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NASA NTRS2015

Liquid Water Cloud Properties During the Polarimeter Definition Experiment (PODEX)

We present retrievals of water cloud properties from the measurements made by the Research Scanning Polarimeter (RSP) during the Polarimeter Definition Experiment (PODEX) held between January 14 and February 6, 2013. The RSP was onboard the high-altitude NASA ER-2 aircraft based at NASA Dryden Aircraft Operation Facility in Palmdale, California. The retrieved cloud characteristics include cloud optical thickness, effective radius and variance of cloud droplet size distribution derived using a parameter-fitting technique, as well as the complete droplet size distribution function obtained by means of Rainbow Fourier Transform. Multi-modal size distributions are decomposed into several modes and the respective effective radii and variances are computed. The methodology used to produce the retrieval dataset is illustrated on the examples of a marine stratocumulus deck off California coast and stratus/fog over California's Central Valley. In the latter case the observed bimodal droplet size distributions were attributed to two-layer cloud structure. All retrieval data are available online from NASA GISS website.

Electromagnetic scattering↗
NASA NTRS2016

Far-Infrared Room-Temperature Focal Plane Modules for Radiation Budget Instrument

This work presents focal plane modules for a Radiation Budget Instrument, a passive remote-sensing instrument that follows the legacy of the Clouds and Earth’s Radiant Energy System (CERES) to measure short and longwave Earth’s radiation budget. The focal plane arrays are micromachined at JPL (Jet Propulsion Laboratory) and integrated into sub-assembly modules to be mounted on the optical telescope of the instrument.

Mariani, Giacomo↗
NASA NTRS2019

Long-Lived In-Situ Solar System Explorer (LLISSE): Potential Contributions to the Next Decade of Solar System Exploration

Venus, while having similar size, mass, and location in the solar system to Earth, varies from Earth in many ways and holds many scientific mysteries despite many missions that have focused on it in the past. Primary differences include Venus' climate, atmosphere, and perhaps most notably the extreme surface conditions. The layers of sulfuric acid clouds and high pressure CO2 laden atmosphere make remote sensing at Venus much less effective than at other solar system bodies. In addition, surface conditions present formidable engineering challenges due to the high temperature, pressure, and reactive chemistry. To date, landed missions have not been able to last more than about 2 hours on the surface [1]. This has resulted in significant knowledge gaps about the surface conditions of this important body in the solar system. The science community has effectively no in-situ temporal data at the Venus surface. These data are critical for the development of a thorough understanding of Venus' weather and the processes by which chemical species interact with each other and are transported throughout the atmospheric column. The LLISSE platform, and its variants, are a foundation for future mission concepts based on a core set of long-lived technologies providing significant new science as well as demonstrating new technical capabilities. After completion, LLISSE has the potential to be a complimentary element to missions going to Venus and would provide unique and important science to missions whether they be orbiters or short duration landers.

Kremic, Tibor↗
NASA NTRS2019

Long-Lived In-Situ Solar System Explorer (LLISSE)

Venus, while having similar size, mass, and location in the solar system to Earth, varies from Earth in many ways and holds many scientific mysteries despite many missions that have focused on it in the past. Primary differences include Venus' climate, atmosphere, and perhaps most notably the extreme surface conditions. The layers of sulfuric acid clouds and high pressure CO2 laden atmosphere make remote sensing at Venus much less effective than at other solar system bodies. In addition, surface conditions present formidable engineering challenges due to the high temperature, pressure, and reactive chemistry. To date, landed missions have not been able to last more than about 2 hours on the surface [1]. This has resulted in significant knowledge gaps about the surface conditions of this important body in the solar system. The science community has effectively no in-situ temporal data at the Venus surface. These data are critical for the development of a thorough understanding of Venus' weather and the processes by which chemical species interact with each other and are transported throughout the atmospheric column. The LLISSE platform, and its variants, are a foundation for future mission concepts based on a core set of long-lived technologies providing significant new science as well as demonstrating new technical capabilities. After completion, LLISSE has the potential to be a complimentary element to missions going to Venus and would provide unique and important science to missions whether they be orbiters or short duration landers.

Kremic, Tibor↗
NASA NTRSDate not supplied

Air Quality Forecasting at Sub-City Scale by Combining Models, Satellites, and Surface Measures

While there are a variety of sources for air quality information, no one source simultaneously allows for high accuracy, low bias, fine spatial resolution, wide spatial coverage, high temporal frequency, and the capability for near-term forecasting of air quality. Global models, like the NASA’s Goddard Earth Observing System -Composition Forecasting (GEOS-CF) model, provide global coverage and forecasting capabilities, but operate at relatively coarse spatial resolution and require ground-truthing with in-situ data. Polar-orbiting satellite data products, like those of the ESA TROPOspheric Monitoring Instrument (TROPOMI), provide higher-spatial-resolution remote sensing of atmospheric composition, but are limited by cloud cover and overpass times and report column-integrated quantities. Surface measurements, both from regulatory-grade monitors and low-cost networks, measure “nose-level” air quality, but may not represent concentration variability across large spatial domains, and (in the case of low-cost sensors) are subject to interference and biases. There exists a great potential to combine these diverse data sources together, using the strengths of some to offset the weaknesses of others to build a more comprehensive picture of air quality. This presentation will summarize results from ongoing efforts to produce such a combined forecast, with application case studies for surface-level Nitrogen Dioxide forecasting in several major US cities. Furthermore, we will examine the relative impacts and benefits of different data sources on the forecasting accuracy at different spatial and temporal scales. Finally, we will examine the potential for integrating low-cost sensors into such a system, both in terms of using these integrated air quality estimates as a baseline from which to calibrate networks of low-cost sensors in the field, and in terms of using dense networks of low-cost sensors to refine the spatial resolution of integrated air quality forecasts.

Air Quality↗
NASA NTRS2006

Properties of CIRRUS Overlapping Clouds as Deduced from the GOES-12 Imagery Data

Understanding the impact of cirrus clouds on modifying both the solar reflected and terrestrial emitted radiations is crucial for climate studies. Unlike most boundary layer stratus and stratocumulus clouds that have a net cooling effect on the climate, high-level thin cirrus clouds can have a warming effect on our climate. Many research efforts have been devoted to retrieving cirrus cloud properties due to their ubiquitous presence. However, using satellite observations to detect and/or retrieve cirrus cloud properties faces two major challenges. First, they are often semitransparent at visible to infrared wavelengths; and secondly, they often occur over a lower cloud system. The overlapping of high-level cirrus and low-level stratus cloud poses a difficulty in determining the individual cloud top altitudes and optical properties, especially when the signals from cirrus clouds are overwhelmed by the signals of stratus clouds. Moreover, the operational satellite retrieval algorithms, which often assume only single layer cloud in the development of cloud retrieval techniques, cannot resolve the cloud overlapping situation properly. The new geostationary satellites, starting with the Twelfth Geostationary Operational Environmental Satellite (GOES-12), are providing a new suite of imager bands that have replaced the conventional 12-micron channel with a 13.3-micron CO2 absorption channel. The replacement of the 13.3-micron channel allows for the application of a CO2-slicing retrieval technique (Chahine et al. 1974; Smith and Platt 1978), which is one of the important passive satellite methods for remote sensing the altitudes of mid to high-level clouds. Using the CO2- slicing technique is more effective in detecting semitransparent cirrus clouds than using the conventional infrared-window method.

Chang, Fu-Lung↗
NASA NTRS2014

A Two-Habit Ice Cloud Optical Property Parameterization for GCM Application

We present a novel ice cloud optical property parameterization based on a two-habit ice cloud model that has been proved to be optimal for remote sensing applications. The two-habit ice model is developed with state-of-the-art numerical methods for light scattering property calculations involving individual columns and column aggregates with the habit fractions constrained by in-situ measurements from various field campaigns. Band-averaged bulk ice cloud optical properties including the single-scattering albedo, the mass extinction/absorption coefficients, and the asymmetry factor are parameterized as functions of the effective particle diameter for the spectral bands involved in the broadband radiative transfer models. Compared with other parameterization schemes, the two-habit scheme generally has lower asymmetry factor values (around 0.75 at the visible wavelengths). The two-habit parameterization scheme was widely tested with the broadband radiative transfer models (i.e. Rapid Radiative Transfer Model, GCM version) and global circulation models (GCMs, i.e. Community Atmosphere Model, version 5). Global ice cloud radiative effects at the top of the atmosphere are also analyzed from the GCM simulation using the two-habit parameterization scheme in comparison with CERES satellite observations.

Yi, Bingqi↗
NASA NTRS2010

Comparison of GOES-Retrieved and In Situ Measurements of Deep Convective Anvil Cloud Microphysical Properties During the Tropical Composition, Cloud and Climate Coupling Experiment (TC(sup 4))

One of the main goals of the Tropical Composition, Cloud and Climate Coupling Experiment (TC(sup 4)) during July and August 2007 was to gain a better understanding of the formation and life cycle of cirrus clouds in the upper troposphere and lower stratosphere and how their presence affects the exchange of water vapor between these layers. Additionally, it is important to compare in situ measurements taken by aircraft instruments with products derived from satellite observations and find a meaningful way to interpret the results. In this study, cloud properties derived using radiance measurements from the Geostationary Operational Environmental Satellite (GOES) imagers are compared to similar quantities from aircraft in situ observations and are examined for meaningful relationships. A new method using dual \angle satellite measurements is used to derive the ice water content (IWC) for the top portion of deep convective clouds and anvils. The results show the in situ and remotely sensed mean microphysical properties agree to within approx.10 microns in the top few kilometers of thick anvils despite the vastly different temporal and spatial resolutions of the aircraft and satellite instruments. Mean particle size and IWC are shown to increase with decreasing altitude in the top few kilometers of the cloud. Given these relationships, it may be possible to derive parameterizations for effective particle size and IWC as a function of altitude from satellite observations

Yost, Christoher R.↗
NASA NTRS2011

Simultaneous Retrieval of Aerosol and Cloud Properties During the MILAGRO Field Campaign

Estimation of Direct Climate Forcing (DCF) due to aerosols in cloudy areas has historically been a difficult task, mainly because of a lack of appropriate measurements. Recently, passive remote sensing instruments have been developed that have the potential to retrieve both cloud and aerosol properties using polarimetric, multiple view angle, and multi spectral observations, and therefore determine DCF from aerosols above clouds. One such instrument is the Research Scanning Polarimeter (RSP), an airborne prototype of a sensor on the NASA Glory satellite, which unfortunately failed to reach orbit during its launch in March of 2011. In the spring of 2006, the RSP was deployed on an aircraft based in Veracruz, Mexico, as part of the Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign. On 13 March, the RSP over flew an aerosol layer lofted above a low altitude marine stratocumulus cloud close to shore in the Gulf of Mexico. We investigate the feasibility of retrieving aerosol properties over clouds using these data. Our approach is to first determine cloud droplet size distribution using the angular location of the cloud bow and other features in the polarized reflectance. The selected cloud was then used in a multiple scattering radiative transfer model optimization to determine the aerosol optical properties and fine tune the cloud size distribution. In this scene, we were able to retrieve aerosol optical depth, the fine mode aerosol size distribution parameters and the cloud droplet size distribution parameters to a degree of accuracy required for climate modeling. This required assumptions about the aerosol vertical distribution and the optical properties of the coarse aerosol size mode. A sensitivity study was also performed to place this study in the context of future systematic scanning polarimeter observations, which found that the aerosol complex refractive index can also be observed accurately if the aerosol optical depth is larger than roughly 0.8 at a wavelength of (0.555 m).

Knobelspiesse, K.↗
NASA NTRS2021

Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data

Domain adaptation techniques have been developed to handle data from multiple sources or domains. Most existing domain adaptation models assume that source and target domains are homogeneous, i.e., they have the same feature space. Nevertheless, many real world applications often deal with data from heterogeneous domains that come from completely different feature spaces. In our remote sensing application, data in source domain (from an active spaceborne Lidar sensor CALIOP onboard CALIPSO satellite) contain 25 attributes, while data in target domain (from a passive spectroradiometer sensor VIIRS onboard Suomi-NPP satellite) contain 20 different attributes. CALIOP has better representation capability and sensitivity to aerosol types and cloud phase, while VIIRS has wide swaths and better spatial coverage but has inherent weakness in differentiating atmospheric objects on different vertical levels. To address this mismatch of features across the domains/sensors, we propose a novel end-to-end deep domain adaptation with domain mapping and correlation alignment (DAMA) to align the heterogeneous source and target domains in active and passive satellite remote sensing data. It can learn domain invariant representation from source and target domains by transferring knowledge across these domains, and achieve additional performance improvement by incorporating weak label information into the model (DAMA-WL). Our experiments on a collocated CALIOP and VIIRS dataset show that DAMA and DAMA-WL can achieve higher classification accuracy in predicting cloud types.

domain adaptation↗
NASA NTRS2017

Quantifying Black Carbon Deposition Over the Greenland Ice Sheet from Forest Fires in Canada

Black carbon (BC) concentrations observed in 22 snowpits sampled in the northwest sector of the Greenland ice sheet in April 2014 have allowed us to identify a strong and widespread BC aerosol deposition event, which was dated to have accumulated in the pits from two snow storms between 27 July and 2 August 2013. This event comprises a significant portion (57 on average across all pits) of total BC deposition over 10 months (July 2013 to April 2014). Here we link this deposition event to forest fires burning in Canada during summer 2013 using modeling and remote sensing tools. Aerosols were detected by both the Cloud-Aerosol Lidar with Orthogonal Polarization (on board CALIPSO) and Moderate Resolution Imaging Spectroradiometer (Aqua) instruments during transport between Canada and Greenland. We use high-resolution regional chemical transport modeling (WRF-Chem) combined with high-resolution fire emissions (FINNv1.5) to study aerosol emissions, transport, and deposition during this event. The model captures the timing of the BC deposition event and shows that fires in Canada were the main source of deposited BC. However, the model underpredicts BC deposition compared to measurements at all sites by a factor of 2100. Underprediction of modeled BC deposition originates from uncertainties in fire emissions and model treatment of wet removal of aerosols. Improvements in model descriptions of precipitation scavenging and emissions from wildfires are needed to correctly predict deposition, which is critical for determining the climate impacts of aerosols that originate from fires.

albedo↗
NASA NTRSDate not supplied

EPIC Cloud Observations with Oxygen Bands Over Snow, Ice and Sunglint Regions

Cloud detections over snow/ice surfaces and sunglint regions are challenging with passive remote sensing instrument due to lack of contract between cold/bright surfaces in the former and glint reflectance that could exceed that of cloudy sky in the latter. We developed novel cloud detection algorithms for these regions utilizing EPIC’s unique oxygen-bands. Over the snow and ice surfaces, a dynamic threshold scheme based on the ratios of two pairs of EPIC’s oxygen bands are developed to significantly improve the existing algorithm in these regions. Over the ocean, we improved the EPIC’s ocean cloud mask algorithm by implementing a dynamic reflectance threshold and supplemental A-band ratio test for cloud detection in the sun glint regions. The new ocean cloud mask algorithm improves the diurnal cycles of cloud fraction over ocean by reducing the artificial peak at local noon time in the glint center latitudes and reducing early morning and afternoon cloud fraction in most oceanic regions.

EPIC↗
NASA NTRS2011

A State-of-the-Art Experimental Laboratory for Cloud and Cloud-Aerosol Interaction Research

The state of the art for predicting climate changes due to increasing greenhouse gasses in the atmosphere with high accuracy is problematic. Confidence intervals on current long-term predictions (on the order of 100 years) are so large that the ability to make informed decisions with regard to optimum strategies for mitigating both the causes of climate change and its effects is in doubt. There is ample evidence in the literature that large sources of uncertainty in current climate models are various aerosol effects. One approach to furthering discovery as well as modeling, and verification and validation (V&V) for cloud-aerosol interactions is use of a large "cloud chamber" in a complimentary role to in-situ and remote sensing measurement approaches. Reproducing all of the complex interactions is not feasible, but it is suggested that the physics of certain key processes can be established in a laboratory setting so that relevant fluid-dynamic and cloud-aerosol phenomena can be experimentally simulated and studied in a controlled environment. This report presents a high-level argument for significantly improved laboratory capability, and is meant to serve as a starting point for stimulating discussion within the climate science and other interested communities.

Fremaux, Charles M.↗
NASA NTRSDate not supplied

RSP Data Status, Updates and Plans from the Team

•All radiance (L1C), aerosol and cloud (L2) products are in the archive. •Revised calibration performed at GSFC in July 2021 applied to reprocessing. •Clouds have smaller drops and higher optical depths (larger droplet number concentrations) in winter than in summer. Cloud top droplet size distributions tend to be narrow with roughly 80% having an effective variance of less than 0.07. This is relevant to how well bulk auto-conversion parameterizations are likely to work at cloud top (order of magnitude effects) and also to assumptions used in the remote sensing of droplet number (~ 10% effect). Real refractive index and effective radius retrievals are consistent with hygroscopic growth of aerosols Real refractive index and effective variance retrievals imply the presence of an insoluble fraction of aerosols Future work on clouds will look at differences in cloud top drizzle formation and auto-conversion rates between the different campaigns and at how well mixed phase clouds can be detected (if at all) from sensors such as VIIRS and PACE OCI.

Research Scanning Polarimeter↗
NASA NTRSDate not supplied

Reconfiguring COSSIR for the Next Generation of Cloud and Precipitation Science

NASA originally developed the Compact Scanning Sub-millimeter Imaging Radiometer (CoSSIR) in the early 2000s, where it was own in the CRYSTAL-FACE and TC4 field experiments. With renewed interest in sub-millimeter remote sensing motivated by the upcoming launch of the EUMETSAT-sponsored Ice Cloud Imager (ICI), along with its potential for inclusion as part of the NASA Decadal Survey Aerosols, CLouds, Convection, and Precipitation (ACCP) observing architecture, CoSSIR is being refurbished to prepare for routine suborbital submillimeter measurements this decade. Upgrades include hardware (procurement of shared parts so that CoSMIR and CoSSIR can fly concurrently) and a change to the channels, with a focus on differential scattering and polarization at eight frequencies ranging from 170 to 640 GHz. As part of the refurbishment, the instrument name has been changed to Configurable Scanning Sub-millimeter Instrument/Radiometer, retaining the same acronym, in order to emphasize the science objectives that are enabled by CoSSIR's unique scanning geometry and channel set. These anticipated capabilities include two-dimensional pro ling of clouds and precipitation and characterization of the geometry (shape and orientation) of large cloud and precipitating ice particles.

Radiometry↗
NASA NTRS2015

Tropical and Arctic Cloud Observations From CALIPSO Between 2008-2014 and its Implications

There has been studies (e.g., Schweiger, 2004) suggest significant increase of Arctic clouds during the last three decades, especially in the western Arctic region. Such studies are based on passive remote sensing that are not highly reliable due to the lack of contrasts in temperature and reflectance between clouds and snow/ice surfaces. Changes in the Arctic clouds can be evaluated more accurately using the space-based lidar measurements from CALIPSO during the last nine years since CALIPSO can provide much more accurate detection and classification of both water and ice clouds in the Arctic. Time series of Arctic cloud properties (e.g., cloud fraction, cloud thermodynamic phase, water cloud depolarization ratio and droplet number concentration) from CALIPSO data are analyzed in this study. This study reveals the changes in both cloud fraction and cloud microphysical properties during the last nine years when CALIPSO data are available. We will evaluate the changes in Arctic cloud fraction and cloud microphysical properties, their seasonal and spatial characteristics and the potential impact on the energy budget and the climate of the Arctic.

Hu, Yongxiang↗
NASA NTRS1984

Proceedings of a Workshop on Polar Stratospheric Clouds: Their Role in Atmospheric Processes

The potential role of polar stratospheric clouds in atmospheric processes was assessed. The observations of polar stratospheric clouds with the Nimbus 7 SAM II satellite experiment were reviewed and a preliminary analysis of their formation, impact on other remote sensing experiments, and potential impact on climate were presented. The potential effect of polar stratospheric clouds on climate, radiation balance, atmospheric dynamics, stratospheric chemistry and water vapor budget, and cloud microphysics was assessed. Conclusions and recommendations, a synopsis of materials and complementary material to support those conclusions and recommendations are presented.

Hamill, P.↗