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NASA NTRSDate not supplied

CERES ERBE-like Instantaneous TOA Estimates (ES-8) in HDF (CER_ES8_Terra-FM2_Edition1-CV)

The ES-8 archival data product contains a 24-hour, single-satellite, instantaneous view of scanner fluxes at the top-of-atmosphere (TOA) reduced from spacecraft altitude unfiltered radiances using Earth Radiation Budget Experiment (ERBE) scanner Inversion algorithms and the ERBE shortwave (SW) and longwave (LW) Angular Distribution Models (ADMs). The ES-8 also includes the total (TOT), SW, LW, and window (WN) channel radiometric data; SW, LW, and WN unfiltered radiance values; and the ERBE scene identification for each measurement. These data are organized according to the CERES 3.3-second scan into 6.6-second records. As long as there is one valid scanner measurement within a record, the ES-8 record will be generated. The following CERES ES8 data sets are currently available: CER_ES8_TRMM-PFM_Edition1 CER_ES8_TRMM-PFM_Edition2 CER_ES8_TRMM-PFM_Transient-Ops2 CER_ES8_Terra-FM1_Edition1 CER_ES8_Terra-FM2_Edition1 CER_ES8_Terra-FM1_Edition2 CER_ES8_Terra-FM2_Edition2 CER_ES8_Aqua-FM3_Edition1 CER_ES8_Aqua-FM4_Edition1 CER_ES8_Aqua-FM3_Edition2 CER_ES8_Aqua-FM4_Edition2 CER_ES8_Aqua-FM3_Edition1-CV CER_ES8_Aqua-FM4_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2006-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

WINDOW UNFILTERED RADIANCE↗

NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Aqua-FM3_Edition1-CV)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2006-11-02] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

WINDOW DETECTOR OUTPUT↗

NASA NTRSDate not supplied

CERES ERBE-like Instantaneous TOA Estimates (ES-8) in HDF (CER_ES8_Aqua-FM3_Edition1-CV)

TOTAL FILTERED RADIANCE↗

NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Aqua-FM4_Edition1-CV)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2005-03-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

SHORTWAVE DETECTOR OUTPUT↗

NASA NTRSDate not supplied

CERES ERBE-like Instantaneous TOA Estimates (ES-8) in HDF (CER_ES8_Aqua-FM4_Edition1-CV)

The ES-8 archival data product contains a 24-hour, single-satellite, instantaneous view of scanner fluxes at the top-of-atmosphere (TOA) reduced from spacecraft altitude unfiltered radiances using Earth Radiation Budget Experiment (ERBE) scanner Inversion algorithms and the ERBE shortwave (SW) and longwave (LW) Angular Distribution Models (ADMs). The ES-8 also includes the total (TOT), SW, LW, and window (WN) channel radiometric data; SW, LW, and WN unfiltered radiance values; and the ERBE scene identification for each measurement. These data are organized according to the CERES 3.3-second scan into 6.6-second records. As long as there is one valid scanner measurement within a record, the ES-8 record will be generated. The following CERES ES8 data sets are currently available: CER_ES8_TRMM-PFM_Edition1 CER_ES8_TRMM-PFM_Edition2 CER_ES8_TRMM-PFM_Transient-Ops2 CER_ES8_Terra-FM1_Edition1 CER_ES8_Terra-FM2_Edition1 CER_ES8_Terra-FM1_Edition2 CER_ES8_Terra-FM2_Edition2 CER_ES8_Aqua-FM3_Edition1 CER_ES8_Aqua-FM4_Edition1 CER_ES8_Aqua-FM3_Edition2 CER_ES8_Aqua-FM4_Edition2 CER_ES8_Aqua-FM3_Edition1-CV CER_ES8_Aqua-FM4_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

TOA FLUX↗

DOE OSTI2024

Scintillation event imaging with a single photon avalanche diode camera

Position and time measurements of scintillation events encode information about the radiation source. Single photon avalanche diode (SPAD) arrays offer multiple-megapixel spatial resolution and tens of picoseconds temporal resolution for detecting single photons. Current lensless designs for measuring scintillation events use sensors that are lower in spatial resolution. Camera-based designs use sensors that are lower in temporal resolution or readout rate and cannot image individual interactions. Here we propose to image scintillation events in a thick, monolithic scintillator using a high-resolution SPAD camera. We demonstrate that a commercial SPAD camera is able to gather sufficient signal to image individual scintillation events and observe 3D shifts in their spatial distribution. Simulations show that a SPAD camera can localize individual scintillation events in 3D. We report direct imaging of gamma-ray interactions in a scintillator with a SPAD camera. The proposed design may allow to measure complex signatures of individual particles interacting in the scintillator.

47 OTHER INSTRUMENTATION↗

NASA NTRS2012

Mapping of CO2 at High Spatiotemporal Resolution using Satellite Observations: Global distributions from OCO-2

Satellite observations of CO2 offer new opportunities to improve our understanding of the global carbon cycle. Using such observations to infer global maps of atmospheric CO2 and their associated uncertainties can provide key information about the distribution and dynamic behavior of CO2, through comparison to atmospheric CO2 distributions predicted from biospheric, oceanic, or fossil fuel flux emissions estimates coupled with atmospheric transport models. Ideally, these maps should be at temporal resolutions that are short enough to represent and capture the synoptic dynamics of atmospheric CO2. This study presents a geostatistical method that accomplishes this goal. The method can extract information about the spatial covariance structure of the CO2 field from the available CO2 retrievals, yields full coverage (Level 3) maps at high spatial resolutions, and provides estimates of the uncertainties associated with these maps. The method does not require information about CO2 fluxes or atmospheric transport, such that the Level 3 maps are informed entirely by available retrievals. The approach is assessed by investigating its performance using synthetic OCO-2 data generated from the PCTM/ GEOS-4/CASA-GFED model, for time periods ranging from 1 to 16 days and a target spatial resolution of 1deg latitude x 1.25deg longitude. Results show that global CO2 fields from OCO-2 observations can be predicted well at surprisingly high temporal resolutions. Even one-day Level 3 maps reproduce the large-scale features of the atmospheric CO2 distribution, and yield realistic uncertainty bounds. Temporal resolutions of two to four days result in the best performance for a wide range of investigated scenarios, providing maps at an order of magnitude higher temporal resolution relative to the monthly or seasonal Level 3 maps typically reported in the literature.

Hammerling, Dorit M.↗

NASA NTRS2023

Optimizing the Resolution of Hydrodynamic Simulations for MCRaT Radiative Transfer Calculations

Despite their discovery about half a century ago, the Gamma-ray burst (GRB) prompt emission mechanism is still not well understood. Theoretical modeling of the prompt emission has advanced considerably due to new computational tools and techniques. One such tool is the PLUTO hydro dynamics code, which is used to numerically simulate GRB outflows. PLUTO uses Adaptive Mesh Refinement to focus computational efforts on the portion of the grid that contains the simulated jet. Another tool is the Monte Carlo Radiation Transfer (MCRaT) code, which predicts electromagnetic signatures of GRBs by conducting photon scatterings within a jet using PLUTO. The effects of the underlying resolution of a PLUTO simulation with respect to MCRaT post-processing radiative transfer results have not yet been quantified. We analyze an analytic spherical outflow and a hydrodynamically simulated GRB jet with MCRaT at varying spatial and temporal resolutions and quantify how decreasing both resolutions affect the resulting mock observations. We find that changing the spatial resolution changes the hydrodynamic properties of the jet, which directly affect the MCRaT mock observable peak energies. We also find that decreasing the temporal resolution artificially decreases the high energy slope of the mock observed spectrum, which increases both the spectral peak energy and the luminosity. We show that the effects are additive when both spatial and temporal resolutions are modified. Our results allow us to understand how decreased hydrodynamic temporal and spatial resolutions affect the results of post-processing radiative transfer calculations, allowing for the optimization of hydrodynamic simulations for radiative transfer codes.

Jose Arita-Escalante↗

NASA NTRS2018

An Overview of the TROPICS NASA Earth Venture Mission

The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA as part of the Earth Venture-Instrument (EVI-3) program. The overarching goal for TROPICS is to provide nearly all-weather observations of 3D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. TROPICS will provide rapid-refresh microwave measurements (median refresh rate better than 60 min for the baseline mission) which can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm life cycle. TROPICS comprises six Cube-Sats in three low-Earth orbital planes. Each CubeSat will host a high-performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapour profiles using three channels near the 183 GHz water vapour absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher-resolution water vapour channels), and a single channel near 205 GHz which is more sensitive to precipitation-sized ice particles. This observing system offers an unprecedented combination of horizontal and temporal resolution to measure environmental and inner-core conditions for tropical cyclones on a nearly global scale and is a major leap forward in the temporal resolution of several key parameters needed for assimilation into advanced data assimilation systems capable of utilizing rapid-update radiance or retrieval data.Launch readiness is currently projected for late 2019.

TROPICS↗

NASA NTRS2016

Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earths Radiation Budget

Satellites always sample the Earth-atmosphere system in a finite temporal resolution. This study investigates the effect of sampling frequency on the satellite-derived Earth radiation budget, with the Deep Space Climate Observatory (DSCOVR) as an example. The output from NASA's Goddard Earth Observing System Version 5 (GEOS-5) Nature Run is used as the truth. The Nature Run is a high spatial and temporal resolution atmospheric simulation spanning a two-year period. The effect of temporal resolution on potential DSCOVR observations is assessed by sampling the full Nature Run data with 1-h to 24-h frequencies. The uncertainty associated with a given sampling frequency is measured by computing means over daily, monthly, seasonal and annual intervals and determining the spread across different possible starting points. The skill with which a particular sampling frequency captures the structure of the full time series is measured using correlations and normalized errors. Results show that higher sampling frequency gives more information and less uncertainty in the derived radiation budget. A sampling frequency coarser than every 4 h results in significant error. Correlations between true and sampled time series also decrease more rapidly for a sampling frequency less than 4 h.

GEOS-5↗

DOE OSTI2026

Daily, 30 m Resolution NDSI Data for the East River Watershed, CO for 2000-2020

This dataset contains daily Normalized Difference Snow Index (NDSI) values at 30 m spatial resolution for the East River watershed in Colorado, USA. The temporal range of these data includes water years 2001-2020. These data were created using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). This model fuses low spatial and high temporal resolution data from MODIS (500 m, daily) with high spatial and low temporal resolution data from Landsat (30 m, 16 days) to create a 30m synthetic daily snow product. This product allows for the analysis of historical snow covered area trends in the East River Watershed at fine spatiotemporal resolutions where it was not available previously. This research was performed as a part of the Department of Energy’s Subsurface Biogeochemical Research Program with the primary intent of better understanding the timing and spatial patterns of water delivery to the Critical Zone in mountain watersheds. Each .zip file contains one "water year" of data (October 1 - September 30; i.e., water year 2010 starts October 1, 2010 and ends September 30, 2011). Each zip file contains the following: STARFM daily Normalized Difference Snow Index (NDSI) fusion data files in GeoTiff format with one layer for each day between Landsat data acquisition dates (i.e., for dates of Landsat acquisition, the Landsat image is included for that date). The study area is located in an area of Landsat path overlap, so Landsat dates acquisitions are every 7-9 days. Landsat NDSI files containing the high spatial (30m), low temporal (7-9 days due to Landsat path overlap) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Dates for which no Landsat data were obtained are included as NoData layers. MODIS NDSI files containing the high temporal (daily), low spatial (500m) resolution data used as input to STARFM in GeoTiff format with one layer for each day. Please note the MODIS data were resampled to 30m pixels for input into the STARFM model. The data have a scale factor of 10,000 and a no data value of -32767. The projection of all datasets is WGS 84 (EPSG: 4326), which has a latitude/longitude based degree resolution of 0.0002694946 X 0.0002694946, and approximates to the 30 m spatial resolution mentioned above. The Layer Index files in .csv format. They contain information for each layer in the above GeoTiff files regarding the corresponding date for each layer, the fraction of pixels in the image that contain valid data (missing data is due to either cloud cover or poor data quality; these values are not percent snow cover). Dates of Landsat overpass are indicated in these files. If no Landsat data were able to be obtained due to cloud cover or lack of Landsat Tier 1 data available on Google Earth Engine, this is also noted.

EARTH SCIENCE > CRYOSPHERE > SNOW/ICE↗

NASA NTRS2018

Overview of the NASA TROPICS CubeSat Constellation Mission

Recent technology advances in miniature microwave radiometers that can be hosted on very small satellites has made possible a new class of affordable constellation missions that provide very high revisit rates of tropical cyclones and other severe weather. The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA as part of the Earth Venture–Instrument (EVI-3) program and is now in development with planned launch readiness in late 2019. The overarching goal for TROPICS is to provide nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones (TCs). TROPICS will provide rapid-refresh microwave measurements (median refresh rate better than 60 minutes for the baseline mission) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. TROPICS will comprise a constellation of at least six CubeSats in three low-Earth orbital planes. Each CubeSat will host a high performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapor profiles using three channels near the 183 GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel at 205 GHz that is more sensitive to precipitation-sized ice particles and low-level moisture. This observing system offers an unprecedented combination of horizontal and temporal resolution in the microwave spectrum to measure environmental and inner-core conditions for TCs on a nearly global scale and is a major leap forward in the temporal resolution of several key parameters needed for assimilation into advanced data assimilation systems capable of utilizing rapid-update radiance or retrieval data. Here, we provide an overview of the mission and an update on current status, with a focus on unique characteristics of the Cubesat system, recent performance simulations on a range of observables to be provided by the constellation, and a summary of science applications.

Blackwell, W. J.↗

NASA NTRS2018

Overview of the NASA TROPICS CubeSat Constellation Mission

Recent technology advances in miniature microwave radiometers that can be hosted on very small satellites has made possible a new class of affordable constellation missions that provide very high revisit rates of tropical cyclones and other severe weather. The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA as part of the Earth Venture-Instrument (EVI-3)program and is now in development with planned launch readiness in late 2019. The overarching goal for TROPICS is to provide nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones (TCs). TROPICS will provide rapid-refresh microwave measurements (median refresh rate better than 60 minutes for the baseline mission) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm life cycle. TROPICS will comprise a constellation of at least six CubeSats in three low-Earth orbital planes. Each CubeSat will host a high performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz (gigahertz) oxygen absorption line, water vapor profiles using three channels near the 183 GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel at 205 GHz that is more sensitive to precipitation-sized ice particles and low-level moisture. This observing system offers an unprecedented combination of horizontal and temporal resolution in the microwave spectrum to measure environmental and inner-core conditions for TCs on a nearly global scale and is a major leap forward in the temporal resolution of several key parameters needed for assimilation into advanced data assimilation systems capable of utilizing rapid-update radiance or retrieval data. Here, we provide an overview of the mission and an update on current status,with a focus on unique characteristics of the Cubesat system, recent performance simulations on a range of observables to be provided by the constellation, and a summary of science applications.

Passive Microwave↗

NASA NTRS2021

A Robust Hybrid Deep Learning Model for Spatiotemporal Image Fusion

Dense time-series remote sensing data with detailed spatial information are highly desired for the monitoring of dynamic earth systems. Due to the sensor tradeoff, most remote sensing systems cannot provide images with both high spatial and temporal resolutions. Spatiotemporal image fusion models provide a feasible solution to generate such a type of satellite imagery, yet existing fusion methods are limited in predicting rapid and/or transient phenological changes. Additionally, a systematic approach to assessing and understanding how varying levels of temporal phenological changes affect fusion results is lacking in spatiotemporal fusion research. The objective of this study is to develop an innovative hybrid deep learning model that can effectively and robustly fuse the satellite imagery of various spatial and temporal resolutions. The proposed model integrates two types of network models: super-resolution convolutional neural network (SRCNN) and long short-term memory (LSTM). SRCNN can enhance the coarse images by restoring degraded spatial details, while LSTM can learn and extract the temporal changing patterns from the time-series images. To systematically assess the effects of varying levels of phenological changes, we identify image phenological transition dates and design three temporal phenological change scenarios representing rapid, moderate, and minimal phenological changes. The hybrid deep learning model, alongside three benchmark fusion models, is assessed in different scenarios of phenological changes. Results indicate the hybrid deep learning model yields significantly better results when rapid or moderate phenological changes are present. It holds great potential in generating high-quality time-series datasets of both high spatial and temporal resolutions, which can further benefit terrestrial system dynamic studies. The innovative approach to understanding phenological changes’ effect will help us better comprehend the strengths and weaknesses of current and future fusion models.

spatiotemporal fusion↗

NASA NTRS2012

A Distributive, Non-Destructive, Real-Time Approach to Snowpack Monitoring

This invention is designed to ascertain the snow water equivalence (SWE) of snowpacks with better spatial and temporal resolutions than present techniques. The approach is ground-based, as opposed to some techniques that are air-based. In addition, the approach is compact, non-destructive, and can be communicated with remotely, and thus can be deployed in areas not possible with current methods. Presently there are two principal ground-based techniques for obtaining SWE measurements. The first is manual snow core measurements of the snowpack. This approach is labor-intensive, destructive, and has poor temporal resolution. The second approach is to deploy a large (e.g., 3x3 m) snowpillow, which requires significant infrastructure, is potentially hazardous [uses a approximately equal to 200-gallon (approximately equal to 760-L) antifreeze-filled bladder], and requires deployment in a large, flat area. High deployment costs necessitate few installations, thus yielding poor spatial resolution of data. Both approaches have limited usefulness in complex and/or avalanche-prone terrains. This approach is compact, non-destructive to the snowpack, provides high temporal resolution data, and due to potential low cost, can be deployed with high spatial resolution. The invention consists of three primary components: a robust wireless network and computing platform designed for harsh climates, new SWE sensing strategies, and algorithms for smart sampling, data logging, and SWE computation.

Frolik, Jeff↗

NASA NTRS2026

Using Satellite Surface Temperature Data to Monitor Urban Heat Island

Exposure to heat is a growing concern nationwide. Temperatures can be elevated in cities compared to surrounding rural areas, referred to as an “urban heat island” (UHI) effect, which is intensified during heat waves. The lack of dense networks of air temperature measurements results in few studies on urban heat. Now, a vast amount of high spatial and temporal satellite data on land surface temperature is available. We identified satellite datasets with the longest surface temperature records but different spatial and temporal resolutions: Landsat (1985-current, biweekly at 60 m and 100 m spatial resolution) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites (2000-current, daily at 1 km spatial resolution). We investigated how satellites with different spatial and temporal resolutions detect UHI effects differently. We hypothesized that 1) a dataset’s spatial resolution impacts the precision of detected UHIs spatially, since high spatial resolution Landsat data better captures spatial variability in temperature, and 2) daily surface temperature data can detect temporal patterns of UHIs and heatwave frequencies. We analyzed Landsat and MODIS satellite data in the Washington, D.C. and Baltimore region. We found that Landsat describes higher spatial variability of the UHI effect than MODIS data. However, MODIS data shows more consistent seasonal surface temperature patterns than Landsat when compared to in situ air temperature measurements. MODIS data was also able to consistently measure the frequency of heat waves. This study demonstrates the value of NASA satellite data for urban heat and climate change studies.

landsat↗

DOE OSTI2025

Design and validation of a nanosecond short-wave infrared streak camera using gaseous detonation experiments

A custom short-wave infrared (SWIR) galvanometric streak camera was developed to provide nanosecond- scale, time-resolved optical diagnostics. The system was designed as a compact, mechanically driven alternative to traditional tube-based streak cameras, using a galvanometer mirror and multiple-reflection optical path to achieve high temporal resolution while maintaining electronic synchronization for trigger sequencing. Temporal resolution achieved 139.5 ns/px, allowing direct conversion of image-slope gradients to physical wave velocities. The instrument was validated using hydrogen-oxygen-argon detonations within a modular detonation tube, capturing transient emission structures and post-detonation decay behavior with microsecond precision. Although signal levels in filtered configurations were limited by lens transmission and detector sensitivity, the system successfully resolved intensity rise and decay characteristics across 10-60 % argon mixtures. The observed trends demonstrate the feasibility of compact galvanometer-based streak systems for high-speed SWIR imaging in reactive environments!

42 ENGINEERING↗

NASA NTRS2018

Concepts for Next Generation Grating Spectrometer Imaging Atmospheric Sounders from LEO and GEO

Spaceborne infrared atmospheric sounders measure the spectrum of the upwelling radiance in the infrared with ultra-high spectral resolution. The resolution is sufficient to measure absorption features of atmospheric constituents enabling retrieval of atmospheric temperature and water vapor profiles, surface emission and atmospheric constituents. The Atmospheric Infrared Sounder (AIRS) on Aqua launched in May of 2002 was the first hyperspectral infrared sounder designed for this purpose and is still operational today. AIRS has been followed by the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp A and B, and the Cross-track Infrared Sounder (CrIS) on Suomi NPP and JPSS. All instruments are operating well improving weather forecast and providing a wealth of information about the atmosphere. Additional CrIS and IASI instruments are expected to be launched providing data of this type into the late 2030’s. AIRS, CrIS and IASI are all Low Earth Orbit (LEO) instruments with nominal spatial resolutions of 14km. Future IR sounders must achieve higher spatial and temporal resolution to match improvements in forecast models and be less costly to match anticipated future budget pressures. Higher temporal resolution can be achieved in several ways including operation in Geostationary Earth Orbit (GEO) or in constellations of SmallSats and CubeSats. Higher spatial resolution can be achieved using larger format focal plane assemblies in the instruments and larger aperture telescopes. Grating spectrometers are well suited to large format FPAs by allowing a wide field of view in a compact package. Concepts for next generation grating spectrometer IR sounders that have been developed over the years at JPL are presented along with technology advancements made to enable these concepts to achieve their stated goals.

Pagano, Thomas S.↗