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Monte Carlo radiative transfer simulations are used to study the atmospheric spread function appropriate to satellite-based sensing of the earth's surface. The parameters which are explored include the nadir angle of view, the size distribution of the atmospheric aerosol, and the aerosol vertical profile.
Strong flare heating that penetrates deeply into the solar chromosphere is examined, and a simple model that is supported by a numerical radiative transfer simulation is applied to study how elevated free electron densities produce markedly increased Stark emission in the wings of hydrogen Lyman and Balmer lines. The proportionality that exists between the observed Stark wing intensity and the total energy deposition in the partially ionized layer is calculated for various Lyman and Balmer lines. It is concluded that when the effects of background opacity sources on the wing enhancements are not important, the magnitude of the nonthermal heating that penetrates the chromosphere may be inferred from the observed line wings. It is predicted that Ly-alpha extended wings will exhibit enhancement of Stark shape, even when inherent damping wing opacity exceeds Stark wing opacity over the entire absorption profile.
The effect of temperature-dependent molecular absorption coefficients on thermal infrared spectral signatures measured from satellite sensors is investigated by comparing results from the atmospheric transmission and radiance codes LOWTRAN and MODTRAN and the accurate multiple scattering radiative transfer model ATRAD for different atmospheric profiles. The sensors considered include the operational NOAA AVHRR and two research instruments planned for NASA's Earth Observing System (EOS): MODIS-N (Moderate Resolution Imaging Spectrometer-Nadir-Mode) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). The difference in band transmittance is as large as 6 percent for some thermal bands within atmospheric windows and more than 30 percent near the edges of these atmospheric windows. The effect of temperature-dependent molecular absorption coefficients on satellite measurements of sea-surface temperature can exceed 0.6 K. Quantitative comparison and factor analysis indicate that more accurate measurements of molecular absorption coefficients and better radiative transfer simulation methods are needed to achieve SST accuracy of 0.3 K, as required for global numerical models of climate, and to develop land-surface temperature algorithms at the 1-K accuracy level.
A practical multiband, hierarchical algorithm for estimating land-surface temperature from NASA's future Earth Observing System (EOS) instruments Moderate Resolution Imaging Spectroradiometer (MODIS) and Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is developed through comprehensive, accurate, radiative transfer simulations at moderate spectral steps of 1-5/cm for wide ranges of atmospheric and surface conditions. The algorithm will accept empirical or estimated information about the surface emissivity and reflectivity and the atmospheric temperature and water-vapor profiles. Ground-based and aircraft measurements are necessary to validate and improve the algorithm and to establish its quality. Its accuracy depends on the calibration accuracy of thermal infrared data, uncertainties in surface heterogeneity, and temperature-dependent atmospheric absorption coefficients. Better knowledge of land-surface spectral emissivities and more accurate coefficients for atmospheric molecular band absorption and water vapor continuum absorption are needed to develop global land-surface temperature algorithms accurate to 1-2 K.
Aerosols in elevated layers were sampled with FSSP-probes and wire impactors over the Pacific ocean aboard the NASA DC-8 aircraft. Analyses of particle size and morphology identifies two distinctly different aerosol types for cases when the mid-visible extinctions exceed 0.2/km. Smaller sizes (effective radii of 0.2 um) and moderate absorption (mid-visible single scattering albedo of.935) are typical for urban-industrial pollution. Larger sizes (effective radii of 0.7 um) and weak absorption (mid-visible single scattering albedo of 0.985) identify dust. This aerosol classification is in agreement with its origin as determined by airmass back trajectory analysis. Based on lidar vertical profiling, aerosol dominated by dust and urban-industrial pollution above 3km were assigned mid-visible optical depths of 0.50 and 0.27, respectively. Radiative transfer simulations, considering a 50% cloud-cover below the aerosol layers, suggest (on a daily tP C)C> basis) small reductions (-4W/m2) to the energy budget at the top of the atmosphere for both aerosol types. For c' 0 dust, more backscattering of sunlight (weaker solar absorption) is compensated by a stronger greenhouse effect due to larger sizes. Forced reductions to the energy budget at the surface are 12W/m2 for both aerosol types. In contrast, impacts on heating rates within the aerosol layers are quite different: While urban-industrial aerosol warms the layer (at +0.6K/day as solar heating dominates), dust cools (at -0.5K/day as infrared cooling dominates). Sensitivity tests show the dependence of the aerosol climatic impact on the optical depth, particle size, absorptivity, and altitude of the layers, as well as clouds and surface properties. Climatic cooling can be eliminated (1) for the urban-industrial aerosol if absorption is increased to yield a mid-visible single scattering albedo of 0.89, or if the ocean is replaced by a land surface; (2) for the dust aerosol if the effective radius is increased from 0.7 to 1.2 um. The removal of low-level clouds doubles the cooling at the top of the atmosphere to about -8W/m2.
Observations of brightness temperature, Tb made over land regions by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer have been analyzed along with the nearly simultaneous measurements of the vertical profiles of reflectivity factor, Z, made by the Precipitation Radar (PR) onboard the TRMM satellite. This analysis is performed to explore the interrelationship between the TMI and PR data in areas that are covered predominantly by convective or stratiform rain. In particular, we have compared on a scale of 20 km, average vertical profiles of Z with the averages of Tbs in the 19, 37 and 85 GHz channels. Generally, we find from these data that as Z increases, Tbs in the three channels decrease due to extinction. In order to explain physically the relationship between the Tb and Z observations, we have performed radiative transfer simulations utilizing vertical profiles of hydrometeors applicable to convective and stratiform rain regions. These profiles are constructed taking guidance from the Z observations of PR and recent LDR and ZDR measurements made by land-based polarimetric radars.
Precipitation Radar (PR) on board the TRMM satellite shows that the average height of 30 dBz in convective rain areas of the tropics varies significantly from one region to the other. When the convection is weak this height is shallow and when convection is strong this height extends deeper into the troposphere. The brightness temperature (Tb) measured by the microwave radiometer by itself does not reflect this nature of convection satisfactorily. Radiative transfer simulations of Tbs reveal that this could be due to the variations in the vertical distribution of optically active water and ice hydrometeors and their density, shape, and size. These variations are not coupled uniquely to the strength of the convective updrafts, and as a result the Tbs do not reflect properly the convective strength indicated by PR. Because of this deficiency in the Tbs the rain rate deduced from them differs from that of PR. For this reason, to improve the estimation of rain rate we have developed an empirical method. In this method a parameter based on the areal extent of the Tbs that exceed a certain magnitude is included along with the Tbs. Rain rate deduced with this approach is better correlated with that of PR when compared to the current Version 5 operational algorithm. The percentage of rain volume as a function of rain rate, for a given region of 5deg lat. X 5deg long. over a period of three months, deduced from this method, is also in better agreement with that of the PR.
We investigate the outgoing broadband longwave (LW, 5 to approx. 200 microns) and window (WIN, 8 to approx. 12 microns) channel radiances at the top of atmosphere (TOA) under clear-sky conditions, using data acquired by the Cloud and the Earth s Radiant Energy System (CERES) and Moderate-Resolution Imaging Spectroradiometer (MODIS) instruments onboard the NASA Terra satellite platform. In this study, detailed analyses are performed on the CERES Single Scanner Footprint TOA/Surface Fluxes and Clouds product to understand the radiative effect of thin cirrus. The data are acquired over the Florida area during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers Florida Area Cirrus Experiment (CRYSTAL-FACE) field program. Of particular interest is the anisotropy associated with the radiation field. Measured CERES broadband radiances are compared to those obtained from rigorous radiative transfer simulations. Analysis of results from this comparison indicates that the simulated radiances tend to be larger than their measured counterparts, with differences ranging from 2.1% to 8.3% for the LW band and from 1.7% to 10.6% for the WIN band. The averaged difference in radiance is approximately 4% for both the LW and WIN channels. A potential cause for the differences could be the presence of thin cirrus (i.e., optically thin ice clouds with visible optical thicknesses smaller than approximately 0.3). The detection and quantitative analysis of these thin cirrus clouds are challenging even with sophisticated multispectral instruments. While large differences in radiance between the CERES observations and the theoretical calculations are found, the corresponding difference in the anisotropic factors is very small (0.2%). Furthermore, sensitivity studies show that the influence due to a 1 K bias of the surface temperature on the errors of the LW and WIN channel radiances is of the same order as that associated with a 2% bias of the surface emissivity. The LW and WIN errors associated with a 5% bias of water vapor amount in the lower atmosphere in conjunction with a 50% bias of water vapor amount in the upper atmosphere is similar to that of a 1 K bias of the vertical temperature profile. Even with the uncertainties considered for these various factors, the simulated LW and WIN radiances are still larger than the observed radiances if thin cirrus clouds are excluded.
Retrieval of aerosol optical properties using shortwave bands from passive satellite sensors, such as MODIS, is typically limited to cloud-free areas. However, if the clouds are thin enough (i.e. thin cirrus) such that the satellite-observed reflectance contains signals under the cirrus layer, and if the optical properties of this cirrus layer are known, the TOA reflectance can be corrected for the cirrus layer to be used for retrieving aerosol optical properties. To this end, we first correct the TOA reflectances in the aerosol bands (0.47, 0.55, 0.65, 0.86, 1.24, 1.63, and 2.12 micron for ocean algorithm and 0.412, 0.47, and 0.65 micron for deep blue algorithm) for the effects of thin cirrus using 1.38 micron reflectance and conversion factors that convert cirrus reflectance in 1.38 micron band to those in aerosol bands. It was found that the conversion factors can be calculated by using relationships between reflectances in 1.38 micron band and minimum reflectances in the aerosol bands (Gao et al., 2002). Refer to the example in the figure. Then, the cirrus-corrected reflectance can be calculated by subtracting the cirrus reflectance from the TOA reflectance in the optically thin case. A sensitivity study suggested that cloudy-sky TOA reflectances can be calculated with small errors in the form of simple linear addition of cirrus-only reflectances and clear-sky reflectances. In this study, we correct the cirrus signals up to TOA reflectance at 1.38 micron of 0.05 where the simple linear addition is valid without extensive radiative transfer simulations. When each scene passes the set of tests shown in the flowchart, the scene is corrected for cirrus contamination and passed into aerosol retrieval algorithms.
The operational Land Imager (OLI) aboard Landsat 8 was launched in February 2013 to continue the Landsat's mission of monitoring earth resources at relatively high spatial resolution. Compared to Landsat heritage sensors, OLI has an additional 443-nm band (termed coastal/aerosol (CA) band), which extends its potential for mapping/monitoring water quality in coastal/inland waters. In addition, OLI's pushbroom design allows for longer integration time and, as a result, higher signal-to-noise ratio (SNR). Using a series of radiative transfer simulations, we provide insights into the radiometric sensitivity of OLI when studying coastal/inland waters. This will address how the changes in water constituents manifest at top-of-atmosphere (TOA) and whether the changes are resolvable at TOA (focal plane) relative to OLI's overall noise.
Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth's radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-resolution sensors, many applications in heterogeneous environments can benefit from higher-resolution albedo products derived from Landsat. We previously developed a "MODIS-concurrent" approach for the 30-meter albedo estimation which relied on combining post-2000 Landsat data with MODIS Bidirectional Reflectance Distribution Function (BRDF) information. Here we present a "pre-MODIS era" approach to extend 30-m surface albedo generation in time back to the 1980s, through an a priori anisotropy Look-Up Table (LUT) built up from the high quality MCD43A BRDF estimates over representative homogenous regions. Each entry in the LUT reflects a unique combination of land cover, seasonality, terrain information, disturbance age and type, and Landsat optical spectral bands. An initial conceptual LUT was created for the Pacific Northwest (PNW) of the United States and provides BRDF shapes estimated from MODIS observations for undisturbed and disturbed surface types (including recovery trajectories of burned areas and non-fire disturbances). By accepting the assumption of a generally invariant BRDF shape for similar land surface structures as a priori information, spectral white-sky and black-sky albedos are derived through albedo-to-nadir reflectance ratios as a bridge between the Landsat and MODIS scale. A further narrow-to-broadband conversion based on radiative transfer simulations is adopted to produce broadband albedos at visible, near infrared, and shortwave regimes.We evaluate the accuracy of resultant Landsat albedo using available field measurements at forested AmeriFlux stations in the PNW region, and examine the consistency of the surface albedo generated by this approach respectively with that from the "concurrent" approach and the coincident MODIS operational surface albedo products. Using the tower measurements as reference, the derived Landsat 30-m snow-free shortwave broadband albedo yields an absolute accuracy of 0.02 with a root mean square error less than 0.016 and a bias of no more than 0.007. A further cross-comparison over individual scenes shows that the retrieved white sky shortwave albedo from the "pre-MODIS era" LUT approach is highly consistent (R(exp 2) = 0.988, the scene-averaged low RMSE = 0.009 and bias = −0.005) with that generated by the earlier "concurrent" approach. The Landsat albedo also exhibits more detailed landscape texture and a wider dynamic range of albedo values than the coincident 500-m MODIS operational products (MCD43A3), especially in the heterogeneous regions. Collectively, the "pre-MODIS" LUT and "concurrent" approaches provide a practical way to retrieve long-term Landsat albedo from the historic Landsat archives as far back as the 1980s, as well as the current Landsat-8 mission, and thus support investigations into the evolution of the albedo of terrestrial biomes at fine resolution.
A data library is developed containing the scattering, absorption, and polarization properties of ice particles in the spectral range from 0.2 to 100 microns. The properties are computed based on a combination of the Amsterdam discrete dipole approximation (ADDA), the T-matrix method, and the improved geometric optics method (IGOM). The electromagnetic edge effect is incorporated into the extinction and absorption efficiencies computed from the IGOM. A full set of single-scattering properties is provided by considering three-dimensional random orientations for 11 ice crystal habits: droxtals, prolate spheroids, oblate spheroids, solid and hollow columns, compact aggregates composed of eight solid columns, hexagonal plates, small spatial aggregates composed of 5 plates, large spatial aggregates composed of 10 plates, and solid and hollow bullet rosettes. The maximum dimension of each habit ranges from 2 to 10,000 microns in 189 discrete sizes. For each ice crystal habit, three surface roughness conditions (i.e., smooth, moderately roughened, and severely roughened) are considered to account for the surface texture of large particles in the IGOM applicable domain. The data library contains the extinction efficiency, single-scattering albedo, asymmetry parameter, six independent nonzero elements of the phase matrix (P11, P12, P22, P33, P43, and P44), particle projected area, and particle volume to provide the basic single-scattering properties for remote sensing applications and radiative transfer simulations involving ice clouds. Furthermore, a comparison of satellite observations and theoretical simulations for the polarization characteristics of ice clouds demonstrates that ice cloud optical models assuming severely roughened ice crystals significantly outperform their counterparts assuming smooth ice crystals.
The Research Scanning Polarimeter (RSP) is an airborne instrument, whose measurements have been extensively used for retrievals of microphysical properties of clouds. In this study we show that for cumulus clouds the information content of the RSP data can be extended by adding the macroscopic parameters of the cloud, such as its geometric shape, dimensions, and height above the ground. This extension is possible by virtue of the high angular resolution and high frequency of the RSP measurements, which allow for geometric constraint of the cloud's 2D cross section between a number of tangent lines of view. The retrieval method is tested on realistic 3D radiative transfer simulations and applied to actual RSP data.
When observed from the ground, optically thick clouds minimally polarize light, while the linear polarization direction (angle) of optically thin clouds contains information about thermodynamic phase. For instruments such at the Cimel radiometers that comprise the AErosol RObotic NEtwork (AERONET), these properties can also be exploited to aid cloud optical property retrievals. Using vector radiative transfer simulations, we explore the conditions most favorable to cloud thermodynamic phase determination, then test with actual AERONET data. Results indicate that this technique may be appropriate for some, but not all, conditions, and motivate a deeper investigation about the polarization direction measurement capability of Cimel instruments, which to date have been primarily used to determine degree of polarization. Recent work explores these measurement issues using a newly installed instrument at the NASA Ames Research Center in Moffett Field, California.
In summer 2016, more than 50 Arctic Barren Ground caribous were found dead on Prince Charles Island (Nunavut, Canada), a species recently classified as threatened. Neither predator nor sign of diseases was observed and reported. The main hypothesis is that caribous were not able to access food due to a very dense snow surface, created by a strong storm system in spring. Using satellite microwave data, a significant increase in brightness temperature polarization ratio at 19 and 37 GHz was observed in spring 2016 (60% higher than previous two winter seasons). Based on microwave radiative transfer simulations, such anomaly can be explained with a very dense snow surface. This is consistent with the succession of storms and strong winds highlighted in ERA‐Interim over Prince Charles Island in spring 2016. Using several sources of data, this study shows that changes in snow conditions explain the caribou die‐off due to restricted foraging.
This paper describes a new discrete wavelength algorithm developed for retrieving volcanic sulfur dioxide (SO2) vertical column density (VCD) from UV observing satellites. The Multi-Satellite SO2 algorithm (MS_SO2) simultaneously retrieves column densities of sulfur dioxide, ozone, and Lambertian effective reflectivity (LER) and its spectral dependence. It is used operationally to process measurements from the heritage Total Ozone Mapping Spectrometer (TOMS) onboard NASA's Nimbus-7 satellite (N7/TOMS: 1978-1993) and from the current Earth Polychromatic Imaging Camera (EPIC) onboard Deep Space Climate Observatory (DSCOVR: 2015-) from the Earth-Sun Lagrange (L1) orbit. Results from MS_SO2 algorithm for several volcanic cases were assessed using the more sensitive principal component analysis (PCA) algorithm. The PCA is an operational algorithm used by NASA to retrieve SO2 from hyperspectral UV spectrometers, such as the Ozone Monitoring Instrument (OMI) onboard NASA's Earth Observing System Aura satellite and Ozone Mapping and Profiling Suite (OMPS) onboard NASA-NOAA Suomi National Polar Partnership (SNPP) satellite. For this comparative study, the PCA algorithm was modified to use the discrete wavelengths of the Nimbus-7/TOMS instrument, described in Sect. S1 of the Supplement. Our results demonstrate good agreement between the two retrievals for the largest volcanic eruptions of the satellite era, such as the 1991 Pinatubo eruption. To estimate SO2 retrieval systematic uncertainties, we use radiative transfer simulations explicitly accounting for volcanic sulfate and ash aerosols. Our results suggest that the discrete-wavelength MS_SO2 algorithm, although less sensitive than hyperspectral PCA algorithm, can be adapted to retrieve volcanic SO2 VCDs from contemporary hyperspectral UV instruments, such as OMI and OMPS, to create consistent, multi-satellite, long-term volcanic SO2 climate data records.
Detecting climate trends on large spatiotemporal scales requires accurate, stable measurements and stable retrieval algorithms. We strive to estimate how time-variant retrieval algorithm biases may impact trend detection. Here we focus on the 3D cloud optical thickness (τc) bias, which is among the largest in passive cloud retrieval algorithms. If this bias is time dependent, a possibility with potential decadal changes in cloud morphology, it may obscure genuine trends in τc. Although previous studies have evaluated the cloud- and sun-view geometry-dependent 3D τc bias on small spatial scales, before our current study none have evaluated the stability of this well-known bias on climate-relevant large spatiotemporal scales. These studies must estimate large scale distributions of the 3D τc bias by cloud type and estimate how cloud type amount may change between two climate states. We employ a novel approach to estimate large scale distributions of 3D τc using a proxy of the bias that quantifies the departure of clouds from satisfying the 1D radiative transfer assumption used in passive τc retrievals. This existing globally-distributed proxy is an angular consistency metric that was developed using fused Moderate-Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) measurements. Calculating the 3D τc bias and the proxy, for known cloud fields enables us to establish statistical relationships between these two quantities, which can be used to calculate large-scale distributions of the 3D τc bias. This approach limits the number of 3D radiative transfer simulations required to only those needed to estimate a statistical relationship between the 3D τc bias for known cloud fields and a proxy of the bias. It is likely that future studies will be needed to evaluate retrieval algorithm bias stability for other geophysical variables as the community develops climate data records from satellite observations and their retrievals. This must be done in addition to monitoring and correcting measurement errors and uncertainties and understanding their impact on retrieved essential climate variables.
On 2019 August 14, the Advanced LIGO and Virgo interferometers detected the high-significance gravitational wave (GW) signal S190814bv. The GW data indicated that the event resulted from a neutron star–black hole (NSBH) merger, or potentially a low-mass binary BH merger. Due to the low false-alarm rate and the precise localization (23 deg^(2) at 90%), S190814bv presented the community with the best opportunity yet to directly observe an optical/near-infrared counterpart to an NSBH merger. To search for potential counterparts, the GROWTH Collaboration performed real-time image subtraction on six nights of public Dark Energy Camera images acquired in the 3 weeks following the merger, covering >98% of the localization probability. Using a worldwide network of follow-up facilities, we systematically undertook spectroscopy and imaging of optical counterpart candidates. Combining these data with a photometric redshift catalog, we ruled out each candidate as the counterpart to S190814bv and placed deep, uniform limits on the optical emission associated with S190814bv. For the nearest consistent GW distance, radiative transfer simulations of NSBH mergers constrain the ejecta mass of S190814bv to be M(ej) < 0.04 Mꙩ at polar viewing angles, or M(ej) < 0.03 Mꙩ if the opacity is κ < 2 sq.cm/g. Assuming a tidal deformability for the NS at the high end of the range compatible with GW170817 results, our limits would constrain the BH spin component aligned with the orbital momentum to be χ < 0.7 for mass ratios Q < 6, with weaker constraints for more compact NSs.