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NASA NTRS2016

Comparative Analysis of NOAA REFM and SNB3GEO Tools for the Forecast of the Fluxes of High-Energy Electrons at GEO

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field B(sub z) observations at L1. The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast.

Balikhin, M. A.↗

NASA NTRS2021

Comparative Analysis of the 2020 November 29 Solar Energetic Particle Event Observed by Parker Solar Probe

We analyze two specific features of the intense solar energetic particle (SEP) event observed by Parker Solar Probe (PSP) between 2020 November 29 and 2020 December 2. The interplanetary counterpart of the coronal mass ejection (CME) on 2020 November 29 that generated the SEP event (hereafter ICME-2) arrived at PSP (located at 0.8 au from the Sun) on 2020 December 1. ICME-225 was preceded by the passage of an interplanetary shock at 18:35 UT on 2020 November 30 (hereafter26S2), that in turn was preceded by another ICME (i.e., ICME-1) observed in situ on 2020 November 30. The two interesting features of this SEP event at PSP are: First, the presence of the intervening ICME-1 affected the evolution of the.8 MeV proton intensity time profiles resulting in the observation of inverted energy spectra throughout the passage of ICME-1. Second, the sheath region preceding ICME-2 was characterized by weak magnetic fields compared to those measured immediately after the passage of the shock S2 and during the passage of ICME-2. Comparison with prior SEP events measured at 1 au but with similar characteristics indicates that (1) low-energy particles accelerated by S2 were excluded from propagating throughout ICME-1, and (2) the low magnetic fields measured in the sheath of ICME-2 resulted from the properties of the upstream solar wind encountered by ICME-2 that was propagated into the sheath; whereas the high energetic particle energy density in the sheath did not play a dominant role in the formation of these low magnetic fields.

D Lario↗

NASA NTRSDate not supplied

Evaluating Diurnal Ozone Emissions: A Comparative Analysis of DSCOVR EPIC, PANDORA, and TOLNet Data for Space-Based Monitoring Assessment: A Case Study by ASDC

Stratospheric ozone occurs naturally in the upper atmosphere, forming a protective layer that shields us from the sun's harmful ultraviolet rays. Tropospheric ozone is not emitted directly into the air but is created by chemical reactions between nitrogen oxides (NOx) and volatile organic compounds (VOC). This reaction happens when pollutants emitted by cars, power plants, industrial boilers, refineries, chemical plants, and other sources chemically react in sunlight [1]. Therefore, increased levels of tropospheric ozone indicate the presence of pollutants in the air. While daily anthropogenic activity causes an increase of ground-level ozone, variation of stratospheric ozone changes happens much slower, so that variation of the total ozone column reflects the variation of the tropospheric column due to natural, e.g., wildfires and anthropogenic air pollution. Both total and tropospheric ozone column products are used in this study. The reflectance spectra measured by the Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) spacecraft are compared with a set of radiative transfer-derived lookup tables for the EPIC filter transmission functions and a wide range of ozone values to retrieve ozone with a maximum resolution of 18 km at the sub-satellite point [2]. EPIC provides total column ozone in level 2 and level 4 products and tropospheric column ozone in level 4 products. Both EPIC Ozone products [2] are available at the Atmospheric Science Data Center (ASDC) at NASA Langley Research Center [3, 4]. Pandora spectrometer instrument measures columnar amounts of trace gases in the atmosphere. These gases (O3, NO2, CH2O) absorb light from the sun at specific wavelengths in the ultraviolet-visible spectrum [5]. Using the theoretical solar spectrum as a reference, Pandora determines trace gas amounts using differential optical absorption spectroscopy (DOAS). Pandora ozone retrievals are available from the Pandonia Global Network [6]. Pandora data from North American major metropolitan areas, New York, NY, Washington DC, Los Angeles, CA, and Mexico City. Tropospheric Ozone Lidar Network (TOLNet) was established in 2012 to provide high spatiotemporal observations of tropospheric ozone to (1) better understand physical processes driving the ozone budget in various meteorological and environmental conditions and (2) validate the tropospheric ozone measurements of space-borne missions [7]. TOLNet data are available at ASDC [8]. While EPIC provides global coverage of ozone retrievals several times daily, temporal resolution may miss some features in daily ozone variations. Ground-based sensors such as Pandora spectrometers and TOLNet lidars provide better temporal resolution while missing continuous spatial coverage. The forthcoming ozone retrieval from the TEMPO mission [9] will provide better spatial and temporal coverage of air quality (including ozone) over North America. This study investigates whether EPIC ozone products can detect diurnal air quality variations and compare ozone temporal development with retrieval by ground-based instruments.

diurnal ozone emissions, DSCOVR EPIC, PANDORA, spa↗

NASA NTRS2023

Comparative Analysis of Empirical and Machine Learning Models for Chla Extraction Using Sentinel-2 and Landsat OLI Data: Opportunities, Limitations, and Challenges

Remote retrieval of near-surface chlorophyll-a (Chla) concentration in small inland waters is challenging due to substantial optical interferences of various water constituents and uncertainties in the atmospheric correction (AC) process. Although various algorithms have been developed to estimate Chla from moderate-resolution terrestrial missions (∼10–60 m), the production of both accurate distribution maps and time series of Chla has proven challenging, limiting the use of remote analyses for lake monitoring. Here, we develop a support vector regression (SVR) model, which uses satellite-derived remote-sensing reflectance spectra () from Sentinel-2 and Landsat-8 images as input for Chla retrieval in a representative eutrophic prairie lake, Buffalo Pound Lake (BPL), Saskatchewan, Canada. Validated against in situ Chla from seven ice-free seasons (N ∼ 200; 2014–2020), the SVR model outperformed both locally tuned, -fed empirical models (Normalized Difference Chlorophyll Index, 2- and 3-band, and OC3) and Mixture Density Networks (MDNs) by 15–65%, while exhibiting comparable performance to a locally trained MDN, with an error of ∼35%. Comparison of Chla retrieval models, AC processors (iCOR, ACOLITE), and radiometric products (Rayleigh-corrected, surface, and top-of-atmosphere reflectance) showed that the best Chla maps and optimal time series (up to 100 mg m−3) were produced using a coupled SVR-iCOR system.

algal blooms↗

NASA NTRS2002

Comparative Analysis of Radiometer Systems Using Non-Stationary Processes

Radiometers require periodic calibration to correct for instabilities in the receiver response. Various calibration techniques exist that minimize the effect of instabilities in the receivers. The optimal technique depends upon many parameters. Some parameters are constrained by the particular application and others can be chosen in the system design. For example, the measurement uncertainty may be reduced to the limits of the resolution of the measurement (sensitivity) if periodic absolute calibration can be performed with sufficient frequency. However if the period between calibrations is long, a reference-differencing technique, i.e. Dicke-type design, can yield better performance. The measurement uncertainty not only depends upon the detection scheme but also on the number of pixels between calibrations, the integration time per pixel, integration time per calibration reference measurement, calibration reference temperature, and the brightness temperature of what is being measured. The best scheme for reducing the measurement uncertainty also depends, in large part, on the stability of the receiver electronics. In this presentation a framework for evaluating calibration schemes for a wide range of system architectures is presented. Two methods for treating receiver non-stationarity are compared with radiometer measurements.

Racette, Paul↗

NASA NTRSDate not supplied