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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Satellite Data Simulator Unit: A Multisensor, Multispectral Satellite Simulator Package

Several multisensor simulator packages are being developed by different research groups across the world. Such simulator packages [e.g., COSP , CRTM, ECSIM, RTTO, ISSARS (under development), and SDSU (this article), among others] share overall aims, although some are targeted more on particular satellite programs or specific applications (for research purposes or for operational use) than others. The SDSU or Satellite Data Simulator Unit is a general-purpose simulator composed of Fortran 90 codes and applicable to spaceborne microwave radiometer, radar, and visible/infrared imagers including, but not limited to, the sensors listed in a table. That shows satellite programs particularly suitable for multisensor data analysis: some are single satellite missions carrying two or more instruments, while others are constellations of satellites flying in formation. The TRMM and A-Train are ongoing satellite missions carrying diverse sensors that observe clouds and precipitation, and will be continued or augmented within the decade to come by future multisensor missions such as the GPM and Earth-CARE. The ultimate goals of these present and proposed satellite programs are not restricted to clouds and precipitation but are to better understand their interactions with atmospheric dynamics/chemistry and feedback to climate. The SDSU's applicability is not technically limited to hydrometeor measurements either, but may be extended to air temperature and humidity observations by tuning the SDSU to sounding channels. As such, the SDSU and other multisensor simulators would potentially contribute to a broad area of climate and atmospheric sciences. The SDSU is not optimized to any particular orbital geometry of satellites. The SDSU is applicable not only to low-Earth orbiting platforms as listed in Table 1, but also to geostationary meteorological satellites. Although no geosynchronous satellite carries microwave instruments at present or in the near future, the SDSU would be useful for future geostationary satellites with a microwave radiometer and/or a radar aboard, which could become more feasible as engineering challenges are met. In this short article, the SDSU algorithm architecture and potential applications are reviewed in brief.

Masunaga, Hirohiko↗
NASA NTRS2014

Earth Radiation Budget Research at the NASA Langley Research Center

In the 1970s research studies concentrating on satellite measurements of Earth's radiation budget started at the NASA Langley Research Center. Since that beginning, considerable effort has been devoted to developing measurement techniques, data analysis methods, and time-space sampling strategies to meet the radiation budget science requirements for climate studies. Implementation and success of the Earth Radiation Budget Experiment (ERBE) and the Clouds and the Earth's Radiant Energy System (CERES) was due to the remarkable teamwork of many engineers, scientists, and data analysts. Data from ERBE have provided a new understanding of the effects of clouds, aerosols, and El Nino/La Nina oscillation on the Earth's radiation. CERES spacecraft instruments have extended the time coverage with high quality climate data records for over a decade. Using ERBE and CERES measurements these teams have created information about radiation at the top of the atmosphere, at the surface, and throughout the atmosphere for a better understanding of our climate. They have also generated surface radiation products for designers of solar power plants and buildings and numerous other applications

Smith, G. Louis↗
NASA NTRS2015

Cloud Computing Technologies Facilitate Earth Research

Under a Space Act Agreement, NASA partnered with Seattle-based Amazon Web Services to make the agency's climate and Earth science satellite data publicly available on the company's servers. Users can access the data for free, but they can also pay to use Amazon's computing services to analyze and visualize information using the same software available to NASA researchers.

Source record↗
NASA NTRS2011

Sea Surface Salinity and Wind Retrieval Algorithm Using Combined Passive-Active L-Band Microwave Data

Aquarius is a combined passive/active L-band microwave instrument developed to map the salinity field at the surface of the ocean from space. The data will support studies of the coupling between ocean circulation, the global water cycle, and climate. The primary science objective of this mission is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean with a spatial resolution of 150 kilometers and a retrieval accuracy of 0.2 practical salinity units globally on a monthly basis. The measurement principle is based on the response of the L-band (1.413 gigahertz) sea surface brightness temperatures (T (sub B)) to sea surface salinity. To achieve the required 0.2 practical salinity units accuracy, the impact of sea surface roughness (e.g. wind-generated ripples and waves) along with several factors on the observed brightness temperature has to be corrected to better than a few tenths of a degree Kelvin. To the end, Aquarius includes a scatterometer to help correct for this surface roughness effect.

ocean salinity↗
NASA NTRS2014

Global Distribution and Trends of Tropospheric Ozone: An Observation-Based Review

Tropospheric ozone plays a major role in Earth's atmospheric chemistry processes and also acts as an air pollutant and greenhouse gas. Due to its short lifetime, and dependence on sunlight and precursor emissions from natural and anthropogenic sources, tropospheric ozone's abundance is highly variable in space and time on seasonal, interannual and decadal time-scales. Recent, and sometimes rapid, changes in observed ozone mixing ratios and ozone precursor emissions inspired us to produce this up-to-date overview of tropospheric ozone's global distribution and trends. Much of the text is a synthesis of in situ and remotely sensed ozone observations reported in the peer-reviewed literature, but we also include some new and extended analyses using well-known and referenced datasets to draw connections between ozone trends and distributions in different regions of the world. In addition, we provide a brief evaluation of the accuracy of rural or remote surface ozone trends calculated by three state-of-the-science chemistry-climate models, the tools used by scientists to fill the gaps in our knowledge of global tropospheric ozone distribution and trends.

Mixing ratios↗
NASA NTRSDate not supplied

A NASA GISTEMP Observational Uncertainty Ensemble: Regional and Monthly Uncertainty

The historical global temperature record is an essential data product for quantifying the variability and change of the Earth system. In recent years, better characterization of observational uncertainty in global and hemispheric trends has become available, but the methodologies are not necessarily applicable to analyses at smaller regional areas, or monthly means, where station sparsity and other systematic issues contribute to greater uncertainty. This work details a gridded uncertainty ensemble of historical temperature anomalies from the Goddard Institute for Space Studies (GISS) Surface Temperature product (GISTEMP) product. This ensemble characterizes the complex spatial and temporal correlation structure of uncertainty in gridded historical temperature, enabling proper uncertainty propagation for climate and social science at regional and monthly scales. This work details the methodology for generating the uncertainty ensemble, key statistics of the uncertainty evolution over space and time, and provides best practices for using the uncertainty ensemble in future studies. Summary statistics from the uncertainty ensemble are in good agreement with production GISTEMP. Two applications of the uncertainty ensemble are also presented. First, the warmest year on record is shown to most likely be 2016 with a 53.2% chance and 2020 as the second most likely with a 44.4% chance. Second, it is shown that the arctic is warming 2.5 - 5 times faster than the globe, significantly faster than the regularly quoted twice as fast.

GISTEMP↗
NASA NTRSDate not supplied

Overview of the Earth System Observatory—Atmosphere Observing System (AOS)

AOS will be the next generation of atmospheric observations for the world. With the loss of EOS this decade, we’d be flying blind to many of the processes that are impacting climate change. AOS science objectives and measurements directly align with DS objectives. AOS complexity directly follows from the complexity of DS objectives. AOS takes advantage of key international partnerships. Urgent need to move forward towards delivering these critical capabilities this decade and early next decade.

Scott Braun↗
NASA NTRS1998

Lidar Measurements of Tropospheric Wind Profiles with the Double Edge Technique

Research has established the importance of global tropospheric wind measurements for large scale improvements in numerical weather prediction. In addition, global wind measurements provide data that are fundamental to the understanding and prediction of global climate change. These tasks are closely linked with the goals of the NASA Earth Science Enterprise and Global Climate Change programs. NASA Goddard has been actively involved in the development of direct detection Doppler lidar methods and technologies to meet the wind observing needs of the atmospheric science community. A variety of direct detection Doppler wind lidar measurements have recently been reported indicating the growing interest in this area. Our program at Goddard has concentrated on the development of the edge technique for lidar wind measurements. Implementations of the edge technique using either the aerosol or molecular backscatter for the Doppler wind measurement have been described. The basic principles have been verified in lab and atmospheric lidar wind experiments. The lidar measurements were obtained with an aerosol edge technique lidar operating at 1064 nm. These measurements demonstrated high spatial resolution (22 m) and high velocity sensitivity (rms variances of 0.1 m/s) in the planetary boundary layer (PBL). The aerosol backscatter is typically high in the PBL and the effects of the molecular backscatter can often be neglected. However, as was discussed in the original edge technique paper, the molecular contribution to the signal is significant above the boundary layer and a correction for the effects of molecular backscatter is required to make wind measurements. In addition, the molecular signal is a dominant source of noise in regions where the molecular to aerosol ratio is large since the energy monitor channel used in the single edge technique measures the sum of the aerosol and molecular signals. To extend the operation of the edge technique into the free troposphere we have developed a variation of the edge technique called the double edge technique. In this paper a ground based aerosol double edge lidar is described and the first measurements of wind profiles in the free troposphere obtained with this lidar will be presented.

Gentry, Bruce M.↗
NASA NTRS1998

Tropospheric Wind Profile Measurements with a Direct Detection Doppler Lidar

Research has established the importance of global tropospheric wind measurements for large scale improvements in numerical weather prediction. In addition, global wind measurements provide data that are fundamental to the understanding and prediction of global climate change. These tasks are closely linked with the goals of the NASA Earth Science Enterprise and Global Climate Change programs. NASA Goddard has been actively involved in the development of direct detection Doppler lidar methods and technologies to meet the wind observing needs of the atmospheric science community. In this paper we describe a recently developed prototype wind lidar system using a direct detection Doppler technique for measuring wind profiles from the surface through the troposphere. This system uses a pulsed ND:YAG laser operating at 1064 nm as the transmitter. The laser pulse is directed to the atmosphere using a 40 cm diameter scan mirror. The portion of the laser energy backscattered from aerosols and molecules is collected by a 40 cm diameter telescope and coupled via fiber optics into the Doppler receiver. Single photon counting APD's are used to detect the atmospheric backscattered signal. The principle element of the receiver is a dual bandpass tunable Fabry Perot etalon which analyzes the Doppler shift of the incoming laser signal using the double edge technique. The double edge technique uses two high resolution optical filters having bandpasses offset relative to one another such that the 'edge' of the first filter's transmission function crosses that of the second at the half power point. The outgoing laser frequency is located approximately at the crossover point. Due to the opposite going slopes of the edges, a Doppler shift in the atmospheric backscattered laser frequency produces a positive change in signal for one filter and a negative change in the second filter. Taking the ratio of the two edge channel signals yields a result which is directly proportional to the component of the wind along the line-of-sight of the laser. Measuring the radial wind in several directions provides sufficient information to determine the true wind speed and direction. The lidar has operated from our laboratory at Goddard since June, 1997. Wind profiles have been obtained to altitudes of 12 km with a vertical resolution of 330 in. Vector wind data are obtained by rotating the scan mirror to measure line-of-sight wind profiles for at least two azimuth angles at an elevation angle of 45 degrees. The precision of the data as determined from the standard deviation of multiple independent lidar profiles is in the range of 1 to 3 m/sec up to 10 km. Good agreement is obtained when the lidar data are compared with the upper air rawinsonde soundings taken at Dulles airport. Examples of the wind lidar data will be presented along with a description of the instrument and future developments.

Gentry, Bruce M.↗
NASA NTRS1994

Taking the initiative: A leadership conference for women in science and engineering

The conference sprang from discussions on the current climate that women face in science, mathematics, engineering, and technology. The conference (and this document) is a beginning, not a culmination, of women's learning leadership skills. Conferees were active, articulate, energetic, and ready to learn leadership qualities, some of which seem universal, others that appear to require skills in specific fields. After the introduction, the workshops and presentations are arranged under vision and direction, barriers, alignment and communication, and motivation and inspiration. Some statistics are presented on women degrees and employment in various fields.

Source record↗
NASA NTRS2016

Comparative Results of AIRS AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

The AIRS Science Team Version 6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRSAMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrISATMS is the only scheduled follow on to AIRSAMSU. The objective of this research is to prepare for generation of a long term CrISATMS level-3 data using a finalized retrieval algorithm that is scientifically equivalent to AIRSAMSU Version-7.

AIRS↗
NASA NTRS2016

Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

AIRS AMSU↗
NASA NTRS2008

NASA Earth Observations Informing Renewable Energy Management and Policy Decision Making

The NASA Applied Sciences Program partners with domestic and international governmental organizations, universities, and private entities to improve their decisions and assessments. These improvements are enabled by using the knowledge generated from research resulting from spacecraft observations and model predictions conducted by NASA and providing these as inputs to the decision support and scenario assessment tools used by partner organizations. The Program is divided into eight societal benefit areas, aligned in general with the Global Earth Observation System of Systems (GEOSS) themes. The Climate Application of the Applied Sciences Program has as one of its focuses, efforts to provide for improved decisions and assessments in the areas of renewable energy technologies, energy efficiency, and climate change impacts. The goals of the Applied Sciences Program are aligned with national initiatives such as the U.S. Climate Change Science and Technology Programs and with those of international organizations including the Group on Earth Observations (GEO) and the Committee on Earth Observation Satellites (CEOS). Activities within the Program are funded principally through proposals submitted in response to annual solicitations and reviewed by peers.

Eckman, Richard S.↗
NASA NTRS2024

NPCC4: Tail Risk, Climate Drivers of Extreme Heat, and New Methods for Extreme Event Projections

We summarize historic New York City (NYC) climate change trends and provide the latest scientific analyses on projected future changes based on a range of global greenhouse gas emissions scenarios. Building on previous NPCC assessment reports, we describe new methods used to develop the projections of record for sea level rise, temperature, and precipitation for NYC, across multiple emissions pathways and analyze the issue of the “hot models” associated with the 6th phase of the Coupled Model Intercomparison Project (CMIP6) and their potential impact on NYC's climate projections. We describe the state of the science on temperature variability within NYC and explain both the large-scale and regional dynamics that lead to extreme heat events, as well as the local physical drivers that lead to inequitable distributions of exposure to extreme heat. We identify three areas of tail risk and potential for its mischaracterization, including the physical processes of extreme events and the effects of a changing climate. Finally, we review opportunities for future research, with a focus on the hot model problem and the intersection of spatial resolution of projections with gaps in knowledge in the impacts of the climate signal on intraurban heat and heat exposure.

NPCC4↗
NASA NTRSDate not supplied

Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder Intercalibration Data Analysis Strategy

One of the prime science objectives of NASA’s Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission is to acquire unprecedentedly accurate Système Internationale (SI)-traceable Earth-view measurements that can be used as reference for intercalibrating the Clouds and the Earth’s Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard NOAA-20 satellite. The hyperspectral nature of CPF measurements will significantly reduce spectrally induced biases when intercalibrating multiband or broadband satellite instruments with CPF. This advancement eliminates the requirement for spectral band adjustment factors, representing a substantial improvement in sensor intercalibration studies. The CPF intercalibration team is aiming to achieve a maximum intercalibration methodology uncertainty of 0.3 % (k=1). Our studies have revealed that the most significant contribution to the targeted uncertainty budget originates from the combined effects of spatial and temporal matching errors. Spatial matching error arises from discrepancies in CPF and target instrument pixel resolution and geolocation uncertainty, while temporal matching error is caused by changes in scene radiances over time, occurring between when the target and reference instruments observe the same scenes. To estimate the maximum expected uncertainty contribution from these sources, spatial and temporal matching noise analyses were conducted using algorithmically filtered Landsat 9 Operational Land Imager (OLI) and Geostationary Operational Environmental Satellite (GOES)-16 ABI CONUS scan data as proxies for CPF and target instruments. In the upcoming conference presentation, we will elaborate on the methodology employed in these experiments, provide details of the data filtering algorithms, and present results of the spatial and temporal matching uncertainty analyses.

Intercalibration↗
NASA NTRSDate not supplied

Open-Source Science-led Development of the Atmosphere Observing System (AOS) Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David Giles↗
NASA NTRSDate not supplied

Open-Source Science-led Development of the AOS Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David M. Giles↗
NASA NTRS2023

Using Satellite-Based Terrestrial Water Storage Data: A Review

Land water storage plays a key role for the Earth’s climate, natural ecosystems, and human activities. Since the launch of the first Gravity Recovery and Climate Experiment (GRACE) mission in 2002, spaceborne observations of changes in terrestrial water storage (TWS) have provided a unique, global perspective on natural and human-induced changes in freshwater resources. Even though they have become much used within the broader Earth system science community, space-based TWS datasets still incorporate important and case-specific limitations which may not always be clear to users not familiar with the underlying processing algorithms. Here, we provide an accessible and illustrated overview of the measurement concept, of the main available data products, and of some frequently encountered technical terms and concepts. We summarize concrete recommendations on how to use TWS data in combination with other hydrological or climatological datasets, and guidance on how to avoid possible pitfalls. Finally, we provide an overview of some of the main applications of GRACE TWS data in the fields of hydrology and climate science. This review is written with the intention of supporting future research and facilitating the use of satellite-based terrestrial water storage datasets in interdisciplinary contexts.

Terrestrial water storage↗