTM衍生数字高程模型（DEM-S）的地形数据，结合气候与地表参数，对澳大利亚全域的月均太阳辐射开展建模。本研究采用SRAD辐射模型（Wilson与Gallant，2000）推导得到以下参数：
• 倾斜地表入射短波辐射
• 短波辐射比值（倾斜地表短波辐射/水平地表短波辐射）
• 入射长波辐射
• 出射长波辐射
• 净长波辐射
• 净辐射
• 天空可视因子（sky view factor）

所有辐射参数的单位均为兆焦/平方米·日（MJ/m²/day），仅短波辐射比值无量纲。天空可视因子指某网格单元相对于水平面的可见天空占比。

本数据集的辐射参数基于各月中旬（14日或15日）的长期平均大气条件（如云量、大气透射率）与地表条件（反照率、植被覆盖度）计算得到，涵盖地形坡度、坡向与遮蔽效应（基于日出至日落期间每5分钟间隔的太阳位置计算），包含直接辐射、散射辐射与天空视域的影响。

本数据集的月均数据以1弧秒分辨率发布，格式为ESRI浮点栅格（ESRI float grid），分幅为1×1度瓦片，共计813张瓦片覆盖澳大利亚全境。1弧秒分辨率镶嵌数据可通过以下链接获取：https://data.csiro.au/dap/landingpage?pid=csiro:18611。

3弧秒分辨率的辐射表面数据由1弧秒分辨率数据通过3×3窗口聚合取均值生成。3弧秒分辨率镶嵌数据可通过以下链接获取：https://data.csiro.au/dap/landingpage?pid=csiro:18612

#### 数据源谱系
1. 1弧秒分辨率SRTM衍生平滑数字高程模型（DEM-S；ANZCW0703014016）
2. 基于1弧秒分辨率SRTM DEM-S提取的坡向数据
3. 基于1弧秒分辨率SRTM DEM-S提取的坡度数据
4. 月均云量占比（Jovanovic等，2011）
5. 基于先进甚高分辨率辐射计（AVHRR）提取的月均反照率（Donohue等，2010）
6. 月均最低与最高气温（澳大利亚气象局）
7. 月均水汽压（澳大利亚气象局）
8. 月均植被覆盖占比（Donohue等，2010）
9. 基于中分辨率成像光谱仪（MODIS，MCD43A3，B3）的月均晴空与云天反照率（Paget与King，2008；美国国家航空航天局陆地过程分布式数据档案中心（NASA LP DAAC），2013）
10. 澳大利亚境内气象站观测的每日日照时长、上午9时与下午3时云量，以及每日太阳辐射数据（澳大利亚气象局）

#### SRAD辐射模型计算说明
本数据集采用SRAD辐射模型（Wilson与Gallant，2000）计算太阳辐射，该模型考量以下因素：
- 日地距离的年际变化
- 基于纬度与季节的太阳几何关系
- 地表相对于太阳的朝向
- 周边地形造成的遮蔽效应
- 晴空与云层的透射特性
- 上午与下午的日照占比（当日无云时段占比）
- 地表反照率
- 地表温度对出射长波辐射的影响，该效应受入射辐射调控，并由植被覆盖度调节
- 基于水汽压的大气发射率

所有输入参数均为各月的长期平均数据，即云量、气温、水汽压、植被覆盖占比、AVHRR反照率与MODIS反照率的月均气候态数据。

环太阳系数在空间与时间维度上均固定为0.25，而晴空大气透射率与云层透射率则为可变参数。其中，透射率指辐射穿过介质（本研究中为空气或云层）的比例；透射性则指特定厚度介质的辐射穿透比例。SRAD模型采用云层透射率参数代表多云时段所有云型的平均穿透特性，并采用晴空透射率参数，以使透射率随太阳在天空中的位置变化，即随辐射抵达地面需穿过的大气厚度变化。晴空透射率τ与云层透射率β通过实测每日辐射与日照时长数据进行校准。

#### 参考文献
1. Donohue R. J., McVicar T. R. and Roderick M. L. (2010a). Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. *Journal of Hydrology*, 386, 186-197, doi:10.1016/j.jhydrol.2010.03.020.
2. Donohue, R. J., T. R. McVicar, L. Lingtao, and M. L. Roderick (2010b). A data resource for analysing dynamics in Australian ecohydrological conditions, *Austral Ecol*, 35, 593–594, doi: 10.1111/j.1442-9993.2010.02144.x.
3. Erbs, D. G., S. A. Klein, and J. A. Duffie (1982), Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation, *Solar Energy*, 28(4), 293-302.
4. Jovanovic, B., Collins, D., Braganza, K., Jakob, D. and Jones, D.A. (2011). A high-quality monthly total cloud amount dataset for Australia. *Climatic Change*, 108, 485-517.
5. NASA Land Processes Distributed Active Archive Center (LP DAAC) (2013). MCD43A3, B3. USGS/Earth Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota
6. Paget, M.J. and King, E.A. (2008). MODIS Land data sets for the Australian region. CSIRO Marine and Atmospheric Research Internal Report No. 004. https://remote-sensing.nci.org.au/u39/public/html/modis/lpdaac-mosaics-cmar
7. Wilson, J.P. and Gallant, J.C. (2000) Secondary topographic attributes, chapter 4 in Wilson, J.P. and Gallant, J.C. *Terrain Analysis: Principles and Applications*, John Wiley and Sons, New York.