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At least 109 records · Page 6

Accessing Suomi NPP OMPS Products through the GES DISC Online Data Services

This presentation will provide an overview of the OMPS products available at the GES DISC archive, as well as demonstrate the various data services provided by the GES DISC. Since the TOMS, SBUV, and EOS Aura (OMI, MLS, HIRDLS) data products are also available from the GES DISC archive, these can be easily accessed and compared with the OMPS data.

OMPS↗

Suomi-NPP VIIRS Day-Night Band On-Orbit Calibration and Performance

The Suomi national polar-orbiting partnership Visible Infrared Imaging Radiometer Suite (VIIRS) instrument has successfully operated since its launch in October 2011. The VIIRS day-night band (DNB) is a panchromatic channel covering wavelengths from 0.5 to 0.9 microns that is capable of observing Earth scenes during both daytime and nighttime at a spatial resolution of 750 m. To cover the large dynamic range, the DNB operates at low-, middle-, and high-gain stages, and it uses an on-board solar diffuser (SD) for its low-gain stage calibration. The SD observations also provide a means to compute the gain ratios of low-to-middle and middle-to-high gain stages. This paper describes the DNB on-orbit calibration methodology used by the VIIRS characterization support team in supporting the NASA Earth science community with consistent VIIRS sensor data records made available by the land science investigator-led processing systems. It provides an assessment and update of the DNB on-orbit performance, including the SD degradation in the DNB spectral range, detector gain and gain ratio trending, and stray-light contamination and its correction. Also presented in this paper are performance validations based on Earth scenes and lunar observations, and comparisons to the calibration methodology used by the operational interface data processing segment.

Chen, Hongda↗

Lessons Learned in the Flight Qualification of the S-NPP and NOAA-20 Solar Array Mechanisms

Deployable solar arrays are the energy source used on almost all Earth orbiting spacecraft and their release and deployment are mission-critical; fully testing them on the ground is a challenging endeavor. The 8 meter long deployable arrays flown on two sequential NASA weather satellites were each comprised of three rigid panels almost 2 meters wide. These large panels were deployed by hinges comprised of stacked constant force springs, eddy current dampers, and were restrained through launch by a set of four releasable hold-downs using shape memory alloy release devices. The ground qualification testing of such unwieldy deployable solar arrays, whose design was optimized for orbital operations, proved to be quite challenging and provides numerous lessons learned. A paperwork review and follow-up inspection after hardware storage determined that there were negative torque margins and missing lubricant, this paper will explain how these unexpected issues were overcome. The paper will also provide details on how the hinge subassemblies, the fully-assembled array, and mechanical ground support equipment were subsequently improved and qualified for a follow-on flight with considerably less difficulty. The solar arrays built by Ball Aerospace Corp. for the Suomi National Polar Partnership (SNPP) satellite and the Joint Polar Satellite System (JPSS-1) satellite (now NOAA-20) were both successfully deployed on-obit and are performing well.

Sexton, Adam↗

Suomi NPP VIIRS Solar Diffuser Screen Transmittance Model and Its Applications

The visible infrared imaging radiometer suite on the Suomi National Polar-orbiting Partnership satellite calibrates its reflective solar bands through observations of a sunlit solar diffuser (SD) panel. Sunlight passes through a perforated plate, referred to as the SD screen, before reaching the SD. It is critical to know whether the SD screen transmittance measured prelaunch is accurate. Several factors such as misalignments of the SD panel and the measurement apparatus could lead to errors in the measured transmittance and thus adversely impact on-orbit calibration quality through the SD. We develop a mathematical model to describe the transmittance as a function of the angles that incident light makes with the SD screen, and apply the model to fit the prelaunch measured transmittance. The results reveal that the model does not reproduce the measured transmittance unless the size of the apertures in the SD screen is quite different from the design value. We attribute the difference to the orientation alignment errors for the SD panel and the measurement apparatus. We model the alignment errors and apply our transmittance model to fit the prelaunch transmittance to retrieve the "true" transmittance. To use this model correctly, we also examine the finite source size effect on the transmittance. Furthermore, we compare the product of the retrieved "true" transmittance and the prelaunch SD bidirectional reflectance distribution function (BRDF) value to the value derived from on-orbit data to determine whether the prelaunch SD BRDF value is relatively accurate. The model is significant in that it can evaluate whether the SD screen transmittance measured prelaunch is accurate and help retrieve the true transmittance from the transmittance with measurement errors, consequently resulting in a more accurate sensor data product by the same amount.

sensors↗

Detecting Nighttime Fire Combustion Phase by Hybrid Application of Visible and Infrared Radiation from Suomi NPP VIIRS

An accurate estimation of biomass burning emissions is 1 partially limited by the lack of knowledge of fire burning phase (smoldering vs. flaming). In recent years, several fire detection products have been developed to provide information of fire radiative power (FRP), location, size, and temperature of fire pixels, but no information regarding fire burning phase is retrieved. The Day-Night band (DNB) aboard Visible Infrared Imaging Radiometer Suite (VIIRS) is sensitive to visible light from flaming fires in nighttime scenes. In contrast, VIIRS 4 m moderate resolution band #13 (M13), though capable of detecting fires at all phases, has no direct sensitivity for discerning fire phase. However, the hybrid usage of VIIRS DNB and M-bands data is hampered by their different scanning technology and spatial resolution. In this study, we present a novel method to rapidly and accurately resample DNB pixel radiances to the footprint of M-band pixels, accounting for onboard detector aggregation schemes and bowtie effect removals. The visible energy fraction (VEF) is subsequently introduced as an indicator of fire burning phase VEF is calculated as the ratio of visible light power (VLP) to FRP for each fire pixel retrieved from the VIIRS 750 m active fire product. A global distribution of VEF values, and thereby the fire phase, is quantitatively obtained, showing smaller VEF values in regions with mostly smoldering wildfires, such as peatland fires in Indonesia, larger VEF values in regions with flaming wildfires over grasslands and savannas in the sub-Sahelian region, and the largest VEF values associated with gas flaring in the Middle East. Mean VEF for different land cover types or regions is highly correlated with modified combustion efficiency (MCE). These results, together with a case study of the 2018 California Camp Fire, show that the VEF has the potential to be an indicator of fire combustion phase for each fire pixel, appropriate for estimating emission factors at the satellite pixel level.

Jun Wang↗

Climate Data Record Derived from Hyperspectral Sounders on AQUA, S-NPP and NOAA 20

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 provides accurate data climate data fusion products from multiple satellite sensors. It eliminates or reduces the errors due to inconsistent L2 algorithms. 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.

climate data record↗

Observation of a Cold Air Outbreak using CrIS on S-NPP and its Comparison with MERRA-2 and ERA-5

A cold air outbreak (CAO) is an extreme weather phenomenon that has significant social and economic impacts over a large region of the midlatitudes. However, the dynamical mechanism governing the occurrence and evolution of CAO events, particularly the role of the stratosphere, is not well understood. Through an analysis of one extreme CAO episode that occurred on 27-31 January 2019 across much of the US Midwest, this presentation examines the thermodynamic structure and impact of stratospheric downward transport using single-field-view (SFOV) satellite products (with a spatial resolution of ~14 km at nadir) from the Cross-track Infrared Sounder (CrIS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite in conjunction with MERRA-2 and ERA5 reanalysis products. The results show that along the path of cold air transport, particularly near the coldest surface center, there exists a large enhancement of O 3 , deep tropopause folding, and significant downward transport of stratospheric dry air, and a warm center above the tropopause that can be observed directly using the brightness temperature (BT) observations from CrIS stratospheric sounding channels. This study provides some observational evidences from CrIS that confirm the impact of stratosphere on CAO through downward transport, and demonstrates the value of the SFOV retrieval products for CAO dynamic transport study and model evaluation.

Xiaozhen Xiong↗

Decade-Long Ozone Profile Record from Suomi NPP OMPS Limb Profiler: Assessment of Version 2.6 Data

We evaluate a decadal ozone profile record derived from the Suomi National Polar-orbiting Partnership (SNPP) Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) satellite instrument. In 2023, the OMPS LP data were re-processed with the new version 2.6 retrieval algorithm that combines measurements from the ultraviolet (UV) and visible (VIS) parts of the spectra and employs the second order Tikhonov regularization to retrieve a single vertical ozone profile between 12.5 km (or cloud tops) and 57.5 km with the vertical resolution of about 1.9 - 2.5 km between 20-55 km. The algorithm uses radiances measured at six UV ozone-sensitive wavelengths (295, 302, 306, 312, 317 and 322 nm) paired with 353 nm, and one VIS wavelength at 606 nm combined with 510 nm and 675 nm to form a triplet. Each wavelength pair or triplet is used over a limited range of tangent altitudes where the sensitivity to ozone changes are strongest. A new implemented aerosol correction scheme is based on a gamma-function particle size distribution. Numerous calibration changes that affected ozone retrievals were also applied to measured LP radiances, including updates in altitude registration, radiometric calibration, stray light, and spectral registration. The key version 2.6 improvement is the reduction in relative drifts between LP ozone and correlative measurements, linked previously to a drift in the version 2.5 LP altitude registration. We compare LP ozone profiles with those from Aura Microwave Limb Sensor (MLS) to quantify ozone changes in version 2.6.

Limb scattering↗

Sensitivity of Spruce/Moss Boreal Forest Net Ecosystem Productivity to Seasonal Anomalies in Weather

Abstract. A process-oriented, daily time step model of a spruce/moss boreal ecosystem simulated 1994 and 1995 productivity for a Boreal Ecosystem-Atmosphere Study site near Thompson, Manitoba. Simulated black spruce net primary productivity (NPP) was 139 g C m(exp -2) in 1994 and 112 in 1995; feathermoss NPP was 13.0 g C m(exp -2) in 1994 and 9.7 in 1995; decomposition was 126 g C m(exp -2) in 1994 and 130 in 1995; net ecosystem productivity (NEP) was an uptake of 26.3 g C m(exp -2)in 1994 and 2.5 in 1995. A very dry period for the first half of the 1995 summer was the major cause of that year's lower productivity. Sensitivity simulations explored the impact of 2-month long warmer, cooler, wetter, and drier spells on ecosystem productivity. Warmer summers decreased spruce NPP, moss NPP, and NEP; cooler summers had the opposite effect. Earlier snowmelt (due to either warmer spring temperatures or reduced winter precipitation) increased moss and spruce NPP; later snowmelt had the opposite effect. The largest effect on decomposition was a 5% reduction due to a drier summer. One-month droughts (April through October) were also imposed on 1975 base year weather. Early summer droughts reduced moss annual NPP by -30-40%; summer droughts reduced spruce annual NPP by 10%; late summer droughts increased moss NPP by about 20% due to reduced respiration; May to September monthly droughts reduced heterotrophic respiration by about 10%. Variability in NEP was up to roughly +/- 35%. Finally, 1975 growing season precipitation was redistributed into frequent, small rainstorms and infrequent, large rainstorms. These changes had no effect on spruce NPP. Frequent rainstorms increased decomposition by a few percent, moss NPP by 50%, and NEP by 20%. Infrequent rainstorms decreased decomposition by 5%, moss NPP by 50% and NEP by 15%. The impact of anomalous weather patterns on productivity of this ecosystem depended on their timing during the year. Multiyear data sets are necessary to understand this behavior and test these types of models.

Frolking, Steve↗

Vertical Structure in Phytoplankton Growth and Productivity Inferred From Biogeochemical-Argo Floats and the Carbon-Based Productivity Model

Estimates of marine net primary production (NPP) commonly rely on limited in situ 14C incubations or satellite-based algorithms mainly constrained to the surface ocean. Here we combine data from biogeochemical Argo floats with a carbon-based productivity model (CbPM) to compute vertically-resolved estimates of NPP. Inferred NPP profiles derived by informing the CbPM with float-based, depth-resolved, bio-optical data are able to qualitatively reproduce the vertical structure in NPP inferred from in situ 14C incubations at various ocean regions. At station ALOHA, float-based estimates agree within uncertainty with productivity observations at depth, but underestimate surface NPP. We test the ability of the CbPM to infer the depth-resolved structure in NPP from bio-optical properties in the mixed layer, in similar fashion as how remote sensing algorithms of ocean productivity operate. In Southern Ocean waters, the depth-reconstructing implementation of the CbPM overestimates phytoplankton division rates and Chl:C below the mixed layer, resulting in artificially high subsurface NPP when compared with the fully float-informed implementation of the model. The CbPM subsurface extrapolation of phytoplankton Chl, Chl:C division rates, and NPP improves by accounting for deep nutrient (iron) stress impacts on photoacclimation in the Southern Ocean. This improvement is also observed in vertically- integrated NPP, where the mean bias between model implementations in depth-integrated productivity south of 30◦S is reduced by 62 % when account for deep iron limitation. Our results demonstrate that profiling data from biogeochemical Argo floats can serve to inform regional adjustments that lead to the improvement of marine productivity algorithms.

NPP↗

Observations of Ocean Primary Productivity Using MODIS

Measuring the magnitude and variability of oceanic net primary productivity (NPP) represents a key advancement toward our understanding of the dynamics of marine ecosystems and the role of the ocean in the global carbon cycle. MODIS observations make two new contributions in addition to continuing the bio-optical time series begun with Orbview-2's SeaWiFS sensor. First, MODIS provides weekly estimates of global ocean net primary productivity on weekly and annual time periods, and annual empirical estimates of carbon export production. Second, MODIS provides additional insight into the spatial and temporal variations in photosynthetic efficiency through the direct measurements of solar-stimulated chlorophyll fluorescence. The two different weekly productivity indexes (first developed by Behrenfeld & Falkowski and by Yoder, Ryan and Howard) are used to derive daily productivity as a function of chlorophyll biomass, incident daily surface irradiance, temperature, euphotic depth, and mixed layer depth. Comparisons between these two estimates using both SeaWiFS and MODIS data show significant model differences in spatial distribution after allowance for the different integration depths. Both estimates are strongly dependence on the accuracy of the chlorophyll determination. In addition, an empirical approach is taken on annual scales to estimate global NPP and export production. Estimates of solar stimulated fluorescence efficiency from chlorophyll have been shown to be inversely related to photosynthetic efficiency by Abbott and co-workers. MODIS provides the first global estimates of oceanic chlorophyll fluorescence, providing an important proof of concept. MODIS observations are revealing spatial patterns of fluorescence efficiency which show expected variations with phytoplankton photo-physiological parameters as measured during in-situ surveys. This has opened the way for research into utilizing this information to improve our understanding of oceanic NPP variability. Deriving the ocean bio-optical properties places severe demands on instrument performance (especially band to band precision) and atmospheric correction. Improvements in MODIS instrument characterization and calibration over the first 16 mission months have greatly improved the accuracy of the chlorophyll input fields and FLH, and therefore the estimates of NPP and fluorescence efficiency. Annual estimates now show the oceanic NPP accounts for 40-50% of the global total NPP, with significant interannual variations related to large scale ocean processes. Spatial variations in ocean NPP, and exported production, have significant effects on exchange of CO2 between the ocean and atmosphere. Further work is underway to improve both the primary productivity model functions, and to refine our understanding of the relationships between fluorescence efficiency and NPP estimates. We expect that the MODIS instruments will prove extremely useful in assessing the time dependencies of oceanic carbon uptake and effects of iron enrichment, within the global carbon cycle.

Esaias, Wayne E.↗

The NPOESS Preparatory Project Science Data Segment: Brief Overview

The NPOESS Preparatory Project (NPP) provides remotely-sensed land, ocean, atmospheric, ozone, and sounder data that will serve the meteorological and global climate change scientific communities while also providing risk reduction for the National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government s future low-Earth orbiting satellite system monitoring global weather and environmental conditions. NPOESS and NPP are a new era, not only because the sensors will provide unprecedented quality and volume of data but also because it is a joint mission of three federal agencies, NASA, NOAA, and DoD. NASA's primary science role in NPP is to independently assess the quality of the NPP science and environmental data records. Such assessment is critical for making NPOESS products the best that they can be for operational use and ultimately for climate studies. The Science Data Segment (SDS) supports science assessment by assuring the timely provision of NPP data to NASA s science teams organized by climate measurement themes. The SDS breaks down into nine major elements, an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. This paper will describe how the NPP SDS will leverage on NASA experience to provide a mission-reliable research capability for science assessment of NPP derived measurements.

Schweiss, Robert J.↗

Reductions in Productivity Due to Land Degradation in the Drylands of the Southwestern United States

Dryland degradation has long been recognized at regional, national, and global scales, yet there are no objective assessments of its location and severity. An assessment of reductions in net primary production (NPP) due to dryland degradation in the southwestern United States is reported. The local NPP scaling (LNS) approach was applied to map the extent and magnitude of degradation. LNS seeks to identify reference sites in which there is no degradation that can be used as a standard for comparison with other sites that share the same environment, except for degradation. Twelve years were analyzed (2000–2011), using Normalized Difference Vegetation Index (NDVI) data (250 m) from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite‐borne multispectral sensor. The results indicated that the total NPP reductions in the study area were about 35.9 ± 4.7 Tg C/yr, which equates to 0.31 ± 0.04 Mg C/ha·y. The NPP reductions in grassland‐savanna and livestock grazing areas were large and mostly consistent between years in spite of large variations in overall NPP caused by differences in land‐use, interannual variations in rainfall, and other aspects of weather. In comparison with other cover types, forested land generally had higher NPP reduction per unit area. The maps also enable attribution of degradation from the finest management units to entire agencies, such as the Bureau of Land Management, which had 50% less production per unit area than the U.S. Forest Service. The degradation within Native American land was low with total NPP reduction of about 2.41 ± 0.24 Tg C/yr and unit area reduction of productivity of just 0.21 ± 0.02 Mg C/ha·yr, yet the percent reduction from potential was in equivalence with other land management agencies.

Noojipady, Praveen↗

Early Assessment of VIIRS On-Orbit Calibration and Support Activities

The Suomi National Polar-orbiting Partnership (S-NPP) satellite, formally the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP), provides a bridge between current and future low-Earth orbiting weather and environmental observation satellite systems. The NASA s NPP VIIRS Characterization Support Team (VCST) is designed to assess the long term geometric and radiometric performance of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard the S-NPP spacecraft and to support NPP Science Team Principal Investigators (PI) for their independent evaluation of VIIRS Environmental Data Records (EDRs). This paper provides an overview of Suomi NPP VIIRS on-orbit calibration activities and examples of sensor initial on-orbit performance. It focuses on the radiometric calibration support activities and capabilities provided by the NASA VCST.

Xiong, Xiaoxiong↗

Net Primary Production of Terrestrial Ecosystems from 2000 to 2009

The CASA (Carnegie-Ames-Stanford) ecosystem model has been used to estimate monthly carbon fluxes in terrestrial ecosystems from 2000 to 2009, with global data inputs from NASA's Terra Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation cover mapping. Net primary production (NPP) flux for atmospheric carbon dioxide has varied slightly from year-to-year, but was predicted to have increased over short multi-year periods in the regions of the high-latitude Northern Hemisphere, South Asia, Central Africa, and the western Amazon since the year 2000. These CASA results for global NPP were found to be in contrast to other recently published modeling trends for terrestrial NPP with high sensitivity to regional drying patterns. Nonetheless, periodic declines in regional NPP were predicted by CASA for the southern and western Untied States, the southern Amazon, and southern and eastern Africa. NPP in tropical forest zones was examined in greater detail to discover lower annual production values than previously reported in many global models across the tropical rainforest zones, likely due to the enhanced detection of lower production ecosystems replacing primary rainforest.

Terrestiral ecosystems↗