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Low-level liquid cloud properties during ORACLES retrieved using airborne polarimetric measurements and a neural network algorithm

In this study we developed a neural network (NN) that can be used to retrieve cloud microphysical properties from multiangular and multispectral polarimetric remote sensing observations. This effort builds upon our previous work, which explored the sensitivity of neural network input, architecture, and other design requirements for this type of remote sensing problem. In particular this work introduces a framework for appropriately weighting total and polarized reflectances, which have vastly different magnitudes and measurement uncertainties. The NN is trained using an artificial training set and applied to research scanning polarimeter (RSP) data obtained during the ORACLES field campaign (ObseRvations of Aerosols above CLouds and their intEractionS). The polarimetric RSP observations are unique in that they observe the same cloud from a very large number of angles within a variety of spectral bands, resulting in a large dataset that can be explored rapidly with a NN approach. The usefulness of applying a NN to a dataset such as this one stems from the possibility of rapidly obtaining a retrieval that could be subsequently applied as a first guess for slower but more rigorous physical-based retrieval algorithms. This approach could be particularly advantageous for more complicated atmospheric retrievals – such as when an aerosol layer lies above clouds like in ORACLES. For RSP observations obtained during ORACLES 2016, comparisons between the NN and standard parametric polarimetric (PP) cloud retrieval give reasonable results for droplet effective radius (r(e): R=0.756, RMSE=1.74 µm) and cloud optical thickness (τ: R=0.950, RMSE=1.82). This level of statistical agreement is shown to be similar to comparisons between the two most well-established cloud retrievals, namely, the polarimetric and the bispectral total reflectance cloud retrievals. The NN retrievals from the ORACLES 2017 dataset result in retrievals of r(e) (R=0.54, RMSE=4.77 µm) and τ (R=0.785, RMSE=5.61) that behave much more poorly. In particular we found that our NN retrieval approach does not perform well for thin (τ<3), inhomogeneous, or broken clouds. We also found that correction for above-cloud atmospheric absorption improved the NN retrievals moderately – but retrievals without this correction still behaved similarly to existing cloud retrievals with a slight systematic offset.

SPECTRAL-RESOLUTION LIDAR↗

Geoscience Laser Altimeter System (GLAS) Loop Heat Pipes: An Eventual First Year On-Orbit

Goddard Space Flight Center's Geoscience Laser Altimeter System (GLAS) is the sole scientific instrument on the Ice, Cloud and land Elevation Satellite (ICESat) that was launched on January 12, 2003 from Vandenberg AFB. A thermal control architecture based on propylene Loop Heat Pipe technology was developed to provide selectable/stable temperature control for the lasers and other electronics over the widely varying mission environment. Following a nominal LHP and instrument start-up, the mission was interrupted with the failure of the first laser after only 36 days of operation. During the 5-month failure investigation, the two GLAS LHPs and the electronics operated nominally, using heaters as a substitute for the laser heat load. Just prior to resuming the mission, following a seasonal spacecraft yaw maneuver, one of the LHPs deprimed and created a thermal runaway condition that resulted in an emergency shutdown of the GLAS instrument. This paper presents details of the LHP anomaly, the resulting investigation and recovery, along with on-orbit flight data during these critical events.

Grob, E.↗

Suborbital Telepresence and Over-the-Horizon Networking

A viewgraph presentation describing the suborbital telepresence project utilizing in-flight network computing is shown. The topics include: 1) Motivation; 2) Suborbital Telepresence and Global Test Range; 3) Tropical Composition, Cloud, and Climate Coupling Experiment (TC4); 4) Data Sets for TC4 Real-time Monitoring; 5) TC-4 Notional Architecture; 6) An Application Integration View; 7) Telepresence: Architectural Framework; and 8) Disruption Tolerant Networks.

Freudinger, Lawrence C.↗

EARTHDATA PUB: A Data Publication Workflow Solution for NASA’s EOSDIS

Each NASA Distributed Active Archive Center (DAAC) faces the challenge of dealing with an increasingly diverse number of publishable data products from diverse data producers. Data producers, on the other hand, may experience pain points when interacting with the EOSDIS for the first time or when publishing different data at different DAACs. As a result, there has been a growing need to develop a common software framework that serves as a common interface for data producers, rigorously defines the data publication procedure for DAAC staff, facilitates the management of various data publication processes, and tracks the progress of data publication. This software should also account for the different configurations at different DAACs. Currently, two primary data publication workflow and tracking tools exist in operation at the EOSDIS: Semi-Automated ingest System (SAuS) and Data Publication workflow Portal (DAPPeR). However, neither tool is cloud-ready. Automated data processing could be managed by Cumulus, an EOSDIS cloud-based data ingest, archive and management system. However, Cumulus does not support manual tasks or on-premise implementations. We propose to develop the Earthdata Publication Minimum Viable Product (Earthdata Pub MVP) -- a cloud-hosted solution that works with both cloud and on-premise systems and implements the communications and exchange requirements generated by the Earthdata Pub information architecture team.

Rice, Justin L.↗

Application of High-Dimensional Fuzzy K-Means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.

Zeng, Shan↗

Adapting CALIPSO Climate Measurements for Near Real Time Analyses and Forecasting

The Cloud-Aerosol Lidar and Infrared Pathfinder satellite Observations (CALIPSO) mission was originally conceived and designed as a climate measurements mission, with considerable latency between data acquisition and the release of the level 1 and level 2 data products. However, the unique nature of the CALIPSO lidar backscatter profiles quickly led to the qualitative use of CALIPSO?s near real time (i.e., ? expedited?) lidar data imagery in several different forecasting applications. To enable quantitative use of their near real time analyses, the CALIPSO project recently expanded their expedited data catalog to include all of the standard level 1 and level 2 lidar data products. Also included is a new cloud cleared level 1.5 profile product developed for use by operational forecast centers for verification of aerosol predictions. This paper describes the architecture and content of the CALIPSO expedited data products. The fidelity and accuracy of the expedited products are assessed via comparisons to the standard CALIPSO data products.

Vaughan, Mark A.↗

VALENTInE: A Concept for a New Frontiers Class Long Duration In-Situ Balloon Mission to Venus

Venus and Earth are similar in bulk composition, size, density, and approximate distance from the Sun, yet Venus’s modern-day climate and surface geology is distinctly different [1]. Previous missions to Venus revealed unusual volcanic features, possible continental crust, widespread volcanic plains, a weak magnetic field [2], and insights into the Venusian atmosphere [3,4]. Unfortunately, data from these missions were limited in spatial and temporal resolution and global extent. A future mission to Venus is critical to address fundamental questions surrounding the chemical composition and dynamics of the Venusian atmosphere [5], its geologic history [6,7], its internal structure [8,9], and its habitability throughout time [10,11]. We present the Venus Air and Land Expedition: a Novel Trailblazer for In situ Exploration (VALENTInE) mission to meet this need. VALENTInE is a variable altitude balloon that will passively float in Venus’s atmosphere between 45 and 55 km altitude. VALENTInE will acquire atmospheric data at varying latitudes and longitudes in addition to mapping the surface geomorphology and mineralogy across multiple terrains. Mission Objectives: The VALENTInE mission concept is driven by four main science objectives: 1. Determine whether the driving force of the superrotation of Venus’s atmosphere is caused by horizontal or vertical momentum transport. 2. Determine whether the atmospheric composition and noble gas inventory of the Venusian atmosphere is a product of outgassing from the initial protoplanetary source or if there are significant contributions from exogenic sources. 3. Determine whether the tesserae regions (particularly Aphrodite Terra) are felsic and relatively older than surrounding regions. 4. Determine if there is any evidence of a recent dynamo preserved in the rock record of Venus. Mission Overview: A balloon architecture provides a robust system that can survive long-term in the Venusian environment while taking accurate measurements of the lower cloud deck and surface. Two prior balloon missions to Venus, VEGA 1 and VEGA 2 in 1984, have demonstrated the potential for such planetary exploration; however, these missions were short-lived (46 hr), with limited range (54 km). Our spacecraft concept consists of a battery powered balloon with a gondola and flyby carrier stage (Fig. 1). Our novel design allows for at least 15 days of atmospheric exploration, including multiple ascents and descents in the Venus atmosphere. VALENTInE is baselined to launch in 2032, cruise on solar power for 128 days, enter, descend, and inflate (EDI) into Venus’s atmosphere above Aphrodite Terra, and float in Venus’s atmosphere for a total nominal mission duration of 15 days. The balloon, able to control its altitude by changing its buoyancy, will make one full circumnavigation every 4–8 days and move poleward ~1 o latitude per day; it will be passively directed by the horizontal air currents on Venus. The balloon can only be controlled in the z direction, and the expected latitude range is ±10° from EDI. The balloon itself will be a tracer for atmospheric structures such as zonal winds [5, 12]. During the 15-day operational period, there will be five dips to 45 km for a compositional study of the lower atmosphere and geological and magnetic mapping of the surface. Dips are used to take images and measurements closer to the surface and to obtain in situ vertical atmospheric profiles between 45 and 55 km. Instruments: The VALENTInE instrument payload will allow for extensive study of the geology, atmosphere, and interior of Venus. The instrument suite consists of six instruments. The mission profile for each instrument is shown in Fig. 2. Lower Atmosphere Meteorology Analyzer (LAMA) is an atmospheric structure instrument consisting of a thermometer, barometer, and accelerometer to continuously measure temperature and pressure as a function of altitude, longitude, and latitude. TracE and Noble Gas Investigator (TENGI) is aneutral mass spectrometer used to sample the dense atmosphere. TENGI will operate continuously at 45 km and 55 km and will measure D/H ratios, as well as Ne, Ar, and O isotopic ratios. Kilometer Scale Spectral Imager (KSSI) is amultispectral imager (850-1150 nm) used to resolve surface features on the order of km. Near InfraRed Multispectral Photometer (NIRMP) is an Infrared (IR) photometer used to image the surface through the clouds to characterize mineral assemblages at five different areas of the surface. NIRMP will be operated during dwell. ELevation REConnaissance (ELREC) is a light detection and ranging (LIDAR) instrument used for measuring topography at five different areas of the surface. The ELREC data will be combined with those of NIRMP to determine mineral assemblages and how they correlate to topography. Magnetic Exploration and Interior Detective (MEID) is a magnetometer used to detect any near-surface magnetic anomalies. The magnetometer will continuously operate at all altitudes. Mission Design: The spacecraft’s propulsion system will have a wet mass of 930 kg and will be launched on an Atlas V rocket. The spacecraft will jettison the payload upon arrival in Venus’s atmosphere before decelerating to orbital velocity. Figure 2. Notional power-dip profile while the balloon is on the dayside. Risks and Challenges: Raising and lowering the spacecraft to dip beneath the haze layer require a large amount of energy. This issue was partly compensated by limiting the number of dips over the 15 day prime mission. Power needs for pumping helium are reduced by slowing the descent speed, which consequently increases spatial resolution of in situ measurements between 45 and 55 km. The main limitation for the duration of the mission is the need to carry 15 days’ worth of batteries. The bus experiences external Venusian temperatures ranging from ~27°C at 55 km altitude to ~110°C at 45 km altitude. These high atmospheric temperatures require thermal protection for the bus (instruments, electronics, and flight systems) during its descent, dwell at 45 km, and ascent. The bus is maintained at a mechanically safe temperature range of -10°C to 50°C using white external paint, multi-layer insulation (MLI), mechanical/thermal isolation (e.g. Ti, composites), and ~57 kg of Phase Change Materials (PCM). Images and spectra taken below the haze dominate the available data transmission regardless of the time spent at 45 km. Therefore, less time at the lower altitude mainly reduces the coverage of in situ measurements there. Further, we assumed an unrealistically low-density material for the helium storage tanks on the gondola. However, this issue is partially resolved if we were to jettison 75% of the spent helium storage tanks. After the entry process, the balloon volume remains mostly inflated and storage tanks are required only for reducing balloon volume in dipping to 45 km. This mission was planned against an expected New Frontiers 5 (NF5) cost cap of $1B, as the NF5 call had not yet been released. The mission we describe fits within the predicted cost cap if the flyby carrier stage, responsible for powering the spacecraft during cruise and for relaying in situ measurements back to Earth, can be contributed by another space agency. Acknowledgments: We thank the JPL Planetary Science Summer School, especially A. Nash, J. Scully, K. Mitchell, L. Lowes, and J. Armijo, and our mentors from JPL Team X. Thank you to our review panel for their insightful review. References: [1] Kane, S. et al. (2019) JGR:Ps, 124 , 2015–2028. [2] Phillips, J. L., & Russell, C. T. (1987). JGR: Space Physics , 92 (A3), 2253-2263. [3] Nakamura, M. et al. (2018) Earth Planets Space, 70 (1), 144. [4] Svedhem, H. et al. (2009) JGR:P 114 (E5). [5] Limaye et al. (2009) Decadal Survey White Paper . [6] Ivanov, M. and Head, J. (2011) PSS, 59 (13) , 1559-1600. [7] Smrekar, S. et al. (2018) Space Sci Rev, 214 (5), 88. [8] O’Rourke, J. et al. (2018) EPSL, 502 , 46-56. [9] O’Rourke J. et al. (2019) GRL , (46), 5768–5777 [10] Way, M. et al. (2016) GRL, 43 (16), 8376-8383. [11] Way, M. et al. (2020) JGR:P, 125 (5), e2019JE006276. [12] Preston, R. A. et al. (1986) Science, 231 (4744), 1414-1416.

Mission Concept↗

DRF: A Software Architecture for a Data Marketplace to Support Advanced Air Mobility

Advanced Air Mobility is a new aviation vision, where unmanned aerial systems will trans- port passengers and cargo across urban and rural areas. Critical to the realization of this vision is the development of a digital marketplace, which allows service providers and consumers operating in the airspace ecosystem to securely exchange data and reasoning insights. In this paper, we present the architecture of a decentralized data marketplace that connects data and reasoning service providers to vehicles and other service consumers along the cloud-to-edge continuum. We also present two example use cases to demonstrate the value of our approach.

Autonomy↗

SatCORPS Hybridized Cloud Product Data Storage: The Design of a Hybrid Data Repository That Leverages the Strengths of the Cloud and the Data Center

There is a strong demand for the near real time NASA Langley Satellite ClOud and Radiation Property retrieval System (SatCORPS) products. As important as real-time information, archived copies of the products form the basis for targeted research focusing on specific events or conditions. To make these SatCORPS products available for downloading, the SatCORPS group has developed a number of tools and technologies to create a hybrid data storage system that leverages the strengths of both cloud and on-premises resources. In this work, we describe the technologies the group uses to marshal disparate data repositories and materialize them into a single searchable overview and give a broad description of the organization of the dataset. As with any implementation, the strengths, weaknesses and constraints surrounding the components establish priorities and provide insight where trade-offs are necessary. We further describe the design and architecture underpinning our hybrid data repository and delivery system.

AWS↗

Leveraging Improvements in Precipitation Measuring from GPM Mission to Achieve Prediction Improvements in Climate, Weather and Hydrometeorology

The main scientific goal of the GPM mission, currently planned for start in the 2007 time frame, is to investigate important scientific problems arising within the context of global and regional water cycles. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood/draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like "core" satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing Operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. GPM is organized internationally, currently involving a partnership between NASA in the US and the National Space Development Agency in Japan. Additionally, the program is actively pursuing agreements with other international partners and domestic scientific agencies and institutions, as well as participation by individual scientists from academia, government, and the private sector to fulfill mission goals and to pave the way for what ultimately is expected to become an internationally-organized operational global precipitation observing system. Notably, the broad societal applications of GPM are reflected in the United Nation s identification of this mission as a foremost candidate for its Peaceful Uses of Space Program. In this presentation, an overview of the GPM mission design will be presented, followed by an explanation of its scientific agenda as an outgrowth of making improvements in rain retrieval accuracy, microphysics dexterity, sampling frequency, and global coverage. All of these improvements offer new means to observe variability in precipitation and water cycle fluxes and to achieve improved predictability of weather, climate, and hydrometeorology. Specifically, the scientific agenda of GPM has been designed to leverage the measurement improvements to improve prognostic model performance, particularly quantitative precipitation forecasting and its linked phenomena at short, intermediate, and extended time scales. The talk will address how GPM measurements will enable better detection of accelerations and decelerations in regional and global water cycle processes and their relationship to climate variability, better impacts of precipitation data assimilation on numerical weather prediction and global climate reanalysis, and better performance from basin scale hydrometeorological models for short and long term flood-drought forecasting and seasonal fresh water resource assessment. Improved hydrometeorological forecasting will be possible by using continuous global precipitation observations to obtain better closure in water budgets and to generate more realistic forcing of the models themselves to achieve more accurate estimates of interception, infiltration, evaporation/transpiration fluxes, storage, and runoff.

Smith, Eric A.↗

Anticipated Improvements in Precipitation Physics and Understanding of Water Cycle from GPM Mission

The GPM mission is currently planned for start in the late-2007 to early-2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycles. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood/draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation s orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. GPM is organized internationally, involving existing, pending, projected, and under-study partnerships which will link NASA and NOAA in the US, NASDA in Japan, ESA in Europe, ISRO in India, CNES in France, and possibly AS1 in Italy, KARI in South Korea, CSA in Canada, and AEB in Brazil. Additionally, the program is actively pursuing agreements with other international collaborators and domestic scientific agencies and institutions, as well as participation by individual scientists from academia, government, and the private sector to fulfill mission goals and to pave the way for what is expected to become an internationally-organized operational global precipitation observing system. Notably, the broad societal applications of GPM are reflected in the United Nation s identification of GPM as a foremost candidate for its Peaceful Uses of Space Program. An overview of the GPM mission design is given, followed by an explanation of its scientific agenda as an outgrowth of making improvements in rain retrieval accuracy, microphysics dexterity, sampling frequency, and global coverage. All of these improvements offer new means to observe variability in precipitation and water cycle fluxes and to achieve improved predictability of weather, climate, and hydrometeorology. Specifically, the scientific agenda of GPM has been designed to leverage the measurement improvements to improve prognostic model performance, particularly quantitative precipitation forecasting and its linked phenomena at short, intermediate, and extended time scales. The talk addresses how GPM measurements will enable better detection of accelerations and decelerations in regional and global water cycle processes and their relationship to climate variability, better impacts of precipitation data assimilation on numerical weather prediction and global climate reanalysis, and better performance from basin scale hydrometeorological models for short and long term flood-drought forecasting and seasonal fresh water resource assessment. These improvements become possible by using more accurate, more microphysically-centric, more frequent, and fully global precipitation observations to achieve better water budget closure and to provide more realistic forcing and assessment of prediction models.

Smith, Eric A.↗

A Physical Validation Program for the GPM Mission

The GPM mission is currently planned for start in the late 2007 - early 2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycling. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. A major requirement before the retrieved rainfall information generated by the GPM mission can be used effectively by prognostic models to improve weather forecasts, hydrometeorological forecasts, and climate model reanalysis simulations is a capability to quantify the error characteristics of the retrievals. A solution for this problem has been upheld in past precipitation missions because of the lack of suitable error modeling systems incorporated into the validation programs and data distribution systems. An overview of how NASA intends to overcome this problem for the GPM mission using a physically-based error modeling approach within a multi-faceted validation program is described. The solution is to first identify specific user requirements and then determine the most stringent of these requirements that embodies all essential error characterization information needed by the entire user community. In the context of NASA s scientific agenda for the GPM mission, the most stringent user requirement is found within the data assimilation community. The fundamental theory of data assimilation vis-a-vis ingesting satellite precipitation information into the pre-forecast initializations is based on quantifying the conditional bias and precision errors of individual rain retrievals, and the space-time structure of the precision error (i.e., the spatial-temporal error covariance). By generating the hardware and software capability to produce this information in a near real-time fashion, and to couple the derived quantitative error properties to the actual retrieved rainrates, all key validation users can be satisfied. The talk will describe the essential components of the hardware and software systems needed to generate such near real-time error properties, as well as the various paradigm shifts needed within the validation community to produce a validation program relevant to the precipitation user community.

Smith, Eric A.↗

Millimeter- and Submillimeter-Wave Remote Sensing Using Small Satellites

Cloud ice properties and processes play fundamental roles in atmospheric radiation and precipitation. Limited knowledge and poor representation of clouds in global climate models have led to large uncertainties about cloud feedback processes under climate change. Ice clouds have been used as a tuning parameter in the models to force agreement with observations of the radiation budget at the top of the atmosphere, and precipitation at the bottom. The lack of ice cloud measurements has left the cloud processes at intermediate altitudes unconstrained. Millimeter (mm) and submillimeter (submm)-wave radiometry is widely recognized for its potential to fill the cloud measurement gap in the middle and upper troposphere. Analyses have shown that channels from 183900 GHz offer good sensitivity to ice cloud scattering and can provide ice water path (IWP) products to an accuracy of 25 by simultaneously retrieving ice particle size (Dme) and IWP. Therefore, it is highly desirable to develop a cost-effective, compact mm/submm-wave instrument for cloud observations that can be deployed on future small satellites.This paper presents a conceptual study for a mm/submm-wave instrument for multispectral measurements of ice clouds. It discusses previous work at these frequencies by NASA Goddard Space Flight Center (GSFC) and the current instrument study, as well as receiver architectures and their anticipated performance. And finally, it describes a microsatellite prototype intended for use with this mm/submm-wave instrument.

small satellites↗

Convective precipitation retrievals from space-borne dual frequency (Ka- and W-band) radar observations

The 2017 Decadal Survey highlighted Earth System Science themes, science and application questions that led to the inclusion aerosols (A), clouds, convection, and precipitation (CCP) in the list of designated observables (DOs) to be pursued within the decade following the survey. Multiple observing system architectures were considered during the NASA A-CCP study, and dual frequency Ka-W band radars have been identified as components of the most likely architectures due to their ability to significantly contribute to the achievement of the science objectives and their synergy with other essential instruments. We present an algorithm to estimate convective precipitation from dual frequency, Ka- and W-band, observations applicable to the observing system architectures considered in the A-CCP study. The algorithm is based on the radar profiling algorithm used within the operational NASA GPM combined algorithm but features an additional module that makes the retrieval problem well-posed in cases of severe attenuation and potential loss of signal below the freezing level. The additional module is developed from GPM combined retrievals and consists of a procedure that generates an ensemble of potential retrievals consistent with the portions of the Ka-band and W-band observation profiles above the noise level. The ensemble solution is refined based on estimates of Path Integrated Attenuation (PIA) from the Surface Reference Technique (SRT) and radiometric observations.

Mircea Grecu↗

Updates in Developing a Prototype Science Pipeline and Full-Volume, Global Hyperspectral Synthetic Data Sets for NASA’s Earth System Observatory’s Upcoming Surface, Biology and Geology Mission

The Surface Biology and Geology (SBG) mission recently passed mission confirmation review and has entered phase A – design and development. SBG will acquire high resolution solar-reflected spectroscopy and thermal infrared observations at a data rate of ~2.5 TB/day and generate products at ~40 TB/day. Given that the per-day volume is greater than NASA’s total extant airborne hyperspectral data collection, collecting, processing, disseminating, and exploiting the SBG data present new challenges. To meet these challenges, we have developed a prototype science pipeline and a full-volume global hyperspectral synthetic data set to help prepare for SBG’s flight (see poster GC42D-0730). Our science pipeline is based on the science processing technology developed for NASA’s Kepler and TESS planet-hunting missions. The pipeline infrastructure, Ziggy, provides a scalable architecture for robust, repeatable, and replicable science and application products that can be run on a range of systems from a laptop to the cloud or a supercomputer. Ziggy is compliant with NASA Procedural Requirement (NPR) 7150.2C, is at a technical readiness level (TRL) of 7 and has been released to github.com/nasa/ziggy. We integrated Ziggy with EO-1/Hyperion workflows to build a prototype pipeline and ingested the 17-year mission archive that provides globally sampled visible through shortwave infrared spectra that are representative of SBG data types and volumes. We fully implemented the first stage and processed the entire 55 TB Hyperion data set from the raw data (Level 0) to top-of-the-atmosphere radiance (Level 1R). We are currently evaluating the ISOFIT atmospheric correction module to convert the L1R data to surface reflectance (Level 2) before reprocessing the full data set to L2. Crosschecks are being performed with RadCalNet as well as with coincident observations by AVIRIS. We are also investigating modern methods for georectifying the Hyperion scenes. Finally, we describe an analysis of the cost to conduct forward processing and reprocessing campaigns for SBG on HECC with dedicated compute and storage resources using the resurrected Hyperion pipeline as a proxy for full-volume SBG data. The analysis demonstrates that SBG L0 data can be processed to L2 on HECC with full reprocessing campaigns every two years for ~$2.6M over a 7-year lifespan. Moreover, 69% of the system capacity would be available for other activities, possibly enabling future open-source science activities, including algorithm development, L3+ processing, .etc.

ESD↗

Towards the Development of a Global Precipitation Measurement (GPM) Mission Concept

The scientific success of the Tropical Rainfall Measuring Mission (TRMM) and additional satellite-focused precipitation retrieval projects have paved the way for a more advanced global precipitation mission. A comprehensive global measuring strategy is currently under study - Global Precipitation Measurement (GPM). The GPM study could ultimately lead to the development of the Global Precipitation Mission. The intent of GPM is to address looming scientific questions arising in the context of global climate-water cycle interactions, hydrometeorology, weather prediction and prediction of freshwater resources, the global carbon cycle, and biogeochemical cycles. This talk overviews the status and scientific agenda of this proposed mission currently planned for launch in the 2007-2008 time frame. GPM is planning to expand the scope of precipitation measurement through the use of a constellation of 6-10 satellites, one of which will be an advanced TRMM-like "core" satellite carry dual-frequency Ku-Ka band radar and a microwave radiometer (e.g. TMI-like). The other constellation members will likely include new lightweight satellites and co-existing operational/research satellites carrying passive microwave radiometers. The goal behind the constellation is to achieve no worse than 3-hour sampling at any spot on the globe. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-su n -synchronous satellites with the "core" satellite providing measurement of cloud-precipitation microphysical processes plus "training calibrating" information to be used with the retrieval algorithms for the constellation satellite measurements. The GPM is organized internationally, currently involving a partnership between NASA in the US, NASDA in Japan, and ESA in Europe (representing the European community). The program is expected to involve additional international partners, other federal agencies, and a diverse collection of scientists from academia, government, and the private sector.

Shepherd, Marshall↗

RainCube and its legacy for the next generation of spaceborne cloud and precipitation radars

The multidimensional challenge of observing cloud and precipitation processes from space has motivated and focused a number of technological developments in the last decade. They span from novel compact instrument architectures to modular millimeter wave phased array solutions. In this paper we summarize the main capabilities offered by three instruments from this new generation, and discuss how they affect formulation of future observing systems.

Rodriguez-Monje, Raquel↗

NASA SNPP SIPS - Following in the Path of EOS

NASA's Earth Science Data Information System (ESDIS) Project has been operating NASA's Suomi National Polar-Orbiting Partnership (SNPP) Science Data Segment (SDS) since the launch in October 2011. At launch, the SDS focused primarily on the evaluation of Sensor Data Records (SDRs) and Environmental Data Records (EDRs) produced by the Joint Polar Satellite System (JPSS), a National Oceanic and Atmosphere Administration (NOAA) Program, as to their suitability for Earth system science. During the summer of 2014, NASA transitioned to the production of standard Earth Observing System (EOS)-like science products for all instruments aboard Suomi NPP. The five Science Investigator-led Processing Systems (SIPS): Land, Ocean, Atmosphere, Ozone, and Sounder were established to produce the NASA SNPP standard Level 1, Level 2, and global Level 3 products developed by the SNPP Science Teams and to provide the products to NASA's Distributed Active Archive Centers (DAACs) for archive and distribution to the user community. The processing, archiving and distribution of data from NASA's Clouds and the Earth's Radiant Energy System (CERES) and Ozone Mapper/Profiler Suite (OMPS) Limb instruments will continue. With the implementation of the JPSS Block 2 architecture and the launch of JPSS-1, the SDS will receive SNPP data in near real-time via the JPSS Stored Mission Data Hub (JSH), as well as JPSS-1 and future JPSS-2 data. The SNPP SIPS will ingest EOS compatible Level 0 data from the EOS Data Operations System (EDOS) element for their data processing, enabling the continuous EOS-SNPP-JPSS Satellite Data Record.

near real time↗