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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Towards the Development of Real-Time Normalized Burn Ratio (NBR) and Delta NBR Imagery from GOES-16/17 and S-NPP

Burned landscapes present difficult hydrologic forecasting challenges for National Weather Service Offices. Burned soils and landscapes can be conducive to the development of flash flooding and landslides from heavy precipitation events. The severity of the burn scar can be directly related to the risk for debris flows and flash flooding. Burned Area Reflectance Classification (BARC) map is generated to indicate the degree of burn severity, which is generated initially by high-resolution satellite imagery from sources such as Landsat, and later by labor-intensive efforts conducted at the burn scar by Burned Area Emergency Response (BAER) teams. The challenge for operational meteorologists is that these sources of information are not readily available in near real-time. Landsat imagery, for example, may only be available about once every eight days, and cloudy conditions can obstruct the observation of the burn scar during a single pass. BAER teams cannot conduct assessments until the wildfire has been at least 40 percent contained (up to 80 percent in some regions), and the process itself can take further days to weeks to complete depending on a number of factors. To help remedy this lapse in knowledge, NASA SPoRT has developed the generation of NBR imagery in the Advanced Weather Interactive Processing System (AWIPS) using data from the operational GOES 16 and 17 satellites and S-NPP. This presentation will discuss the development of the GOES- and SNPP-derived NBR and dNBR imagery and their initial evaluation by real-time decision makers.

Berndt, Emily↗
NASA NTRS2019

Ozone Vertical Profile Satellite Measurements by S-NPP OMPS, Aura MLS, and Sentinel-5P TROPOMI

NASA has been monitoring ozone variations from space since 1970 with the launch of the Backscatter Ultraviolet instrument (BUV) on Nimbus- 4. Ozone in the Earth’s stratosphere and troposphere plays a crucial role in protecting life from harmful solar UV radiation, and it also influences Earth’s climate. The vertical distribution of ozone is used in modeling forecasts, verifying model analysis and simulations, and improving the measurement of tropospheric ozone that is a toxic constituent of air pollution. The Microwave Limb Sounder (MLS) on the EOS Aura spacecraft has been monitoring long-term continuous stratosphere ozone vertical behaviors since 2004. The Ozone Mapper Profile Suite (OMPS) on the Suomi National Polar-orbiting Partnership (S-NPP) was launched in 2011. Two of its three instruments, the Limb Profiler (LP) and the Nadir Profiler (NP), are designed to map ozone profiles with full global coverage (~6 days for NP) and a high level of vertical accuracy (1-km reporting record for LP) in the stratosphere and upper troposphere. The TROPOspheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel-5 Precursor (S5P), launched in 2017, aims to retrieve ozone profiles in both the troposphere and up to top-of-atmosphere (TOA) by using UV radiation measurements in a spectral range of 270-320 nm. S5P/TROPOMI ozone profile products are planned to become available in April 2020. This presentation will concentrate on satellite ozone vertical profile data collections from OMPS and MLS which are archived at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). TROPOMI ozone vertical profiles for the troposphere and to top-of-atmosphere will become available at NASA GES DISC in 2020. The presentation briefly explores their potential complementary usability in determining three-dimensional ozone global distributions with high temporal and spatial resolutions.

Zeng, Jian↗
NASA NTRS2019

The Inter-Calibration of the DSCOVR EPIC Imager 2 with Aqua-MODIS and NPP-VIIRS

The Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) continuously observes the illuminated disk from the Lagrange-1 point. The EPIC sensor was designed to monitor the diurnal variation of ozone, clouds, aerosols, and vegetation, especially those features that benefit from observation near-backscatter conditions. The EPIC sensor does not contain any onboard calibration systems. This study describes the inter-calibration of EPIC channels 5 (0.44 μm), 6 (0.55 μm), 7 (0.68 μm), and 10 (0.78 μm) with respect to Aqua-MODIS and NPP-VIIRS. The calibration is transferred using coincident ray-matched reflectance pairs over all-sky tropical ocean (ATO) and deep convective cloud (DCC) targets. A robust and automated image-alignment technique based on feature matching was formulated to improve the navigation quality of the EPIC images. The EPIC V02 dataset exhibits improved navigation over V01. Because the visible channels display similar spatial features, a single visible channel can be used to co-register the remaining visible bands. The VIIRS-referenced EPIC ATO and DCC ray-matched calibration coefficients are within 0.3%. The EPIC four-year calibration trends based on VIIRS are within 0.15%/year. The MODIS-based EPIC calibration coefficients were compared against the Geogdzhayev and Marshak 2018 published calibration coefficients and are found to be within 1.6%.

DSCOVR↗
NASA NTRSDate not supplied

PRELIMINARY JPSS-3 VIIRS POLARIZATION SENSITIVITY AND COMPARISON WITH S-NPP, JPSS-1 AND -2

The Visible-Infrared Imaging Radiometer Suite (VIIRS) was first launched on-board the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft in October of 2011. There have been three subsequent builds of the VIIRS sensor for the Joint Polar Satellite System (JPSS) program with JPSS-1, -2 and -3 having launch dates of November 2017, March 2022 and 2026 respectively. There is also a JPSS-4 VIIRS, that is in hardware integration during 2020, with a launch date of 2031. VIIRS has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). Ocean Color/Chlorophyll (OCC) products use calibrated Science Data Records (SDRs) for bands M1-M7(0.412-0.865μm) to compute their ocean chemistry products. These bands require accurate polarization sensitivity characterization to compensate for polarized upwelling Rayleigh scatter and produce accurate OCC Environment Data Products (EDRs). VIIRS polarization sensitivity requirement failures have driven hardware modifications to the bandpass filters and dichroic beam splitter over the program. This paper will discuss the preliminary JPSS-3 polarization results and how these hardware modifications, as the JPSS program progresses, have affected the sensor performance. Comparisons of the polarization sensitivities between sensor builds will be discussed along with the hardware modifications that contributed to their differences.

VIIRS↗
NASA NTRSDate not supplied

Preliminary JPSS-3 VIIRS Polarization Sensitivity and Comparison with S-NPP, JPSS-1 and -2

The Visible-Infrared Imaging Radiometer Suite (VIIRS) was first launched on-board the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft in October of 2011. There have been three subsequent builds of the VIIRS sensor for the Joint Polar Satellite System (JPSS) program with JPSS-1, -2 and -3 having launch dates of November 2017, March 2022 and 2026 respectively. There is also a JPSS-4 VIIRS, that is in hardware integration during 2020, with a launch date of 2031. VIIRS has 22 bands: 7 thermal emissive bands (TEBs), 14 reflective solar bands (RSBs) and a Day Night Band (DNB). Ocean Color/Chlorophyll (OCC) products use calibrated Science Data Records (SDRs) for bands M1-M7 (0.412-0.865μm) to compute their ocean chemistry products. These bands require accurate polarization sensitivity characterization to compensate for polarized upwelling Rayleigh scatter and produce accurate OCC Environment Data Products (EDRs). VIIRS polarization sensitivity requirement failures have driven hardware modifications to the bandpass filters and dichroic beam splitter over the program. This paper will discuss the preliminary JPSS-3 polarization results and how these hardware modifications, as the JPSS program progresses, have affected the sensor performance. Comparisons of the polarization sensitivities between sensor builds will be discussed along with the hardware modifications that contributed to their differences.

VIIRS↗
NASA NTRSDate not supplied

A New, Efficient, and Consistent Method for Generating Climate Data Record from Operational Hyperspectral Sounder Instruments on AQUA, S-NPP and NOAA 20

Operational IR sounders such AIRS on NASA Aqua, CrIS on S-NPP and on NOAA 20 satellites provide high quality hyperspectral measurements for weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It can provide fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

Xu Liu↗
NASA NTRSDate not supplied

Ten Year Ozone Profile Record From Suomi NPP OMPS Limb Profiler

In this study, we evaluate a decadal ozone profile record derived from Suomi NPP Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP). The data from OMPS LP were re-processed with the new retrieval algorithm from 2012 to present. The new reprocessing includes adjustments in both Level 1 and Level 2 algorithms. The sensor’s altitude registration, updates in radiometric calibrations, under-sampling and stray light corrections were addressed in Level 1 processing. The new retrieval algorithm (version 2.7) combines measurements from UV and VIS parts of the spectra to retrieve a single vertical ozone profile between 12.5 km (or cloud tops) and 57.5 km, unlike to previous version 2.5 where ozone profiles were retrieved independently from UV and VIS. To improve ozone retrievals in the Upper Troposphere Lower Stratosphere (UTLS) region, we implemented a new aerosol correction that assumes a gamma-function particle size distribution. In addition, ozone and nitrogen dioxide cross sections and climatologies were updated. We discuss sensitivity of the ozone retrievals to implemented changes in Level 1 and Level 2 algorithms. We focus our analysis on evaluation of the stability of the 10-year record from OMPS LP. We show results from the internal methods for characterizing the stability of the LP altitude registration and compare the LP reflectivity and ozone with the similar quantities measured by OMPS nadir sensors. Finally, we will show results from comparisons with independent satellite (MLS and SAGE III) and ozone sonde measurements.

Ozone↗
NASA NTRS2025

Validation of Formaldehyde Products From Three Satellite Retrievals (OMI SAO, OMPS-NPP SAO, and OMI BIRA) in the Marine Atmosphere With Four Seasons of Atom Aircraft Observations

Formaldehyde (HCHO) in the atmosphere is an intermediate product from the oxidation of methane and non-methane volatile organic compounds. In remote marine regions, HCHO variability is closely related to atmospheric oxidation capacity and modeled HCHO in these regions is usually added as a global satellite HCHO background. Thus, it is important to understand and validate the levels of satellite HCHO over the remote oceans. Here we intercompare three satellite retrievals of total HCHO columns (OMI-SAO (v004), OMPS-NPP SAO, and OMI BIRA) and validate them against in situ observations from the NASA Atmospheric Tomography Mission (ATom) mission. All retrievals are correlated with ATom integrated columns over remote oceans, with OMI SAO (v004) showing the best agreement. This is also reflected in the mean bias (MB) for OMI SAO (-0.73±0.87) x 10 15 molec cm -2 , OMPS SAO (-0.76±0.88) x 10 15 molec cm -2 , and OMI BIRA (-1.40±1.11) x 10 15 molec cm -2 . We recommend the OMI-SAO (v004) retrieval for remote ocean atmosphere studies. Three satellite HCHO retrievals and in situ ATom columns all generally captured the spatial and seasonal distributions of HCHO in the remote ocean atmosphere. Retrieval bias varies by latitude and season, but a persistent low bias is found in all products at high latitudes and the general low bias is most severe for the OMI BIRA product. Examination of retrieval components reveals slant column corrections have a larger impact on the retrievals over remote marine regions while AMFs play a smaller role. This study informs that the potential latitude-dependent biases in the retrievals require further investigation for improvement and should be considered when using marine HCHO satellite data, and vertical profiles from in situ instruments are crucial for validating satellite retrievals.

Atom↗
NASA NTRS2015

Extending the Deep Blue aerosol record from SeaWiFS and MODIS to NPP-VIIRS

Deep Blue expands AOD coverage to deserts and other bright surfaces. Using multiple similar satellite sensors enables us to obtain a long data record. The Deep Blue family consists of three separate aerosol optical depth (AOD) retrieval algorithms: 1. Bright Land: Surface reflectance database, BRDF correction. AOD retrieved separately at each of 412, 470/490, (650) nm. SSA retrieved for heavy dust events. 2. Dark Land: Spectral/directional surface reflectance relationship. AOD retrieved separately at 470/490 and 650 nm. 3. Water: Surface BRDF including glint, foam, underlight. Multispectral inversion (Not present in MODISdataset) All report the AOD at 550 nm, and Ångström exponent (AE).

SeaWiFS and MODIS↗
NASA NTRS2000

BOREAS TE-6 NPP For The Tower Flux, Carbon Evaluation, and Auxiliary Sites

The BOREAS TE-6 team collected several data sets to examine the influence of vegetation, climate, and their interactions on the major carbon fluxes for boreal forest species. This data set contains estimates of the biomass produced by the plant species at the TF, CEV, and AUX sites in the SSA and NSA for a given year. Temporally, the data cover the years of 1985 to 1995. The plant biomass production (i.e., aboveground, belowground, understory, litterfall), spatial coverage, and temporal nature of measurements varied between the TF, CEV, and AUX sites as deemed necessary by BOREAS principal investigators. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distrobuted Activity Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2010

New Water Disinfection Technology for Earth and Space Applications as Part of the NPP Fellowship Research

There is the need for a safe, low energy consuming and compact water disinfection technology to maintain water quality for human consumption. The design of the reactor should present no overheating and a constant temperature, with good electrical and optical performance for a UV water treatment system. The study assessed the use of UVA-LEDs to disinfectant water for MS2 Bacteriophage. The log reduction was sufficient to meet US EPA standards as a secondary disinfectant for maintaining water quality control. The study also explored possible inactivation of Pseudomonas aeruginosa and E. coli.

SilvestryRodriquez, Nadia↗
NASA NTRS2011

A Maximum Likelihood Approach to Determine Sensor Radiometric Response Coefficients for NPP VIIRS Reflective Solar Bands

Optical sensors aboard Earth orbiting satellites such as the next generation Visible/Infrared Imager/Radiometer Suite (VIIRS) assume that the sensors radiometric response in the Reflective Solar Bands (RSB) is described by a quadratic polynomial, in relating the aperture spectral radiance to the sensor Digital Number (DN) readout. For VIIRS Flight Unit 1, the coefficients are to be determined before launch by an attenuation method, although the linear coefficient will be further determined on-orbit through observing the Solar Diffuser. In determining the quadratic polynomial coefficients by the attenuation method, a Maximum Likelihood approach is applied in carrying out the least-squares procedure. Crucial to the Maximum Likelihood least-squares procedure is the computation of the weight. The weight not only has a contribution from the noise of the sensor s digital count, with an important contribution from digitization error, but also is affected heavily by the mathematical expression used to predict the value of the dependent variable, because both the independent and the dependent variables contain random noise. In addition, model errors have a major impact on the uncertainties of the coefficients. The Maximum Likelihood approach demonstrates the inadequacy of the attenuation method model with a quadratic polynomial for the retrieved spectral radiance. We show that using the inadequate model dramatically increases the uncertainties of the coefficients. We compute the coefficient values and their uncertainties, considering both measurement and model errors.

Lei, Ning↗
NASA NTRS2011

Pre-Launch Evaluation of the NPP VIIRS Land and Cryosphere EDRs to Meet NASA's Science Requirements

This paper summarizes the NASA Visible Infrared Imaging Radiometer Suite (VIIRS) Land Science team's findings to date with respect to the utility of the VIIRS Land and Cryosphere EDRs to meet NASA's science requirements. Based on previous assessments and results from a recent 51-day global test performed by the Land Product Evaluation and Analysis Tool Element (Land PEATE), the NASA VIIRS Land Science team has determined that, if all the Land and Cryosphere EDRs are to serve the needs of the science community, a number of changes to several products and the Interface Data Processing Segment (IDPS) algorithm processing chain will be needed. In addition, other products will also need to be added to the VIIRS Land product suite to provide continuity for all of the MODIS land data record. As the NASA research program explores new global change research areas, the VIIRS instrument should also provide the polar-orbiting imager data from which new algorithms could be developed, produced, and validated.

Roman, Miguel O.↗
NASA NTRS2012

Characterization of NPP Visible/Infrared Imager Radiometer Suite (VIIRS) Reflective Solar Bands Dual Gain Anomaly

The Visible/Infrared Imager Radiometer Suite (VIIRS) contains six dual gain bands in the reflective solar spectrum. The dual gain bands are designed to switch gain mode at pre-defined thresholds to achieve high resolution at low radiances while maintaining the required dynamic range for science. During pre-launch testing, an anomaly in the electronic response before transitioning from high to low gain was discovered and characterized. On-orbit, the anomaly was confirmed using MODIS data collected during Simultaneous Nadir Overpasses (SNOs). The analysis of the Earth scene data shows that dual gain anomaly can be determined at the orbital basis. To characterize the dual gain anomaly, the anomaly region and electronic offsets were tracked per week during the first 8 month of VIIRS operation. The temporal analysis shows the anomaly region can drift ~20 DN and is impacted by detectors DC Restore. The estimated anomaly flagging regions cover ~2.5 % of the high gain dynamic range and are consistent with prelaunch and on-orbit LUT. The prelaunch results had a smaller anomaly range (30-50 DN) and are likely the results of more stable electronics from the shorter data collection time. Finally, this study suggests future calibration efforts to focus on the anomaly's impact on science products and possible correction method to reduce uncertainties.

Lee, Shihyan↗