88 research outputs found
Quantitative relation between PMSE and ice mass density
Radar reflectivities associated with Polar Mesosphere Summer Echoes (PMSE)
are compared with measurements of ice mass density in the mesopause region.
The 54.5 MHz radar Moveable Atmospheric Radar for Antarctica (MARA), located
at the Wasa/Aboa station in Antarctica (73° S, 13° W) provided
PMSE measurements in December 2007 and January 2008. Ice mass density was
measured by the Solar Occultation for Ice Experiment (SOFIE). The radar
operated continuously during this period but only measurements close to local
midnight are used for comparison, to coincide with the local time of the
measurements of ice mass density. The radar location is at high geographic
latitude but low geomagnetic latitude (61°) and the measurements were
made during a period of very low solar activity. As a result, background
electron densities can be modelled based on solar illumination alone. We find
a close correlation between the time and height variations of radar
reflectivity and ice mass density, at all PMSE heights, from 80 km up to 95 km.
A quantitative expression relating radar reflectivities to ice mass
density is found, including an empirical dependence on background electron
density. Using this relation, we can use PMSE reflectivities as a proxy for
ice mass density, and estimate the daily variation of ice mass density from
the daily variation of PMSE reflectivities. According to this proxy, ice mass
density is maximum around 05:00–07:00 LT, with lower values around local noon, in
the afternoon and in the evening. This is consistent with the small number of
previously published measurements and model predictions of the daily
variation of noctilucent (mesospheric) clouds and in contrast to the daily
variation of PMSE, which has a broad daytime maximum, extending from 05:00 LT to
15:00 LT, and an evening-midnight minimum
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Persistence of upper stratospheric wintertime tracer variability into the Arctic spring and summer
Using data from the Aeronomy of Ice in the Mesosphere (AIM) and Aura
satellites, we have categorized the interannual variability of winter- and
springtime upper stratospheric methane (CH4). We further show the effects
of this variability on the chemistry of the upper stratosphere throughout the
following summer. Years with strong wintertime mesospheric descent followed
by dynamically quiet springs, such as 2009, lead to the lowest summertime
CH4. Years with relatively weak wintertime descent, but strong springtime
planetary wave activity, such as 2011, have the highest summertime CH4. By
sampling the Aura Microwave Limb Sounder (MLS) according to the occultation
pattern of the AIM Solar Occultation for Ice Experiment (SOFIE), we show that
summertime upper stratospheric chlorine monoxide (ClO) almost perfectly
anticorrelates with the CH4. This is consistent with the reaction of
atomic chlorine with CH4 to form the reservoir species, hydrochloric acid
(HCl). The summertime ClO for years with strong, uninterrupted mesospheric
descent is about 50 % greater than in years with strong horizontal
transport and mixing of high CH4 air from lower latitudes. Small, but
persistent effects on ozone are also seen such that between 1 and 2 hPa, ozone
is about 4–5 % higher in summer for the years with the highest CH4
relative to the lowest. This is consistent with the role of the chlorine
catalytic cycle on ozone. These dependencies may offer a means to monitor
dynamical effects on the high-latitude upper stratosphere using summertime
ClO measurements as a proxy. Additionally, these chlorine-controlled ozone decreases,
which are seen to maximize after years with strong uninterrupted wintertime
descent, represent a new mechanism by which mesospheric descent can affect
polar ozone. Finally, given that the effects on ozone appear to persist much
of the rest of the year, the consideration of winter/spring dynamical
variability may also be relevant in studies of ozone trends
Observations of aerosol by the HALOE Experiment onboard UARS: A preliminary validation
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94744/1/grl6692.pd
HALOE Algorithm Improvements for Upper Tropospheric Sounding
This report details the ongoing efforts by GATS, Inc., in conjunction with Hampton University and University of Wyoming, in NASA's Mission to Planet Earth UARS Science Investigator Program entitled "HALOE Algorithm Improvements for Upper Tropospheric Soundings." The goal of this effort is to develop and implement major inversion and processing improvements that will extend HALOE measurements further into the troposphere. In particular, O3, H2O, and CH4 retrievals may be extended into the middle troposphere, and NO, HCl and possibly HF into the upper troposphere. Key areas of research being carried out to accomplish this include: pointing/tracking analysis; cloud identification and modeling; simultaneous multichannel retrieval capability; forward model improvements; high vertical-resolution gas filter channel retrievals; a refined temperature retrieval; robust error analyses; long-term trend reliability studies; and data validation. The current (first-year) effort concentrates on the pointer/tracker correction algorithms, cloud filtering and validation, and multi-channel retrieval development. However, these areas are all highly coupled, so progress in one area benefits from and sometimes depends on work in others
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On the seasonal onset of polar mesospheric clouds and the breakdown of the stratospheric polar vortex in the Southern Hemisphere
Southern Hemisphere (SH) polar mesospheric clouds (PMCs), also known as noctilucent clouds, have been observed to be more variable and, in general, dimmer than their Northern Hemisphere (NH) counterparts. The precise cause of these hemispheric differences is not well understood. This paper focuses on one aspect of the hemispheric differences: the timing of the PMC season onset. Observations from the Aeronomy of Ice in the Mesosphere satellite indicate that in recent years the date on which the PMC season begins varies much more in the SH than in the NH. Using the Canadian Middle Atmosphere Model, we show that the generation of sufficiently low temperatures necessary for cloud formation in the SH summer polar mesosphere is perturbed by year‐to‐year variations in the timing of the late‐spring breakdown of the SH stratospheric polar vortex.
These stratospheric variations, which persist until the end of December, influence the propagation of gravity waves up to the mesosphere. This adds a stratospheric control to the temperatures in the polar mesopause region during early summer, which causes the onset of PMCs to vary from one year to another. This effect is much stronger in the SH
than in the NH because the breakdown of the polar vortex occurs much later in the SH, closer in time to the PMC season
Dissociable and Paradoxical Roles of Rat Medial and Lateral Orbitofrontal Cortex in Visual Serial Reversal Learning
Version 1.3 AIM SOFIE Measured Methane (CH4): Validation and Seasonal Climatology
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
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
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
NRLMSIS 2.0: A Whole-Atmosphere Empirical Model of Temperature and Neutral Species Densities
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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