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The Multi-Angle Imaging SpectroRadiometer (MISR) is being developed at JPL for the AM1 spacecraft in the Earth Observing System (EOS) series. This paper reports on the progress of instrument fabrication and testing, and it discusses the strategy to use the instrument for studying tropospheric aerosols.
Aerosols and clouds play important roles in Earth?s climate system, but limitations in our ability to observe them globally limit our understanding of the climate system and our ability to model it. The CALIPSO satellite was developed to provide new capabilities to observe aerosol and cloud from space. CALIPSO carries the first polarization-sensitive lidar to fly in space, which has now provided a four-year record of global aerosol and cloud profiles. This paper briefly summarizes the status of the CALIPSO mission, describes some of the results from CALIPSO, and presents highlights of recent improvements in data products.
Space-borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT (Greenhouse Gases Observing Satellite) and OCO-2 (Orbiting Carbon Observatory 2), however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high-latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO-2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint. Plain Language Summary: Active and passive remote sensors show the potential to provide unprecedented information on the carbon cycle. With the all-season sampling, active remote sensors are more capable of constraining high-latitude emissions. The reduced sensitivity to cloud and aerosol also makes active sensors more capable of providing information in cloudy and polluted scenes with sufficient accuracy. These experiments account for errors that are fundamental to the top-down approach for constraining emissions, and even including these sources of error, we show that satellite remote sensors are critical for understanding the carbon cycle.
Ground-based measurements strongly support the hypothesis that pollutant materials of anthropogenic origin are being transported over long distances in the midtroposphere and are a significant source of acid rain, acid snow, trace metal deposition, ozone and visibility-reducing aerosols in remote oceanic and polar regions of the Norhern Hemisphere. Atmospheric sulphur budget calculations and studies of acid rain on Bermuda indicate that a large fraction of pollutant materials emitted into the atmosphere in eastern North America are advected eastwards over the North Atlantic Ocean. The first direct airborne measurements of the vertical distribution of tropospheric aerosols over the western North Atlantic is reported here. A newly developed airborne differential adsorption lidar system was used to obtain continuous, remotely sensed aerosol distributions along its flight path. The data document two episodes of long-distance transport of pollutant materials from North America over the North Atlantic Ocean.
The improvement of an understanding of the variation of the aerosol backscattering at 10.6 micron within the free troposphere and the development model to describe this was undertaken. The analysis combines theoretical modeling with the results contained within three independent data sets. The data sets are obtained by the SAGE I/SAM II satellite experiments, the GAMETAG flight series and by direct backscatter measurements. The theoretical work includes use of a bimodal, two component aerosol model, and the study of the microphysical and associated optical changes occurring within an aerosol plume. A consistent picture is obtained, which describes the variation of the aerosol backscattering function in the free troposphere with altitude, latitude, and season. Most data are available and greatest consistency is found inside the Northern Hemisphere.
NeuralMie was developed to improve the representation of aerosol optical properties in E3SM, the DOE's Earth system model. NeuralMie is able to closely emulate numerical solutions to the problem at a fraction of the computational cost. TAMie was written to generate training data for NeuralMie.
Abstract Hyperparameter optimization (HPO) is an important step in machine learning (ML) model development, but common practices are archaic—primarily relying on manual or grid searches. This is partly because adopting advanced HPO algorithms introduces added complexity to the workflow, leading to longer computation times. This poses a notable challenge to ML applications, as suboptimal hyperparameter selections curtail the potential of ML model performance, ultimately obstructing the full exploitation of ML techniques. In this article, we present a two-step HPO method as a strategic solution to curbing computational demands and wait times, gleaned from practical experiences in applied ML parameterization work. The initial phase involves a preliminary evaluation of hyperparameters on a small subset of the training dataset, followed by a reevaluation of the top-performing candidate models postretraining with the entire training dataset. This two-step HPO method is universally applicable across HPO search algorithms, and we argue it has attractive efficiency gains. As a case study, we present our recent application of the two-step HPO method to the development of neural network emulators for aerosol activation. Although our primary use case is a data-rich limit with many millions of samples, we also find that using up to 0.0025% of the data—a few thousand samples—in the initial step is sufficient to find optimal hyperparameter configurations from much more extensive sampling, achieving up to 135× speedup. The benefits of this method materialize through an assessment of hyperparameters and model performance, revealing the minimal model complexity required to achieve the best performance. The assortment of top-performing models harvested from the HPO process allows us to choose a high-performing model with a low inference cost for efficient use in global climate models (GCMs).
The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite developed by the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) launched in May 2024 carries a novel 94 GHz cloud profiling radar (CPR) with Doppler capability. This work describes the open-source instrument simulator Orbital-Radar, which transforms high-resolution radar data from field observations or forward simulations of numerical models to CPR primary measurements and uncertainties. The transformation accounts for sampling geometry and surface effects. We demonstrate Orbital-Radar's ability to provide realistic CPR views of typical cloud and precipitation scenes. The presented case studies show small-scale convection, marine stratus clouds, and Arctic mixed-phase cloud cases. These results provide valuable insights into the capabilities and challenges of the EarthCARE CPR mission and its advantages over the CloudSat CPR. Finally, Orbital-Radar allows for evaluating kilometre-scale numerical weather prediction models with EarthCARE CPR observations. So, Orbital-Radar can generate calibration and validation (Cal/Val) data sets already pre-launch. Nevertheless, an evaluation of synthetic CPR output data to accurate EarthCARE CPR data is missing.
The activities under a cooperative agreement for the development of a computer network are briefly summarized. Research activities covered are: computer operating systems optimization and integration; software development and implementation of the IRIS (Infrared Imaging of Shuttle) Experiment; and software design, development, and implementation of the APS (Aerosol Particle System) Experiment.
The work accomplished with the MAS (MODIS Airborne Simulator) during the TOGA-COARE (Tropical Ocean Global Atmosphere - Coupled Ocean Atmosphere Response Experiment) from January through June 1993 included cloud investigations with longwave CO2 channels (out to 13.9 microns) that reconfigured spectral channels. The comparison data was used with HIRS (high resolution Infrared Radiation Sounder) data from FIRE (First ISSCP Regional Experiment), CEPEX, and SCAR (Smoke Clouds, Aerosol and Radiation) data for the development of a two layer cloud CO2 slicing algorithm and the development of multi-spectral cloud detection algorithms (specifically tri-spectral) for cloud identification. Regarding the latter, a clustering analysis was added to improve cloud identification within the scatter diagram of tri-spectral (8, 11, and 12 microns) brightness temperatures. Via the regressions of the 8 - 11 and the 11 - 12 micron brightness temperature differences versus precipitable water, the problem of clear sky identification in the scatter diagram was further addressed. Comparison of the tri-spectral technique and visible channel reflectance ratioing indicate the tri-spectral infrared method distinguishes cloud phase more consistently in mixed cloud scenes rather than single phase cloud scenes where visible ratioing performs best.
The Ozone Monitoring Instrument (OMI) on board NASA s Aura satellite was launched in July 2004, and is now providing daily global observations of total column ozone, NO2, and SO2, as well as aerosol information. Algorithms have also been developed to produce daily tropospheric ozone and NO2 products. The tropospheric ozone product reported here is a tropospheric residual computed through use of Aura Microwave Limb Sounder (MLS) ozone profile data to quantify stratospheric ozone. We are investigating the applicability of OMI products for use in air quality modeling, forecasting, and analysis. These investigations include comparison of the OMI tropospheric O3 and NO2 products with global and regional models and with lower tropospheric aircraft observations. Large-scale transport of pollution seen in the OM1 tropospheric O3 data is compared with output from NASA's Global Modeling Initiative global chemistry and transport model. On the regional scale we compare the OMI tropospheric O3 and NO2 with fields from the National Oceanic and Atmospheric Administration and Environmental Protection Agency (NOAA/EPA) operational Eta/CMAQ air quality forecasting model over the eastern United States. This 12-km horizontal resolution model output is roughly of equivalent resolution to the OMI pixel data. Correlation analysis between lower tropospheric aircraft O3 profile data taken by the University of Maryland over the Mid-Atlantic States and OMI tropospheric column mean volume mixing ratio for O3 will be presented. These aircraft data are representative of the lowest 3 kilometers of the atmosphere, the region in which much of the locally-generated and regionally-transported ozone exists.
The OMPS Limb Profiling (LP) instrument was launched on NOAA's Suomi NPP (SNPP) weather satellite in October 2011. The instrument measures limb-scattered radiation in the ultraviolet, visible and NIR wavelengths with high vertical resolution (~2 km) and relatively dense spatial and temporal sampling (several thousand measurements/day covering the entire sunlit globe). These measurements have very high sensitivity to stratospheric aerosols due to long path of the incoming solar photons through the aerosol layer. However, unlike the recently launched ISS/SAGE III that directly measures extinction of solar/lunar radiation by gases and particles along the line of sight (LOS) of the instrument, information content of OMPS LP measurements is complex. It consists of solar radiation singly scattered and attenuated by aerosols, air, and trace gases along the LOS of the instrument, as well as diffuse upwelling radiation from the lower atmosphere that also gets scattered and attenuated into the LOS. To unscramble this complex signal one needs to have good knowledge of aerosol size distribution (ASD) and their complex refractive index. We will describe our recent efforts in constraining the ASD parameters by analyzing in-situ balloon data from Laramie, Wyoming; aerosol microphysical model data from CARMA; and spectral information provided by OMPS LP. We will also discuss our proposed methodology to reï¬ne this information by adjusting the microphysical properties of the aerosols to make data from various occultation and scattering instruments internally consistent. This is a generalized version of the technique employed by AERONET in which solar extinction data are combined with scattered radiation measured by the almucantar technique to determine aerosol particle shape, complex refractive index and size distribution. We suggest that such closure studies are essential to develop confidence in space-based data to validate aerosol microphysical models, such as CARMA, and aerosol chemistry- transport models, such as GOCART, and for estimating radiative forcing due to stratospheric aerosols in both volcanic and quiescent time periods.
As a common phenomenon over Antarctica, blowing snow (BLSN), especially the large BLSN storms, play an important role in the Antarctic surface mass balance, radiation budget, and planetary boundary layer processes. This study presents the work on BLSN storm identification and analysis with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite. Spectral analysis shows that BLSN identification is feasible with MODIS daytime data. A random forest machine learning model is developed and observations from the Cloud‐Aerosol Lidar with Orthogonal Polarization are used for training. Model performance results show that machine‐learning based classification can achieve over 90% overall accuracy when classifying MODIS pixels into cloud, clear, and BLSN categories. The machine learning model is applied to MODIS observations during the month of October 2009 for BLSN storm analysis. Results show that the size of BLSN storms has a large spectrum and can reach hundreds of thousands km2. The MODIS based BLSN storm frequency map extends the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations coverage limit from 82°S to the South Pole. A BLSN storm belt, which extends from the South Pole region to the coastal area between 130°E and 160°E along the Transantarctic Mountains, provides a potential pathway of snow transport. These results are important in improving the understanding of BLSN impact on Antarctic surface mass balance and boundary layer processes.
Aerosols –clouds, hazes, and dusts –are a key part of planetary mass and energy balance, but difficult to study remotely. Current technology limits in situ measurements to once-in-a-lifetime flagship missions, which is not enough to characterize such highly dynamic systems. AERACEPT (AErosol Rapid Analysis Combined Entry Probe/sonde Technology) is an early-stage technology allowing asingle aeroshell body toact as both anentry vehicle and aerosol-samplingpassivedescent sonde, using the aeroshell’sown velocityto drive aerosol capture and separationthrough a series of embedded inlets.It takes advantage ofrecently developed thermal protection materials (3D-CC and 3MDCP)in combination withheritage aerosol sampling technologies fromboth planetary and airborne science (high-speed inlets and particle separation). By eliminating the need for heat shield separation, deployable parachutes, ordescent control, AERACEPT reducesthe mass, volume, and complexity ofplanetary aerosol sampling. Verifying AERACEPT’s performance involves modeling interdependencies between the size and geometry of the sampling inlets, the material response of the hypersonic phase of entry, the thermal conditions throughout the probe’s descent, the subsonic flow and particle sampling efficiency, the needed amount of sample, andthe cadence at which the sample can be analyzed. AERACEPT’s current predictions, using the Nephele Venus cloud mission concept (sampling between 63km to 39km, all subsonic) indicates AERACEPT can obtain >20 μL of particle material (roughly 10x the limit of detection) from droplets larger than 0.2 μm, with sample heating limited to <15 K above ambient. Validation testing for the thermal material response model has recently been performed at the UIUC Plasmatron facility, and for the flow and particle capture models is planned for this fall at the Ames Fluid Mechanics Laboratory.
The Laser In space Technology Experiment, Shuttle Laser Altimeter and the Mars Observer Laser Altimeter have demonstrated accurate measurements of atmospheric backscatter and Surface heights from space. The recent MOLA measurements of the Mars surface have 40 cm vertical resolution and have reduced the global uncertainty in Mars topography from a few km to about 5 m. The Geoscience Laser Altimeter System (GLAS) is a next generation lidar for Earth orbit being developed as part of NASA's Icesat Mission. The GLAS design combines a 10 cm precision surface lidar with a sensitive dual wavelength cloud and aerosol lidar. GLAS will precisely measure the heights of the Earth's polar ice sheets, establish a grid of accurate height profiles of the Earth's land topography, and profile the vertical backscatter of clouds and aerosols on a global scale. GLAS is being developed to fly on a small dedicated spacecraft in a polar orbit with a 590 630 km altitude at inclination of 94 degrees. GLAS is scheduled to launch in the summer 2001 and to operate continuously for a minimum of 3 years with a goal of 5 years. The primary mission for GLAS is to measure the seasonal and annual changes in the heights of the Greenland and Antarctic ice sheets. GLAS will continuously measure the vertical distance from orbit to the Earth's surface with 1064 nm pulses from a ND:YAG laser at a 40 Hz rate. Each 5 nsec wide laser pulse is used to produce a single range measurement, and the laser spots have 66 m diameter and about 170 m center-center spacings. When over land GLAS will profile the heights of the topography and vegetation. The GLAS receiver uses a 1 m diameter telescope and a Si APD detector. The detector signal is sampled by an all digital receiver which records each surface echo waveform with I nsec resolution and a stored echo record lengths of either 200, 400, or 600 samples. Analysis of the echo waveforms within the instrument permits discrimination between cloud and surface echoes. Ground based echo analysis permits precise ranging, determining the roughness or slopes of the surface as well as the vertical distributions of vegetation illuminated by the laser. Accurate knowledge of the laser beam's pointing angle is needed to prevent height biases when over sloped surfaces. For surfaces with 2 deg. slopes, knowledge of pointing angle of the beam's centroid to about 8 urad is needed to achieve 10 cm height accuracy. GLAS uses a stellar reference system (SRS) to determine the pointing angle of each laser firing relative to inertial space. The SRS uses a high precision star camera oriented toward local zenith and a gyroscope to determine the inertial orientation of the SRS optical bench. The far field pattern of each laser is measured pulse relative to the star camera with a laser reference system (LRS). Optically measuring each laser far field pattern relative to the orientation of the star camera and gyroscope permits the precise pointing angle of each laser pulse to be determined. GLAS will also determine the vertical distributions of clouds and aerosols by measuring the vertical profile of laser energy backscattered by the atmosphere at both 1064 and 532 nm. The 1064 nm measurements use the Si APD detector and profile the height and vertical structure of thicker clouds. The measurements at 532 nm use new highly sensitive photon counting, detectors, and measure the height distributions of very thin Clouds and aerosol layers. With averaging these can be used to determine the height of the planetary boundary layer. The instrument design and expected performance will be discussed.
We are in the process of developing a nadir-viewing, aircraft-based high spectral resolution lidar (HSRL) at NASA Langley Research Center. The system is designed to measure backscatter and extinction of aerosols and tenuous clouds. The primary uses of the instrument will be to validate spaceborne aerosol and cloud observations, carry out regional process studies, and assess the predictions of chemical transport models. In this paper, we provide an overview of the instrument design and present the results of simulations showing the instrument's capability to accurately measure extinction and extinction-to-backscatter ratio.
The Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height and single scattering albedo (SSA) for biomass burning smoke aerosols. By using multiple satellite sensors synergistically, ASHE can provide the height information over much broader areas than lidar observations alone. The complete ASHE algorithm uses aerosol data from MODIS or VIIRS, OMI or OMPS, and CALIOP. A simplified algorithm also exists that does not require CALIOP data as long as the SSA of the aerosol layer is provided by another source. Several updates have recently been made: inclusion of dust layers in the retrieval process, better determination of the input aerosol layer height from CALIOP, improvement in aerosol optical depth (AOD) for nonspherical dust, development of quality assurance (QA) procedure, etc.
A ground-based Differential Absorption Lidar (DIAL) is being developed with the capability to measure range-resolved and column amounts of atmospheric CO2. This system is also capable of providing high-resolution aerosol profiles and cloud distributions. It is being developed as part of the NASA Earth Science Technology Office s Instrument Incubator Program. This three year program involves the design, development, evaluation, and fielding of a ground-based CO2 profiling system. At the end of a three-year development this instrument is expected to be capable of making measurements in the lower troposphere and boundary layer where the sources and sinks of CO2 are located. It will be a valuable tool in the validation of NASA Orbiting Carbon Observatory (OCO) measurements of column CO2 and suitable for deployment in the North American Carbon Program (NACP) regional intensive field campaigns. The system can also be used as a test-bed for the evaluation of lidar technologies for space-application. This DIAL system leverages 2-micron laser technology developed under a number of NASA programs to develop new solid-state laser technology that provides high pulse energy, tunable, wavelength-stabilized, and double-pulsed lasers that are operable over pre-selected temperature insensitive strong CO2 absorption lines suitable for profiling of lower tropospheric CO2. It also incorporates new high quantum efficiency, high gain, and relatively low noise phototransistors, and a new receiver/signal processor system to achieve high precision DIAL measurements.