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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2019

The Legacy and Future of the International Earth Science Constellation (ESC)

The most recent Decadal Survey placed high value on continuing constellation science. The ESC has evolved by seeing new missions joining and old missions retiring. Most recently, GCOM-W1, Landsat-8, and OCO-2 joined during 2012-2014. Landsat-9 is set to join in 2020. Each new mission provides new and improved suite of sensors. The new sensors also benefit both from the multitude of other existing on-orbit sensors as well as from the long-term cross-calibrated climate observations from the sensors that preceded them. At the same time, existing missions leave the constellation due to low fuel reserves or aging spacecraft subsystems. For example, CloudSat and CALIPSO left the ESC orbits in 2018, although they plan to continue making coordinated science observations at their new lower altitudes. This ESC evolution is expected to continue and this paper will discuss the opportunities for other new missions to join the ESC.

afternoon constellation↗
NASA NTRS2022

Direct Comparisons Between GPM-DPR and CloudSat Snowfall Retrievals

Two spaceborne radars currently in orbit enable the sampling of snowfall near the surface and throughout the atmospheric column, namely, CloudSat’s Cloud Profiling Radar (CPR) and the Global Precipitation Measurement mission’s Dual-Frequency Precipitation Radar (GPM-DPR). In this paper, a direct comparison of the CPR’s 2C-SNOW-PROFILE (2CSP), the operational GPM-DPR algorithm (2ADPR) and a neural network (NN) retrieval applied to the GPM-DPR data is performed using coincident observations between both radars. Examination of over 3500 profiles within moderate to strong precipitation (Ka band ≥ 18 dBZ) show that the NN retrieval provides the closest retrieval of liquid equivalent precipitation rate R immediately above the melting level to the R retrieved just below the melting layer, agreeing within 5%. Meanwhile, 2CSP retrieves a maximum value of R at −15°C, decreases by 35% just above the melting layer, and is about 50% smaller than the GPM-DPR retrieved R below the melting layer. CPR-measured reflectivity shows median reduction of 2–3 dB from −15° to −2.5°C, likely the reason for the 2CSP retrieval reduction of R . Two case studies from NASA field campaigns [i.e., Olympic Mountains Experiment (OLYMPEX) and Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS)] provide analogs to the type of precipitating systems found in the comparison between retrieval products. For the snowfall events that GPM-DPR can observe, this work suggests that the 2CSP retrieval is likely underestimating the unattenuated reflectivity, resulting in a potential negative, or low, bias in R . Future work should investigate how frequently the underestimated reflectivity profiles occur within the CPR record and quantify its potential effects on global snowfall accumulation estimation.

Atmosphere↗
NASA NTRS2009

Small Earth Observing Satellites Flying with Large Satellites in the A-Train

This paper/poster presents a real-life example of the benefits of flying small satellites with other satellites, large or small, and vice versa. Typically, most small satellites fly payloads consisting of one or two instruments and fly in orbits that are independent from that of other satellites. The science data from these satellites are either used in isolation or correlated with instrument data from other satellites. Data correlation with other satellites is greatly improved when the measurements of the same point or air mass are taken at approximately the same time. Scientists worldwide are beginning to take advantage of the opportunities for improved data correlation, or coincidental science, offered by the international Earth Observing Constellation known as the A-Train (sometimes referred to as the Afternoon Constellation). Most of the A-Train satellites are small - the A-Train is anchored by two large NASA satellites (EOS-Aqua and EOS-Aura), but consists also of 5 small satellites (CloudSat, CALIPSO, PARASOL, OCO and Glory these last two will join in 2009). By flying in a constellation, each mission benefits from coincidental observations from instruments on the other satellites in the constellation. Essentially, from a data point of view, the A-Train can be envisioned as a single, virtual science platform with multiple instruments. Satellites in the A-Train fly at 705 km in sun-synchronous orbits. Their mean local times at the equator are within seconds to a few minutes of each other. This paper describes the challenges of operating an international constellation of independent satellites from the U.S. and Europe to maximize the coincidental science opportunities while at the same time minimizing the level of operational interactions required between team members. The A-Train mission teams have been able to demonstrate that flying as members of an international constellation does not take away the flexibility to accommodate new requirements. Specific examples will be cited, including CloudSat's relocation (to accommodate a new viewing angle for the CALIPSO satellite), Glory's replan to move closer to PARASOL, and OCO's long term plans to minimize on-orbit operations costs while maintaining safety. In all cases, safety is ensured, science returns are enhanced, and operational flexibility is retained to the maximum extent possible.

Kelly, Angelita C.↗
NASA NTRS2006

Initial Results from CALIPSO

CALIPSO will carry the first polarization lidar in orbit, along with infrared and visible passive imagers, and will fly in formation as part of the Afternoon Constellation (A-train). The acquisition of observations which are simultaneous and coincident with observations from other instruments of the A-train will allow numerous synergies to be realized from combining CALIPSO observations with observations from other platforms. In particular, cloud observations from the CALIPSO lidar and the CloudSat radar will complement each other, together encompassing the variety of clouds found in the atmosphere, from thin cirrus to deep convective clouds. CALIPSO has been developed within the framework of a collaboration between NASA and CNES and is currently scheduled to launch, along with the CloudSat satellite, in spring 2006. This paper will present an overview of the CALIPSO mission, including initial results.

Winker, David M.↗
NASA NTRSDate not supplied

25 Years of CALIPSO

Selected for development in 1998 and launched together with CloudSat in 2006, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations(CALIPSO) mission terminated science operations in the summer of 2023 aftercompleting17 years of on-orbit observations. As one of NASA’s Earth System Science Pathfinder missions, CALIPSO was truly a pathfinder. CALIPSO observations have provided a new perspective on clouds and aerosol and have not only met but far exceeded the original objectives of the mission. Many unanticipated findings and data applications have been discovered along the way. Fly-ing with many other remote sensing instruments, as part of the A-train constellation, stimulated the discovery of numerous retrieval synergies between lidar and other sensors. This paper describes how the CALIPSO mission came to be, discusses some of the early choices made by the CALIPSO team that shaped the mission, and some of the challenges facing the team in developing the first-ever global climatologies of aerosol and cloud based on lidar observations.

Space lidar↗
NASA NTRS2002

CloudSat system engineering: techniques that point to a future success

Over the past three years the CloutSat Project, a NASA Earth System Science Pathfinder mission to provide from space the first global survey of cloud profiles and cloud physical properties, has implemented a successful project system engineering approach. Techniques learned through heuristic reasoning of past project events and professional experience were applied along with select methods recently touted to increase effectiveness without compromising effiency.

CloudSat system engineering project management↗
NASA NTRS2005

Analysis For Monitoring the Earth Science Afternoon Constellation

The Earth Science Afternoon Constellation consists of Aqua, Aura, PARASOL, CALIPSO, Cloudsat, and the Orbiting Carbon Observatory (OCO). The coordination of flight dynamics activities between these missions is critical to the safety and success of the Afternoon Constellation. This coordination is based on two main concepts, the control box and the zone-of-exclusion. This paper describes how these two concepts are implemented in the Constellation Coordination System (CCS). The CCS is a collection of tools that enables the collection and distribution of flight dynamics products among the missions, allows cross-mission analyses to be performed through a web-based interface, performs automated analyses to monitor the overall constellation, and notifies the missions of changes in the status of the other missions.

Demarest, Peter↗
NASA NTRS2007

A Contrast in Use of Metrics in Earth Science Data Systems

In recent years there has been a surge in the number of systems for processing, archiving and distributing remotely sensed data. Such systems, working independently as well as in collaboration, have been contributing greatly to the advances in the scientific understanding of the Earth system, as well as utilization of the data for nationally and internationally important applications. Among such systems, we consider those that are developed by or under the sponsorship of NASA to fulfill one of its strategic objectives: "Study Earth from space to advance scientific understanding and meet societal needs." NASA's Earth science data systems are of varying size and complexity depending on the requirements they are intended to meet. Some data systems are regarded as NASA's "Core Capabilities" that provide the basic infrastructure for processing, archiving and distributing a set of data products to a large and diverse user community in a robust and reliable manner. Other data systems constitute "Community Capabilities". These provide specialized and innovative services to data users and/or research products offering new scientific insight. Such data systems are generally supported by NASA through peer reviewed competition. Examples of Core Capabilities are 1. Earth Observing Data and Information System (EOSDIS) with its Distributed Active Archive Centers (DAACs), Science Investigator-led Processing Systems (SIPSs), and the EOS Clearing House (ECHO); 2. Tropical Rainfall Measurement Mission (TRMM) Science Data and Information System (TSDIS); 3. Ocean Data Processing System (ODPS); and 4. CloudSat Data Processing Center. Examples of Community Capabilities are projects under the Research, Education and Applications Solutions Network (REASON), and Advancing Collaborative Connections for Earth System Science (ACCESS) Programs. In managing these data system capabilities, it is necessary to have well-established goals and to measure progress relative to them. Progress is measured through "metrics", which can be a combination of quantitative as well as qualitative assessments. The specific metrics of interest depend on the user of the metrics as well as the type of data system. The users of metrics can be data system managers, program managers, funding agency or the public. Data system managers need metrics for assessing and improving the performance of the system and for future planning. Program managers need metrics to assess progress and the value of the data systems sponsored by them. Also, there is a difference in the metrics needed for core capabilities that tend to be more complex, larger and longer-term compared to community capabilities and the community capabilities that tend to be simpler, smaller and shorter-term. Even among community capabilities there are differences; hence the same set of metrics does not apply to all. Some provide data products to users, some provide services that enable better utilization of data or interoperability among other systems, and some are a part of a larger project where provision of data or services is only a minor activity. There is also a contrast between metrics used for internal and external purposes. Examples of internal purposes are: ensuring that the system meets its requirements, and planning for evolution and growth. Examples of external purposes are: providing to sponsors indicators of success of the systems, demonstrating the contributions of the system to overall program success, etc. This paper will consider EOSDIS, REASON and ACCESS programs to show the various types of metrics needed and how they need to be tailored to the types of data systems while maintaining the overall management goals of measuring progress and contributions made by the data systems.

Ramapriyan, Hampapuram↗
NASA NTRS2010

Evolution of the Tropical Cyclone Integrated Data Exchange And Analysis System (TC-IDEAS)

The Tropical Cyclone Integrated Data Exchange and Analysis System (TC-IDEAS) is being jointly developed by the Jet Propulsion Laboratory (JPL) and the Marshall Space Flight Center (MSFC) as part of NASA's Hurricane Science Research Program. The long-term goal is to create a comprehensive tropical cyclone database of satellite and airborne observations, in-situ measurements and model simulations containing parameters that pertain to the thermodynamic and microphysical structure of the storms; the air-sea interaction processes; and the large-scale environment.

CloudSat↗
NASA NTRS2013

The Role of Cloud and Precipitation Radars in Convoys and Constellations

We provide an overview of which benefits a radar, and only a radar, can provide to any constellation of satellites monitoring Earth's atmosphere; which aspects instead are most useful to complement a radar instrument to provide accurate and complete description of the state of the troposphere; and finally which goals can be given a lower priority assuming that other types of sensors will be flying in formation with a radar.

Aerosol/Cloud/Ecosystems (ACE)↗
NASA NTRS2002

The Impact of Maneuver Failures on the EOS Afternoon Constellation

The first four satellites, Aqua, CloudSat, Calipso, and Parasol, in NASA's EOS Afternoon constellation will fly in similar orbits within 4 minutes of each other. This study was undertaken to examine the effect of one or more missions failing to perform a scheduled orbit maintenance maneuver. Tools were developed to rapidly calculate the initial orbital elements for the satellites that established the formation. Baseline maneuver strategies were implemented to maintain the desired spacing of the satellites. Maneuver failures were examined and close approach opportunities were identified. It was found that close-approaches between CloudSat and Calipso could occur in less than one day after a missed maneuver if close coordination between the missions is not achieved.

Demarest, Peter↗
NASA NTRS2019

CloudSat Bias on Falling Snow Estimates Over the Daylight Only Operational Period (2012-2019)

Falling snow is a key component for the global atmospheric, hydrological and energy cycles, and its retrieval from space-based observations represents the best current capability to evaluate it globally. The Global Precipitation Measurement (GPM) Mission Core Observatory, launched in 2014, together with its constellation sensors, can provide quasi-global precipitation estimates every 30 minutes (for level 3 products). Evaluation and validation efforts for such products are crucial, and for global evaluations, one of the most suitable instruments is the Cloud Profiling Radar (CPR) on board CloudSat, which is sensitive to light rain and falling snow. However, due to a battery anomaly in 2011, during its period of overlapping observations with GPM the CPR has operated in a Daylight Only Operations mode (DO-Op) in which it makes measurements primarily during only the daylit portion of its orbit. The goal of this work is to estimate biases inherent in global snowfall amounts derived from CPR measurements due to this shift to DO-Op mode. We use CloudSat's snowfall measurements during its Full Operations (Full-Op) period from 2006 to 2010 to evaluate the impact DO-Op mode would have had during this period. Results indicate that omitting the nocturnal component of the diurnal cycle of snowfall has nonnegligible impact on snowfall amounts in some regions. The lack of nighttime data during DO-Op biases the latitudinally averaged mean snowfall rates as well as some regional values. Hemispheric differences in bias may be due to more pronounced diurnal variability in the northern hemisphere owing to more prevalent land surface versus the southern hemisphere. The results highlight the need to sample consistently with the CloudSat observations or to adjust snowfall estimates derived from CloudSat when using DO-Op data to evaluate other precipitation products.

Milani, Lisa↗
NASA NTRS2008

Current Scientific Progress and Future Scientific Prospects Enabled by Spaceborne Precipitation Radar Measurements

First, we examine current scientific progress and understanding that have been possible through use of spaceborne precipitation radar measurements being provided by the TRMM and CloudSat satellites. Second, we look across a future 20-year time frame to assess how and why anticipated improvements in space radar systems will further advance scientific progress into topic areas once considered beyond the realm of space-based remote sensing. JAXA's 13.8 GHz Ku-band cross-track scanning Precipitation Radar (PR) developed for flight on NASA's non-sun-synchronous, diurnally-precessing TRMM satellite, was the first Earth radar flown in space that was designed specifically for precipitation measurement. Its proven accuracy in measuring global rainfall in the tropics and sub-tropics and its unanticipated longevity in continuing these measurements beyond a full decade have established the standards against which all follow-up and future space radars will be evaluated. In regards to the current PR measurement time series, we will discuss a selection of major scientific discoveries and impacts which have set the stage for future radar measuring systems. In fact, the 2nd contemporary space radar applicable for terrestrial precipitation measurement, i.e., JPL-CSA's 94 GHz nadir-staring Cloud Profiling Radar (CPR) flown on NASA's sun-synchronous CloudSat satellite, although designed primarily for measurement of non-precipitating cloud hydrometeors and aerosols, has also unquestionably advanced precipitation measurement because CPR's higher frequency and greatly increased sensitivity (approximately 30 dBZ) has enabled global observations of light rain rate spectrum processes (i.e., rain rates below 0.05 mm per hourand of precipitation processes in the high troposphere (particularly ice phase processes). These processes are beyond reach of the TRMM radar because the PR sensitivity limit is approximately 17 dBZ which means its lower rain rate cutoff is around 0.3 mm per hour and its vertical profiling acuity is greatly limited above the melting layer. Thus, the newer CPR measurements have become important for a variety of scientific reasons that will be highlighted and assessed. In considering scientific progress likely to stem from future precipitation radar systems, we will specifically examine possible scientific impacts from three anticipated missions for which NASA and various of its space agency partners are expected to lead the way. These three missions are: (1) the nearterm Global Precipitation Measuring (GPM) Mission; (2) the decadal timeline Aerosol and Cloud Experiment (ACE) Mission; and the post-decadal timeline NEXRAD in Space (NIS) Mission. The observational capabilities of the planned radar systems for each of these three satellite missions are distinct from each other and each provides progressive improvements in precipitation measuring and scientific research capabilities relative to where we are now -- insofar as TRMM PR and the CloudSat CPR capabilities. The potential innovations in scientific research will be discussed in a framework of likely synergisms between next-generation radar capabilities and accessible dynamical and microphysical properties that have heretofore evaded detection.

Smith, Eric A.↗
NASA NTRSDate not supplied

Towards a Marine Stratus Climatology on Drizzle Occurrence from CALIPSO

Marine stratus are a predominant feature of our planet with the annual mean coverage exceeding 20%. They strongly reflect sunlight, yet exert only a modest effect on outgoing infrared radiation, providing a significant net cooling to the Earth’s radiative balance. Their formation is coupled to boundary layer circulations that are driven, in part, by cloud top radiative cooling and evaporative cooling from precipitation in downdrafts. Understanding how these cloud systems evolve as the climate changes is a key question that requires additional information on their lifecycle and microphysical properties to accurately represent their behavior in global circulation models. From a large-scale perspective, insight into the microphysical properties of marine stratus at cloud top can be realized through estimates of the effective radius (Re) of the droplet size distributions derived from MODIS observations. Estimates on the occurrence of rain/drizzle are available from CloudSat. Together these observations indicate that precipitation frequently occurs in clouds with higher cloud top Re. This relationship is consistent with the well documented shift in cloud top droplet size distributions towards fewer, yet larger droplets prior the onset of precipitation. Here we report on a new and complementary set observations from the CALIPSO mission. The approach derives an extinction-to-backscatter ratio (Sc, also known as the cloud lidar ratio) using an established relationship that depends on observations of the lidar attenuated backscatter and volume depolarization ratio within the cloud. Because Sc is strongly and inversely related to Re, a change in the derived Sc from higher to lower values corresponds to a change in the droplet size distribution as seen by MODIS. This change in the lidar signals at cloud top clearly identifies clouds that are capable of precipitation. The presentation provides a brief overview of the approach for deriving Sc and compares CALIOP-derived Sc with observations from other techniques. CALIOP classifications of drizzling clouds, based on the retrieved values Sc, are compared to independent, collocated assessments of drizzle occurrence reported in the standard CloudSat data products. Regional and seasonal comparisons highlight the strengths and weaknesses of the two sensors. A machine learning approach that combines information from both CALIOP and CloudSat showcases possible improvements in the global identification of scenes likely to contain rain-bearing clouds.

CALIPSO↗
NASA NTRS2006

What does reflection from cloud sides tell us about vertical distribution of cloud droplets?

In order to accurately measure the interaction of clouds with aerosols, we have to resolve the vertical distribution of cloud droplet sizes and determine the temperature of glaciation for clean and polluted clouds. Knowledge of the droplet vertical profile is also essential for understanding precipitation. So far, all existing satellites either measure cloud microphysics only at cloud top (e.g., MODIS) or give a vertical profile of precipitation sized droplets (e.g., Cloudsat). What if one measures cloud microphysical properties in the vertical by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides? This was the idea behind CLAIM-3D (A 3D - cloud aerosol interaction mission) recently proposed by NASA GSFC. This presentation will focus on the interpretation of the radiation reflected from cloud sides. In contrast to plane-parallel approximation, a conventional approach to all current operational retrievals, 3D radiative transfer will be used for interpreting the observed reflectances. As a proof of concept, we will show a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with prescribed microphysics. Instead of fixed values of the retrieved effective radii, the probability density functions of droplet size distributions will serve as possible retrievals.

Marshak, A.↗
NASA NTRS2000

A systematic risk management approach employed on the CloudSat project

The CloudSat Project has developed a simplified approach for fault tree analysis and probabilistic risk assessment. A system-level fault tree has been constructed to identify credible fault scenarios and failure modes leading up to a potential failure to meet the nominal mission success criteria.

risk management fault tree analysis probabilistic ↗