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At least 1,621 records · Page 90
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NASA NTRSDate not supplied

Overview of GSICS visible calibration methods.

Global Space-based Inter-Calibration System (GSICS) is an international collaborative effort initiated in 2005 by the World Meteorological Organization (WMO) and the Coordination Group for Meteorological Satellites (CGMS) to 1-monitor, 2-improve and 3-harmonize the quality of observations from operational weather and environmental satellites of the Global Observing System (GOS). GSICS aims at ensuring consistent accuracy among space-based observations worldwide for climate monitoring, weather forecasting, and environmental applications by 1-monitoring instrument performance, 2-operational inter-calibration of satellite instruments, 3-radiometrically scaling observations to absolute reference standards, 4-recalibration of archived datasets. Although many of the GSIC visible inter-calibration methods are based on medium pixel-level imagers such as MODIS, VIIRS, AVHRR, and geostationary sensors, the methods are applicable to high spatial resolution imagery such as Landsat. For sensor inter-calibration efforts, coincident ray-matched reflectance pairs are used to transfer the calibration from the reference to the target instrument. Spectral band adjustment factors (SBAF) are applied to account for any spectral band differences. For sensor stability monitoring, PICS, deep convective cloud (DCC) and polar ice Earth viewed targets are utilized. GSICS uses the moon for stability monitoring by using the GSICS Implementation of the USGS Robotic Lunar Observatory (ROLO) model (GIRO). GSICS is looking forward to the launch of CLARREO on the international space station (ISS) in 2023. The CLARREO hyperspectral reflective solar band (RSB) sensor will establish an absolute calibration reference in space, which will characterize invariant targets and will inter-calibrate concurrent sensors. Examples of these calibration methods will be presented at the workshop.

Visible calibration methods↗
NASA NTRS2020

Sensitivity of Multispectral Imager Liquid Water Cloud Microphysical Retrievals to the Index of Refraction

A cloud property retrieved from multispectral imagers having spectral channels in the shortwave infrared (SWIR) and/or midwave infrared (MWIR) is the effective particle radius (CER), a radiatively relevant weighting of the cloud particle size distribution. The physical basis of the CER retrieval is the dependence of SWIR/MWIR cloud reflectance on the cloud particle single scattering absorption, which in turn depends on the complex index of refraction of bulk liquid water (or ice) in addition to the cloud particle size. There is a general consistency in the choice of the liquid water index of refraction by the cloud remote sensing community, largely due to the few available independent datasets and compilations. Here we examine the sensitivity of CER retrievals to the available laboratory index of refraction datasets in the SWIR and MWIR using the retrieval software package that produces NASA’s standard MODIS/VIIRS continuity cloud products. The sensitivity study incorporates two laboratory index of refraction datasets that include measurements at supercooled water temperatures, one in the SWIR [Kou et al., 1993] and one in the MWIR [Wagner et al., 2005]. Neither has been broadly utilized in the cloud remote sensing community. It is shown that these two new datasets can significantly change CER retrievals (e.g., 1-2 μm) relative to common datasets used by the community. Further, index of refraction data for a 265 K water temperature results in more consistent retrievals between the two spectrally distinct 2.2 μm atmospheric window channels on MODIS and VIIRS. As a result, the 265 K values from the SWIR and MWIR index of refraction datasets were adopted for use in the production version of the continuity cloud product. The results indicate the need to better understand temperature-dependent bulk water absorption and uncertainties in these spectral regions.

MODIS↗
NASA NTRSDate not supplied

On the use of DSCOVR EPIC to monitor the visible calibration stability of polar orbiting imagers to improve the next edition of the CERES climate data record.

The NASA CERES project has provided the climate quality observed TOA and computed surface fluxes to the scientific community. CERES instruments are onboard the Terra, Aqua, NPP, and NOAA-20 spacecraft. CERES uses MODIS and VIIRS imagers to retrieve cloud properties needed to convert CERES footprint radiance observations into fluxes using empirically derived angular directional models obtained during early CERES record. CERES utilizes geostationary sensors to infer the regional diurnal fluxes in between Terra and Aqua CERES observations. The imagers are also used to radiometrically scale the geostationary sensors (GEO) radiances to the imager calibration reference to ensure that the GEO derived cloud properties and broadband TOA fluxes are consistent in both space and time. Both the imager and GEO retrieved cloud properties are used to compute the surface fluxes. The Aqua-MODIS, SNPP-VIIRS, and NOAA-20 VIIRS afternoon imagers will also need to be radiometrically scaled to the same common calibration reference. Although all three imagers employ onboard solar diffusers, the calibration is not consistent over time due to instrument anomalies and ageing of the onboard calibrators. The CERES imager and GEO calibration group (IGCG) has been tasked to remove the imager channel calibration drifts for the next CERES reprocessing effort. The team will rely primarily on deep convective clouds, desert, and polar ice invariant targets to monitor the imager channel stability. The team uses ray-matched radiance pairs to radiometrically scale the SNPP and NOAA-20 VIIRS sensors to Aqua-MODIS. The radiometric scaling is further validated using geostationary imagers as transfer radiometers. The DSCOVR satellite was launched on February 25, 2015 and orbits around the L1 Lagrange point directly between the Earth and the sun. The EPIC instrument onboard DSCOVR employs a CCD array to image the Earth approximately every 2-hours. The EPIC sensor contains no onboard calibration systems. However, multiple inter-calibration studies have shown that the EPIC imager is very stable in time. This is likely due to the DSCOVR satellite being located about a 1.5M km from the Earth, where very little Earth reflected solar radiation degrades the optics. The excellent radiometric stability of EPIC allows the CERES IGCG to utilize the EPIC observations as a stable reference for monitoring the calibration stability of the three afternoon imagers, as well as to validate the radiometric scaling factors between them. Examples of the imager relative calibration using EPIC before and after radiometric scaling will be shown along with the results from the use of invariant targets to remove imager calibration drifts.

DSCOVR-EPIC↗
NASA NTRS2023

The Polarimetric Radar Scattering Properties of Oriented Aggregates

The scattering properties of aggregates are studied herein. Early aggregates (<7 monomers) of branched planar crystals and mature aggregates (up to 100 monomers) of columns are randomly generated with varying assumptions about the monomer attachment processes and the orientation behavior during collection. The resulting physical properties of the aggregates correspond well with prior in situ and retrieved sizes and shapes. Assumed azimuthally uniform orientations during collection and monomer pivoting upon attachment resulted in flatter and denser aggregates. The column aggregates had lower density and more spherical shapes than the branched planar crystal aggregates. The scattering properties were calculated using the discrete dipole approximation for a set of orientation angles and transformed to spectral coefficients representing modes of orientation angle variability. The zeroth- and second-order coefficients dominate this variability, with the zeroth-order coefficients representing the scattering properties for randomly oriented particles. The second-order coefficients for backscatter showed differences between horizontal and vertical polarization increasing with density, and these coefficients for specific differential phase increase with both mass and density. Similarly, coefficients for the copolar covariance decreased with density. Rapid changes in the contributions to the radar moments from the second-order coefficients from low to moderate density were observed, likely due to the increasing presence of horizontally aligned monomers in the aggregate structure. Differences in how differential reflectivity and correlation coefficient evolve with the orientation distribution parameters suggest that these measurements, along with specific differential phase and reflectivity, provide complementary information about aggregate sizes, shapes, and orientation distributions.

Cloud microphysics↗
NASA NTRSDate not supplied

Cloud and Precipitation Analyses using Merged Datasets from Two Airborne Microwave Radiometers Covering 10–183 GHz

Microwave radiometers provide valuable insight into the structure and characteristics of clouds and precipitation. In NASA’s airborne remote-sensing arsenal, the Advanced Microwave Precipitation Radiometer (AMPR) and the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) have been used extensively in field campaigns throughout the world. AMPR operates with four channels between 10.7 and 85.5 GHz, while CoSMIR operates with nine channels ranging from 50.3 to 183.31 GHz. Although these datasets provide key information when used separately, the combination of these radiometers covers virtually the full range of frequencies used by the Global Precipitation Measurement (GPM) Microwave Imager (GMI), enabling suborbital observations to compare with GPM spaceborne measurements. This presentation will detail the merger of AMPR and CoSMIR data during two NASA airborne field campaigns: the Integrated Precipitation and Hydrology Experiment (IPHEx) and the Olympic Mountains Experiment / Radar Definition Experiment (OLYMPEX/RADEX). Other field campaigns, such as the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS), may be included as well. Using the merged brightness temperature dataset, features of precipitating and non-precipitating clouds containing liquid and/or ice hydrometeors will be discussed from selected flight segments. Geophysical retrievals derived from these brightness temperatures using a one-dimensional variational (1DVAR) technique and/or multi-linear regression equations will also be employed in these analyses. Observed transitions between precipitating and non-precipitating systems will be explored in greater detail. Dropsonde data will be used to provide environmental contexts throughout each flight, and additional observations (e.g., from airborne and/or land-based radar) will be incorporated to supplement the radiometer-based results. The broader implications of these results and pathways for future work will also be discussed.

Corey G. Amiot↗
NASA NTRS1994

The Area Coverage of Geophysical Fields as a Function of Sensor Field-of View

In many remote sensing studies of geophysical fields such as clouds, land cover, or sea ice characteristics, the fractional area coverage of the field in an image is estimated as the proportion of pixels that have the characteristic of interest (i.e., are part of the field) as determined by some thresholding operation. The effect of sensor field-of-view on this estimate is examined by modeling the unknown distribution of subpixel area fraction with the beta distribution, whose two parameters depend upon the true fractional area coverage, the pixel size, and the spatial structure of the geophysical field. Since it is often not possible to relate digital number, reflectance, or temperature to subpixel area fraction, the statistical models described are used to determine the effect of pixel size and thresholding operations on the estimate of area fraction for hypothetical geophysical fields. Examples are given for simulated cumuliform clouds and linear openings in sea ice, whose spatial structures are described by an exponential autocovariance function. It is shown that the rate and direction of change in total area fraction with changing pixel size depends on the true area fraction, the spatial structure, and the thresholding operation used.

Key, Jeffrey R.↗
DOE OSTI2025

Contact Freezing of Water Droplets by Crystalline Organic Acids

The ability of water to freeze into ice crystals in mixed-phase clouds affects physical properties, including particle size, precipitation rates, and radiative properties. The presence of an insoluble particle at the surface of water droplets can promote ice nucleation at temperatures higher than that of pure water, even in the absence of a collision. However, contact freezing remains an underexplored mode of ice nucleation. Here, we present a study of atmospherically relevant organic acids and their role as effective ice-nucleating particles (INP) in contact mode using a Raman-microscope-equipped environmental chamber. We determined contact freezing temperatures induced by solid crystals of docosanol, adipic acid, cis-pinonic acid, fumaric acid, 4-hydroxybenzoic acid, palmitic acid, phthalic acid, sebacic acid, stearic acid, terephthalic acid, and vanillic acid. All solids except fumaric acid promoted contact freezing of water droplets at significantly higher temperatures than pure water in the chamber (−15.0 to −18.5 °C vs −21.3 °C). Physical and chemical properties were identified which correlate with greater effectiveness of INPs in the contact mode, including crystal lattice mismatch with ice, carbon number, and insolubility in water. In conclusion, we suggest that the presence of these organic solids in atmospheric aerosols may promote atmospheric ice nucleation at warm temperatures.

Clouds↗
NASA NTRS2005

Phytoplankton in the Beaufort and Chukchi Seas: Distributions, Dynamics and Environmental Forcing

Time-series of remotely sensed distributions of phytoplankton, sea ice, surface temperature, albedo, and clouds were examined to evaluate the impact of the variability of environmental conditions and physical forcing on the phytoplankton distribution in the Beaufort and Chukchi Seas. Large-scale distributions of these parameters were studied for the first time using weekly and monthly composites from April 1998 through September 2002. The basic data set used in this study are phytoplankton pigment concentration derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), ice concentration obtained from the Special Sensor Microwave Imager (SSM/I) and surface temperature, cloud cover, and albedo derived from the Advanced Very High Resolution Radiometer (AVHRR). Seasonal variations of the sea ice cover was observed to be the dominant environmental factor as the ice edge blooms followed the retreating marginal ice zones northward. Blooms were most prominent in the southwestern Chukchi Sea, and were especially persistent immediately north of the Bering Strait in nutrient- rich Anadyr water and in some fronts. Chlorophyll concentrations are shown to increase from a nominal value during onset of melt in April to a maximum value in mid-spring or summer depending on location. Large interannual variability of ice cover and phytoplankton distributions was observed with the year 1998 being uniquely associated with an early season occurrence of a massive bloom. This is postulated to be caused in part by a rapid response of phytoplankton to an early retreat of the sea ice cover in the Beaufort Sea region. Correlation analyses showed relatively high negative correlation between chlorophyll and ice concentration with the correlation being highest in May, the correlation coefficient being -0.45. 1998 was also the warmest among the five years globally and the sea ice cover was least extensive in the Beaufort-Khukchi Sea region, partly because of the 1997-98 El Nino. Strong correlations were noted between ice extent and surface temperature, the correlation coefficient being highest at - 0.79 in April, during the onset of the bloom period

Wang, Jian↗
NASA NTRS1988

National plans for aircraft icing and improved aircraft icing forecasts and associated warning services

Recently, the United States has increased its activities related to aircraft icing in numerous fields: ice phobics, revised characterization of icing conditions, instrument development/evaluation, de-ice/anti-ice devices, simulated supercooled clouds, computer simulation and flight tests. The Federal Coordinator for Meteorology is involved in two efforts, one a National Plan on Aircraft Icing and the other a plan for Improved Aircraft Icing Forecasts and Associated Warning Services. These two plans will provide an approved structure for future U.S. activities related to aircraft icing. The recommended activities will significantly improve the position of government agencies to perform mandated activities and to enable U.S. manufacturers to be competitive in the world market.

Pass, Ralph P.↗
NASA NTRS2000

Structural Characterization of Crystalline Ice Nanoclusters

Water ice nanoclusters are useful analogs for studying a variety of processes that occur within icy grains in the extraterrestrial environment. The surface of ice nanoclusters prepared in the laboratory is similar to the surface of interstellar ice grains. In cold molecular clouds, the silicate cores of interstellar grains are typically approx. 100 nm in diameter and have a coating of impure amorphous water ice. Depositional, thermal and radiolytic processes leave the surface and subsurface molecules in a disordered state. In this state, structural defects become mobile and reactions of trapped gases and small molecules can occur. The large surface area of nanocluster deposits relative to their bulk allows for routine observation of such surface-mediated processes. Furthermore, the disordered surface and subsurface layers in nanocluster deposits mimic the structure of amorphous ice rinds found on interstellar dust grains. Transmission Electron Microscopy (TEM has been used tn characterize the crystallinity, growth mechanism, and size distribution of nanoclusters formed from a mixture of water vapor with an inert carrier gas that has been rapidly cooled to 77K. E M imaging reveals a Gaussian size distribution around a modal diameter that increases from approx. 15 to 30 nm as the percentage of water vapor within the mixture increases from 0.5 to 2.007, respectively . TEM bright and dark field imaging also reveals the crystalline nature of the clusters. h4any of the clusters show a mosaic structure in which crystalline domains originate at the center Other images show mirror planes that are separated by approx. 10 nm. Electron diffraction patterns of these clusters show that the clusters are composed of cubic ice with only a small hexagonal component. Further, the crystalline domain size is approximately the same as the modal diameter suggesting that the clusters are single crystals.

Blake, David↗
DOE OSTI2022

Ice processes in Antarctica: identification via multi-wavelength active and passive measurements and model evaluation (Final Report)

This project is based on new multi-frequency radar observations collected during the AWARE field campaign in 2016 at McMurdo Station by the ARM Mobile facility. Three scientific goals have been achieved. We have developed ice and mixed-phase cloud microphysics retrievals from multi-wavelength radar observations and ancillary observations, generally applicable at ARM sites. These technique generally better characterize the size of the ice crystals, their equivalent water content and the degree of riming better than using single wavelength techniques. We have characterized ice microphysical properties and ice processes via multi-frequency signatures. We have identified a unique mode in the McMurdo dataset appearing at quite cold temperature that we have attributed to riming processes. Triple frequency radar measurements unfortunately were available only for a short period but our work lays the foundation for building climatological and testing their replicability in models. Simultaneously case studies from the AWARE campaign have been exploited to evaluate and improve the NASA GISS ModelE3 climate model, including selection of case studies for combined goals of (i) running side-by-side using large-eddy simulation (LES) and ModelE3 in single-column model (SCM) mode and (ii) fingerprinting cloud processes in multi-wavelength radar observations. The different components of this work have contributed to 15 published papers with two currently under review.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Investigating the Relative Roles of INPs and CCN in a Simulated Thunderstorm Using a New Immersion Freezing Algorithm

Microphysical processes in deep convective clouds are sensitive to the number concentrations of cloud condensation nuclei (CCN) and ice nucleating particles (INPs), but the effects of INPs are less studied. Modeling studies investigating the effects of INPs and/or CCN on deep convection typically retain a volume‐dependent raindrop freezing relation. The resulting neglect of aerosol accumulation in raindrops via drop collisions has likely produced unrealistic storm responses to INPs in past studies. To address this deficiency, a new immersion freezing algorithm was developed and embedded in a bulk microphysics scheme that freezes both cloud drops and raindrops using the same immersion freezing INP (IF‐INP) activity spectrum based on measurements. Multiple idealized simulations of a single case of deep convection observed during the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign were conducted, with microphysical differences produced by independently altering IF‐INP temperature dependencies and CCN number concentrations from their observed values. Surface precipitation in all simulations resulted almost exclusively from riming graupel that melted upon descending to the surface. Rainfall and cold pools were substantially and systematically weakened with increased CCN due to decreased graupel riming rates but were relatively insensitive to variations in the magnitude and slope of IF‐INP spectra due to compensating depletion of supercooled liquid water. These compensating processes were a consequence of the accumulation of IF‐INPs in raindrops, encouraging caution in studying IF‐INP effects upon thunderstorms using traditional volume‐dependent drop freezing relationships.

CCN↗
NASA NTRS2000

Remote sensing of convective clouds with Microwave Limb Sounder

Deep convection lifts up many large ice particles to the upper troposphere where they can be detected with microwave sensors from space, using limb-viewing techniques. Microwave Limb Sounder (MLS) has unique advantages in measuring these high clouds and their ice mass with vertical resolution.

Microwave Limb Sounder↗
NASA NTRS1998

Microwave Brightness Temperatures of Tilted Convective Systems

Aircraft and ground-based radar data from the Tropical Ocean and Global Atmosphere Coupled-Ocean Atmosphere Response Experiment (TOGA COARE) show that convective systems are not always vertical. Instead, many are tilted from vertical. Satellite passive microwave radiometers observe the atmosphere at a viewing angle. For example, the Special Sensor Microwave/Imager (SSM/I) on Defense Meteorological Satellite Program (DMSP) satellites and the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) on the TRMM satellite have an incident angle of about 50deg. Thus, the brightness temperature measured from one direction of tilt may be different than that viewed from the opposite direction due to the different optical depth. This paper presents the investigation of passive microwave brightness temperatures of tilted convective systems. To account for the effect of tilt, a 3-D backward Monte Carlo radiative transfer model has been applied to a simple tilted cloud model and a dynamically evolving cloud model to derive the brightness temperature. The radiative transfer results indicate that brightness temperature varies when the viewing angle changes because of the different optical depth. The tilt increases the displacements between high 19 GHz brightness temperature (Tb(sub 19)) due to liquid emission from lower level of cloud and the low 85 GHz brightness temperature (Tb(sub 85)) due to ice scattering from upper level of cloud. As the resolution degrades, the difference of brightness temperature due to the change of viewing angle decreases dramatically. The dislocation between Tb(sub 19) and Tb(sub 85), however, remains prominent.

Hong, Ye↗
NASA NTRS2024

Classifying Microwave Radiometer Observations Over the Netherlands Into Dry, Shallow-, and Non-Shallow Precipitation Using A Random Forest Model

Spaceborne microwave radiometers represent an important component of the Global Precipitation Measurement (GPM) mission due to their frequent sampling of rain systems. Microwave radiometers measure microwave radiation (brightness temperatures, Tb), which can be converted into precipitation estimates with appropriate assumptions. However, detecting shallow precipitation systems using space-borne radiometers is challenging, especially over land, as their weak signals are hard to differentiate from those associated with dry conditions. This study uses a random forest model (RF) to classify microwave radiometer observations as dry, shallow, or nonshallow over the Netherlands - a region with varying surface conditions and frequent occurrence of shallow precipitation. The RF is trained on five years of data (2016-2020) and tested with two independent years (2015, 2021). The observations are classified using ground-based weather radar echo top heights. Various RF models are assessed, such as using only GPM’s Microwave Imager (GMI) Tb values as input features or including spatially aligned ERA-5 2-meter temperature and freezing level reanalysis and/or Dual Precipitation Radar (DPR) observations. Independent of the input features, the model performs best in summer and worst in winter. The model classifies observations from high-frequency channels (≥85 GHz) with lower Tb-values as non-shallow, higher values as dry, and those in between as shallow. Misclassified footprints exhibit radiometric characteristics corresponding to their assigned class. Case studies reveal dry observations misclassified as shallow are associated with lower Tb-values, likely resulting from the presence of ice particles in non-precipitating clouds. Shallow footprints misclassified as dry are likely related to the absence of ice particles.

Linda Bogerd↗
DOE OSTI2021

Observed and Simulated Variability of Droplet Spectral Dispersion in Convective Clouds Over the Amazon

Abstract In this study, the variability of the spectral dispersion of droplet size distributions (DSDs) in convective clouds is investigated. Analyses are based on aircraft measurements of growing cumuli near the Amazon basin, and on numerical simulations of an idealized ice‐free cumulus. In cleaner clouds, the relative dispersion , defined as the ratio of the standard deviation to the mean value of the droplet diameter, is negatively correlated with the ratio of the cloud water content ( ) to the adiabatic liquid water content ( ), while no strong correlation between and is seen in polluted clouds. Bin microphysics numerical simulations suggest that these contrasting behaviors are associated with the effect of collision‐coalescence in cleaner clouds, and secondary droplet activation in polluted clouds, in addition to the turbulent mixing of parcels that experienced different paths within the cloud. Collision‐coalescence simultaneously broadens the DSDs and decreases , explaining the inverse relationship between and in cleaner clouds. Secondary droplet activation broadens the DSDs but has little direct impact on . The combination of a rather modest DSD broadening due to weak collision‐coalescence with enhanced droplet activation in both diluted and highly undiluted cloud regions may contribute to maintain a relatively uniform within polluted clouds. These findings can be useful for parameterizing the shape parameter ( ) of gamma DSDs in bulk microphysics cloud‐resolving models. It is shown that emulating the observed relationship improves the estimation of the collision‐coalescence rate in bulk microphysics simulations compared to the bin simulations.

54 ENVIRONMENTAL SCIENCES↗