地表太陽輻射對於生態系的平衡、農業的開發以及區域氣候的變化有顯著的影響。為了監測地表太陽輻射的變化，科學家們自1990年代起開始建立高精確度的地表太陽輻射監測網。然而，地面太陽輻射分布隨空間之變異相當大，使用最接近的觀測資料來作為太陽光電系統架設評估使用並不可靠。因此，本研究使用衛星觀測及單層輻射傳遞模式的架構，計算出區域中每日地表太陽輻射之二維分布。使用MTSAT-2衛星可見光波段之觀測可代表地球向外短波輻射之量值；Aura衛星上之OMI儀器提供了大氣總臭氧氣柱的觀測；Aqua及Terra衛星上的MODIS系統則提供了氣膠光學厚度及地表反照率之觀測；可降水量之分布則使用了NASA的Merra2再分析資料。本研究方法同時需要數個站點的地面太陽輻射觀測進行調整，已建立完整的計算模型，後續使用時則只需要各項大氣成分之觀測以及MTSAT-2衛星可見光波段之觀測資料。我們使用2013及2014年之各觀測資料進行模式建立，再使用2015年之資料進行模式計算並與氣象局地面太陽輻射觀測資料驗證。
結果顯示，此研究方法在可以應付台灣的複雜地形、高氣膠濃度以及各種類的天氣系統變化，計算出可靠的每日地表太陽輻射分布。其結果與氣象局16個地面太陽輻射觀測站的資料相比，整體的相對平均標準偏差(Relative mean bias error)為 +1.91%，相對方均根誤差(Relative root mean square error)為 15.37%。將臭氧、氣膠、與水汽分別固定為0並計算新的地表太陽輻射分布，再與原先計算之結果相比，可以得到這三個物種對太陽輻射的衰減。結果顯示水汽與臭氧分別造成了25%及2%的地表太陽輻射衰減。氣膠則衰減了12%的地表太陽輻射，其中又以彰化至屏東縣的沿海有最大的衰減率。
本研究提供了一個可靠的地面太陽輻射計算模式，用以計算台灣地面太陽輻射分布。儘管其精確度仍然不如維護良好的輻射觀測系統，但仍能提供可信的太陽輻射的分布作為太陽光電系統的設置和評估使用。另外，由氣膠對太陽輻射的衰減分析，可以推測若未來台灣的空氣污染能夠獲得有效的控制，在台灣西南部可以增加至多12%的太陽輻射量。

Solar radiation at Erath surface has notable impacts on the sustainability of ecology, management of agriculture, and even changes of regional climate. In order to monitor the variation of surface solar irradiance, scientists have built many networks measuring atmospheric radiation with high accuracy since 1990s. However, while looking for a location for new photovoltaic (PV) plant, it is not reliable to use the nearest surface measurement of irradiances representing solar energy of the site since the surface solar measurements vary significantly over space. Therefore, this thesis provides a method to derive daily regional 2-D surface solar irradiance based on satellite measurements and one-layer radiative transfer model. Data from MTSAT-2 visible band are used as a sum of out-going visible radiation. The absorption of ozone is calculated with total column ozone from OMI sensor onboard AURA satellite. Precipitable water from MERRA2 reanalysis data are used to calculate the absorption of water vapor. Attenuation of aerosol is calculated from MODIS 8-day averaged aerosol dataset. Surface measurement of solar irradiance from some locations are also needed to adjust the model. Finally, the datasets in 2013 and 2014 are used to construct the model, and data in 2015 were used to validate the accuracy of the derived daily surface solar irradiance.
As a result, this model has the ability to represent the distribution of surface solar irradiance over Taiwan with effects of annual variation of solar position, cloud formation along terrain, and aerosol loading by human abilities. The model calculation indicates a high consistency of daily irradiance with a relative mean bias error of +1.91% and relative root mean square error of 15.37% while comparing with 16 surface solar measurement sites in Taiwan. The solar radiation reduction due to the existing of ozone, water vapor and aerosols are calculated by subtracting the derived surface solar irradiance from the one without ozone, water vapor, or aerosols. Our results show a 25 % reduction of surface radiation caused by water vapor, and 2 % reduction by ozone. Aerosols also reduce solar radiation by up to 12 % in Taiwan. The maximum reduction of radiation by aerosols are located at south western Taiwan from Chunghua to Pintung County where many factories and companies are built. This result suggests that southern Taiwan has higher availability of solar energy resource but it is also hampered by higher aerosol loading. Although the precision of the method is not as good as surface measurements, this work provides a reliable and efficient database for the site survey of PV plants over Taiwan.

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