102 research outputs found

    Investigating an unusually large 28-day oscillation in mesospheric temperature over Antarctica using ground-based and satellite measurements

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    The Utah State University (USU) Advanced Mesospheric Temperature Mapper (AMTM) was deployed at the Amundsen‐Scott South Pole Station in 2010 to measure OH temperature at ~87 km as part of an international network to study the mesospheric dynamics over Antarctica. During the austral winter of 2014, an unusually large amplitude ~28‐day oscillation in mesospheric temperature was observed for ~100 days from the South Pole Station. This study investigates the characteristics and global structure of this exceptional planetary‐scale wave event utilizing ground‐based mesospheric OH temperature measurements from two Antarctic stations (South Pole and Rothera) together with satellite temperature measurements from the Microwave Limb Sounder (MLS) on the Aura satellite, and the Solar Occultation For Ice Experiment (SOFIE) on the Aeronomy of Ice in the Mesosphere (AIM) satellite. Our analyses have revealed that this large oscillation is a winter time, high latitude phenomenon, exhibiting a coherent zonal wave #1 structure below 80 km altitude. At higher altitudes, the wave was confined in longitude between 180‐360°E. The amplitude of this oscillation reached ~15 K at 85 km and it was observed to grow with altitude as it extended from the stratosphere into the lower thermosphere in the southern hemisphere. The satellite data further established the existence of this oscillation in the northern hemisphere during the boreal winter time. The main characteristics and global structure of this event as observed in temperature are consistent with the predicted 28‐day Rossby Wave (1,4) mode

    Version 1.3 AIM SOFIE Measured Methane (CH4): Validation and Seasonal Climatology

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    The V1.3 methane (CH4) measured by the Aeronomy of Ice in the Mesosphere (AIM) Solar Occultation for Ice Experiment (SOFIE) instrument is validated in the vertical range of ~25–70 km. The random error for SOFIE CH4 is ~0.1–1% up to ~50 km and degrades to ~9% at ∼ 70 km. The systematic error remains at ~4% throughout the stratosphere and lower mesosphere. Comparisons with CH4 data taken by the SCISAT Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) and the Envisat Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) show an agreement within ~15% in the altitude range ~30–60 km. Below ~25 km SOFIE CH4 is systematically higher (≥20%), while above ~65 km it is lower by a similar percentage. The sign change from the positive to negative bias occurs between ~55 km and ~60 km (or ~40 km and ~45 km) in the Northern (or Southern) Hemisphere. Methane, H2O, and 2CH4 + H2O yearly differences from their values in 2009 are examined using SOFIE and MIPAS CH4 and the Aura Microwave Limb Sounder (MLS) measured H2O. It is concluded that 2CH4 + H2O is conserved with altitude up to an upper limit between ~35 km and ~50 km depending on the season. In summer this altitude is higher. In the Northern Hemisphere the difference relative to 2009 is the largest in late spring and the established difference prevails throughout summer and fall, suggesting that summer and fall are dynamically quiet. In both hemispheres during winter there are disturbances (with a period of ~1 month) that travel downward throughout the stratosphere with a speed similar to the winter descent. ©2016. American Geophysical Union

    NRLMSIS 2.1: An Empirical Model of Nitric Oxide Incorporated Into MSIS

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    We have developed an empirical model of nitric oxide (NO) number density at altitudes from similar to 73 km to the exobase, as a function of altitude, latitude, day of year, solar zenith angle, solar activity, and geomagnetic activity. The model is part of the NRLMSIS (R) 2.1 empirical model of atmospheric temperature and species densities; this upgrade to NRLMSIS 2.0 consists solely of the addition of NO. MSIS 2.1 assimilates observations from six space-based instruments: UARS/HALOE, SNOE, Envisat/MIPAS, ACE/FTS, Odin/SMR, and AIM/SOFIE. We additionally evaluated the new model against independent extant NO data sets. In this paper, we describe the formulation and fitting of the model, examine biases between the data sets and model and among the data sets, compare with another empirical NO model (NOEM), and discuss scientific aspects of our analysis

    NRLMSIS 2.1: An Empirical Model of Nitric Oxide Incorporated Into MSIS

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    We have developed an empirical model of nitric oxide (NO) number density at altitudes from ∼73 km to the exobase, as a function of altitude, latitude, day of year, solar zenith angle, solar activity, and geomagnetic activity. The model is part of the NRLMSIS® 2.1 empirical model of atmospheric temperature and species densities; this upgrade to NRLMSIS 2.0 consists solely of the addition of NO. MSIS 2.1 assimilates observations from six space-based instruments: UARS/HALOE, SNOE, Envisat/MIPAS, ACE/FTS, Odin/SMR, and AIM/SOFIE. We additionally evaluated the new model against independent extant NO data sets. In this paper, we describe the formulation and fitting of the model, examine biases between the data sets and model and among the data sets, compare with another empirical NO model (NOEM), and discuss scientific aspects of our analysis

    Magnesium isotopes of the bulk solar wind from Genesis diamond‐like carbon films

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    NASA's Genesis Mission returned solar wind (SW) to the Earth for analysis to derive the composition of the solar photosphere from solar material. SW analyses control the precision of the derived solar compositions, but their ultimate accuracy is limited by the theoretical or empirical models of fractionation due to SW formation. Mg isotopes are “ground truth” for these models since, except for CAIs, planetary materials have a uniform Mg isotopic composition (within ≤1‰) so any significant isotopic fractionation of SW Mg is primarily that of SW formation and subsequent acceleration through the corona. This study analyzed Mg isotopes in a bulk SW diamond‐like carbon (DLC) film on silicon collector returned by the Genesis Mission. A novel data reduction technique was required to account for variable ion yield and instrumental mass fractionation (IMF) in the DLC. The resulting SW Mg fractionation relative to the DSM‐3 laboratory standard was (−14.4‰, −30.2‰) ± (4.1‰, 5.5‰), where the uncertainty is 2ơ SE of the data combined with a 2.5‰ (total) error in the IMF determination. Two of the SW fractionation models considered generally agreed with our data. Their possible ramifications are discussed for O isotopes based on the CAI nebular composition of McKeegan et al. (2011)

    NRLMSIS 2.0: A Whole-Atmosphere Empirical Model of Temperature and Neutral Species Densities

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    NRLMSIS® 2.0 is an empirical atmospheric model that extends from the ground to the exobase and describes the average observed behavior of temperature, eight species densities, and mass density via a parametric analytic formulation. The model inputs are location, day of year, time of day, solar activity, and geomagnetic activity. NRLMSIS 2.0 is a major, reformulated upgrade of the previous version, NRLMSISE-00. The model now couples thermospheric species densities to the entire column, via an effective mass profile that transitions each species from the fully mixed region below ~70 km altitude to the diffusively separated region above ~200 km. Other changes include the extension of atomic oxygen down to 50 km and the use of geopotential height as the internal vertical coordinate. We assimilated extensive new lower and middle atmosphere temperature, O, and H data, along with global average thermospheric mass density derived from satellite orbits, and we validated the model against independent samples of these data. In the mesosphere and below, residual biases and standard deviations are considerably lower than NRLMSISE-00. The new model is warmer in the upper troposphere and cooler in the stratosphere and mesosphere. In the thermosphere, N2 and O densities are lower in NRLMSIS 2.0; otherwise, the NRLMSISE-00 thermosphere is largely retained. Future advances in thermospheric specification will likely require new in situ mass spectrometer measurements, new techniques for species density measurement between 100 and 200 km, and the reconciliation of systematic biases among thermospheric temperature and composition data sets, including biases attributable to long-term changes

    NRLMSIS 2.0: A Whole-Atmosphere Empirical Model of Temperature and Neutral Species Densities

    Get PDF
    NRLMSIS® 2.0 is an empirical atmospheric model that extends from the ground to the exobase and describes the average observed behavior of temperature, eight species densities, and mass density via a parametric analytic formulation. The model inputs are location, day of year, time of day, solar activity, and geomagnetic activity. NRLMSIS 2.0 is a major, reformulated upgrade of the previous version, NRLMSISE-00. The model now couples thermospheric species densities to the entire column, via an effective mass profile that transitions each species from the fully mixed region below ~70 km altitude to the diffusively separated region above ~200 km. Other changes include the extension of atomic oxygen down to 50 km and the use of geopotential height as the internal vertical coordinate. We assimilated extensive new lower and middle atmosphere temperature, O, and H data, along with global average thermospheric mass density derived from satellite orbits, and we validated the model against independent samples of these data. In the mesosphere and below, residual biases and standard deviations are considerably lower than NRLMSISE-00. The new model is warmer in the upper troposphere and cooler in the stratosphere and mesosphere. In the thermosphere, N2 and O densities are lower in NRLMSIS 2.0; otherwise, the NRLMSISE-00 thermosphere is largely retained. Future advances in thermospheric specification will likely require new in situ mass spectrometer measurements, new techniques for species density measurement between 100 and 200 km, and the reconciliation of systematic biases among thermospheric temperature and composition data sets, including biases attributable to long-term changes
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