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NASA NTRS1994

Cirrus cloud retrieval using infrared sounding data: Multilevel cloud errors

In this study we perform an error analysis for cloud-top pressure retrieval using the High-Resolution Infrared Radiometric Sounder (HIRS/2) 15-microns CO2 channels for the two-layer case of transmissive cirrus overlying an overcast, opaque stratiform cloud. This analysis includes standard deviation and bias error due to instrument noise and the presence of two cloud layers, the lower of which is opaque. Instantaneous cloud pressure retrieval errors are determined for a range of cloud amounts (0.1-1.0) and cloud-top pressures (850-250 mb). Large cloud-top pressure retrieval errors are found to occur when a lower opaque layer is present underneath an upper transmissive cloud layer in the satellite field of view (FOV). Errors tend to increase with decreasing upper-cloud effective cloud amount and with decreasing cloud height (increasing pressure). Errors in retrieved upper-cloud pressure result in corresponding errors in derived effective cloud amount. For the case in which a HIRS FOV has two distinct cloud layers, the difference between the retrieved and actual cloud-top pressure is positive in all cases, meaning that the retrieved upper-cloud height is lower than the actual upper-cloud height. In addition, errors in retrieved cloud pressure are found to depend upon the lapse rate between the low-level cloud top and the surface. We examined which sounder channel combinations would minimize the total errors in derived cirrus cloud height caused by instrument noise and by the presence of a lower-level cloud. We find that while the sounding channels that peak between 700 and 1000 mb minimize random errors, the sounding channels that peak at 300-500 mb minimize bias errors. For a cloud climatology, the bias errors are most critical.

Baum, Bryan A.↗

NASA NTRS2008

Integration of Satellite-Derived Cloud Phase, Cloud Top Height, and Liquid Water Path into an Operational Aircraft Icing Nowcasting System

Operational products used by the U.S. Federal Aviation Administration to alert pilots of hazardous icing provide nowcast and short-term forecast estimates of the potential for the presence of supercooled liquid water and supercooled large droplets. The Current Icing Product (CIP) system employs basic satellite-derived information, including a cloud mask and cloud top temperature estimates, together with multiple other data sources to produce a gridded, three-dimensional, hourly depiction of icing probability and severity. Advanced satellite-derived cloud products developed at the NASA Langley Research Center (LaRC) provide a more detailed description of cloud properties (primarily at cloud top) compared to the basic satellite-derived information used currently in CIP. Cloud hydrometeor phase, liquid water path, cloud effective temperature, and cloud top height as estimated by the LaRC algorithms are into the CIP fuzzy logic scheme and a confidence value is determined. Examples of CIP products before and after the integration of the LaRC satellite-derived products will be presented at the conference.

Haggerty, Julie↗

NASA NTRS1983

Thunderstorm top structure observed by aircraft overflights with an infrared radiometer

Thunderstorm top structure is examined with high spatial resolution radiometric data (visible and infrared) from aircraft overflights together with other storm views, including geosynchronous satellite observations. Results show that overshooting cumuliform towers appear as distinct cold areas in the high resolution, 11-micron IR aircraft images, but that the geosynchronous satellite observations significantly overestimate the thunderstorm-top IR brightness temperature, T(B), due to field of view effects. Profiles of cloud top height and T(B) across overshooting features indicate an adiabatic cloud surface lapse rate. However, one-dimensional cloud model results indicate that when comparing thunderstorm top temperature and height at different times or different storms, a temperature-to-height conversion of about 7 K/km is appropriate. Examination of mature storm evolution indicates that, during periods when the updraft is relatively intense, the satellite IR 'cold point' is aligned with the low-level radar reflectivity maximum, but during periods of updraft weakening and lowering cloud top heights, the satellite T(B) minimum occurs downwind with cirrus anvil debris. The growth period of a relatively weak cumulonimbus cluster is also examined with aircraft and satellite data.

Adler, R. F.↗

NASA NTRS1992

Stratocumulus cloud properties derived from simultaneous satellite and island-based instrumentation during FIRE

Cloud parameters derived from visible and infrared window data from the Geostationary Operational Environmental Satellite (GOES) are compared to corresponding properties determined from instrumentation on San Nicolas Island off the coast of California during the First ISCCP Regional Experiment marine stratocumulus intensive field observations period in July 1987. Examination of the satellite imagery revealed that the apparent bias can be explained by the persistence of the clouds over the northwest part of the island during periods of clearing around the island. Diurnal variations in the cloud cover were very significant; minimum cloudiness occurred during the late afternoon and maximum cloudiness early in the morning. Relationships were established between the satellite-derived cloud optical depth and two surface-observed quantities: cloud liquid water path and cloud thickness. Simultaneous observations of liquid water path and satellite-derived cloud optical depth were used to infer effective cloud-droplet radius, resulting in good agreement with correlative data. The diurnal variations in cloud amount are accompanied by changes in cloud thickness, cloud-top height, cloud liquid water path, and effective droplet size. These observations provide the most complete picture, to date, of the diurnal cycle of marine stratocumulus clouds, confirming previous satellite-based inferences of the diurnal behavior of marine stratocumulus at larger scales.

Minnis, Patrick↗

NASA NTRS2011

EPIC Radiance Simulator for Deep Space Climate ObserVatoRy (DSCOVR)

The Deep Space Climate ObserVatoRy (DSCOVR) is a planned space weather mission for the Sun and Earth observations from the Lagrangian L1 point. Onboard of DSCOVR is a multispectral imager EPIC designed for unique observations of the full illuminated disk of the Earth with high temporal and 10 km spatial resolution. Depending on latitude, EPIC will observe the same Earth surface area during the course of the day in a wide range of solar and view zenith angles in the backscattering view geometry with the scattering angle of 164-172 . To understand the information content of EPIC data for analysis of the Earth clouds, aerosols and surface properties, an EPIC radiance Simulator was developed covering the UV -VIS-NIR range including the oxygen A and B-bands (A=340, 388, 443, 555, 680, 779.5, 687.7, 763.3 nm). The Simulator uses ancillary data (surface pressure/height, NCEP wind speed) as well as MODIS-based geophysical fields such as spectral surface bidirectional reflectance, column water vapor, and properties of aerosols and clouds including optical depth, effective radius, phase and cloud top height. The original simulations are conducted at 1 km resolution using the look-up table approach and then are averaged to 10 km EPIC radiances. This talk will give an overview of the EPIC Simulator with analysis of results over the continental USA and northern Atlantic.

Lyapustin, Alexei↗

NASA NTRS2015

The Impact of Assimilating Precipitation-affected Radiance on Cloud and Precipitation in Goddard WRF-EDAS Analyses

High-frequency TMI and AMSR-E radiances, which are sensitive to precipitation over land, are assimilated into the Goddard Weather Research and Forecasting Model- Ensemble Data Assimilation System (WRF-EDAS) for a few heavy rain events over the continental US. Independent observations from surface rainfall, satellite IR brightness temperatures, as well as ground-radar reflectivity profiles are used to evaluate the impact of assimilating rain-sensitive radiances on cloud and precipitation within WRF-EDAS. The evaluations go beyond comparisons of forecast skills and domain-mean statistics, and focus on studying the cloud and precipitation features in the jointed rainradiance and rain-cloud space, with particular attentions on vertical distributions of height-dependent cloud types and collective effect of cloud hydrometers. Such a methodology is very helpful to understand limitations and sources of errors in rainaffected radiance assimilations. It is found that the assimilation of rain-sensitive radiances can reduce the mismatch between model analyses and observations by reasonably enhancing/reducing convective intensity over areas where the observation indicates precipitation, and suppressing convection over areas where the model forecast indicates rain but the observation does not. It is also noted that instead of generating sufficient low-level warmrain clouds as in observations, the model analysis tends to produce many spurious upperlevel clouds containing small amount of ice water content. This discrepancy is associated with insufficient information in ice-water-sensitive radiances to address the vertical distribution of clouds with small amount of ice water content. Such a problem will likely be mitigated when multi-channel multi-frequency radiances/reflectivity are assimilated over land along with sufficiently accurate surface emissivity information to better constrain the vertical distribution of cloud hydrometers.

WRF-EDAS Analyses↗

NASA NTRSDate not supplied

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral instruments produce high-resolution and information-dense radiance spectra, thus offering the opportunity to reduce uncertainties in retrieval products. An optimal estimation-based cirrus cloud optical and microphysical product retrieval is under development for the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Earth Surface Mineral Dust Source Investigation (EMIT) instruments, and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder). The spectral coverage of all three instruments includes the ultraviolet, visible, and near-infrared. In this study a very fast radiative transfer model, the Principal Component-based Radiative Transfer Model in the solar spectral region (PCRTM-Solar), is used for forward modeling computations. This will reduce the computational burden in the forward radiance and Jacobian calculations as the cost function is minimized, enabling the entire AVIRIS, EMIT, and CLARREO-Pathfinder spectral range to be used in the optimal estimation framework. Using the entire spectrum will maximize the information content, resulting in a more robust and more accurate retrieval. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water. Preliminary results will be shown.

Jeffrey Mast↗

NASA NTRSDate not supplied

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral shortwave instruments produce high-resolution and information-dense spectra, thus offering the opportunity to reduce uncertainties in retrieval products. We are in the process of developing a retrieval that uses the very fast Principal Component Radiative Transfer Model in the solar spectral region (PCRTM-Solar) in the forward model calculations. This retrieval will use measured reflectances from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder) instruments. In this manuscript we present progress towards a reference retrieval employing a widely used, verified, accurate, yet computationally slower radiative transfer modeling technique. The reference retrieval, while too slow for using the complete hyperspectral measurement, will allow us to study the behavior of retrieval products and help us verify results from our in-development fast retrieval. Both retrievals will use the optimal estimation retrieval framework. In this manuscript we present results from an uncertainty analysis considering three uncertainty sources for a cirrus cloud retrieval in the form of error covariance matrices: reflectance uncertainty due to water vapor, the reflectance uncertainty due to ice crystal scattering assumptions, and the instrument measurement uncertainty. Results show that the uncertainty due to habit selection is the largest, while that due to water vapor is at most 0.6% relative to channel reflectance. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water.

Cirrus cloud↗

NASA NTRS2012

Cloud Height Retrieval with Oxygen A and B Bands for the Deep Space Climate Observatory (DSCOVR) Mission

Planned to fly in 2014, the Deep Space Climate Observatory (DSCOVR) would see the whole sunlit half of the Earth from the L 1 Lagrangian point and would provide simultaneous data on cloud and aerosol properties with its Earth Polychromatic Imaging Camera (EPIC). EPIC images the Earth on a 2Kx2K CCD array, which gives a horizontal resolution of about 10 km at nadir. A filter-wheel provides consecutive images in 10 spectral channels ranging from the UV to the near-IR, including the oxygen A and B bands. This paper presents a study of retrieving cloud height with EPIC's oxygen A and B bands. As the first step, we analyzed the effect of cloud optical and geometrical properties, sun-view geometry, and surface type on the cloud height determination. Second, we developed two cloud height retrieval algorithms that are based on the Mixed Lambertian-Equivalent Reflectivity (MLER) concept: one utilizes the absolute radiances at the Oxygen A and B bands and the other uses the radiance ratios between the absorption and reference channels of the two bands. Third, we applied the algorithms to the simulated EPIC data and to the data from SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) observations. Results show that oxygen A and B bands complement each other: A band is better suited for retrievals over ocean, while B band is better over vegetated land due to a much darker surface. Improvements to the MLER model, including corrections to surface contribution and photon path inside clouds, will also be discussed.

Yang, Yuekui↗

NASA NTRSDate not supplied

ARM Data as A Resource for Validation of NASA PACE Cloud Retrievals

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will launch in January 2024 and continue and improve upon satellite data records in its eponymous domains. PACE will carry a broad-swath hyperspectral imager, OCI, which will provide MODIS/VIIRS-type cloud data products (i.e. a cloud mask, top height, visible optical thickness, droplet effective radius, phase, and derived water path). It will also carry two multi-angle polarimeters (HARP2 and SPEXone) which will not only provide the above but also enable retrievals of additional cloud properties (e.g. droplet effective variance, ice crystal asymmetry parameter). Validating satellite-based cloud retrievals is challenging. We plan to use several ARM data streams to evaluate PACE cloud data products and are prototyping our analyses using retrievals from MODIS on the Aqua satellite and OLCI on the Sentinel-3A satellite. This poster shows how we plan to use ARM data to evaluate liquid water path (via MWRRET) and cloud top height retrievals (via KARZASRCL), with example results from these proxy sensors and ARM data from the SGP, ENA, and NSA sites. We seek comments from and collaborations with the ARM community to get the most out of our respective data streams.

ARM↗

NASA NTRS2017

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

MAIAC AO↗

NASA NTRS1994

Microphysical modeling of cirrus. 2: Sensitivity studies

The one-dimensional cirrus model described in part 1 of this issue has been used to study the sensitivity of simulated cirrus microphysical and radiative properties to poorly known model parameters, poorly understood physical processes, and environmental conditions. Model parameters and physical processes investigated include nucleation rate, mode of nucleation (e.g., homogeneous freezing of aerosols and liquid droplets or heterogeneous deposition), ice crystal shape, and coagulation. These studies suggest that the leading sources of uncertainty in the model are the phase change (liquid-solid) energy barrier and the ice-water surface energy which dominate the homogeneous freezing nucleation rate and the coagulation sticking efficiency at low temperatures which controls the production of large ice crystals (radii greater than 100 mcirons). Environmental conditions considered in sensitivity tests were CN size distribution, vertical wind speed, and cloud height. We found that (unlike stratus clouds) variations in the total number of condensation nuclei (NC) have little effect on cirrus microphysical and radiative properties, since nucleation occurs only on the largest CN at the tail of the size distribution. The total number of ice crystals which nucleate has little or no relationship to the number of CN present and depends primarily on the temperature and the cooling rate. Stronger updrafts (more rapid cooling) generate higher ice number densities, ice water content, cloud optical depth, and net radiative forcing. Increasing the height of the clouds in the model leads to an increase in ice number density, a decrease in effective radius, and a decrease in ice water content. The most prominent effect of increasing cloud height was a rapid increase in the net cloud radiative forcing which can be attributed to the change in cloud temperature as well as change in cloud ice size distributions. It has long been recognized that changes in cloud height or cloud area have the greatest potential for causing feedbacks on climate change. Our results suggest that variations in vertical velocity or cloud microphysical changes associatd with cloud height changes may also be important.

Jensen, Eric J.↗

NASA NTRS2002

Defining Top-of-Atmosphere Flux Reference Level for Earth Radiation Budget Studies

To estimate the earth's radiation budget at the top of the atmosphere (TOA) from satellite-measured radiances, it is necessary to account for the finite geometry of the earth and recognize that the earth is a solid body surrounded by a translucent atmosphere of finite thickness that attenuates solar radiation differently at different heights. As a result, in order to account for all of the reflected solar and emitted thermal radiation from the planet by direct integration of satellite-measured radiances, the measurement viewing geometry must be defined at a reference level well above the earth s surface (e.g., 100 km). This ensures that all radiation contributions, including radiation escaping the planet along slant paths above the earth s tangent point, are accounted for. By using a field-of- view (FOV) reference level that is too low (such as the surface reference level), TOA fluxes for most scene types are systematically underestimated by 1-2 W/sq m. In addition, since TOA flux represents a flow of radiant energy per unit area, and varies with distance from the earth according to the inverse-square law, a reference level is also needed to define satellite-based TOA fluxes. From theoretical radiative transfer calculations using a model that accounts for spherical geometry, the optimal reference level for defining TOA fluxes in radiation budget studies for the earth is estimated to be approximately 20 km. At this reference level, there is no need to explicitly account for horizontal transmission of solar radiation through the atmosphere in the earth radiation budget calculation. In this context, therefore, the 20-km reference level corresponds to the effective radiative top of atmosphere for the planet. Although the optimal flux reference level depends slightly on scene type due to differences in effective transmission of solar radiation with cloud height, the difference in flux caused by neglecting the scene-type dependence is less than 0.1%. If an inappropriate TOA flux reference level is used to define satellite TOA fluxes, and horizontal transmission of solar radiation through the planet is not accounted for in the radiation budget equation, systematic errors in net flux of up to 8 W/sq m can result. Since climate models generally use a plane-parallel model approximation to estimate TOA fluxes and the earth radiation budget, they implicitly assume zero horizontal transmission of solar radiation in the radiation budget equation, and do not need to specify a flux reference level. By defining satellite-based TOA flux estimates at a 20-km flux reference level, comparisons with plane-parallel climate model calculations are simplified since there is no need to explicitly correct plane-parallel climate model fluxes for horizontal transmission of solar radiation through a finite earth.

Loeb, N. G.↗

NASA NTRS1991

Cloud area determination from AVIRIS data using water vapor channels near 1 micron

Fractional cloud area is derived from spectral images collected by the Airborne Visible-IR Imaging Spectrometer (AVIRIS). The derivation is made by ratioing radiances near the 0.94- and the 1.14-microns water vapor band centers against those in the intermediate atmospheric window regions. The derivation makes use of the facts that (1) the reflectances of most ground targets vary approximately linearly with wavelength in the 0.94- and the 1.14-micron water vapor band absorption regions, and (2) the peak absorptions of the water vapor band over cloudy areas are smaller than those over nearby clear surface areas because of the rapidly decreasing atmospheric water vapor concentration with height. The band ratioing technique effectively discriminates among clouds and surface areas having similar reflectance values.

Gao, Bo-Gai↗

NASA NTRS1977

Scattering in the atmosphere of Venus. III - Line profiles and phase curves for Rayleigh scattering

Spectral line profiles, curves of growth, and curves for the equivalent width of a line as a function of Venus phase angle have been computed for a Rayleigh scattering cloud and compared with those for a cloud of isotropic scatterers. The results are very similar for the two kinds of scattering, with the exception of the curves of equivalent width as a function of Venus phase angle. These latter curves exhibit the 'inverse phase effect' and rule out a scale height of the clouds much less than half the scale height of the gas. The optical depth of the clouds is approximately 100.

Young, L. D. G.↗

NASA NTRS2004

Near-Real Time Cloud Properties and Aircraft Icing Indices from GEO and LEO Satellites

Imagers on many of the current and future operational meteorological satellites in geostationary Earth orbit (GEO) and lower Earth orbit (LEO) have enough spectral channels to derive cloud microphysical properties useful for a variety of applications. The products include cloud amount, phase, optical depth, temperature, height and pressure, thickness, effective particle size, and ice or liquid water path, shortwave albedo, and outgoing longwave radiation for each imager pixel. Because aircraft icing depends on cloud temperature, droplet size, and liquid water content as well as aircraft variables, it is possible to estimate the potential icing conditions from the cloud phase, temperature, effective droplet size, and liquid water path. A prototype icing index is currently being derived over the contiguous USA in near-real time from Geostationary Operational Environmental Satellite (GOES-10 and 12) data on a half-hourly basis and from NOAA- 16 Advanced Very High Resolution (AVHRR) data when available. Because the threshold-based algorithm is sensitive to small errors and differences in satellite imager and icing is complex process, a new probability based icing diagnosis technique is developed from a limited set of pilot reports. The algorithm produces reasonable patterns of icing probability and intensities when compared with independent model and pilot report data. Methods are discussed for improving the technique for incorporation into operational icing products.

Minnis, Patrick↗

NASA NTRS1973

Atmospheric effects on ocean surface temperature sensing from the NOAA satellite scanning radiometer.

Investigation of the effects of atmosphere state, nadir angle, cloud amount, cloud height, and random noise on ocean surface temperature sensing from the NOAA series satellites. The results obtained include the finding that a 10% cloud cover can introduce errors that range from 0.5 K to 4 K depending on cumuloform cloud height, which makes necessary a complete cloud elimination in the analysis. A correction scheme for cloud-free conditions is developed that is essentially free of bias.

Maul, G. A.↗

NASA NTRS1994

11 micrometer emissivities and droplet radii for marine stratocumulus

The results of a new multispectral infrared retrieval scheme for obtaining fractional cloud cover and 11 micrometer emissivity with those of the spatial coherence method which obtains fractional cloud cover assuming that the clouds are opaque at infrared wavelengths. Both methods are applied to 4-km NOAA advanced very high resolution radiometer global area coverage data for 250-km-scale regions containing single-layered marine stratocumulus off the coast of South America. The average 11 micrometer emissivity for low level clouds is found to be between 0.70 and 0.85. The low emissivity is evidently due to the thinning of clouds at their edges. Semitransparent cloud edges evidently make up a substantial portion of the area covered by such clouds. This result indicates that cloud cover obtained using the spatial coherence method is underestimated by 0.1 to 0.2, as has been claimed in a previous study. The fractional cloud cover for the ensemble of 250-km-scale regions studied here increased slightly from 0.60 for daytime observations to 0.63 for nighttime observations. The 11 micrometer emissivity also increased slightly, but about half of the increase was related to the increase in cloud cover and a decrease in the relative area covered by cloud edge material. Presumably, the other half was due to an increase in cloud liquid water. Cloud height showed no significant change. The average effective droplet radius increased from 9.3 micrometers for daytime observations to 10.2 micrometers at night.

Luo, Gang↗