d8ce54cb1c5ae135addc24e351ee34f7 Roca-Pons-Ninyerola_atmosphere_3610773.pdf a63cb1f562ba3f3603ec90244616ad767c05666c Roca-Pons-Ninyerola_atmosphere_3610773.pdf be7d404fc82ecf48d529527bdaa3248fea1ed046aa58289cfa685b616887b6e6 Roca-Pons-Ninyerola_atmosphere_3610773.pdf Title: A Comparison of Different Solar Radiation Models in the Iberian Peninsula Subject: Solar radiation is a first-order essential climate variable like temperature and precipitation. Its significant spatiotemporal variability, mainly due to atmospheric conditions, makes modelling particularly challenging, especially in regions with complex atmospheric dynamics and sparse meteorological stations. This study evaluates 6 solar radiation models (SARAH, PVGIS, Constant Atmospheric Conditions, Physical Solar Model, CAMS Worldwide, and InsolMets) using monthly measurements from 141 ground-based stations across the Iberian Peninsula from 2004–2020. Although all models consistently captured intra-annual variability, discrepancies in absolute values arise due to factors such as the differences in their functional designs and input parameters. InsolMets, which integrates cloud optical thickness, cloud fractional cover, the diffuse radiation component, and enhanced solar illumination geometry, was the most robust model, showing relevant improvements (61.5% in January, 59.7% in November, and 52.0% in December) compared to the worst-performing model (constant atmospheric conditions). Using as a threshold three times the root-mean-square error (RMSE) proposed by the Global Climate Observing System, InsolMets achieved the highest number of months (10) under this limit, also achieving the best overall result, with only 1 month showing non-significant correlations over the same time span. Nevertheless, SARAH and PVGIS matched InsolMets’ performance during March, November, and December. The results provide insights for selecting and improving solar radiation estimations, highlighting the need to incorporate remote sensing atmospheric data to minimize uncertainties. While all models that account for atmospheric effects enhance accuracy, InsolMets stands out as the most accurate model for estimating solar radiation across the Iberian Peninsula throughout the year, achieving the lowest RMSE and normalized RMSE values. Keywords: solar radiation; solar energy; spatiotemporal atmospheric data; quality filters; model validation processes; model comparison Author: Catalina Roca-Fernández, Xavier Pons and Miquel Ninyerola Creator: LaTeX with hyperref Producer: pdfTeX-1.40.25 CreationDate: Thu May 15 08:29:02 2025 CEST ModDate: Tue May 20 10:29:39 2025 CEST Custom Metadata: no Metadata Stream: yes Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 31 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 2105931 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- GSINYH+VnURWPalladioL Type 1 Custom yes yes yes 10 0 CKLBGW+URWPalladioL-Roma Type 1 Custom yes yes yes 16 0 YCULCY+URWPalladioL-Bold Type 1 Custom yes yes yes 22 0 WDKRSQ+URWPalladioL-Ital Type 1 Custom yes yes yes 27 0 XKAFMT+MinionPro-Regular CID Type 0C Identity-H yes yes yes 815 0 BVKSVL+CMSY10 Type 1 Builtin yes yes yes 62 0 VHXXZC+EURM10 Type 1 Builtin yes yes yes 76 0 CEOHVJ+PalatinoLinotype-Roman CID TrueType Identity-H yes yes yes 94 0 TGAFZB+PalatinoLinotype-Bold CID TrueType Identity-H yes yes yes 102 0 ZFYKFP+PalatinoLinotype-Italic TrueType WinAnsi yes yes yes 110 0 HJBLNZ+PalatinoLinotype-Bold TrueType WinAnsi yes yes yes 114 0 JZYXPV+PalatinoLinotype-Roman TrueType WinAnsi yes yes yes 118 0 CEOHVJ+PalatinoLinotype-Roman CID TrueType Identity-H yes yes yes 143 0 TGAFZB+PalatinoLinotype-Bold CID TrueType Identity-H yes yes yes 151 0 ZFYKFP+PalatinoLinotype-Italic TrueType WinAnsi yes yes yes 159 0 HJBLNZ+PalatinoLinotype-Bold TrueType WinAnsi yes yes yes 163 0 JZYXPV+PalatinoLinotype-Roman TrueType WinAnsi yes yes yes 167 0 JUDXBO+CMBSY10 Type 1 Builtin yes yes yes 196 0 CEOHVJ+PalatinoLinotype-Roman CID TrueType Identity-H yes yes yes 204 0 TGAFZB+PalatinoLinotype-Bold CID TrueType Identity-H yes yes yes 212 0 ZFYKFP+PalatinoLinotype-Italic TrueType WinAnsi yes yes yes 220 0 HJBLNZ+PalatinoLinotype-Bold TrueType WinAnsi yes yes yes 224 0 JZYXPV+PalatinoLinotype-Roman TrueType WinAnsi yes yes yes 228 0 QQXUPP+PazoMath Type 1 Builtin yes yes yes 237 0 CEOHVJ+PalatinoLinotype-Roman CID TrueType Identity-H yes yes yes 253 0 ZFYKFP+PalatinoLinotype-Italic TrueType WinAnsi yes yes yes 261 0 HJBLNZ+PalatinoLinotype-Bold TrueType WinAnsi yes yes yes 265 0 JZYXPV+PalatinoLinotype-Roman TrueType WinAnsi yes yes yes 269 0 CEOHVJ+PalatinoLinotype-Roman CID TrueType Identity-H yes yes yes 286 0 TGAFZB+PalatinoLinotype-Bold CID TrueType Identity-H yes yes yes 294 0 ZFYKFP+PalatinoLinotype-Italic TrueType WinAnsi yes yes yes 302 0 HJBLNZ+PalatinoLinotype-Bold TrueType WinAnsi yes yes yes 306 0 JZYXPV+PalatinoLinotype-Roman TrueType WinAnsi yes yes yes 310 0 MOKKFP+ArialMT TrueType WinAnsi yes yes yes 314 0 Jhove (Rel. 1.28.0, 2023-05-18) Date: 2025-05-31 04:43:48 CEST RepresentationInformation: Roca-Pons-Ninyerola_atmosphere_3610773.pdf ReportingModule: PDF-hul, Rel. 1.12.4 (2023-03-16) LastModified: 2025-05-30 12:49:54 CEST Size: 2105931 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 825 FreeObjects: 2 IncrementalUpdates: 1 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: Methods Destination: section.2 Children: Item: Title: Solar Radiation Models Destination: subsection.2.1 Item: Title: SARAH Model Destination: subsection.2.2 Item: Title: PVGIS Model Destination: subsection.2.3 Item: Title: Constant Atmospheric Conditions Model Destination: subsection.2.4 Item: Title: Physical Solar Model Destination: subsection.2.5 Item: Title: CAMS Worldwide Model Destination: subsection.2.6 Item: Title: InsolMets Model Destination: subsection.2.7 Item: Title: Results and Discussion Destination: section.3 Item: Title: Conclusions Destination: section.4 Item: Title: Appendix A Destination: appendix.A. Item: Title: Appendix B Destination: appendix.B. Item: Title: References Destination: appendix.C. Info: Title: A Comparison of Different Solar Radiation Models in the Iberian Peninsula Author: Catalina Roca-Fernández, Xavier Pons and Miquel Ninyerola Subject: Solar radiation is a first-order essential climate variable like temperature and precipitation. Its significant spatiotemporal variability, mainly due to atmospheric conditions, makes modelling particularly challenging, especially in regions with complex atmospheric dynamics and sparse meteorological stations. This study evaluates 6 solar radiation models (SARAH, PVGIS, Constant Atmospheric Conditions, Physical Solar Model, CAMS Worldwide, and InsolMets) using monthly measurements from 141 ground-based stations across the Iberian Peninsula from 2004 2020. Although all models consistently captured intra-annual variability, discrepancies in absolute values arise due to factors such as the differences in their functional designs and input parameters. InsolMets, which integrates cloud optical thickness, cloud fractional cover, the diffuse radiation component, and enhanced solar illumination geometry, was the most robust model, showing relevant improvements (61.5% in January, 59.7% in November, and 52.0% in December) compared to the worst-performing model (constant atmospheric conditions). Using as a threshold three times the root-mean-square error (RMSE) proposed by the Global Climate Observing System, InsolMets achieved the highest number of months (10) under this limit, also achieving the best overall result, with only 1 month showing non-significant correlations over the same time span. Nevertheless, SARAH and PVGIS matched InsolMets’ performance during March, November, and December. The results provide insights for selecting and improving solar radiation estimations, highlighting the need to incorporate remote sensing atmospheric data to minimize uncertainties. While all models that account for atmospheric effects enhance accuracy, InsolMets stands out as the most accurate model for estimating solar radiation across the Iberian Peninsula throughout the year, achieving the lowest RMSE and normalized RMSE values. Keywords: solar radiation; solar energy; spatiotemporal atmospheric data; quality filters; model validation processes; model comparison Creator: LaTeX with hyperref Producer: pdfTeX-1.40.25 CreationDate: Thu May 15 08:29:02 CEST 2025 ModDate: Tue May 20 10:29:39 CEST 2025 ID: 0xe3682ae93be61d02e455bb2187046058, 0x92e64a5c4c78e8458a430ce61c9bb869 Filters: FilterPipeline: FlateDecode Fonts: Type0: Font: BaseFont: XKAFMT+MinionPro-Regular Encoding: Identity-H ToUnicode: true Type1: Font: BaseFont: CKLBGW+URWPalladioL-Roma FontSubset: true FirstChar: 2 LastChar: 252 FontDescriptor: FontName: CKLBGW+URWPalladioL-Roma Flags: Symbolic FontBBox: -166, -283, 1021, 943 FontFile: true EncodingDictionary: Differences: true ToUnicode: true Font: BaseFont: JUDXBO+CMBSY10 FontSubset: true FirstChar: 0 LastChar: 1 FontDescriptor: FontName: JUDXBO+CMBSY10 Flags: Symbolic FontBBox: -26, -940, 1332, 825 FontFile: true ToUnicode: true Font: BaseFont: YCULCY+URWPalladioL-Bold FontSubset: true FirstChar: 3 LastChar: 225 FontDescriptor: FontName: YCULCY+URWPalladioL-Bold Flags: Symbolic FontBBox: -152, -301, 1000, 935 FontFile: true EncodingDictionary: Differences: true ToUnicode: true Font: BaseFont: GSINYH+VnURWPalladioL FontSubset: true FirstChar: 160 LastChar: 225 FontDescriptor: FontName: GSINYH+VnURWPalladioL Flags: Symbolic FontBBox: -166, -283, 1021, 943 FontFile: true EncodingDictionary: Differences: true ToUnicode: true Font: BaseFont: WDKRSQ+URWPalladioL-Ital FontSubset: true FirstChar: 2 LastChar: 250 FontDescriptor: FontName: WDKRSQ+URWPalladioL-Ital Flags: Symbolic FontBBox: -170, -305, 1010, 941 FontFile: true EncodingDictionary: Differences: true ToUnicode: true Font: BaseFont: VHXXZC+EURM10 FontSubset: true FirstChar: 28 LastChar: 28 FontDescriptor: FontName: VHXXZC+EURM10 Flags: Symbolic FontBBox: -32, -243, 1060, 720 FontFile: true ToUnicode: true Font: BaseFont: QQXUPP+PazoMath FontSubset: true FirstChar: 229 LastChar: 229 FontDescriptor: FontName: QQXUPP+PazoMath Flags: Symbolic FontBBox: -40, -283, 878, 946 FontFile: true ToUnicode: true Font: BaseFont: BVKSVL+CMSY10 FontSubset: true FirstChar: 0 LastChar: 21 FontDescriptor: FontName: BVKSVL+CMSY10 Flags: Symbolic FontBBox: -29, -960, 1116, 775 FontFile: true ToUnicode: true CIDFontType0: Font: BaseFont: XKAFMT+MinionPro-Regular CIDSystemInfo: Registry: Adobe Registry: Identity Supplement: 0 FontDescriptor: FontName: XKAFMT+MinionPro-Regular Flags: Serif, Symbolic FontBBox: -290, -360, 1684, 989 FontFile3: true XMP: application/pdf Catalina Roca-Fernández, Xavier Pons and Miquel Ninyerola Solar radiation is a first-order essential climate variable like temperature and precipitation. Its significant spatiotemporal variability, mainly due to atmospheric conditions, makes modelling particularly challenging, especially in regions with complex atmospheric dynamics and sparse meteorological stations. This study evaluates 6 solar radiation models (SARAH, PVGIS, Constant Atmospheric Conditions, Physical Solar Model, CAMS Worldwide, and InsolMets) using monthly measurements from 141 ground-based stations across the Iberian Peninsula from 2004–2020. Although all models consistently captured intra-annual variability, discrepancies in absolute values arise due to factors such as the differences in their functional designs and input parameters. InsolMets, which integrates cloud optical thickness, cloud fractional cover, the diffuse radiation component, and enhanced solar illumination geometry, was the most robust model, showing relevant improvements (61.5% in January, 59.7% in November, and 52.0% in December) compared to the worst-performing model (constant atmospheric conditions). Using as a threshold three times the root-mean-square error (RMSE) proposed by the Global Climate Observing System, InsolMets achieved the highest number of months (10) under this limit, also achieving the best overall result, with only 1 month showing non-significant correlations over the same time span. Nevertheless, SARAH and PVGIS matched InsolMets’ performance during March, November, and December. The results provide insights for selecting and improving solar radiation estimations, highlighting the need to incorporate remote sensing atmospheric data to minimize uncertainties. While all models that account for atmospheric effects enhance accuracy, InsolMets stands out as the most accurate model for estimating solar radiation across the Iberian Peninsula throughout the year, achieving the lowest RMSE and normalized RMSE values. 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