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Results for “solar zenith angle”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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25 records · Page 2

Inferring the photolysis rate of NO 2 in the stratosphere based on satellite observations

NO and NO 2 (NO x ) play major roles in both tropospheric and stratospheric chemistry. This paper provides a novel method to obtain a global and accurate photolysis rate for NO 2 based on satellite data. The photolysis rate J(NO 2 ) dominates the daytime diurnal variation of NO x photochemistry. Here the spatial variation of J(NO 2 ) at 50–90°S in December from 20–40km is obtained using data from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) experiment. Because NO and NO 2 rapidly exchange with one another in the daytime, J(NO 2 ) can be attained assuming steady state, and the results are shown to be consistent with model results. The J(NO 2 ) value decreases as the solar zenith angle increases and has a weak altitude dependence. A key finding is that satellite-derived J(NO 2 ) increases in the polar regions, in good agreement with model predictions, due to the effects of ice and snow on surface albedo. Thus, the method presented here provides an observation-based check on the role of albedo in driving polar photochemistry.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of liquid cloud albedo susceptibility in E3SM using coupled eastern North Atlantic surface and satellite retrievals

The impact of aerosol number concentration on cloud albedo is a persistent source of spread in global climate predictions due to multi-scale, interactive atmospheric processes that remain difficult to quantify. We use 5 years of geostationary satellite and surface retrievals at the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) eastern North Atlantic (ENA) site in the Azores to evaluate the representation of liquid cloud albedo susceptibility for overcast cloud scenes in the DOE Energy Exascale Earth System Model version 1 (E3SMv1) and provide possible reasons for model–observation discrepancies. The overall distribution of surface 0.2 % CCN concentration values is reasonably simulated, but simulated liquid water path (LWP) is lower than observed and layer mean droplet concentration (N d ) comparisons are highly variable depending on the N d retrieval technique. E3SMv1's cloud albedo is greater than observed for given LWP and N d values due to a lower cloud effective radius than observed. However, the simulated albedo response to N d is suppressed due to a correlation between the solar zenith angle (SZA) and N d created by the seasonal cycle that is not observed. Controlling for this effect by examining the cloud optical depth (COD) shows that E3SMv1's COD response to CCN concentration is greater than observed. For surface-based retrievals, this is only true after controlling for cloud adiabaticity because E3SMv1's adiabaticities are much lower than observed. Assuming a constant adiabaticity in surface retrievals as done in top-of-atmosphere (TOA) retrievals narrows the retrieved ln N d distribution, which increases the cloud albedo sensitivity to ln N d to match the TOA sensitivity. The greater sensitivity of COD to CCN is caused by a greater Twomey effect in which the sensitivity of N d to CCN is greater than observed for TOA-retrieved N d , and once model–observation cloud adiabaticity differences are removed, this is also true for surface-retrieved N d . The LWP response to N d in E3SMv1 is overall negative as observed. Despite reproducing the observed LWP–N d relationship, observed clouds become much more adiabatic as N d increases, while E3SMv1 clouds do not, associated with more heavily precipitating clouds that are partially but not completely caused by deeper clouds and weaker inversions in E3SMv1. These cloud property differences indicate that the negative LWP–N d relationship is likely not caused by the same mechanisms in E3SMv1 and observations. The negative simulated LWP response also fails to mute the excessively strong Twomey effect, highlighting potentially important confounding factor effects that likely render the LWP–N d relationship non-causal. N d retrieval scales and assumptions, particularly related to cloud adiabaticity, contribute to substantial spreads in the model–observation comparisons, though enough consistency exists to suggest that aerosol activation, drizzle, and entrainment processes are critical areas to focus E3SMv1 development for improving the fidelity of aerosol–cloud interactions in E3SM.

54 ENVIRONMENTAL SCIENCES↗

Solar Resource Measurements in Eugene, OR: Cooperative Research and Development Final Report, CRADA Number CRD-07-00252

Site-specific, long-term, continuous, and high-resolution measurements of solar irradiance are important for developing renewable resource data. These data are used for several research and development activities consistent with the NLR mission: establish a national 3-year climatological database of measured solar irradiances; provide high quality ground-truth data for satellite remote sensing validation; support development of radiative transfer models for estimating solar irradiance from available meteorological observations; provide solar resource information needed for technology deployment and operations. Data acquired under this agreement will be available to the public through NLR's Measurement & Instrumentation Data Center – MIDC (http://www.nlr.gov/midc) Or the Renewable Resource Data Center - RReDC (http://rredc.nlr.gov). The MIDC offers a variety of standard data display, access, and analysis tools designed to address the needs of a wide user audience (e.g., industry, academia, and government interests).

14 SOLAR ENERGY↗

Solar position confounds the relationship between ecosystem function and vegetation indices derived from solar and photosynthetically active radiation fluxes

Vegetation indices derived from solar and photosynthetically active radiation (PAR) sensors (i.e. radiation derived) have been under-utilized in inferring ecosystem function, despite measurement capability at hundreds of sites. This under-utilization may be attributed to reported mismatches among the seasonality of radiation- and satellite-derived vegetation indices and canopy photosynthesis; herein referred to as measurement biases. In this work, biases in radiation derived reflectance and vegetation indices were assessed using a decadal record of satellite and ground based spectroradiometer data, ecosystem phenology and CO 2 fluxes, and radiation derived vegetation indices (i.e. the Normalized Difference Vegetation Index [NDVI], the two band Enhanced Vegetation Index [EVI2]) from a high latitude tundra site (i.e. Imnaviat). At Imnaviat, we found poor correspondence between the three types of reflectance and vegetation indices, especially during the latter part of the growing season. Radiation derived vegetation indices resulted in incorrect estimates of phenological timing of up to a month and poor relationships with canopy photosynthesis (i.e. Gross Ecosystem Exchange (GEE)). These mismatches were attributed to solar position (i.e. solar zenith and azimuth angle) and a method, based on the diel visible and near-infrared albedo variation, was developed to improve the performance of the vegetation indices. The ability of radiation derived vegetation indices to infer GEE and phenological dates drastically improved once radiation derived vegetation indices were corrected for solar position associated biases at Imnaviat. Moreover, radiation derived vegetation indices became better aligned with MODerate resolution Imaging Spectroradiometer (MODIS) satellite estimates after solar position associated biases were corrected at Imnaviat and at 25 Fluxnet sites (~90 site years) across North America. Corrections developed here provide a way forward in understanding daily ecosystem function or filling large gaps in eddy covariance data at a significant number of Fluxnet sites.

54 ENVIRONMENTAL SCIENCES↗

Integration of GOES Data for Solar Resource Assessment of the Contiguous United States

The National Solar Radiation Database (NSRDB), produced by the National Laboratory of the Rockies (NLR), provides high-resolution solar resource data for the contiguous United States (CONUS) using Geostationary Operational Environmental Satellite (GOES) East and West observations. This study evaluates the integration of multi-satellite data within the GOES-East/West overlap regions, where conventional longitude-based selection methods often produce an artificial boundary seam. Our results demonstrate that an advanced blending algorithm, which incorporates sun-satellite scattering angles and satellite viewing zenith angles, improves NSRDB accuracy and creates a spatially continuous dataset. Validation against ground-based irradiance measurements reveals reductions in both percentage error (PE) and normalized Root Mean Square Error (nRMSE), particularly in the central United States. The dynamical integration of multi-satellite data provides a robust foundation for more precise modeling of solar resource and improved spatiotemporal analysis of solar ramp across the CONUS.

14 SOLAR ENERGY↗

Equating Reference Cell and Broadband Pyranometer Data

An adjustment algorithm has been developed for broadband Class-A pyranometers, to modify the pyranometer data such that it more closely matches that of silicon-based reference cells. The adjustment algorithm uses modeled clear-sky spectral data as one of its inputs. The adjustment also uses a reference cell angle of incidence modifier. A comparison between the pyranometer and the reference cells is performed with and without the adjustment applied. The adjustment aligns the pyranometer and reference cell data to within +-2 % under clear skies when the zenith angle is less than 70 degrees .

incident angle modifier↗

PV Reference Cells for Outdoor Use: An Investigation of Calibration Factors

Reference cells are widely used in the photovoltaic (PV) industry to measure irradiance. For field applications and outdoor use, a variety of products are on the market, and they are often perceived as a low-cost alternative to thermopile radiometers. But reference cell characteristics differ substantially from the latter, therefore measurements made by one category of instrument cannot be substituted for or directly compared with the other. The National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory is currently in a multiyear effort to develop guidance and recommendations for the design and use of outdoor reference cells, with a view to reducing inconsistencies and measurement uncertainty. The core of this effort is the long-term deployment of 39 units of 10 distinct types made by 6 manufacturers. This report compares the calibration factors provided by manufacturers - which most users rely upon - to those measured at a high level of accuracy by NREL's Cell Lab. It also reports on the application of the Broadband Outdoor Radiometer Calibration (BORCAL) method to reference cells. As a group, the factory calibrations for the crystalline silicon cells showed a small positive bias of +0.7%, with a tight distribution around this value. This is a very good result for the manufacturers. The two World Photovoltaic Scale cells constituted outliers, with a mean deviation of -0.8%, which is still within the reported uncertainty ranges. The data collected during the BORCAL procedures show a strong and systematic fluctuation of the apparent responsivity of the reference cells over the course of a day, which was anticipated. Consequently, the standard BORCAL R@45 calibration factors underestimated the reference cell responsivities by 1%-4%. An alternate responsivity indicator was developed, R'@30, incorporating adjustments for temperature response, spectral response, and directional response. This reduced the mean deviation to -0.4% compared to the Cell Lab. Further, two independent BORCAL sessions were able to produce the same values to within ±0.2%. This could be a viable approach for verifying reference cells using existing BORCAL infrastructure, for example, to evaluate their long-term stability. The daily profiles of responsivity obtained during the BORCAL sessions (provided in Appendix A) show clear patterns of differences between models, which provides evidence that their directional responses differ from each other; thus, two sensors that are calibrated correctly might give the same reading at 30° zenith angle but systematically different readings at 60°. The impact of these inconsistencies in field operation will be quantified using the long-term observations started in 2020.

14 SOLAR ENERGY↗