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Cloud and surface radiative properties and their effects on the earth and surface radiation budgets are obtained based on global daily visible and IR radiance measurements. The magnitude of cloud property variations and their effects on radiation increase strongly with decreasing space/time scales. Cloud properties are systematically different between land and ocean, with ocean having larger cloud cover with somewhat larger optical thicknesses and lower cloud top altitudes. Although cloud variations appear to be the primary cause of regional radiation budget variability at 5-30 daytime scales, the effects of their seasonal variations at larger spatial scales are less important than the changes associated with changes in solar declination and atmospheric/surface temperatures. The largest seasonal variations in radiation occur in the 30-60 deg latitude band in each hemisphere. Although clouds have a net cooling effect on the global, annual mean radiation balance at both the top of the atmosphere and the surface, their net effect on regional, seasonal balances is much more varied.
Operational satellite imager radiances are valuable for deriving many different physical parameters that can be used for a variety of weather, aviation, and energy applications. The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) applies a suite of algorithms to meteorological satellite data to provide cloud properties, radiative fluxes and other parameters on a global scale. The use of cloud computing has enabled recent enhancements to process a constellation of geostationary satellites at higher spatiotemporal resolutions than previously possible that meet low latency and near real-time needs. Data taken from Meteosat-8 and -11, Himawari, GOES-16, and -17 are processed and combined with operational polar orbiting satellite data and composited on a 3-km grid to provide global coverage. To improve the utility of the data products, machine learning and other innovative methods are applied in various ways to help minimize data product uncertainties under the most challenging conditions and to improve their consistency at all times of day. An update on recent SatCORPS enhancements is presented, highlighting the community benefits achieved with the use of cloud computing and machine learning.
Radiative cooling is a promising solid-state, non-vapor-compression technology for passive refrigeration and air conditioning. Although this phenomenon occurs naturally, achieving a significant amount of cooling to make it a technically and economically viable technology requires highly engineered, spectrally selective radiative surfaces. These characteristics make radiative cooling difficult to estimate, particularly when it is integrated with other systems such as photovoltaic panels or building envelopes. The complexity further increases when the substrate also participates in the radiative cooling (along with the radiative coating). Energy estimation is becoming increasingly critical because of the recent focus on the semitransparent radiative coatings that transmit a variety of colors to enhance the aesthetic appeal of the system. In this work, we propose an iterative method to calculate the effective radiative properties, which provides the same net radiative cooling that would be observed using the spectral properties at both the coating and substrate surfaces. Compared to traditional methods that rely on either computationally expensive full spectral analysis or methods for averaging each radiative surface parameter locally, our proposed method focuses on calculating effective properties that provide the same the net cooling effect as a full spectral analysis by accounting the emissivity, absorptivity, and transmissivity collectively, thereby providing an overall estimation error of less than 0.2%. We believe that this study will be beneficial to the engineering communities that employ complex simulation codes and require lumped solar and thermal radiation related parameters.
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Radiative heat exchange between specularly reflecting surfaces with direction dependent properties
Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model. together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.
Atmospheric aerosols influence climate by scattering and absorbing radiation in clear air (direct effects) and by serving as cloud condensation nuclei, modifying the microphysical properties of clouds, influencing radiation and precipitation development (indirect effects). Much of present uncertainty in forcing of climate change is due to uncertainty in the relations between aerosol microphysical and optical properties and their radiative influences (direct effects) and between microphysical properties and their ability to serve as cloud condensation nuclei at given supersaturations (indirect effects). This paper introduces a special section that reports on a field campaign conducted at the Department of Energy Atmospheric Radiation Measurement site in North Central Oklahoma in May, 2003, examining these relations using in situ airborne measurements and surface-, airborne-, and space-based remote sensing.
Biophysical properties and radiation balance components were measured at the Streletskaya Steppe Reserve of the Russian Republic in July 1991. Steppe vegetation parameters characterized include leaf area index (LAI), leaf angle distribution, mean tilt angle, canopy height, leaf spectral properties, leaf water potential, fraction of absorbed photosynthetically active radiation (APAR), and incoming and outgoing shortwave and longwave radiation. Research results, biophysical parameters, radiation balance estimates, and sun-view geometry effects on estimating APAR are discussed. Incoming and outgoing radiation streams are estimated using bidirectional spectral reflectances and bidirectional thermal emittances. Good agreement between measured and modeled estimates of the radiation balance were obtained.
Radiative properties are critical to quantify radiative energy fluxes between surfaces and in participating media. However, there is limited experimental data on temperature-dependent radiative properties of materials. Herein, this work focuses on experimentally measuring temperature-dependent diffuse reflectance in the near- and mid-infrared spectra (1–20 μm) for ceramic particles with applications as heat-transfer and thermal-storage media in concentrated solar power (CSP) plants. Specifically, a commercially available sintered bauxite proppant, ACCUCAST ID80, and its primary chemical constituents—alumina (Al 2 O 3 ) and silica (SiO 2 )—are measured in powder form using a Fourier transform infrared spectrometer (FTIR) coupled with a specialized diffuse reflectance accessory and a heated stage. Room-temperature diffuse reflectance measurements show increased absorption in tests with greater mass fractions of the ceramic samples. There is a strong correlation in the measured reflectance spectra of ACCUCAST with alumina and silica in the spectral range 2000–500 cm –1 (5–20 μm). Whereas, for shorter wavelengths (< 5 μm), the absorptance for ACCUCAST is greater than the absorptance for alumina and silica, indicating contributions from other chemical species present in the composite material. For the first time, temperature-dependent diffuse reflectance measurements are reported for ACCUCAST up to 1000 °C. These results are compared against those of alumina and silica through the calculation of a thermal emittance. All three materials exhibit a calculated emittance of ~0.9 at room temperature. However, this value decreases to ~0.6 for ACCUCAST and drops to less than 0.4 for alumina and silica at 1000 °C. Thermal cycling in air at 1000 °C resulted in a visible color change from dark grey to light orange for ACCUCAST and a subsequent larger increase in reflectance for wavelengths less than 5 μm as compared to ACCUCAST thermally cycled at 1000 °C in vacuum. Alumina and silica spectra proved to be largely unaffected by thermal cycling under atmospheric conditions. Overall, this study establishes a powerful technique for the characterization of radiative properties of particulate materials as a function of temperature and presents a detailed case study of ACCUCAST, a candidate for next-generation particle-based CSP.
We will evaluate the radiation transport properties of epoxy-martian regolith composites. Such composites, which would use both in situ materials and chemicals fabricated from elements found in the martian atmosphere, are candidates for use in habitats on Mars. The principal objective is to evaluate the transmission properties of these materials with respect to the protons and heavy charged particles in the galactic cosmic rays which bombard the martian surface. The secondary objective is to evaluate fabrication methods which could lead to technologies for in situ fabrication. The composites will be prepared by NASA Langley Research Center using simulated martian regolith. Initial evaluation of the radiation shielding properties will be made using transport models developed at NASA-LaRC and the results of these calculations will be used to select the composites with the most favorable radiation transmission properties. These candidates will then be empirically evaluated at particle accelerators which produce beams of protons and heavy charged particles comparable in energy to the radiation at the surface of Mars.
Mission crews in space outside the Earth s magnetic field will be exposed to high energy heavy charged particles in the galactic cosmic radiation (GCR). These highly ionizing particles will be a source of radiation risk to crews on extended missions to the Moon and Mars, and the biological effects of and countermeasures to the GCR have to be investigated as part of the planning of exploration-class missions. While it is impractical to shield spacecraft and planetary habitats against the entire GCR spectrum, biological and physical studies indicate that relatively modest amounts of shielding are effective at reducing the radiation dose. However, nuclear fragmentation in the shielding materials produces highly penetrating secondary particles, which complicates the problem: in some cases, some shielding is worse than none at all. Therefore the radiation transport properties of potential shielding materials need to be carefully investigated. One intriguing option for a Mars mission is the use of material from the Martian surface, in combination with chemicals carried from Earth and/or fabricated from elements found in the Martian atmosphere, to construct crew habitats. We have measured the transmission properties of epoxy-Martian regolith composites with respect to heavy charged particles characteristic of the GCR ions which bombard the Martian surface. The composites were prepared at NASA Langley Research Center using simulated Martian regolith, in the process also evaluating fabrication methods which could lead to technologies for in situ fabrication on Mars. Initial evaluation of the radiation shielding properties is made using radiation transport models developed at NASA-LaRC, and the results of these calculations are used to select the composites with the most favorable radiation transmission properties. These candidates are then evaluated at particle accelerators which produce beams of heavy charged particles representative in energy and charge of the radiation at the surface of Mars. The ultimate objective is to develop the models into a design tool for use by mission planners, flight surgeons and radiation health specialists.
Global, daily, visible, and infrared radiance measurements from the NOAA-5 Scanning Radiometer (SR) are analyzed for the months of January, April, July, and October 1977 to infer surface radiative properties. A radiative transfer model that simulates the spectral and angular characteristics of the NOAA-5 SR measurements is used to retrieve monthly mean surface visible reflectances and temperature at 25 km resolution. These surface properties were found sufficiently accurate for simulation of clear sky radiances to determine global, seasonal variations in cloudiness. Further comparisons of these results with other data highlight the analysis difficulties and radiative model shortcomings that must be overcome to monitor regional and seasonal variations of earth's surface. These preliminary results also provide an estimate of the magnitude of these variations.