On evaluating density driven groundwater flow in the closed basin

The hydrogeochemical cycle in the Pilot Valley, a closed basin, is subject to climate variability over a wide range of spatial and temporal scales over long period of time. Saturated and Unsaturated Transport Model (SUTRA) is employed in the Pilot Valley to simulate subsurface and density driven groundwater flow under various climatic and geologic conditions. A Maxey-Eakin method with coupled catchment model, aridity index and incomplete beta function for groundwater recharge distribution is integrated into the SUTRA model for various simulations. A Rayleigh number is used to analyze these circulation patterns of flow under variable climate and geologic conditions. The simulation results, under different groundwater recharge rates, indicate the existence or absence of free convection flow and salt nose movement under the playa and towards hinge line. The simulation result for a historical wet period (12 ka) has a narrow salt nose extent and a historical dry period (6 ka) has a wider salt nose extent. High permeability values generate more free convective cells and low permeability values generate less or eliminate free convective cells in the flow domain. This study will help minimize damage from extreme climatic conditions which occur frequently in the study area and also help manage water resources efficiently

Regridding Uncertainty for Statistical Downscaling of Solar Radiation

Initial steps in statistical downscaling involve being able to compare observed data from regional climate models (RCMs). This prediction requires (1) regridding RCM output from their native grids and at differing spatial resolutions to a common grid in order to be comparable to observed data and (2) bias correcting RCM data, via quantile mapping, for example, for future modeling and analysis. The uncertainty associated with (1) is not always considered for downstream operations in (2). This work examines this uncertainty, which is not often made available to the user of a regridded data product. This analysis is applied to RCM solar radiation data from the NA-CORDEX data archive and observed data from the National Solar Radiation Database housed at the National Renewable Energy Lab. A case study of the mentioned methods over California is presented.Comment: 16 pages, 5 figures, submitted to: Advances in Statistical Climatology, Meteorology and Oceanograph

A Benchmark of Simple Measurement Systems for Direct Irradiance

Accurate direct normal irradiance (DNI) measurements are essential for the design and the operation of concentrating solar power systems. Several measurement systems for DNI are available to users, but all commonly used systems still have drawbacks. Sun trackers with pyranometers and a pyrheliometer are expensive and require permanent checks and maintenance by qualified personnel, for example due to tracking errors and soiling effects. Simpler, i.e. more economic and robust sensors may have shortcomings regarding accuracy under various atmospheric conditions and might not be significantly less susceptible to soiling and user errors. Validations and benchmarking of simple radiometers for solar energy applications have been presented. To the best of our knowledge, no benchmarking study is available which evaluates some more recent simple measurement systems which are relevant for solar applications in 2023. Furthermore, most previous benchmarking studies did not measure atmospheric parameters like circumsolar irradiance which may directly influence the measurements of these sensors. We close this gap by benchmarking relevant measurement systems (Rotating Shadowband Irradiometer RSI and Rotating Shadowband Pyranometer RSP 4G; Delta-T SPN1, EKO MS-90, PyranoCam, Sunto CaptPro) at multiple sites. We also evaluate the influence of relevant atmospheric parameters which we measure with dedicated instruments at one site. We include the PyranoCam system in our benchmarking, a novel radiometer system suitable for all solar irradiance components including DNI. It consists of a pyranometer and a fisheye camera that takes photos of the whole sky and employs a combined physical and machine-learning model. The results of the study provide improved estimates of the sensors’ accuracies for a specific application and climatic condition and can assist in the development of corrections for the sensor technologies

Physically based correction of systematic errors of Rotating Shadowband Irradiometers

Accurate measurements of direct normal, diffuse horizontal and global horizontal irradiance (DNI, DHI and GHI) are needed for meteorological studies and are essential for the solar resource assessment at potential solar power plant sites. Often, these potential sites are remote and hence require robust sensors that require minimal maintenance that are not affected strongly by soiling. Therefore, Rotating Shadowband Irradiometers (RSI) are widely used for resource assessment. To achieve the required accuracy, corrections for the raw values of RSIs depending on systematic temperature, incidence angle and spectral errors must be used, and a thorough calibration of the sensor head must be applied. The existing correction functions are derived from comparisons of RSIs to thermopile radiometers at selected sites and therefore empirical. Their accuracy is considered to be site dependent. In this work a new correction and calibration method is presented that removes the systematic errors using a physical approach. It is based on information of the sensor properties as well as measurements of its directional response, and incorporates the atmospheric conditions at the measurement site. In this case, no empiric relations obtained from a specific site are required. The method requires estimates of the current DHI and GHI spectra during each measurement of the RSI. Based on these spectra, a spectral correction, which includes a spectrum dependent temperature correction, can be made without employing empirical relationships. The new physical calibration and correction method is tested at three sites and reaches similar results compared to the empirical functions. This is already achieved with rudimentary estimations of the GHI and DHI spectra and we expect that these estimations can be improved in the future. The results indicate that the physical approach reduces the problematic location dependence of the current calibration and correction methods. The physical correction and calibration method show promise for a further improvement of the RSI accuracy

Overview of Solar Radiation Resource Concepts (Chapter 2)

International audienc

Uncertainty of Rotating Shadowband Irradiometers and Si-Pyranometers Including the Spectral Irradiance Error

Concentrating solar power projects require accurate direct normal irradiance (DNI) data including uncertainty specifications for plant layout and cost calculations. Ground measured data are necessary to obtain the required level of accuracy and are often obtained with Rotating Shadowband Irradiometers (RSI) that use photodiode pyranometers and correction functions to account for systematic effects. The uncertainty of Si-pyranometers has been investigated, but so far basically empirical studies were published or decisive uncertainty influences had to be estimated based on experience in analytical studies. One of the most crucial estimated influences is the spectral irradiance error because Si-photodiode-pyranometers only detect visible and color infrared radiation and have a spectral response that varies strongly within this wavelength interval. Furthermore, analytic studies did not discuss the role of correction functions and the uncertainty introduced by imperfect shading. In order to further improve the bankability of RSI and Si-pyranometer data, a detailed uncertainty analysis following the Guide to the Expression of Uncertainty in Measurement (GUM) has been carried out. The study defines a method for the derivation of the spectral error and spectral uncertainties and presents quantitative values of the spectral and overall uncertainties. Data from the PSA station in southern Spain was selected for the analysis. Average standard uncertainties for corrected 10 min data of 2 % for global horizontal irradiance (GHI), and 2.9 % for DNI (for GHI and DNI over 300 W/m²) were found for the 2012 yearly dataset when separate GHI and DHI calibration constants were used. Also the uncertainty in 1 min resolution was analyzed. The effect of correction functions is significant. The uncertainties found in this study are consistent with results of previous empirical studies