Clear-sky Radiation Model Research Articles

Effects of spatial scale of atmospheric reanalysis data on clear-sky surface radiation modeling in tropical climates: A case study for Singapore

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.

Land Surface Temperature Reconstruction Under Long-Term Cloudy-Sky Conditions at 250 m Spatial Resolution: Case Study of Vinschgau/Venosta Valley in the European Alps

In this article, we present a new concept for predicting satellite-derived land surface temperature (LST) under cloudy skies over vegetated areas in the Alps. Although many different reconstruction methods have been developed, they require rarely available inputs, or they restore missing pixels from clear-sky observations with low spatial resolution (1–5 km), which makes them unreliable in heterogenous ecosystems. Given these limitations, we propose a station-based procedure to predict cloud-covered grids from 1-km Terra MODIS LST at 250 m spatial resolution. First, we explored correlations between ground-measured LST and air temperature in conjunction with other geo-biophysical variables under cloudy-sky conditions derived from ESRA clear-sky radiation model. Considering a high site dependency driven by different landcovers, in-situ data were aggregated into three groups (forest, permanent crops, grassland) and then, models were established. Next, the regressions were applied to 250-m gridded predictors to estimate cloud-covered LST pixels for six Terra MODIS LST images in 2014. While for permanent crops and forest group linear modelling was the most efficient, neural networks achieved the best performance for grasslands. The reconstructions showed reasonable LST distribution considering landscape heterogeneity of the region. The results were validated against timeseries of ground-measured LST in 2014. The models achieved reliable performance with an average R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of 0.84 and root-mean-square error of 2.12 °C. Despite some limitations, mainly due to diversified character of cloudy-sky conditions and high heterogeneity of gridded predictors, the method can effectively reconstruct overcast MODIS data at subpixel level, which shows great potential for producing cloud-free LSTs in complex ecosystems

Atmospheric water vapor radiative effects on shortwave radiation under clear skies: A global spatiotemporal analysis

This global study analyzes how the total column water vapor (in terms of precipitable water, PW) is related to the attenuation of shortwave solar radiation (SWR) using data from the MERRA-2 reanalysis during 2000–2014 and SWR simulations obtained with the REST2 clear-sky radiation model. The water vapor radiative effect (WVRE) on SWR attenuation is investigated by comparing the clear-sky SWR predictions under humid and ideally dry atmospheres, whereas the quantitative effect of PW on WVRE is determined using the concept of precipitable water efficiency (PWE).At global scale, WVRE exhibits a distinct seasonal pattern ranging from –80.2 to 0 W m‐2, with lower values in humid regions where PW is typically high (>4 cm), making the water vapor contribution relatively small. This is attributed to the saturation effect in water vapor absorption. Over arid regions, the solar irradiance attenuation is mainly controlled by the high aerosol loads, and less negative WVRE values are found. Over high-altitude regions, the low PW reduces the atmospheric absorption, resulting in low absolute WVRE magnitudes.PWE is found to extend globally between –133.7 and 0 W m‐2 cm‐1 on a monthly scale. This range is smaller on a long-term mean monthly or annual basis. On a long-term basis, the monthly PWE results are mainly concentrated between −20 and 0 W m−2 cm−1, generating leptokurtic and left-skewed distributions peaking between −10 and −8 W m−2 cm−1, depending on month. PWE is inversely related to PW on a long-term annual scale, indicating that PWE tends to zero under very humid conditions. A general nonlinear model is proposed to evaluate the hourly PWE at global scale on a monthly basis, separately for the two hemispheres.A PW trend analysis reveals that the Middle East, equatorial regions, central Europe, and Australia exhibit significant temporal trends, further inducing significant trends in WVRE. For those areas, WVRE trends are calculated between −3.3 and 1.5 W m−2 over the entire 15-year period.In addition, the global WVRE over landmasses is classified in terms of the Köppen-Geiger (KG) climate classification system. The most pronounced radiative effects are found over the equatorial regions, with an average WVRE of −63 W m−2. The Arid KG class provides a complex WVRE pattern ranging from −66 to −24 W m−2. Further segregation of this class shows strongly variable WVRE, induced by local climate differentiation. Over Warm Temperate climates, WVRE is found to vary widely according to the various KG subclasses. For the Cold climate class, PW is mainly concentrated around 1 cm and WVRE is low. The Polar regions include high mountains where WVRE is low, with a median close to −28 W m−2.

Prediction of Harvested Energy for Wireless Sensor Node

Energy harvesting wireless sensor nodes are interesting for the Internet of Things, since they can provide continuous operation by adapting workload not only to the current energy reserves, but to the amount of energy that can be harvested in the future also. We present a multistage day ahead hourly solar energy prediction algorithm. The predictor uses cloud cover and precipitation probability predictions from weather forecast obtained once per day for 24 hours in advance. To compensate for short-term weather changes until the next weather forecast data is obtained, forecast errors of humidity and atmospheric pressure are fed to the fuzzy logic filter. The filter adjusts predictions of cloud cover and precipitation probability, which are applied to the clear-sky radiation model in order to obtain prediction of solar energy. The prediction of solar energy is additionally corrected based on the energy prediction error in the preceding time slot. The results show that the proposed predictor outperforms the state-of-the-art predictors in terms of prediction error. Proposed predictor and state-of-the-art predictors were also evaluated using a simulated wireless sensor node with the simple energy management algorithm, where the proposed predictor was the most efficient at maintaining energy neutrality.

Quality Control of Global Horizontal Irradiance Estimates through BSRN, TOACs and Air Temperature/Sunshine Duration Test Procedures

Solar Radiation (SR) data are required for many disciplines and applications. The ground measurement of SR data is hampered by technical and operational errors. Therefore, several approaches have been developed to detect these errors. This study aimed to compare two quality tests of hourly Global Horizontal Irradiance (GHI) estimates through the Baseline Surface Radiation Network (BSRN) of the World Meteorological Organization (WMO) and Top of Atmosphere irradiance and Clear sky (TOACs) on a horizontal plane. Each of these tests has a threshold to pass data, which leads to different results. A newly developed quality test method is presented that uses Sunshine Duration (SD) and Air Temperature (AT) to check hourly GHI and is applied to data from 20 meteorological stations in northeast Iraq. The new method was validated using independent high quality data from six stations in various regions with the same climate regime. The method consists of several tests that compare ground data with upper and lower limits of radiation at the top of the atmosphere, using a clear sky radiation model and the relation between SD and AT with SR to determine data values of dubious quality. The rate of error flags generally range from 1% to 27%. The findings show that SD and AT can be used to support other quality tests and to detect nearly 2% additional dubious data values compared to BSRN and TOACs tests. The SD test tends to work like a consistency check but AT does not work like that according to the validation result. However, AT can be used to test the plausibility of data. The argument for using AT in this study may be impractical for other climate conditions. The results suggest that a combination of tests can lead to a better quality of ground data, especially when the components of SR are unviable. Using climate variables for further checks is another possibility.

Design and Performance of Two Axes Solar Tracker

The possible energy gain in the case of two axes tracking as well as a fixed system with Equator facing tilted solar PV module with latitude angle and daily optimum slope is calculated basing on Hottel clear sky radiation model (HM) and ex-terrestrial solar radiation model (ESRM). The calculated results are compared with the data obtained from a PV system with 252 Wpeak power module installed on a two axes solar tracker which was designed and constructed locally. The main components of the tracker are introduced. It was found that, the maximum possible energy gain calculated basing on HM and ESRM are practically identic. For example, on 25 August from 8 O’clock to solar noon, the hourly energy gain values of HM are 1.672, 1.336, 1.170, 1.098 and 1.097 while they are 1.677, 1.337, 1.170, 1.098 and 1.098 in the case of ESRM. The corresponding measured values on the same day are 1.746, 1.36, 1.16, 1.043 and 1.027. Thus, the theoretical data are consistent with the measured ones. Moreover, it was found that the tracked system is more economic feasible than latitude tilted similar one with a relative solar energy gain of 0.32%.

Validating nine clear sky radiation models in Australia

There have been many validation studies of clear sky solar radiation models, however, to date, no such analysis has been completed for Australia. Clear sky models are essential for estimating the generation potential of various solar energy technologies, the basic calibration of radiation measuring equipment, quality control of solar radiation datasets, engineering design (e.g. heating and cooling of buildings) and in agricultural and biological sciences (e.g. forestry). All of these areas are of considerable interest to the Australian economy and will benefit from an assessment of clear sky radiation models. With the recent provision of one-minute interval radiation data by the Australian Bureau of Meteorology for 20 sites across Australia, such a study can now be undertaken at a level not previously possible. Using up to ten years of data from each of 14 of these sites, clear sky periods are extracted through an automated detection algorithm. With these clear sky periods identified, nine of the most prominent beam and global clear sky radiation models are assessed using the relative Mean Bias Error, relative Root Mean Square Error and Coefficient of Determination as metrics. Further testing assessed model performance as a function of solar zenith angle and apparent solar time. Results show that for global clear sky simulations, the Solis, Esra and REST2 approaches perform best, while the Iqbal, Esra and REST2 methods are the most proficient clear sky beam models.

Simulation of Energy Production in Grid-Connected Photovoltaic Systems From Measured and Calculated Data From Clear-Sky Radiation Model

This paper presents a comparison of the energy production in grid-connected photovoltaic systems (GCPPS) from measured and calculated radiation data. The Linke turbidity (TL) factor for the region of Porto Alegre, Brazil, was extracted considering the data of direct solar radiation from the typical meteorological year (TMY). The average annual turbidity value obtained of 4.03 agrees with the wet climate of the region which presents only 17.26% of clear-sky days. There was a difference of 27.5% in the results of the produced energy, which drops to 6.5% when compared with only sunny days in the region, suggesting that the model in the current configuration for this type of estimate is barely adequate.

A hybrid modelling approach for assessing solar radiation

A hybrid technique for solar radiation estimation, a core part of hydrological cycle, is presented in this study which parameterises the cloud cover effect (cloud cover index) not just from the geostationary satellites but also the PSU/NCAR’s Mesoscale Modelling system (MM5) model. This, together with output from a global clear sky radiation model and observed datasets of temperature and precipitation are used as inputs within the Gamma test (GT) environment for the development of nonlinear models for global solar radiation estimation. The study also explores the ability of Gamma test to determine the optimum input combination and data length selection. Artificial neural network- and local linear regression-based nonlinear techniques are used to test the proposed methodology, and the results have shown a high degree of correlation between the observed and estimated values. It is believed that this study will initiate further exploration of GT for improving informed data and model selection.

KPV: A clear-sky index for photovoltaics

The rapidly growing installed base of distributed solar photovoltaic (PV) systems is causing increased interest in forecasting their power output. A key step towards this is accurately estimating the output from a PV system based on the known output from a nearby PV system. However, each PV system is unique with its own hardware configuration, orientation, shading, etc. Thus, the process of using the power output from one system to estimate the power output of another nearby system is not necessarily straightforward. In order to address these challenges, a modified clear-sky index for photovoltaics is proposed. This index is the ratio of the instantaneous PV power output to the instantaneous theoretical clear-sky power output derived from a clear-sky radiation model and PV system simulation routine. This definition performs better than previous clear-sky indices when both PV systems’ characteristics are known and the two PV systems have similar orientations. Through this index, the performance of a nearby PV system can be predicted quite accurately. This is demonstrated through the analysis of power output data from five residential PV systems in Canberra, Australia.

Use of a clear-day solar radiation model to homogenize solar radiation measurements in Hawai‘i

The reliability of solar irradiance measurements is dependent on the calibration of the pyranometer used to make them. Internationally recognized standards for pyranometer calibrations require resources that may not be available to all observers. To fill this gap, we propose a method of homogenizing hourly solar radiation time series based on comparison of clear-sky radiation observations against estimates derived from a clear-sky radiation model. Inhomogeneities in the record are identified based on shifts in pyranometer response in relation to the model estimates, and corrected to produce a homogeneous time series. This method was applied to the ∼23year record of hourly solar irradiance measurements recorded at three climate stations along a 870m elevation gradient (2120–2990m) on the slopes of Haleakalā Volcano, Maui, Hawai‘i. Corrections resulted in changes in monthly solar radiation of as much as 6.8–7.4% among the three stations.

Spatial patterns of surface hoar properties and incoming radiation on an inclined forest opening

AbstractAvalanche hazard evaluation relies in part on representative snowpack stability observations. Thus, understanding the spatial patterns of snowpack instabilities and their environmental determinants is crucial. This case study integrates intensive field observations with spatial modeling to identify associations between incoming radiation, surface hoar development and its subsequent shear strength across an inclined forest opening. We examined a buried surface hoar layer in southwest Montana, USA, over five sampling days, collecting 824 SnowMicroPen resistance profiles and performing 352 shear frame tests. Spatial models of incoming long- and shortwave radiation were generated for the surface hoar formation period using modeled hemispheric sky visibility, physically based parameters and the Bird Clear Sky Radiation Model in a Geographic Information System. Before burial, the surface hoar persisted despite moderate winds and relatively high air temperatures. The buried surface hoar layer thickness varied between 3 and 21 mm within a distance of 30 m. Modeled incoming radiation explained spatial variations in layer thickness and shear strength. In areas exposed to large amounts of radiation, the surface hoar layer was strong and thin, while areas with limited incoming radiation (due to high sky visibility and shading) possessed a thicker surface hoar layer that sheared more easily. This demonstrates the usefulness of microclimate modeling for slope-scale avalanche hazard evaluation. We also identify that over the 3 week sample period, strengthening occurred without thinning of the surface hoar layer.

Solar radiation estimation in ungauged catchments

Modelling in ungauged catchments has always been a complicated issue due to scarcity of the requisite data. Therefore, hydrologists have to rely on indirect techniques of estimation. A novel approach is hereby presented for solar radiation estimation in ungauged catchments using readily available datasets of temperature and precipitation. The rationale is that the extraterrestrial radiation is attenuated not only by different atmospheric processes but also by weather phenomena. A comparison of four clear sky radiation models was made and the best model output together with temperature and precipitation data was analysed using the gamma test for best input combination and data length selection. This led to the development of a non-linear artificial neural network model for solar radiation estimation. Results show a good correlation between the observed and estimated values, depicting the usefulness of gamma test in model development. The study is novel in the sense that this is the first time the gamma test has been used for hourly solar radiation estimation in ungauged catchments and hence extends their solar radiation records. Moreover, the regionalisation of the proposed model to other catchments would also aid solar radiation estimation in such catchments.

Editorial: Integrated modelling for regional water management

MSc, PhDIntegrated hydrological and hydrogeological modelling playsan important role in regional water management. Numericalmodelling of the complicated components of the hydrologicalcycle and related quality characteristics can be an effective toolfor decision support in water management. This is becausesome inherent mechanisms and system behaviours cannoteasily be quantitatively measured and are not experimentallyaccessible in the systems of hydro-geo-atmospheres. The EUwater framework directives introduced an innovative,integrated and holistic approach to the protection andmanagement of water resources which requires integratedmodelling approaches at catchment scale for its properimplementation (Yang and Wang, 2010).This issue of Water Management brings together recentprogress and advances in the numerical modelling tools used tosupport water management. A number of interesting and novelnumerical models are used to study precipitation that couldprovide useful input to other hydrological and hydrogeologicalmodels. Rainfall was also linked to sooding forecast by way ofnumerical models. Some of the papers presented in this issueextend further studies of hydrogeological modelling forparameter estimation, saline intrusion and density dependentÞnite difference modelling. These works provide integratedmodelling approaches for precipitation, sooding andgroundwater issues, not only in quantity but also for quality.In the Þrst paper, Cao et al. (2010) present a new approach todetermine the distributed threshold rainfall for sash sooding tosupport practical sood warning. It is built upon a 2D fullhydrodynamic model incorporating rainfall, inÞltration loss andboundary resistance. The numerical solution of the model wasachieved by the second-order total-variation-diminishingversion of the weighted-average-sux method along with theHarten-LaxÐvan Leer contact (HLLC) approximate Riemannsolver for the homogeneous equations, and a RungeÐKuttascheme for the ordinary differential equations of the sourceterms. The applicability of the new approach is demonstrated asapplied to real sash sooding-prone areas in Hunan Province,China. The threshold rainfall for sash sooding, resulting fromrainfall of short durations, was quantiÞed, which indicated ahigh risk of sash sooding in the local areas and promptedeffective measures to avoid economic and social losses.Creating a harmony between hydraulic constructions and anatural water environment for people to live in is a veryinteresting issue for watershed management. Attempts to bringtwo consicting viewpoints from hydraulic engineers andecologists into reconciliation show the practical difÞculties ofsuch a harmony. In the paper by Chou et al. (2010) the conceptof emergy is introduced and used to assess the contribution ofnatural environment to the human economic system. Theauthors applied the emergy synthesis in this paper as a tool tostudy the catchment management approach in Taiwan. Theemergy contributions of a river at different levels of the globaland regional hydrological cycle are evaluated. Two newindicators for river management Ð river pulsing index andemergy matching index Ð are developed to judge the trade-offbetween economy and ecology.Hydrological modelling in ungauged catchments has alwaysbeen a complicated issue due to scarcity of the requisite data.In most cases, hydrologists quite often have to rely on indirectestimations based upon limited data or desk studies. Shamim etal. (2010) propose a novel approach for solar radiationestimation in ungauged catchments using readily availabledatasets of temperature and precipitation using a non-linearartiÞcial neural network model. The rationale is that theextraterrestrial radiation is attenuated not only by differentatmospheric processes, but also by weather phenomena. Acomparison of four clear sky radiation models was made andthe best model output together with temperature andprecipitation data was analysed using the gamma test for bestinput combination and data length selection. The work showeda good calibration between the observed and estimated valuesusing gamma test in model development.Reliable and accurate estimation of aquifer parameters is a keyprocess for reliable groundwater management. A number ofstochastic optimisation tools are available to solve the non-linear aquifer parameters using gradient-based techniques butalso conventional stabilisation techniques. The paper byKambhammettu and King (2010) demonstrates how toaccelerate and stabilise the conventional LevenbergÐMarquardtalgorithm. A generalised Matlab code was developed toestimate the transmissivity and storage coefÞcient of theconÞned aquifer using residual drawdowns in an observationwell. The application of the method was illustrated by twodatasets from different sources and the results were comparedwith previous studies. The paper demonstrates that this methodcan estimate the parameters accurately with a more rapidconvergence in comparison with the conventional algorithms.Water Management 163 Issue WM7 Editorial Yang 325

A generalized procedure to generate clear-sky radiation data for any location

Accurate estimation of clear-sky radiation is needed in many engineering and architectural applications. In this study, data from four different locations with differing climatic conditions are used to evaluate two clear-sky radiation models referred to as the Page model and the Yang model. Statistical tests were used to determine their performance. The locations chosen were Aswan in Egypt, Jodhpur in India, Bahrain and Gerona in Spain. Using readily available meteorological data, both models produced good results above 400 W/m-super-2, although the Page model was found to perform better in dry climates and the Yang model in more humid locations. Selective use of one model over the other according to the prevailing climate thus produces an overall improvement in the data generated. It is suggested that investigations should be undertaken to further improve the models under discussion. Copyright The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

The estimation of solar radiation in New Zealand

Measurements of solar radiation which were made during the solar energy projects at DSIR, together with Meteorological Service data have been used to establish New Zealand parameters for the ASHRAE clear sky radiation model. It is shown that these new parameters give good agreement between observed and estimated values for both horizontal and vertical surfaces. There is, however, some complication for east- and south-facing surfaces. The values of sky-diffuse radiation on clear days were appreciably lower than those observed in the US and some other countries. Otherwise the diffuse/global ratios differed by not more than 15% from those of other investigators for most of the range.

Modeling clear day insolation at sea level in Hawaii

Daily totals of insolation under cloudless skies measured over an eleven year period, 1976 to 1987, at Honolulu, Hawaii are presented and compared with estimates from several clear sky radiation models. Results provide a baseline for applied and scientific research in the Islands and the central Pacific in general.