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Cloud Fraction from Cloud Mask vs Total Sky Imager Comparison of 1 and 4 km Data The native resolution of the vis channel on GOES Imager is roughly 1 km.

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Presentation on theme: "Cloud Fraction from Cloud Mask vs Total Sky Imager Comparison of 1 and 4 km Data The native resolution of the vis channel on GOES Imager is roughly 1 km."— Presentation transcript:

1 Cloud Fraction from Cloud Mask vs Total Sky Imager Comparison of 1 and 4 km Data The native resolution of the vis channel on GOES Imager is roughly 1 km and resolution of the thermal channels is 4 km. PATMOS-x processes both 1 and 4km GOES imager data. When processing 4km data, the vis channel is under-sampled. When processing 1 km data, the thermal channels are over-sampled. The images below show example of 1 and 4 km cloud optical thickness over OH/PA/WV on Day 88 of 2013 at 17:32Z. The vis channel is most relevant for solar energy and the benefits outweigh the errors introduced by the thermal channel sampling. We are assuming the closer we approach the spatial and temporal scales that impact solar energy plants, the better. High Resolution Cloud Products from GOES to Support the Solar Power Industry Andrew K Heidinger 1, Christine C Molling 2 1. STAR, NOAA/NESDIS, Madison, WI; 2. CIMSS/SSEC, University of Wisconsin, Madison, WI Introduction The Department of Energy’s SunShot Initiative seeks to make un- subsidized solar power as affordable as that generated by fossil fuels. One barrier to affordable solar power is the inability for large power generation facilities to forecast short-term power ramps caused by transient clouds, and the inability to accurately forecast power generation capacity 24 hours in advance. NOAA and the UW CIMSS are supporting the SunShot effort by providing high resolution cloud products derived from GOES imagery. While the standard NOAA operation products (GSIP) are generated hourly from 4 km data, the resolution of the data provided for SunShot will be 1 km (spatial) and 15 minute (temporal). GOAL IS TO AID THE DEVELOPMENT OF SHORT-TERM SOLAR ENERGY FORECATS MADE BY THE SUNSHOT TEAMS (NCAR & IBM). Methodology The PATMOS-x cloud algorithms are used in the NESDIS operational AVHRR and GOES cloud processing systems and based on the GOES- R AWG approaches. PATMOS-x will be run at UW/CIMSS using data from the SSEC Data Center. Relevant products are cloud optical depth, solar transmission/albedo, phase and height. PATMOS-x can also generate SASRAB solar fluxes incoordination with the SASRAB developer (Dr. Istvan Laszlo) Goal to generate products within 5 minutes using domains from GOES/East and GOES/West over the CONUS region. SURFRAD Comparison The validation of the PATMOS-x cloud properties for solar energy applications is accomplished via comparisons to the SURface RADiation Network (SURFRAD) run by NOAA/OAR/ESRL. SURFRAD is also a part of the NOAA SunShot Effort. SURFRAD provides downwelling/upwelling solar and thermal fluxes at the surface and other meteorological parameters. We derived a cloud transmission using the SURFRAD fluxes and a simple model of the clear-sky solar fluxes. Conclusions NOAA and UW/CIMSS are supporting an important DOE/NOAA solar energy initiative (SunShot). NOAA will provide GOES cloud products leveraging GOES-R AWG research to aid in the short-term forecasting of cloudiness over solar energy sites. The new 1 km results are shown to agree well with SURFRAD estimates of cloud transmission. Correlation with SURFRAD is higher using 1 km than 4 km results but more advanced comparison techniques are needed to better quantify this. Impact of Spatial Resolution on Performance These images show 3 days of cloud transmission comparisons from 1-km PATMOS-x and SURFRAD. SURFRAD sites are PSU, GWN and BON. 15-minute window for SURFRAD 10-km window for PATMOS-x Results are not-conclusive but correlations are higher with 1km vs. 4 km data. More advanced comparisons (use wind to adjust window) are being developed. Ramp Potential = Max – Min Transmission. RAMPS are large deviations in solar energy that represent a large forecasting issue for solar energy. 1 km 4 km Computation of Cloud Solar Transmission from SURFRAD Cloud transmission is a product from the PATMOS-x DCOMP algorithm. Converting SURFRAD fluxes into a cloud transmission allows for a direct comparison to the GOES-derived cloud transmission. This process is highlighted below. The TOA downward solar flux and the atmospheric transmission are modeled (blue lines). The Cloud Transmission = the Total Trans / The Non-Cloud Trans. Computation of Cloud Solar Transmission from SURFRAD Cloud transmission is a product from the PATMOS-x DCOMP algorithm. Converting SURFRAD fluxes into a cloud transmission allows for a direct comparison to the GOES-derived cloud transmission. This process is highlighted below. The TOA downward solar flux and the atmospheric transmission are modeled (blue lines). The Cloud Transmission = the Total Trans / The Non-Cloud Trans. 1km product resolves more cloud breaks. 1km (n=53) & 4km (n=4) are averaged over 5km box. * PATMOS-x products are more accurate than TSI at low sun angles. * Ohio West Virginia Pennsylvania Ohio West Virginia Pennsylvania andrew.heidinger@noaa.gov christine.molling@ssec.wisc.edu


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