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NASA NTRSDate not supplied

Composition and Climate Impacts of Increasing Launches to Low Earth Orbit

We present simulations of an Earth system model in which launch vehicles inject gaseous and particulate combustion products into the stratosphere. We considered two plausible scenarios representative for the year 2050, one with 1000 launches per year and another with 10 times more, all of which assuming heavy lift (80 tons to low Earth orbit; LEO) launches using methane as a proxy for liquefied natural gas (LNG) fuel. An industry-standard plume flowfield model was used to predict emission of gaseous species including carbon monoxide, nitrogen oxides, and water vapor. Black carbon was introduced assuming vacuum emission equal 25% of equivalent kerosene engine. The gas emissions showed marginal or insignificant changes in atmospheric composition, while the black carbon emission was found to be the most influential component. Feedbacks involve tropopause and stratospheric warming, followed by a moistening of the stratosphere via tropospheric water vapor intrusions, together with a reduction in global albedo. The fact that LNG-fueled rockets could be a concern from aerosol emissions in our simulations, despite burning more efficiently than conventional fuels, underscores the need to better understand actual black carbon emissions from rocket engines in order to accurately predict the global impacts of launch vehicles on future climate.

Earth system model↗
NASA NTRS2011

Ares I-X Range Safety Analyses Overview

Ares I-X was the first test flight of NASA's Constellation Program's Ares I Crew Launch Vehicle designed to provide manned access to low Earth orbit. As a one-time test flight, the Air Force's 45th Space Wing required a series of Range Safety analysis data products to be developed for the specified launch date and mission trajectory prior to granting flight approval on the Eastern Range. The range safety data package is required to ensure that the public, launch area, and launch complex personnel and resources are provided with an acceptable level of safety and that all aspects of prelaunch and launch operations adhere to applicable public laws. The analysis data products, defined in the Air Force Space Command Manual 91-710, Volume 2, consisted of a nominal trajectory, three sigma trajectory envelopes, stage impact footprints, acoustic intensity contours, trajectory turn angles resulting from potential vehicle malfunctions (including flight software failures), characterization of potential debris, and debris impact footprints. These data products were developed under the auspices of the Constellation's Program Launch Constellation Range Safety Panel and its Range Safety Trajectory Working Group with the intent of beginning the framework for the operational vehicle data products and providing programmatic review and oversight. A multi-center NASA team in conjunction with the 45th Space Wing, collaborated within the Trajectory Working Group forum to define the data product development processes, performed the analyses necessary to generate the data products, and performed independent verification and validation of the data products. This paper outlines the Range Safety data requirements and provides an overview of the processes established to develop both the data products and the individual analyses used to develop the data products, and it summarizes the results of the analyses required for the Ares I-X launch.

Starr, Brett R.↗
NASA NTRS2011

Ares I-X Range Safety Flight Envelope Analysis

Ares I-X was the first test flight of NASA's Constellation Program's Ares I Crew Launch Vehicle designed to provide manned access to low Earth orbit. As a one-time test flight, the Air Force's 45th Space Wing required a series of Range Safety analysis data products to be developed for the specified launch date and mission trajectory prior to granting flight approval on the Eastern Range. The range safety data package is required to ensure that the public, launch area, and launch complex personnel and resources are provided with an acceptable level of safety and that all aspects of prelaunch and launch operations adhere to applicable public laws. The analysis data products, defined in the Air Force Space Command Manual 91-710, Volume 2, consisted of a nominal trajectory, three sigma trajectory envelopes, stage impact footprints, acoustic intensity contours, trajectory turn angles resulting from potential vehicle malfunctions (including flight software failures), characterization of potential debris, and debris impact footprints. These data products were developed under the auspices of the Constellation's Program Launch Constellation Range Safety Panel and its Range Safety Trajectory Working Group with the intent of beginning the framework for the operational vehicle data products and providing programmatic review and oversight. A multi-center NASA team in conjunction with the 45th Space Wing, collaborated within the Trajectory Working Group forum to define the data product development processes, performed the analyses necessary to generate the data products, and performed independent verification and validation of the data products. This paper outlines the Range Safety data requirements and provides an overview of the processes established to develop both the data products and the individual analyses used to develop the data products, and it summarizes the results of the analyses required for the Ares I-X launch.

Starr, Brett R.↗
NASA NTRS2016

Overview of the SMAP Applications and the SMAP Early Adopters Program - NASA's First Mission-Directed Outreach Effort

Satellite data provide global observations of many of the earths system processes and features. These data are valuable for developing scientific products that increase our understanding of how the earths systems are integrated. The water, energy and carbon cycle exchanges between the land and atmosphere are linked by soil moisture. NASAs Soil Moisture Active Passive (SMAP) mission provides soil moisture and freeze thaw measurements from space and allows scientists to link the water energy and carbon cycles. In order for SMAP data to be best integrated into decision support systems, the mission has engaged with the stakeholder community since 2009 and has attempted to scale the utility of the data to the thematic societal impacts of the satellite product applications. The SMAP Mission, which launched on January 31, 2015, has actively grown an Early Adopter (EA) community as part of its applications effort and worked with these EAs to demonstrate a scaled thematic impact of SMAP data product in societally relevant decision support applications. The SMAP mission provides global observations of the Earths surface soil moisture, providing high accuracy, resolution and continuous global coverage. Through the Early Adopters Program, the SMAP Applications Team will spend the next 2 years after launch documenting and evaluating the use of SMAP science products in applications related to weather forecasting, drought, agriculture productivity, floods, human health and national security.

SMAP↗
NASA NTRS2007

Overview of TRMM Data Products and Services

November 27, 2007 marks the l0th anniversary of the launch of the Tropical Rainfall Measuring Mission (TRMM) satellite. In anticipation of this anniversary, this paper will present an overview of the various TRMM data products currently available including the standard products, near real-time products, special products, and prototype products. It also will present an easy way to obtain these data. TRMM standard products have been publicly available since a few months after launch in November 1997. TRMM is currently on version 6 of the data product. Version 3 was the "at launch" version. The approval for each of these versions came through the Joint TRMM Science Team. Standard products are divided into 3 categories: single TRMM instrument, Visible Infrared Scanner (VIRS), TRMM Microwave Imager (TMI), and Precipitation Radar (PR); combined TRMM products (PR and TMI); finally TRMM and other satellites (combined, TMI, SSMI, AMSRE, AMSU). The single TRMM instrument products are processed through 4 levels: Level lA, science data packets processed into orbital files; Level 1B and lC, geolocated data at the instrument field of view; Level 2, geolocated, geophysical parameters at the instrument field of view; Level 3, time aggregated, gridded geophysical parameters. These products are available with 24 hours of production through an anonymous ftp account on trmmopen.gsfc.nasa.gov. The TRMM data system started to produce near real-time products at the end of 1999. They are currently available only through a controlled user account. However, approval to get access to this account can be obtained by sending a note to Erich.F.Stoclter@nasa.gov providing the reason for access and contact information including a valid email. TRMM is not restricting access but needs the information to determine the usefulness of near-real time data to the general science community including applications agencies. TRMM near real-time products are swath products up to Level 2 of processing. The oldest data in the swath is generally no older than 120 minutes when it becomes available to the community. The real-time products including a VIRS level lB, a TMI parameter reduced 1B, a TMI level 2 parameter reduced rain product, a PR level 2 surface rain product, and a PR level 2 rain product with 25 vertical levels. Currently, TRMM also produces a gridded 3 hour global merged product from several radiometers including AMSU and from radiometercalibrated IR data. The paper also describes several simple-format gridded text products available fiom the trmmopen.gsfc.nasa.gov anonymous fip server denoted as 3668 products. These products were produced to provide rain estimates from the three TRMM instruments in a universal format (ASCII) that requires very little data format knowledge. The paper goes on to describe prototype L1 radiometer products that apply an early intercalibration approach that provides a starting point to be used for Global Precipitation Measurement mission radiometer products. The paper also provides a brief overview of a precipitation features data product being produced using TRMM products including the Lighting Imaging Sensor (LIS) using an algorithm developed at the University of Utah and distributed by that organization. The paper concludes with some possible changes to products that are planned for the next reprocessing cycle and special services such as geographical subsetting available to the science community.

Stocker, Erich Franz↗
NASA NTRS2016

Soil Moisture Active Passive Mission L4_C Data Product Assessment (Version 2 Validated Release)

The SMAP satellite was successfully launched January 31st 2015, and began acquiring Earth observation data following in-orbit sensor calibration. Global data products derived from the SMAP L-band microwave measurements include Level 1 calibrated and geolocated radiometric brightness temperatures, Level 23 surface soil moisture and freezethaw geophysical retrievals mapped to a fixed Earth grid, and model enhanced Level 4 data products for surface to root zone soil moisture and terrestrial carbon (CO2) fluxes. The post-launch SMAP mission CalVal Phase had two primary objectives for each science product team: 1) calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the L1 science requirements. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product pertaining to the validated release. The L4_C validated product release effectively replaces an earlier L4_C beta-product release (Kimball et al. 2015). The validated release described in this report incorporates a longer data record and benefits from algorithm and CalVal refinements acquired during the SMAP post-launch CalVal intensive period. The SMAP L4_C algorithms utilize a terrestrial carbon flux model informed by SMAP soil moisture inputs along with optical remote sensing (e.g. MODIS) vegetation indices and other ancillary biophysical data to estimate global daily net ecosystem CO2 exchange (NEE) and component carbon fluxes for vegetation gross primary production (GPP) and ecosystem respiration (Reco). Other L4_C product elements include surface (10 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture and landscape freeze/thaw (FT) controls on GPP and respiration (Kimball et al. 2012). The L4_C product encapsulates SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and underlying FT and soil moisture constraints to these processes, 2) documenting primary connections between terrestrial water, energy and carbon cycles, and 3) improving understanding of terrestrial carbon sink activity in northern ecosystems. There are no L1 science requirements for the L4_C product; however self-imposed requirements have been established focusing on NEE as the primary product field for validation, and on demonstrating L4_C accuracy and success in meeting product science requirements (Jackson et al. 2012). The other L4_C product fields also have strong utility for carbon science applications; however, analysis of these other fields is considered secondary relative to primary validation activities focusing on NEE. The L4_C targeted accuracy requirements are to meet or exceed a mean unbiased accuracy (ubRMSE) for NEE of 1.6 g C/sq m/d or 30 g C/sq m/yr, emphasizing northern (45N) boreal and arctic ecosystems; this is similar to the estimated accuracy level of in situ tower eddy covariance measurement-based observations (Baldocchi 2008).

Cal/Val↗
NASA NTRS2001

MODIS Snow-Cover Products

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. These products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to the currently available operation products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set is generated for long-term climates studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the product. The snow product suite starts with a 500-m resolution swath snow-cover map which is gridded to the Integerized Sinusoidal Grid to produce daily and eight-day composite tile products. The sequence then proceeds to a climate-modeling grid product at 5-km spatial resolution, with both daily and eight-day composite products. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.

Hall, Dorothy K.↗
NASA NTRS2002

MODIS Snow-Cover Products

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. MODIS snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to or enhancement of the currently-available operational products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The MODIS snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at about 5.6-km spatial resolution, with both daily and 8-day composite products. Each pixel of the CMG contains fraction of snow cover from 40 - 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02 - 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented to show some early validation work.

Hall, Dorothy K.↗
NASA NTRS2014

Soil Moisture Data Assimilation in the NASA Land Information System for Local Modeling Applications and Improved Situational Awareness

As part of the NASA Soil Moisture Active Passive (SMAP) Early Adopter (EA) program, the NASA Shortterm Prediction Research and Transition (SPoRT) Center has implemented a data assimilation (DA) routine into the NASA Land Information System (LIS) for soil moisture retrievals from the European Space Agency's Soil Moisture Ocean Salinity (SMOS) satellite. The SMAP EA program promotes application‐driven research to provide a fundamental understanding of how SMAP data products will be used to improve decision‐making at operational agencies. SPoRT has partnered with select NOAA/NWS Weather Forecast Offices (WFOs) that use output from a real‐time regional configuration of LIS, without soil moisture DA, to initialize local numerical weather prediction (NWP) models and enhance situational awareness. Improvements to local NWP with the current LIS have been demonstrated; however, a better representation of the land surface through assimilation of SMOS (and eventually SMAP) retrievals is expected to lead to further model improvement, particularly during warm‐season months. SPoRT will collaborate with select WFOs to assess the impact of soil moisture DA on operational forecast situations. Assimilation of the legacy SMOS instrument data provides an opportunity to develop expertise in preparation for using SMAP data products shortly after the scheduled launch on 5 November 2014. SMOS contains a passive L‐band radiometer that is used to retrieve surface soil moisture at 35‐km resolution with an accuracy of 0.04 cu cm cm (exp -3). SMAP will feature a comparable passive L‐band instrument in conjunction with a 3‐km resolution active radar component of slightly degraded accuracy. A combined radar‐radiometer product will offer unprecedented global coverage of soil moisture at high spatial resolution (9 km) for hydrometeorological applications, balancing the resolution and accuracy of the active and passive instruments, respectively. The LIS software framework manages land surface model (LSM) simulations and includes an Ensemble Kalman Filter for conducting land surface DA. SPoRT has added a module to read, quality‐control and bias‐correct swaths of Level II SMOS soil moisture retrievals prior to assimilation within LIS. The impact of SMOS DA is being tested using the Noah LSM. Experiments are being conducted to examine the impacts of SMOS soil moisture DA on the resulting LISNoah fields and subsequent NWP simulations using the Weather Research and Forecasting (WRF) model initialized with LIS‐Noah output. LIS‐Noah soil moisture will be validated against in situ observations from Texas A&M's North American Soil Moisture Database to reveal the impact and possible improvement in soil moisture trends through DA. WRF model NWP case studies will test the impacts of DA on the simulated near‐surface and boundary‐layer environments, and precipitation during both quiescent and disturbed weather scenarios. Emphasis will be placed on cases with large analysis increments, especially due to contributions from regional irrigation patterns that are not represented by precipitation input in the baseline LIS‐Noah run. This poster presentation will describe the soil moisture DA methodology and highlight LIS‐Noah and WRF simulation results with and without assimilation.

Case, Jonathan L.↗
NASA NTRS2019

Approach for Propagating Radiometric Data Uncertainties Through NASA Ocean Color Algorithms

Spectroradiometric satellite observations of the ocean are commonly referred to as “ocean color” remote sensing. NASA has continuously collected, processed, and distributed ocean color datasets since the launch of the Sea-viewing Wide-field-of-view Sensor (SeaWiFS) in 1997. While numerous ocean color algorithms have been developed in the past two decades that derive geophysical data products from sensor-observed radiometry, few papers have clearly demonstrated how to estimate measurement uncertainty in derived data products. As the uptake of ocean color data products continues to grow with the launch of new and advanced sensors, it is critical that pixel-by-pixel data product uncertainties are estimated during routine data processing. Knowledge of uncertainties can be used when studying long-term climate records, or to assist in the development and performance appraisal of bio-optical algorithms. In this method paper we provide a comprehensive overview of how to formulate first-order first-moment (FOFM) calculus for propagating radiometric uncertainties through a selection of bio-optical models. We demonstrate FOFM uncertainty formulations for the following NASA ocean color data products: chlorophyll-a pigment concentration (Chl), the diffuse attenuation coefficient at 490 nm (K(sub d,490)), particulate organic carbon (POC), normalized fluorescent line height (nflh), and inherent optical properties (IOPs). Using a quality-controlled in situ hyperspectral remote sensing reflectance (R(sub rs,i)) dataset, we show how computationally inexpensive, yet algebraically complex, FOFM calculations may be evaluated for correctness using the more computationally expensive Monte Carlo approach. We compare bio-optical product uncertainties derived using our test R(sub rs) dataset assuming spectrally-flat, uncorrelated relative uncertainties of 1, 5, and 10%. We also consider spectrally dependent, uncorrelated relative uncertainties in R(sub rs). The importance of considering spectral covariances in R(sub rs), where practicable, in the FOFM methodology is highlighted with an example SeaWiFS image. We also present a brief case study of two POC algorithms to illustrate how FOFM formulations may be used to construct measurement uncertainty budgets for ecologically-relevant data products. Such knowledge, even if rudimentary, may provide useful information to end-users when selecting data products or when developing their own algorithms.

Bio-optics↗
NASA NTRS2016

Leadership Development Program Final Project

TOSC is NASA's prime contractor tasked to successfully assemble, test, and launch the EM1 spacecraft. TOSC success is highly dependent on design products from the other NASA Programs manufacturing and delivering the flight hardware; Space Launch System(SLS) and Multi-Purpose Crew Vehicle(MPCV). Design products directly feed into TOSC's: Procedures, Personnel training, Hardware assembly, Software development, Integrated vehicle test and checkout, Launch. TOSC senior management recognized a significant schedule risk as these products are still being developed by the other two (2) programs; SVE and ACE positions were created.

Design products required for Engineering↗
NASA NTRS1998

Catalogue of X-Ray Texture Data for Al-Cu-Li Alloy 1460, 2090, 2096 and 2195 Near-Net-Shape Extrusions, Sheet and Plate

The effect of crystallographic texture on the mechanical properties of near-net-shape extrusions is of major interest ff these products are to find application in launch vehicle or aircraft structures. The objective of this research was to produce a catalogue containing quantitative texture information for extruded product, sheet and plate. The material characterized was extracted from wide, integrally stiffened panels fabricated from the Al-Cu-Li alloys 1460, 2090, 2096 and 2195. The textural characteristics of sheet and plate products of the same alloys were determined for comparison purposes. The approach involved using X-ray diffraction to generate pole figures in combination with orientation distribution function analysis. The data were compiled as a function of location in the extruded cross-sections and the variation in the major deformation- and recrystallization-related texture components was identified.

Hales, Stephen J.↗
NASA NTRS2016

Investigation of Unsteady Pressure-Sensitive Paint (uPSP) and a Dynamic Loads Balance to Predict Launch Vehicle Buffet Environments

This NESC assessment examined the accuracy of estimating buffet loads on in-line launch vehicles without booster attachments using sparse unsteady pressure measurements. The buffet loads computed using sparse sensor data were compared with estimates derived using measurements with much higher spatial resolution. The current method for estimating launch vehicle buffet loads is through wind tunnel testing of models with approximately 400 unsteady pressure transducers. Even with this relatively large number of sensors, the coverage can be insufficient to provide reliable integrated unsteady loads on vehicles. In general, sparse sensor spacing requires the use of coherence-length-based corrections in the azimuthal and axial directions to integrate the unsteady pressures and obtain reasonable estimates of the buffet loads. Coherence corrections have been used to estimate buffet loads for a variety of launch vehicles with the assumption methodology results in reasonably conservative loads. For the Space Launch System (SLS), the first estimates of buffet loads exceeded the limits of the vehicle structure, so additional tests with higher sensor density were conducted to better define the buffet loads and possibly avoid expensive modifications to the vehicle design. Without the additional tests and improvements to the coherence-length analysis methods, there would have been significant impacts to the vehicle weight, cost, and schedule. If the load estimates turn out to be too low, there is significant risk of structural failure of the vehicle. This assessment used a combination of unsteady pressure-sensitive paint (uPSP), unsteady pressure transducers, and a dynamic force and moment balance to investigate the integration schemes used with limited unsteady pressure data by comparing them with direct integration of extremely dense fluctuating pressure measurements. An outfall of the assessment was to evaluate the potential of using the emerging uPSP technique in a production test environment for future launch vehicles. The results show that modifications to the current technique can improve the accuracy of buffet estimates. More importantly, the uPSP worked remarkably well and, with improvements to the frequency response, sensitivity, and productivity, will provide an enhanced method for measuring wind tunnel buffet forcing functions (BFFs).

Schuster, David M.↗
NASA NTRS2010

Modular Approach to Launch Vehicle Design Based on a Common Core Element

With a heavy lift launch vehicle as the centerpiece of our nation's next exploration architecture's infrastructure, the Advanced Concepts Office at NASA's Marshall Space Flight Center initiated a study to examine the utilization of elements derived from a heavy lift launch vehicle for other potential launch vehicle applications. The premise of this study is to take a vehicle concept, which has been optimized for Lunar Exploration, and utilize the core stage with other existing or near existing stages and boosters to determine lift capabilities for alternative missions. This approach not only yields a vehicle matrix with a wide array of capabilities, but also produces an evolutionary pathway to a vehicle family based on a minimum development and production cost approach to a launch vehicle system architecture, instead of a purely performance driven approach. The upper stages and solid rocket booster selected for this study were chosen to reflect a cross-section of: modified existing assets in the form of a modified Delta IV upper stage and Castor-type boosters; potential near term launch vehicle component designs including an Ares I upper stage and 5-segment boosters; and longer lead vehicle components such as a Shuttle External Tank diameter upper stage. The results of this approach to a modular launch system are given in this paper.

Creech, Dennis M.↗
NASA NTRS2009

Using Dome C for Moderate Resolution Imaging Spectroradiometer Calibration Stability and Consistency

Currently, there are two nearly identical moderate resolution imaging spectroradiometer (MODIS) instruments operated in space: one on the Terra spacecraft launched in December 1999 and another on the Aqua spacecraft launched in May 2002. MODIS has 36 spectral bands with wavelengths covering from visible (VIS) to long-wave infrared (LWIR). Since launch, M0DIS observations and data products have significantly enabled studies of changes in the Earth system of land, oceans, and atmosphere. In order to maintain its on-orbit calibration and data product quality, MODIS was built with a comprehensive set of on-board calibrators. MODIS reflective solar bands (RSB) are calibrated on-orbit by a system that consists of a solar diffuser (SD) and a solar diffuser stability monitor(SDSM) on a regular basis. Its thermal emissive bands (TEB) calibration is executed on a scan-by-scan basis using an on-board blackbody (BB). The MODIS Characterization Support Team (MCST) at NASA/GSFC has been responsible for supporting sensor calibration and characterization tasks from pre-launch to post launch. In this paper,we describe current MCST efforts and progress made to examine sensor stability and intercalibration consistency using observations over Dome Concordia, Antarctica. Results show that this site can provide useful calibration reference for Earth-observing sensors.

Xiong, Xiaoxiong↗
NASA NTRSDate not supplied

Senteniel-6 Radio Occultation Product Released by NASA GES DISC to Supplement Satellite Remote Sensing Datasets for PBL Study

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) curates hyperspectral atmospheric sounder remote sensing and numerical model reanalysis datasets which have been utilized in the Planetary Boundary Layer (PBL) research and applications. The hyperspectral sounder remote-sensing datasets include the Atmospheric Infrared Sounder (AIRS) on the Aqua satellite to the Cross-track Infrared Sounder (CrIS) on Suomi--National Polar- orbiting Partnership (NPP) and National Oceanic and Atmospheric Administration -20 (N NOAA-20)/ Joint Polar-orbiting Satellite System -1 (JPSS-1). The Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) global reanalysis product provides a data record commencing in 1980. The sounder remote sensing and reanalysis datasets include temperature, water vapor, and trace gas profile down to the PBL, and also have a derived PBL height as well. A nearly 10-year (June 2006 to December 2015) seasonal and annual PBL height climatology dataset from COSMIC Global Navigation Satellite System (GNSS) radio occultation (RO) measurement is also available from the GES DISC. In collaboration with Sentinel-6 Project, the GES DISC is implementing curation activities for GNSS RO products from the Sentinel-6A/Sentinel-6 Michael Freilich satellite launched on November 21, 2020. Sentinel-6A RO products provide refractivity, temperature, and humidity profile with finer vertical resolution, leveraging PBL research and application as a supplement to the hyperspectral sounder remote sensing and reanalysis products. The public release of Sentinel- 6A RO products is scheduled for mid-October of 2021. In this presentation, we will introduce all Senitnel-6A products and services, and demonstrate use cases studying the PBL by combining these products with other GES DISC archived data products.

Feng Ding↗
NASA NTRS2016

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗
NASA NTRS2024

JPSS-4 VIIRS Version 2 at-Launch Relative Spectral Response Characterization

The JPSS-4 VIIRS sensor, the last in a JPSS program that will eventually span some 25+ years of on-orbit data collection, has completed its pre-launch test program. The test program included measurements for characterizing the VIIRS relative spectral response (RSR) in support of the Sensor and Environmental Data Records that will be generated from JPSS-4 VIIRS on-orbit observations after launch. Subject matter experts of the Government Team’s VIIRS DAWG have analyzed the VIIRS spectral measurements and produced the VIIRS spectral characterization, in the form of band averaged and supporting detector level RSR for each VIIRS band. The characterization is based upon the analysis of independent SpMA dual monochromator (all bands) and GSFC GLAMR laser system (reflectance bands only) spectral measurements. The SpMA and GLAMR measurements for reflectance bands (DNBLGS and DNBMGS, I1-I3, M1-M11) were combined to produce a “fused” RSR. For emissive bands (I4, I5, M12-M16), the SpMA measurements provide the entire characterization. The effort has led to the VIIRS Version 2 RSR product, the official at-launch RSR characterization for the JPSS-4 VIIRS mission, which is currently slated to be the next launch (expected Fall 2027) of the JPSS program. As expected, the JPSS-4 RSR are a close match to those of JPSS-3 and JPSS-2 (NOAA-21) VIIRS, while showing some spectral position and shape differences with SNPP and JPSS-1 (NOAA-20) VIIRS. An assessment on compliance with spectral performance metrics finds that VIIRS bandaverage RSR are compliant on nearly all metrics, with only a single minor exception. The Version 2 RSR will be available under EAR99 restrictions to the science community on the restricted access NASA Sharepoint.

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