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NASA NTRS1992

Cirrus microphysics and radiative transfer - Cloud field study on 28 October 1986

An analysis of remote-sensing measurements which had detected an inhomogeneous cloud structure, at 6-11 km altitude, in the data acquired during the FIRE 86 experiment in a 75 x 50 km cirrus cloud field, has derived fluxes whose comparison with modeled fluxes imply a modeling-based underestimation of both solar reflectivity/attenuation and downward IR fluxes. Reconciliation of model results with measurements can be achieved either by adding large concentrations of ice crystals or by altering the backscattering properties of ice crystals.

Kinne, Stefan↗

NASA NTRSDate not supplied

CALIGOLA: A New Spaceborne Lidar Mission

Agenzia Spaziale Italiana (ASI) and NASA are partnering on an exciting new spaceborne lidar mission known as CALIGOLA (i.e., the Cloud and Aerosol Lidar for Global Scale observations of the Ocean-Land-Atmosphere) that seeks to significantly advance our understanding of Earth’s coupled ocean-land-atmosphere systems. By flying an innovative multi-wavelength, polarization-sensitive Raman lidar that will simultaneously acquire elastic backscatter and fluorescence measurements, CALIGOLA will provide new insights into the processes that influence climate, weather, and air quality by vertically profiling microphysical and optical properties of clouds and aerosols. The mission will also probe phytoplankton biomass and zooplankton dynamics and provide observations of surface vegetation, ice, and snow. The mission is planned for launch early next decade and baselined to fly in an orbit that is compatible with NASA’s AOS-Sky mission. This formation flying configuration will enable synergistic retrievals between observations from CALIGOLA and the polarimeter and radar measurements planned for AOS-Sky and thus greatly enhance our ability to explore and characterize the intricate processes that govern the interactions between different components of the Earth system. The presentation will highlight CALIGOLA’s significant science objectives and describe the pioneering instrument that will enable us to achieve these objectives.

Chip Trepte↗

NASA NTRS2008

Testing of Cloud Microphysics Scheme with Snow Events

One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve precipitation measurements in mid- and high-latitudes during cold seasons through the use of high-frequency passive microwave radiometry. For this, the Weather Research Forecast (WRF) model with the Goddard microphysics scheme is coupled with the Satellite Data Simulation Unit (WRF-SDSU) that has been developed to facilitate the over-snowfall retrieval algorithm by providing virtual cloud library and microwave brightness temperature (To) measurements consistent to the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF in snowstorm events (January 20-22, 2007) over the Canadian CloudSat/CALIPSO Validation Project (C3VP) site up in Ontario, Canada. In this meeting, we will present the performance of the Goddard cloud microphysics scheme both with 2ice (ice and snow) and 3ice (ice, snow and graupel) as well as other WRF microphysics schemes. Results will be compared with the King Radar data. We will also use the WRF model outputs to drive the Goddard SDSU to calculate radiances and backscattering signals consistent to satellite direct observations. These simulated radiance are evaluated against the measurement from A-Train satellites.

Tao, Wei-Kuo↗

NASA NTRS2021

Maya Forest Water Resources I: Using NASA Earth Observations to Map Forested Inundation in the Maya Forest

As climate change increases the severity and frequency of extreme weather events in the tropics, it is vital for the safety of local communities and the health of ecosystems to monitor seasonal inundation. Forested inundation affects the ability of forested wetlands to provide ecosystem services, such as flood mitigation, water filtration, carbon storage, and erosion mitigation. While ground-based monitoring has traditionally been used to map inundation extent, those methods are costly and time-intensive. The NASA DEVELOP team focused on seasonal inundation throughout 2008 in the Maya Forest, when changes in inundation were drastic. To monitor seasonal inundation, our team used in situ field data and Earth observations from Landsat 7 Enhanced Thematic Mapper (ETM+), Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) 1, Shuttle Radar Topography Mission (SRTM), and products from the Ice, Cloud, and Land Elevation Satellite (ICESat). The team applied a Random Forest algorithm to Landsat 7 imagery, generating an object-level land cover classification with an overall accuracy of 72.1% and forest class with 100% recall and 78% precision. The team applied L-band backscatter thresholds from existing literature to forest-masked ALOS imagery and refined the thresholds in an iterative process using field data and hydrology models to delineate seasonal inundation extent. These publicly available data products help end users from Belize’s Land Information Center (LIC) and Forest Department, Guatemala’s Center for Monitoring and Evaluation (CEMEC), and Mexico’s El Colegio de la Frontera Sur (ECOSUR) to inform land management and protect community infrastructure.

Madelyn Savan↗

NASA NTRSDate not supplied

Snow Depth from AMSR-2 Using Multispectral Satellite Data in an Artificial Neural Network

By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu et al. (2022) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, an artificial neural network (ANN) algorithm, employing several channels from Advanced Microwave Scanning Radiometer 2 (AMSR-2) and the humidity vertical profiles from Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System for Instrument Teams (GEOS-IT) product, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained ANN snow-depth was applied to 2018 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. The validation data (different from the training set) of ANN snow depth from AMSR-2 showed a good agreement with time matched and co-located snow-depth values from ICESat-2. The bias was near zero, with mean absolute error (MAE) 0.05 cm and a root-mean-square-error (RMSE) 0.08 cm. Prior applying the trained ANN snow depth to AMSR-2 data, a cloud screening algorithm was developed with a similar approach. A separate ANN cloud mask was trained to determine an AMSR-2 pixel is clear or cloudy with time and geolocation matched 2015 CALIOP Vertical Feature Mask (VFM) over Arctic sea ice. The ANN cloud mask from AMSR-2 under-estimated cloud fraction by 3-6% compared to CALIOP . The additional research is needed to conclusively evaluate the ANN cloud mask accuracy. Finally, this paper will lay the foundation for a sustained long-term snowfall and snow-storm monitoring system. The future Cloud Aerosol LIdar for Global scale Observations of the ocean-Land Atmosphere system (CALIGOLA) mission will provide a means to calculate snow depth from the lidar backscattering pathlength distribution, benefiting from the UV, visible and infrared pulses. With the calculated snow depth as the truth one could develop a machine learning algorithm, as it was done in this paper, using a passive microwave instrument available at that time to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.

Neural Network↗

NASA NTRS1993

CO2 lidar observations of Mount Pinatubo debris: FIRE 2 and longer-term measurements

The volcanic debris in the stratosphere from the June 1991 eruption of Mt. Pinatubo first appeared over the NOAA Wave Propagation Laboratory (WPL) field site near Boulder, Colorado (40.15 N, 105.23 W), in July of 1991. The presence of the Pinatubo cloud has allowed us to characterize both the tropospheric and stratospheric aerosol backscatter using the NOAA/WPL CO2 Doppler lidar. The lidar has measured vertical backscatter profiles at lambda = 10.59 mu m for over a decade. Analysis of this dense set of profiles reveals the effects of atmospheric and microphysical processes during the buildup and decay of Mt. Pinatubo's clouds. Further information on the NOAA lidar, specifically calibrations using a hard target, can be found in Post and Cupp (1990). We present results of those measurements for June 15, 1991, through December 31, 1992. During that period of longer-term measurements, WPL took part in FIRE II (First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment II), from November 12 through December 8, 1991, measuring vertical backscatter profiles almost daily. One of the mechanisms for purging stratospheric aerosols is tropopause folding, which occurs in cold-core extratropical cyclones. Tropospheric mass loading occurs during folding events which can substantially increase the amount of ice nuclei in the upper troposphere, and may affect the formation of cirrus in that region. Spring and fall are prominent times for tropopause folding events because of the migration of the subtropical and polar jet streams during the transition seasons. Sassen has suggested that the volcanic aerosols from Pinatubo played a role in the formation of cirrus during FIRE II, particularly during a period of moist subtropical flow on December 5-6, 1991.

Levinson, David H.↗

NASA NTRS2023

Polarization Calibration Using Solar Radiation Background Signal Scattered from Dense Cirrus Clouds in the Visible and Ultraviolet Wavelength Regimes

In this presentation we describe the application of a previously developed technique that is now being used to correct the daytime polarization calibration of the CALIPSO lidar. The technique leverages the fact that the solar radiation background signals from dense cirrus clouds are largely unpolarized due to the internal multiple reflections within the non-spherical ice particles and the multiple scattering that occurs among these particles. Therefore, the ratio of polarization components of the cirrus background signals provides a good estimate for the polarization gain ratio (PGR) of the lidar. Using airborne backscatter lidar measurements, this technique was demonstrated to work well in the infrared regime. However, in the visible and ultraviolet regime, the molecular contribution is too large to be ignored, and thus corrections must be applied to account for the highly polarizing characteristics of the molecular scattering. Ignoring molecular scattering contributions can cause PGR errors of 2-3% at 532 nm, where the CALIPSO lidar makes its depolarization measurement. Because of the wavelength dependence of -4 of the molecular scattering, the PGR error can be even larger at the 355 nm wavelength that will be used by ESA’s EarthCARE lidar. To correct the molecular scattering contributions to the lidar received solar background signal, a look-up table has been created using a polarization-sensitive radiative transfer model. This presentation describes the theory and implementation of the molecular scattering correction.

Zhaoyan Liu↗

NASA NTRS2001

Correlation Between Cirrus Particle Optical Properties: Microphysics and Implications for Spaceborne Remote Sensing

Cirrus measurements obtained with a ground-based polarization Raman lidar at 67.9 deg N in arctic winter reveal a strong correlation between the particle optical properties, specifically depolarization ratio and extinction-to-backscatter ratio, for ambient cloud temperatures above approximately -45 C, and an anti-correlation for colder temperatures. Similar correlations are evident in a 2-year midlatitude (53.4 deg N) cirrus data set. Scattering calculations show that the observed dependences can be interpreted in terms of the shapes and sizes of the cirrus ice particles. These findings suggest a retrieval method for determining cirrus extinction profiles from spaceborne lidar polarization data.

Reichardt, Jens↗

DOE OSTI2025

A new technique to retrieve aerosol vertical profiles using micropulse lidar and ground-based aerosol measurements

Accurately characterizing the vertical distribution of aerosols and their cloud-forming properties is crucial for understanding aerosol-cloud interactions and their impact on climate. This study presents a novel technique for retrieving vertical profiles of aerosols, cloud condensation nuclei (CCN), and ice nucleating particles (INP) by combining micropulse lidar, radiosonde, and ground-based aerosol measurements. Herein, the technique is applied to data collected by our team at Texas A&M University during the Tracking Aerosol Convection Interactions ExpeRiment (TRACER) campaign. Ground-based aerosol size distribution and CCN counter data are used to estimate the value of the aerosol hygroscopicity parameter, κ. The derived κ, together with Mie scattering theory and the relative humidity profile from the radiosonde, is used to estimate aerosol size growth and the associated increase in backscatter at each altitude. We then correct the lidar backscatter to dry conditions to produce the dry aerosol backscatter coefficient profile. The dry aerosol backscatter coefficient profile is linearly scaled to collocated surface measurements of aerosols, CCN, and INP to produce corresponding vertical profiles. Combining lidar backscatter profiles with aerosol and cloud nucleation measurements leads to a more realistic representation of vertical distributions of aerosol properties. The method could be readily applied to lidar measurements in future field campaigns.

Chen, Bo [Texas A & M Univ., College Station, TX (↗

NASA NTRS1989

The 27-28 October 1986 FIRE IFO cirrus case study: Cirrus parameter relationships derived from satellite and lidar data

Cirrus cloud radiative and physical characteristics are determined using a combination of ground-based, aircraft, and satellite measurements taken as part of the First ISCCP Regional Experiment (FIRE) Cirrus Intensive Field Observations (IFO) during October and November 1986. Lidar backscatter data are used to define cloud base, center, and top heights and the corresponding temperatures. Coincident GOES 4 km visible (0.65 microns) and 8 km infrared window (11.5 microns) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance mode. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8 km for the 71 scenes. An average visible scattering efficiency of 2.1 was found for this data set. The results reveal a significant dependence of scattering efficiency on cloud temperature.

Minnis, Patrick↗

NASA NTRS1990

The 27-28 October 1986 FIRE IFO cirrus case study - Cirrus parameter relationships derived from satellite and lidar data

Minnis, Patrick↗

NASA NTRS1995

Condensed Water in Tropical Cyclone "Oliver", 8 February 1993

On February 8, 1993, the NASA DC-8 aircraft profiled from 10,000 to 37,000 feet (3.1-11.3 km) pressure altitude in a stratified section of tropical cyclone "Oliver" over the Coral Sea northeast of Australia. Size, shape and phase of cloud and precipitation particles were measured with a 2-D Greyscale probe. Cloud/precipitation particles changed from liquid to ice as soon as the freezing level was reached near 17,000 feet (5.2 km) pressure altitude. The cloud was completely glaciated at -5 C. There was no correlation between ice particle habit and ambient temperature. In the liquid phase, the precipitation-cloud drop concentration was 4.0 x 10(exp 3)/cu m, the geometric mean diameter D(sub g) = 0.5-0.7 mm, and the liquid water content 0.7-1.9 g m(exp-3). The largest particles anywhere in the cloud, dominated by fused dendrites at concentrations similar to that of raindrops (2.5 x 10(exp 3) m(exp -3)) but a higher condensed water content(5.4 g/cu m estimated) were found in the mixed phase; condensed water is removed very effectively from the mixed layer due to high settling velocities of the large mixed particles. The highest number concentration (4.9 x 10(exp 4)/cu m, smallest size (D(sub g) = 0.3-0.4 mm), largest surface area (up to 2.6 x 10 (exp 2) sq cm/cu m at 0.4- 1.0 g/cu m of condensate) existed in the ice phase at the coldest temperature (- 40 C) at 35,000 feet ( 10.7 km). Each cloud contained aerosol (haze particles) in addition to cloud particles. The aerosol total surface area exceeded that of the cirrus particles at the coldest temperature. Thus, aerosols must play a significant role in the upscattering of solar radiation. Light extinction (6.2/km) and backscatter (0.8/sr/km) was highest in the coldest portion of the cirrus cloud at the highest altitude.

Pueschel, R. F.↗

NASA NTRS2005

Height Distribution Between Cloud and Aerosol Layers from the GLAS Spaceborne Lidar in the Indian Ocean Region

The Geoscience Laser Altimeter System (GLAS), a nadir pointing lidar on the Ice Cloud and land Elevation Satellite (ICESat) launched in 2003, now provides important new global measurements of the relationship between the height distribution of cloud and aerosol layers. GLAS data have the capability to detect, locate, and distinguish between cloud and aerosol layers in the atmosphere up to 40 km altitude. The data product algorithm tests the product of the maximum attenuated backscatter coefficient b'(r) and the vertical gradient of b'(r) within a layer against a predetermined threshold. An initial case result for the critical Indian Ocean region is presented. From the results the relative height distribution between collocated aerosol and cloud shows extensive regions where cloud formation is well within dense aerosol scattering layers at the surface. Citation: Hart, W. D., J. D. Spinhime, S. P. Palm, and D. L. Hlavka (2005), Height distribution between cloud and aerosol layers from the GLAS spaceborne lidar in the Indian Ocean region,

Hart, William D.↗

NASA NTRS1996

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

Cirrus cloud radiative and physical characteristics are determined using a combination of ground based, aircraft, and satellite measurements taken as part of the First ISCCP Region Experiment (FIRE) cirrus intensive field observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center and top heights and the corresponding temperatures. Coincident GOES-4 4-km visible (0.65 micrometer) and 8-km infrared window (11.5 micrometer) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 062 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance , extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface-based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature wer ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperature and cloud thickness from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. the parameterization of visible reflectance in terms of cloud optical depth and clear sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous advanced very high resolution radiometer (AVHRR) data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloud pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study or cirrus cloud scattering processes and remote sensing techniques.

Minnis, Patrick↗

NASA NTRS1986

Lidar measurement of stratospheric aerosol at Syowa Station, Antarctica

Lidar measurement on Antarctic aerosols were made during the Antarctic Middle Atmosphere (AMA) period, 1983 to 1985, at Syowa Station. Topics measured are winter enhancement aerosol layer and volcanic effect of El Chichon on the Antarctic stratosphere aerosols. The large depolarization ratio (maximum value was about 0.8) seems to support sublimation growth of ice crystals. The lidar measurements showed a meaningful time lag between aerosol content increase and depolarization ratio increase. Considering the balloon observations made in early winter, it was speculated that an increase in large particle number concentration also contributed to the winter enhancement. The El Chichon cloud spread to the Antarctic region by the beginning of 1983. The temporal change of integrated backscatter coefficient shows a clear decay pattern, although strong winter enhancement superposes.

Iwasaka, Y.↗

NASA NTRS1991

Corona-producing cirrus cloud properties derived from polarization lidar and photographic analyses

Polarization lidar data are used to demonstrate that clouds composed of hexagonal ice crystals can generate multiple-ringed colored coronas. Although relatively uncommon in the mid-latitude cirrus sample, the coronas are associated with unusual cloud conditions that appear to be effective in generating the displays. Invariably, the cirrus cloud tops are located at or slightly above elevated tropopauses at temperatures between -60 and -70 C. The cloud top region also generates relatively strong laser backscattering and unusually high 0.5-0.7 linear depolarization ratios. Color photograph analysis of corona ring angles indicates crystals with mean diameters of from 12 to 30 microns. The cirrus cloud types were mainly subvisual to thin cirrostratus, but also included fibrous cirrus. Estimated cloud optical thicknesses at the 0.694-micron laser wavelength ranged from about 0.001 to 0.2, where the upper limit reflects the effects of multiple scattering and/or unfavorable changes in particle characteristics in deep cirrus clouds.

Sassen, Kenneth↗

NASA NTRS1990

The 27-28 October 1986 FIRE IFO Cirrus Case Study: Cirrus Parameter Relationships Derived from Satellite and Lidar Data

Cirrus cloud radiative and physical characteristics are determined using a combination of ground-based, aircraft, and satellite measurements taken as part of the FIRE Cirrus Intensive Field Observations (IFO) during October and November 1986. Lidar backscatter data are used with rawinsonde data to define cloud base, center, and top heights and the corresponding temperatures. Coincident GOES 4-km visible (0.65 micro-m) and 8-km infrared window (11.5 micro-m) radiances are analyzed to determine cloud emittances and reflectances. Infrared optical depth is computed from the emittance results. Visible optical depth is derived from reflectance using a theoretical ice crystal scattering model and an empirical bidirectional reflectance model. No clouds with visible optical depths greater than 5 or infrared optical depths less than 0.1 were used in the analysis. Average cloud thickness ranged from 0.5 km to 8.0 km for the 71 scenes. Mean vertical beam emittances derived from cloud-center temperatures were 0.62 for all scenes compared to 0.33 for the case study (27-28 October) reflecting the thinner clouds observed for the latter scenes. Relationships between cloud emittance, extinction coefficients, and temperature for the case study are very similar to those derived from earlier surface- based studies. The thicker clouds seen during the other IFO days yield different results. Emittances derived using cloud-top temperature were ratioed to those determined from cloud-center temperature. A nearly linear relationship between these ratios and cloud-center temperature holds promise for determining actual cloud-top temperatures and cloud thicknesses from visible and infrared radiance pairs. The mean ratio of the visible scattering optical depth to the infrared absorption optical depth was 2.13 for these data. This scattering efficiency ratio shows a significant dependence on cloud temperature. Values of mean scattering efficiency as high as 2.6 suggest the presence of small ice particles at temperatures below 230 K. The parameterization of visible reflectance in terms of cloud optical depth and clear-sky reflectance shows promise as a simplified method for interpreting visible satellite data reflected from cirrus clouds. Large uncertainties in the optical parameters due to cloud reflectance anisotropy and shading were found by analyzing data for various solar zenith angles and for simultaneous AVHRR data. Inhomogeneities in the cloud fields result in uneven cloud shading that apparently causes the occurrence of anomalously dark, cloudy pixels in the GOES data. These shading effects complicate the interpretation of the satellite data. The results highlight the need for additional study of cirrus cloud scattering processes and remote sensing techniques.

Minnis, Patrick↗

NASA NTRS2009

The 20-22 January 2007 Snow Events over Canada: Microphysical Properties

One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve precipitation measurements in mid- and high-latitudes during cold seasons through the use of high-frequency passive microwave radiometry. Toward this end, the Weather Research and Forecasting (WRF) model with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF-SDSU) that has been developed to facilitate over-land snowfall retrieval algorithms by providing a virtual cloud library and microwave brightness temperature (Tb) measurements consistent with the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF for snowstorm events (January 20-22, 2007) that took place over the Canadian CloudSAT/CALIPSO Validation Project (C3VP) ground site (Centre for Atmospheric Research Experiments - CARE) in Ontario, Canada. In this paper, the performance of the Goddard cloud microphysics scheme both with 2ice (ice and snow) and 3ice (ice, snow and graupel) as well as other WRF microphysics schemes will be presented. The results are compared with data from the Environment Canada (EC) King Radar, an operational C-band radar located near the CARE site. In addition, the WRF model output is used to drive the Goddard SDSU to calculate radiances and backscattering signals consistent with direct satellite observations for evaluating the model results.

Tao. W.K.↗