Potential of AOD Retrieval Using Atmospheric Emitted Radiance Interferometer (AERI)

Aerosols in the atmosphere play an essential role in the radiative transfer process due to their scattering, absorption, and emission. Moreover, they interrupt the retrieval of atmospheric properties from ground-based and satellite remote sensing. Thus, accurate aerosol information needs to be obtained. Herein, we developed an optimal-estimation-based aerosol optical depth (AOD) retrieval algorithm using the hyperspectral infrared downwelling emitted radiance of the Atmospheric Emitted Radiance Interferometer (AERI). The proposed algorithm is based on the phenomena that the thermal infrared radiance measured by a ground-based remote sensor is sensitive to the thermodynamic profile and degree of the turbid aerosol in the atmosphere. To assess the performance of algorithm, AERI observations, measured throughout the day on 21 October 2010 at Anmyeon, South Korea, were used. The derived thermodynamic profiles and AODs were compared with those of the European center for a reanalysis of medium-range weather forecasts version 5 and global atmosphere watch precision-filter radiometer (GAW-PFR), respectively. The radiances simulated with aerosol information were more suitable for the AERI-observed radiance than those without aerosol (i.e., clear sky). The temporal variation trend of the retrieved AOD matched that of GAW-PFR well, although small discrepancies were present at high aerosol concentrations. This provides a potential possibility for the retrieval of nighttime AOD.

New sampling strategy mitigates a solar-geometry-induced bias in sub-kilometre vapour scaling statistics derived from imaging spectroscopy

Upcoming spaceborne imaging spectrometers will retrieve clear-sky total column water vapour (TCWV) over land at a horizontal resolution of 30–80 m. Here we show how to obtain, from these retrievals, exponents describing the power-law scaling of sub-kilometre horizontal variability in clear-sky bulk planetary boundary layer (PBL) water vapour (q) accounting for realistic non-vertical sunlight paths. We trace direct solar beam paths through large eddy simulations (LES) of shallow convective PBLs and show that retrieved 2-D water vapour fields are “smeared” in the direction of the solar azimuth. This changes the horizontal spatial scaling of the field primarily in that direction, and we address this by calculating exponents perpendicular to the solar azimuth, that is to say flying “across” the sunlight path rather than “towards” or “away” from the Sun. Across 23 LES snapshots, at solar zenith angle SZA = 60∘ the mean bias in calculated exponent is 38 ± 12 % (95 % range) along the solar azimuth, while following our strategy it is 3 ± 9 % and no longer significant. Both bias and root-mean-square error decrease with lower SZA. We include retrieval errors from several sources, including (1) the Earth Surface Mineral Dust Source Investigation (EMIT) instrument noise model, (2) requisite assumptions about the atmospheric thermodynamic profile, and (3) spatially nonuniform aerosol distributions. By only considering the direct beam, we neglect 3-D radiative effects such as light scattered into the field of view by nearby clouds. However, our proposed technique is necessary to counteract the direct-path effect of solar geometries and obtain unique information about sub-kilometre PBL q scaling from upcoming spaceborne spectrometer missions.

Forecasting of Wind and Solar Farm Output in the Australian National Electricity Market: A Review

Accurately forecasting the output of grid connected wind and solar systems is critical to increasing the overall penetration of renewables on the electrical network. This is especially the case in Australia, where there has been a massive increase in solar and wind farms in the last 15 years, as well as in roof top solar, both domestic and commercial. For example, in 2020, 27% of the electricity in Australia was from renewable sources, and in South Australia almost 60% was from wind and solar. In the literature, there has been extensive research reported on solar and wind resource, entailing both point and interval forecasts, but there has been much less focus on the forecasting of output from wind and solar systems. In this review, we canvass both what has been reported and also what gaps remain. In the case of the latter topic, there are numerous aspects that are not well dealt with in the literature. We have added discussion on the value of forecasts, rather than just focusing on forecast skill. Further, we present a section on how to deal with conditionally changing variance, a topic that has little focus in the literature. One other topic may be particularly important in Australia at the moment, but may become more widespread. This is how to deal with the concept of a clear sky output from a solar farm when the field is oversized compared to the inverter capacity, resulting in a plateau for the output.

Updated GOES-13 Heliosat-2 Method for Global Horizontal Irradiation in the Americas

Increasing the utilization of renewable energy is at the center of most sustainability policies. Solar energy is the most abundant resource of this type on Earth, and optimizing its use requires the optimal estimation of surface solar irradiation. Heliosat-2 is one of the most popular methods of global horizontal irradiation (GHI) estimation. Originally developed for the Meteosat satellite, Heliosat-2 has been modified in previous work to deal with GOES-13 data and named here GOES_H2. This model has been validated through the computation of indicators and irradiation maps for the Guiana Shield. This article proposes an improved version of GOES_H2, which has been combined with a radiative transfer parameterization (RTP) and the McClear clear-sky model (MC). This new version, hereafter designated RTP_MC_GOES_H2, was tested on eight stations from the Baseline Surface Radiation Network, located in North and South America, and covered by GOES-13. RTP_MC_GOES_H2 improves the hourly GHI estimates independently of the type of sky. This improvement is independent of the climate, no matter the station, the RTP_MC_GOES_H2 gives better results of MBE and RMSE than the original GOES_H2 method. Indeed, the MBE and RMSE values, respectively, change from −11.93% to −2.42% and 23.24% to 18.24% for North America and from −4.35% to 1.79% and 19.97% to 17.37 for South America. Moreover, the flexibility of the method may allow to improve results in the presence of snow cover and rainy/variable weather. Furthermore, RTP_MC_GOES_H2 results outperform or equalize those of other operational models.

ASSESSMENT OF SOLAR ENERGY POTENTIAL FOR A RADIALLY STAGGERED HELIOSTATS FIELD USING SUN TRACKING METHOD

This article deals with the potential assessment of tower type solar thermal power system. An algorithm was developed to employ sun-tracking method, which provides the characteristic angles of the heliostats such that the incoming beams of sun rays are reflected to the receiver. A suite of MATLAB code was developed to implement the mathematical models for a quick evaluation of solar energy potential in a radially staggered heliostat field for the capital city of Kingdom of Saudi Arabia, Riyadh. An existing clear-sky model in the literature was used to compute hourly insolation. Optical efficiencies and heat collected by the receiver (from individual heliostat in the field on hourly basis) were computed and the monthly-averaged daily results were presented zone-wise and for the complete heliostat field. It was observed that the optical efficiency of the heliostat decreases with increasing distance from the receiver tower; this was due to increasing spillage of the reflected rays and decreasing cosine efficiency with increasing distance of the heliostat from the receiver tower. Results showed that annual average optical efficiency of the field is nearly forty-nine percent.

Comparative Investigation of Daylight Glare Probability (DGP) Comfort Classes in Clear Sky Condition

Glare is considered one of the most important variables to reach visual comfort and visual quality. It represents one of the fundamental barriers for an effective use of daylighting in buildings. One of the best performing and robust glare prediction models, relative to other available metrics, is a Daylight Glare Probability (DGP). Based on a validated and precise methodology (RADIANCE) the aim of this work is to compare the DGP model (original cut-off values) with new cut-off values that differ according to the time of day (morning, noon and afternoon). Both cut-off values were compared at more than 300 simulated conditions of daylighting in an interior space. This work offers the originality of studying recently proposed cut-off values in climate luminous with predominant clear sky conditions. Currently, the application of these new cutoff values is reduced to the field of science or simulation professionals. The results showed important differences (64.86%) between the categories proposed by both cut-off values. Nevertheless, these differences do not have a significant impact in glare prediction (< 2.7%), in terms of glare absence (DGP <0.38) and presence (DGP >0.38). This analysis made it possible: (i) to regionally apply the main current corpus criteria regarding glare issues as well as emergent proposals and (ii) to present new experimental data aimed at helping the field and, together with other works, improving the tools used by professionals on a daily basis.

Remote Sensing of solar surface radiation – A reflection of concepts, applications and input data based on experience with the effective cloud albedo

Accurate solar surface irradiance data (SSI) is a prerequisite for efficient planning and operation of solar energy sys- tems. Respective data are also essential for climate monitoring and analysis. Satellite-based SSI has grown in importance over the last few decades. However, a retrieval method is needed to relate the measured radiances at the satellite to the solar surface irradiance. In a widespread classical approach, these radiances are used directly to derive the effective cloud albedo (CAL) as basis for the estimation of the solar surface irradiance. This approach has been already introduced and discussed in the early 1980s. Various approaches are briefly discussed and analyzed, including an overview of open questions and opportunities for improvement. Special emphasis is placed on the reflection of fundamental physical laws and atmospheric measurement tech- niques. In addition, atmospheric input data and key applications are briefly discussed. It is concluded that the well established observational-based CAL approach is still an excellent choice for the retrieval of the cloud transmission. The coupling with Look-Up-Table based clear sky models enables the estimation of solar surface irradiance with high accuracy and homogeneity. This could explain why, despite its age, the direct CAL approach is still used by key players in energy meteorology and the climate community. For the clear sky input data it is recommended to use ECMWF forecast and reanalysis data.

Tropospheric Attenuation in GeoSurf Satellite Constellations

In GeoSurf satellite constellations, any transmitter/receiver, wherever it is located, is linked to a satellite with zenith paths. We have studied the tropospheric attenuation predicted for some reference sites (Canberra, Holmdel, Pasadena, Robledo, and Spino d’Adda), which also set the meridian along which we have considered sites with latitudes ranging between 60° N and 60° S. At the annual probability of 1% of an average year, in the latitude between 30° N and 30° S, there are no significant differences between GEO slant paths and GeoSurf zenith paths. On the contrary, at 0.1% and 0.01% annual probabilities, large differences are found for latitudes greater than 30° N or 30° S. For comparing the tropospheric attenuation in GeoSurf paths with that expected in LEO highly variable slant paths, we have considered, as reference, a LEO satellite constellation orbiting in circular at 817 km. GeoSurf zenith paths “gain” several dBs compared to LEO slant paths. The more static total clear-sky attenuation (water vapor, oxygen, and clouds) in both GEO and LEO slant paths shows larger values than GeoSurf zenith paths. Both for rain and clear-sky attenuations, Northern and Southern Hemispheres show significant differences.