Optimal interpolation of satellite derived irradiance and ground data

Antonio T. Lorenzo; Matthias Morzfeld; William F. Holmgren; Alexander D. Cronin

doi:10.1109/PVSC.2017.8366671

Optimal interpolation of satellite derived irradiance and ground data

Antonio T. Lorenzo, Matthias Morzfeld, William F. Holmgren, Alexander D. Cronin

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We describe how Bayesian data assimilation can be used to improve nowcasts of irradiance over small, city-scale, spatial areas. Specifically, we use optimal interpolation (OI) to improve satellite derived estimates of global horizontal irradiance (GHI) using ground truth data that was collected sparsely over Tucson, AZ. Our results show that the local data indeed improves the satellite derived estimates of GHI. A key to success with OI in this context is to prescribe correlations based on cloudiness, rather than spatially. OI can be used with a variety of data, e.g., rooftop photovoltaic production data or irradiance data, as well as with several different satellite derived irradiance models.

Original language	English (US)
Title of host publication	2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2035-2038
Number of pages	4
ISBN (Electronic)	9781509056057
DOIs	https://doi.org/10.1109/PVSC.2017.8366671
State	Published - 2017
Event	44th IEEE Photovoltaic Specialist Conference, PVSC 2017 - Washington, United States Duration: Jun 25 2017 → Jun 30 2017

Publication series

Name	2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017

Other

Other	44th IEEE Photovoltaic Specialist Conference, PVSC 2017
Country/Territory	United States
City	Washington
Period	6/25/17 → 6/30/17

Keywords

Data assimilation
Optimal interpolation
Remote sensing
Solar irradiance

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials

Access to Document

10.1109/PVSC.2017.8366671

Cite this

Lorenzo, A. T., Morzfeld, M., Holmgren, W. F., & Cronin, A. D. (2017). Optimal interpolation of satellite derived irradiance and ground data. In 2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017 (pp. 2035-2038). (2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PVSC.2017.8366671

Optimal interpolation of satellite derived irradiance and ground data. / Lorenzo, Antonio T.; Morzfeld, Matthias; Holmgren, William F. et al.
2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 2035-2038 (2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lorenzo, AT, Morzfeld, M, Holmgren, WF & Cronin, AD 2017, Optimal interpolation of satellite derived irradiance and ground data. in 2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017. 2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017, Institute of Electrical and Electronics Engineers Inc., pp. 2035-2038, 44th IEEE Photovoltaic Specialist Conference, PVSC 2017, Washington, United States, 6/25/17. https://doi.org/10.1109/PVSC.2017.8366671

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title = "Optimal interpolation of satellite derived irradiance and ground data",

abstract = "We describe how Bayesian data assimilation can be used to improve nowcasts of irradiance over small, city-scale, spatial areas. Specifically, we use optimal interpolation (OI) to improve satellite derived estimates of global horizontal irradiance (GHI) using ground truth data that was collected sparsely over Tucson, AZ. Our results show that the local data indeed improves the satellite derived estimates of GHI. A key to success with OI in this context is to prescribe correlations based on cloudiness, rather than spatially. OI can be used with a variety of data, e.g., rooftop photovoltaic production data or irradiance data, as well as with several different satellite derived irradiance models.",

keywords = "Data assimilation, Optimal interpolation, Remote sensing, Solar irradiance",

author = "Lorenzo, {Antonio T.} and Matthias Morzfeld and Holmgren, {William F.} and Cronin, {Alexander D.}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 44th IEEE Photovoltaic Specialist Conference, PVSC 2017 ; Conference date: 25-06-2017 Through 30-06-2017",

year = "2017",

doi = "10.1109/PVSC.2017.8366671",

language = "English (US)",

series = "2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2035--2038",

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T1 - Optimal interpolation of satellite derived irradiance and ground data

AU - Lorenzo, Antonio T.

AU - Morzfeld, Matthias

AU - Holmgren, William F.

AU - Cronin, Alexander D.

PY - 2017

Y1 - 2017

N2 - We describe how Bayesian data assimilation can be used to improve nowcasts of irradiance over small, city-scale, spatial areas. Specifically, we use optimal interpolation (OI) to improve satellite derived estimates of global horizontal irradiance (GHI) using ground truth data that was collected sparsely over Tucson, AZ. Our results show that the local data indeed improves the satellite derived estimates of GHI. A key to success with OI in this context is to prescribe correlations based on cloudiness, rather than spatially. OI can be used with a variety of data, e.g., rooftop photovoltaic production data or irradiance data, as well as with several different satellite derived irradiance models.

AB - We describe how Bayesian data assimilation can be used to improve nowcasts of irradiance over small, city-scale, spatial areas. Specifically, we use optimal interpolation (OI) to improve satellite derived estimates of global horizontal irradiance (GHI) using ground truth data that was collected sparsely over Tucson, AZ. Our results show that the local data indeed improves the satellite derived estimates of GHI. A key to success with OI in this context is to prescribe correlations based on cloudiness, rather than spatially. OI can be used with a variety of data, e.g., rooftop photovoltaic production data or irradiance data, as well as with several different satellite derived irradiance models.

KW - Data assimilation

KW - Optimal interpolation

KW - Remote sensing

KW - Solar irradiance

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SP - 2035

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ER -

Optimal interpolation of satellite derived irradiance and ground data

Abstract

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Keywords

ASJC Scopus subject areas

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