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At least 1,333 records · Page 74

Montana Water Resources II: Enhancing a Moisture Index for Drought and Flood Monitoring in the Missouri River Basin

The Missouri River Basin is a major global breadbasket, containing large amounts of agricultural land. Recent devastating weather events have motivated regional organizations to dedicate efforts to drought and flood monitoring and early warning systems. The DEVELOP team partnered with the following organizations: Montana Climate Office, NOAA National Weather Service (NWS) Missouri Basin River Forecast Center, NOAA Regional Climate Services of the Central Region, NOAA Physical Sciences Laboratory, and the US Army Corps of Engineers' Missouri River Basin Water Management Division. The team collaborated with the partners in their efforts to monitor flood and drought by enhancing a composite moisture index (CMI) for the Missouri River Basin. The CMI leverages NASA Earth observations to derive snow cover data from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) mission and snow water equivalent and snowdepth datasets from the NOAA NWS National Operational Hydrologic Remote Sensing Center’s Snow Data Assimilation System (SNODAS). Building upon this framework, the team added groundwater storage data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On missions, soil moisture data from Soil Moisture Active Passive (SMAP), and United States Geological Survey in situ streamflow data to the CMI. To test the tool’s validity, the team compared the CMI results to historically extreme dry and extreme wet years, March 2017 and March 2019, respectively. The CMI accurately reflects both 2017 and 2019 climate conditions in the Missouri River Basin. The refined CMI enhances the understanding of antecedent soil moisture conditions and improves flood and drought forecasting in the Missouri River Basin before the growing season.

Chloe Schneider↗

Constraining estimates of terrestrial carbon uptake: new opportunities using long‐term satellite observations and data assimilation

Summary The response of terrestrial carbon uptake to increasing atmospheric [ CO 2 ], that is the CO 2 fertilization effect ( CFE ), remains a key area of uncertainty in carbon cycle science. Here we provide a perspective on how satellite observations could be better used to understand and constrain CFE . We then highlight data assimilation ( DA ) as an effective way to reconcile different satellite datasets and systematically constrain carbon uptake trends in Earth System Models. As a proof‐of‐concept, we show that joint DA of multiple independent satellite datasets reduced model ensemble error by better constraining unobservable processes and variables, including those directly impacted by CFE . DA of multiple satellite datasets offers a powerful technique that could improve understanding of CFE and enable more accurate forecasts of terrestrial carbon uptake.

Smith, William K.↗

An object-oriented approach to the management of meteorological and hydrological data

An interface to several meteorological and hydrological databases have been developed that enables researchers efficiently to access and interrelate data through a customized menu system. By extending a relational database system with object-oriented concepts, each user or group of users may have different 'views' of the data to allow user access to data in customized ways without altering the organization of the database. An application to COHMEX and WetNet, two earth science projects within NASA Marshall Space Flight Center's Earth Science and Applications Division, are described.

Graves, S. J.↗

Information management challenges of the EOS Data and Information System

An overview of the current information management concepts that are embodied in the plans for the Earth Observing System Data and Information System (EOSDIS) is presented, and some of the technology development and application areas that are envisioned to be particularly challenging are introduced. The Information Management System (IMS) is the EOSDIS element that provides the primary interface between the science users and the data products and services of EOSDIS. The goals of IMS are to define a clear and complete set of functional requirements and to apply innovative methods and technologies to satisfy them. The information management functions are described in detail, and some applicable technolgies are discussed. Some of the general issues affecting the successful development and operation of the information management element are addressed.

Mcdonald, Kenneth R.↗

HIRIS - NASAS's High-Resolution Imaging Spectrometer for the Earth Observing System

Modern Earth science is beginning to examine interactions among the different terrestrial components at all temporal and spatial scales. Such a global perspective requires an integrated remote-sensing program, the Earth Observing System (EOS), which uses instruments throughout the electromagnetic spectrum to collect data about the Earth's surface, oceans and atmosphere over a range of selected scales. At the finest scales, we will require instruments capable of detailed sampling both spatially and spectrally. We have designed the High-Resoulution Imaging Spectrometer (HIRIS) to acquire simultaneous images in 192 spectral bands in the dominant wavelengths of the solar spectrum, 0.4 to 2.5 micrometers, at a spectral sampling interval of 10 nm. The ground instantaneous field of view (GIFOV) will be 30 m over a 24 km swath. A pointing capability will allow image acquisition up to +52 deg/-30 deg down track and +/-45 deg or more cross-track. Thus we will be able to study surface spectral bidirectional reflectance properties and variations in atmospheric attenuation with viewing angle. The cross-track pointing will also allow multiple viewing opportunities during one 16-day orbital revisit cycle, so that any part of the Earth may be imaged in a two-day period.

Dozier, J.↗

Spaceflight Operations Services Grid Prototype

NASA over the years has developed many types of technologies and conducted various types of science resulting in numerous variations of operations, data and applications. For example, operations range from deep space projects managed by JPL, Saturn and Shuttle operations managed from JSC and KSC, ISS science operations managed from MSFC and numerous low earth orbit satellites managed from GSFC that are varied and intrinsically different but require many of the same types of services to fulfill their missions. Also, large data sets (databases) of Shuttle flight data, solar system projects and earth observing data exist which because of their varied and sometimes outdated technologies are not and have not been fully examined for additional information and knowledge. Many of the applications/systems supporting operational services e.g. voice, video, telemetry and commanding, are outdated and obsolete. The vast amounts of data are located in various formats, at various locations and range over many years. The ability to conduct unified space operations, access disparate data sets and to develop systems and services that can provide operational services does not currently exist in any useful form. In addition, adding new services to existing operations is generally expensive and with the current budget constraints not feasible on any broad level of implementation. To understand these services a discussion of each one follows. The Spaceflight User-based Services are those services required to conduct space flight operations. Grid Services are those Grid services that will be used to overcome, through middleware software, some or all the problems that currently exists. In addition, Network Services will be discussed briefly. Network Services are crucial to any type of remedy and are evolving adequately to support any technology currently in development.

Bradford, Robert N.↗

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_FM1+FM2_Edition2)

The ERBE-like Monthly Geographical Averages (ES-4) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2002-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

NET FLUX↗

High Data Rates for AubieSat-2 A & B, Two CubeSats Performing High Energy Science in the Upper Atmosphere

This paper will discuss a proposed CubeSat size (3 Units / 6 Units) telemetry system concept being developed at Marshall Space Flight Center (MSFC) in cooperation with Auburn University. The telemetry system incorporates efficient, high-bandwidth communications by developing flight-ready, low-cost, PROTOFLIGHT software defined radio (SDR) payload for use on CubeSats. The current telemetry system is slightly larger in dimension of footprint than required to fit within a 0.75 Unit CubeSat volume. Extensible and modular communications for CubeSat technologies will provide high data rates for science experiments performed by two CubeSats flying in formation in Low Earth Orbit. The project is a collaboration between the University of Alabama in Huntsville and Auburn University to study high energy phenomena in the upper atmosphere. Higher bandwidth capacity will enable high-volume, low error-rate data transfer to and from the CubeSats, while also providing additional bandwidth and error correction margin to accommodate more complex encryption algorithms and higher user volume.

Sims, William H.↗

A Global Capacity Building Vision for Societal Applications of Earth Observing Systems and Data: Key Questions and Recommendations

Capacity building using Earth observing (EO) systems and data (i.e., from orbital and nonorbital platforms) to enable societal applications includes the network of human, nonhuman, technical, nontechnical, hardware, and software dimensions that are necessary to successfully cross the valley [of death; see NRC (2001)] between science and research (port of departure) and societal application (port of arrival). In many parts of the world (especially where ground-based measurements are scarce or insufficient), applications of EO data still struggle for longevity or continuity for a variety of reasons, foremost among them being the lack of resilient capacity. An organization is said to have resilient capacity when it can retain and continue to build capacity in the face of unexpected shocks or stresses. Stresses can include intermittent power and limited Internet bandwidth, constant need for education on ever-increasing complexity of EO systems and data, communication challenges between the ports of departure and arrival (especially across time zones), and financial limitations and instability. Shocks may also include extreme events such as disasters and losing key staff with technical and institutional knowledge.

shocks↗

Expanding NASA and Roscosmos Scientific Collaboration on the International Space Station

The International Space Station (ISS) is a world-class laboratory orbiting in space. NASA and Roscosmos have developed a strong relationship through the ISS Program Partnership, working together and with the other ISS Partners for more than twenty years. Since 2013, based on a framework agreement between the Program Managers, NASA and Roscosmos are building a joint program of collaborative research on ISS. This international collaboration is developed and implemented in phases. Initially, members of the ISS Program Science Forum from NASA and TsNIIMash (representing Roscosmos) identified the first set of NASA experiments that could be implemented in the "near term". The experiments represented the research categories of Technology Demonstration, Microbiology, and Education. Through these experiments, the teams from the "program" and "operations" communities learned to work together to identify collaboration opportunities, establish agreements, and jointly plan and execute the experiments. The first joint scientific activity on ISS occurred in January 2014, and implementation of these joint experiments continues through present ISS operations. NASA and TsNIIMash have proceeded to develop "medium term" collaborations, where scientists join together to improve already-proposed experiments. A major success is the joint One-Year Mission on ISS, with astronaut Scott Kelly and cosmonaut Mikhail Kornienko, who returned from ISS in March, 2016. The teams from the NASA Human Research Program and the RAS Institute for Biomedical Problems built on their considerable experience to design joint experiments, learn to work with each other's protocols and processes, and share medical and research data. New collaborations are being developed between American and Russian scientists in complex fluids, robotics, rodent research and space biology, and additional human research. Collaborations are also being developed in Earth Remote Sensing, where scientists will share data from imaging systems mounted on ISS as well as other orbiting spacecraft to improve our understanding of the Earth and its climate. NASA and Roscosmos continue to encourage international scientific cooperation and expanded use of the ISS Laboratory. "Long-term", larger collaborations will achieve scientific objectives that no single national science team or agency can achieve on its own. The joint accomplishments achieved so far have paved the way for a stronger international scientific community and improved results and benefits from ISS.

Hasbrook, Pete↗

CERES Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_TRMM-PFM-VIRS_Beta1)

The Monthly Gridded Radiative Fluxes and Clouds (FSW) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLOUD OVERLAP↗

Cost-Effective Telemetry and Command Ground Systems Automation Strategy for the Soil Moisture Active Passive (SMAP) Mission

Soil Moisture Active Passive (SMAP) is an Earth-orbiting, remote-sensing NASA mission slated for launch in 2014.[double dagger] The ground data system (GDS) being developed for SMAP is composed of many heterogeneous subsystems, ranging from those that support planning and sequencing to those used for real-time operations, and even further to those that enable science data exchange. A full end-to-end automation of the GDS may result in cost savings during mission operations, but it would require a significant upfront investment to develop such comprehensive automation. As demonstrated by the Jason-1 and Wide-field Infrared Survey Explorer (WISE) missions, a measure of "lights-out" automation for routine, orbital pass ground operations can still reduce mission cost through smaller staffing of operators and limited work hours. The challenge, then, for the SMAP GDS engineering team is to formulate an automated operations strategy--and corresponding system architecture--to minimize operator intervention during operations, while balancing the development cost associated with the scope and complexity of automation. This paper discusses the automated operations approach being developed for the SMAP GDS. The focus is on automating the activities involved in routine passes, which limits the scope to real-time operations. A key subsystem of the SMAP GDS--NASA's AMMOS Mission Data Processing and Control System (AMPCS)--provides a set of capabilities that enable such automation. Also discussed are the lights-out pass automations of the Jason-1 and WISE missions and how they informed the automation strategy for SMAP. The paper aims to provide insights into what is necessary in automating the GDS operations for Earth satellite missions.

remote-sensing↗

Perceived Costs and Benefits of ICON Science and Foundational Documents associated with “Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles"

This data package is associated with the publication "Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles" in Earth and Space Science (Goldman et al. 2022; https://doi.org/10.1029/2021EA002099). The manuscript is an introductory article for a special collection of commentary articles across 19 geoscience disciplines that explore the challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross-system transferability of science outcomes. This data package contains data, figures, and R scripts associated with the cost/benefit analysis presented in the manuscript. The writing teams involved in the special collection placed each letter of ICON on a plot with perceived cost on one axis and perceived benefit on the other to summarize their perceptions of pursuing each principle of ICON science. These data were subsequently quantified and analyzed. Files are saved as .csv, .R, and .pdf. This data package also contains (1) the public foundational and instructional documents that enabled the crowdsourced creation of the special collection; (2) file-level metadata (flmd) that lists each file in the data package with a description; (3) data dictionary (dd) that defines column headers that appear in csv files. Files are saved as .pdf and .csv.

54 ENVIRONMENTAL SCIENCES↗

A Simple, Scalable, Script-based Science Processor

The production of Earth Science data from orbiting spacecraft is an activity that takes place 24 hours a day, 7 days a week. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), this results in as many as 16,000 program executions each day, far too many to be run by human operators. In fact, when the Moderate Resolution Imaging Spectroradiometer (MODIS) was launched aboard the Terra spacecraft in 1999, the automated commercial system for running science processing was able to manage no more than 4,000 executions per day. Consequently, the GES DAAC developed a lightweight system based on the popular Per1 scripting language, named the Simple, Scalable, Script-based Science Processor (S4P). S4P automates science processing, allowing operators to focus on the rare problems occurring from anomalies in data or algorithms. S4P has been reused in several systems ranging from routine processing of MODIS data to data mining and is publicly available from NASA.

Lynnes, Christopher↗

ESS-DIVE Reporting Format for Location Metadata

The ESS-DIVE location metadata reporting format provides instructions and templates for reporting a minimum set of metadata for discrete point locations in geographic space represented by x, y, and z coordinates. This format was created based on a need for earth and environmental science researchers to more consistently provide metadata about locations where they conduct studies. To create the format, we incorporated elements from ESS-DIVE’s community reporting formats as well as 12 additional data standards or other data resources (e.g., databases, data systems, or repositories). In the template, we ask researchers to indicate unique locations using Location IDs and indicate hierarchies of locations through parent location IDs. We also provide additional optional fields for researchers to indicate how they measured the point location and the date and time that the location was first used as a research siteThis dataset contains support documentation for the reporting format (README.md and instructions.md), a terminology guide (guide.md), a crosswalk indicating how this reporting format relates to existing standards and data resources (Location_metadata_crosswalk.csv), a data dictionary (dd.csv), file-level metadata (flmd.csv), and the location metadata templates in both CSV (Location_metadata_template.csv) and Excel formats (Location_metadata_template.xlsx).

54 ENVIRONMENTAL SCIENCES↗

Contents of the JPL Distributed Active Archive Center (DAAC) archive, version 2-91

The Distributed Active Archive Center (DAAC) archive at the Jet Propulsion Laboratory (JPL) includes satellite data sets for the ocean sciences and global change research to facilitate multidisciplinary use of satellite ocean data. Parameters include sea surface height, surface wind vector, sea surface temperature, atmospheric liquid water, and surface pigment concentration. The Jet Propulsion Laboratory DAAC is an element of the Earth Observing System Data and Information System (EOSDIS) and will be the United States distribution site for the Ocean Topography Experiment (TOPEX)/POSEIDON data and metadata.

Smith, Elizabeth A.↗

The Tropical Rainfall Measuring Mission and the development of its observatory

The paper describes a cooperative program between NASA and NASDA, the Tropical Rainfall Measuring Mission (TRMM), which is an earth system science mission designed to study characteristics of the rainfall occurring over the tropics and subtropics. The salient features of the TRMM are described, with special attention given to the mission parameters, the instrument complement, the TRMM observatory, and the command and data handling subsystem. Also discussed are the TRMM requirement factors and the resulting approach to the TRMM observatory design.

Lavigna, Thomas A.↗