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Solar resource assessments most generally require atmospheric information, which is customarily acquired from gridded datasets. The spatial scale mismatch problem, i.e., the difference in spatial representativeness of gridded data and in situ measurements, therefore becomes relevant. This study examines how the gridded data used as inputs to clear-sky radiation models can affect their performance at urban scale. The tropical island of Singapore is selected for the case study. Aerosol optical depth at 550 nm (AOD550), Å ngström exponent (AE), and precipitable water (PW) from both the MERRA-2 reanalysis and ground-based stations (AERONET and SuomiNet) are collected between 2013–2020. Firstly, it is found that, relatively to the AERONET ground truth, the bias in MERRA-2's AOD550 is more prominent than that in AE or PW. Next, the bias propagation from the gridded inputs (AOD550, AE, and PW) to clear-sky radiation predictions is explored using various models. The estimated clear-sky direct normal irradiance (DNIcs) is more sensitive to AOD550 variation than the clear-sky global horizontal irradiance (GHIcs). Six clear-sky radiation models, five of which accept MERRA-2 gridded inputs, are compared with each other, and with the in situ irradiance measurements recorded at 9 sites. The inter-model difference across Singapore is remarkably consistent because the whole island fits inside a single MERRA-2 grid cell. Under high-AOD550 situations, however, the inter-model deviation becomes large for both GHIcs and DNIcs. The conventional model-versus-measurement comparison shows that each model achieves very different site-to-site performance, largely because the spatially-averaged inputs cannot fully represent the micro-climatic variability. Relatively speaking, no clear-sky radiation model significantly outperforms its peers. The simple MAC2 model and the empirical (locally derived) Yang GHIcs-only model are recommended for Singapore. • MERRA-2 reanalysis aerosol optical depth and water vapor validation using two AERONET stations at Singapore. • Aerosol and water vapor biases impact clear-sky irradiance modeling. • Clear-sky radiation models evaluated in situ and intercompared at 9 sites. • Risks and benefits of using MERRA-2 atmospheric data over small areas. [ABSTRACT FROM AUTHOR]

Abstract: We analyse Singapore global horizontal irradiance (GHI) measurements to estimate clear sky GHI in the equator region. The data consists of a one-year period of clear sky GHI at three solar irradiance monitoring stations in Singapore, namely, First Zero Energy House in Singapore (1.3094∘N, 103.9160∘E) located in the east of the country, Solar Energy Research Institute of Singapore (1.3007∘N, 103.7718∘E) in the mid-west, and Nanyang Technology University Intelligence Systems Center (1.3436∘N, 103.6792∘E) in the west. Several empirical clear sky models are considered for a Singapore case study. An regression method is proposed to parameterise the model of choice for Singapore''s measured GHI. The developed model is validated using GHI measurements from difference stations over different time periods. [Copyright &y& Elsevier]

Anthropogenic haze, caused at least in parts by forest and agricultural land clearing fires in Sumatra (Indonesia), is occasionally causing air quality issues in Singapore, located 150–300 km east of the majority of these “hot spots”. The resulting air pollution partially blocks sunlight from reaching the ground, and consequently affects the electric power generation of solar photovoltaic (PV) systems in Singapore. In this work, a methodology is presented to estimate the haze-induced reduction of the light intensity reaching PV panels and the corresponding loss in the electric energy yield. An assessment of a major haze event in June 2013 is the basis for the loss analysis, which takes into account data filtering techniques in order to isolate cloudless conditions for inter-comparison between clear and hazy days. Data from previous years in non-hazy conditions serve as baseline for the determination of the clear sky conditions for Singapore. The novel method is further applied to investigate the power output of ten PV systems in Singapore during the June 2013 haze event. It is found that poor air quality levels during this event caused yield losses of PV systems in Singapore in the range of 15–25%. [ABSTRACT FROM AUTHOR]