Differences in ozone retrieval in MIPAS channels A and AB: a spectroscopic issue

Discrepancies in ozone retrievals in MIPAS channels A (685–970cm−1) and AB (1020–1170cm−1) have been a long-standing problem in MIPAS data analysis, amounting to an interchannel bias (AB–A) of up to 8% between ozone volume mixing ratios in the altitude range 30–40km. We discuss various candidate explanations, among them forward model and retrieval algorithm errors, interchannel calibration inconsistencies and spectroscopic data inconsistencies. We show that forward-modelling errors as well as errors in the retrieval algorithm can be ruled out as an explanation because the bias can be reproduced with an entirely independent retrieval algorithm (GEOFIT), relying on a different forward radiative transfer model. Instrumental and calibration issues can also be refuted as an explanation because ozone retrievals based on balloon-borne measurements with a different instrument (MIPAS-B) and an independent level-1 data processing scheme produce a rather similar interchannel bias. Thus, spectroscopic inconsistencies in the MIPAS database used for ozone retrieval are practically the only reason left. To further investigate this issue, we performed retrievals using additional spectroscopic databases. Various versions of the HITRAN database generally produced rather similar channel AB–A differences. Use of a different database, namely GEISA-2015, led to similar results in channel AB, but to even higher ozone volume mixing ratios for channel A retrievals, i.e. to a reversal of the bias. We show that the differences in MIPAS channel A retrievals result from about 13% lower air-broadening coefficients of the strongest lines in the GEISA-2015 database. Since the errors in line intensity of the major lines used in MIPAS channels A and AB are reported to be considerably lower than the observed bias, we posit that a major part of the channel AB–A differences can be attributed to inconsistent air-broadening coefficients as well. To corroborate this assumption we show some clearly inconsistent air-broadening coefficients in the HITRAN-2008 database. The interchannel bias in retrieved ozone amounts can be reduced by increasing the air-broadening coefficients of the lines in MIPAS channel AB in the HITRAN-2008 database by 6%–8%

The SPARC Water Vapor Assessment II: assessment of satellite measurements of upper tropospheric humidity

Nineteen limb-viewing data sets (occultation, passive thermal, and UV scattering) and two nadir upper tropospheric humidity (UTH) data sets are intercompared and also compared to frost-point hygrometer balloon sondes. The upper troposphere considered here covers the pressure range from 300-100 hPa. UTH is a challenging measurement, because concentrations vary between 2-1000 ppmv (parts per million by volume), with sharp changes in vertical gradients near the tropopause. Cloudiness in this region also makes the measurement challenging. The atmospheric temperature is also highly variable ranging from 180-250 K. The assessment of satellite-measured UTH is based on coincident comparisons with balloon frost-point hygrometer sondes, multi-month mapped comparisons, zonal mean time series comparisons, and coincident satellite-to-satellite comparisons. While the satellite fields show similar features in maps and time series, quantitatively they can differ by a factor of 2 in concentration, with strong dependencies on the amount of UTH. Additionally, time-lag response-corrected Vaisala RS92 radiosondes are compared to satellites and the frost-point hygrometer measurements. In summary, most satellite data sets reviewed here show on average similar to 30 % agreement amongst themselves and frost-point data but with an additional similar to 30 % variability about the mean bias. The Vaisala RS92 sonde, even with a time-lag correction, shows poor behavior for pressures less than 200 hPa

The SPARC Water Vapor Assessment II: assessment of satellite measurements of upper tropospheric humidity

Nineteen limb-viewing data sets (occultation, passive thermal, and UV scattering) and two nadir upper tropospheric humidity (UTH) data sets are intercompared and also compared to frost-point hygrometer balloon sondes. The upper troposphere considered here covers the pressure range from 300–100 hPa. UTH is a challenging measurement, because concentrations vary between 2–1000 ppmv (parts per million by volume), with sharp changes in vertical gradients near the tropopause. Cloudiness in this region also makes the measurement challenging. The atmospheric temperature is also highly variable ranging from 180–250 K. The assessment of satellite-measured UTH is based on coincident comparisons with balloon frost-point hygrometer sondes, multi-month mapped comparisons, zonal mean time series comparisons, and coincident satellite-to-satellite comparisons. While the satellite fields show similar features in maps and time series, quantitatively they can differ by a factor of 2 in concentration, with strong dependencies on the amount of UTH. Additionally, time-lag response-corrected Vaisala RS92 radiosondes are compared to satellites and the frost-point hygrometer measurements. In summary, most satellite data sets reviewed here show on average ∼30 % agreement amongst themselves and frost-point data but with an additional ∼30 % variability about the mean bias. The Vaisala RS92 sonde, even with a time-lag correction, shows poor behavior for pressures less than 200 hPa

The SPARC water vapour assessment II: comparison of annual, semi-annual and quasi-biennial variations in stratospheric and lower mesospheric water vapour observed from satellites

In the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II), the amplitudes and phases of the annual, semi-annual and quasi-biennial variation in stratospheric and lower mesospheric water were compared using 30 data sets from 13 different satellite instruments. These comparisons aimed to provide a comprehensive overview of the typical uncertainties in the observational database which can be considered in subsequent observational and modelling studies. For the amplitudes, a good agreement of their latitude and altitude distribution was found. Quantitatively there were differences in particular at high latitudes, close to the tropopause and in the lower mesosphere. In these regions, the standard deviation over all data sets typically exceeded 0.2 ppmv for the annual variation and 0.1 ppmv for the semi-annual and quasi-biennial variation. For the phase, larger differences between the data sets were found in the lower mesosphere. Generally the smallest phase uncertainties can be observed in regions where the amplitude of the variability is large. The standard deviations of the phases for all data sets were typically smaller than a month for the annual and semi-annual variation and smaller than 5 months for the quasi-biennial variation. The amplitude and phase differences among the data sets are caused by a combination of factors. In general, differences in the temporal variation of systematic errors and in the observational sampling play a dominant role. In addition, differences in the vertical resolution of the data, the considered time periods and influences of clouds, aerosols as well as non-local thermodynamic equilibrium (NLTE) effects cause differences between the individual data sets

JIRAM/Juno limb observations of H3+ in the mid- and low latitude Jovian atmosphere

NASA's Juno mission has been investigating Jupiter since August 2016, providing unprecedented insights into the giant planet's atmosphere. The Jupiter Infrared Auroral Mapper (JIRAM) experiment, on board Juno, performed spectroscopic observations of the H3+ emissions in both auroral regions (Dinelli et al., 2017; Adriani et al., 2017; Mura et al., 2017) and at mid-latitudes. In this work we analyse observations acquired over five orbits by the JIRAM spectrometer during the period from August 2016 to March 2017. In particular, during these observations, the spectrometer slit sampled Jupiter's limb over latitudes ranging from 60∘ equatorward, in both hemispheres. Limb spectra show typical H3+ emission features in the 3-4 μm spectral band, used to retrieve the H3+ densities and temperatures. Spatial resolution of the limb observations ranges between 50 and 130 km and is favourable for investigating the vertical distribution of H3+. Vertical profiles of H3+ limb intensities, in the 3-4 μm spectral band, are presented along with preliminary retrievals of the vertical profiles of H3+ volume mixing ratio (VMR). We compare our results with predictions from various atmospheric models. Acknowledgments The project JIRAM is funded by the Italian Space Agency

The SPARC water vapor assessment II: intercomparison of satellite and ground-based microwave measurements

As part of the second SPARC (Stratosphere–troposphere Processes And their Role in Climate) water vapor assessment (WAVAS-II), we present measurements taken from or coincident with seven sites from which ground-based microwave instruments measure water vapor in the middle atmosphere. Six of the ground-based instruments are part of the Network for the Detection of Atmospheric Composition Change (NDACC) and provide datasets that can be used for drift and trend assessment. We compare measurements from these ground-based instruments with satellite datasets that have provided retrievals of water vapor in the lower mesosphere over extended periods since 1996. We first compare biases between the satellite and ground-based instruments from the upper stratosphere to the upper mesosphere. We then show a number of time series comparisons at 0.46 hPa, a level that is sensitive to changes in H2O and CH4 entering the stratosphere but, because almost all CH4 has been oxidized, is relatively insensitive to dynamical variations. Interannual variations and drifts are investigated with respect to both the Aura Microwave Limb Sounder (MLS; from 2004 onwards) and each instrument's climatological mean. We find that the variation in the interannual difference in the mean H2O measured by any two instruments is typically  ∼  1%. Most of the datasets start in or after 2004 and show annual increases in H2O of 0–1 % yr−1. In particular, MLS shows a trend of between 0.5 % yr−1 and 0.7 % yr−1 at the comparison sites. However, the two longest measurement datasets used here, with measurements back to 1996, show much smaller trends of +0.1 % yr−1 (at Mauna Loa, Hawaii) and −0.1 % yr−1 (at Lauder, New Zealand)

Morphology of the Auroral Tail of Io, Europa, and Ganymede From JIRAM L-Band Imager

Jupiter hosts intense auroral activity associated with charged particles precipitating into the planet's atmosphere. The Galilean moons orbiting within the magnetosphere are swept by the magnetic field: the resulting perturbation travels along field lines as Alfven waves, which are able to accelerate electrons toward the planet, producing satellite-induced auroral emissions. These emissions due to the moons, known as footprints, can be detected in various wavelengths (UV, visible, IR) outside the main auroral emission as multiple bright spots followed by footprint tails. Since 2016 the Juno spacecraft orbiting Jupiter has surveyed the polar regions more than 30 times at close distances. Onboard the spacecraft, the Jovian InfraRed Auroral Mapper (JIRAM) is an imager and spectrometer with an L-band imaging filter suited to observe auroral features at unprecedented spatial resolution. JIRAM revealed a rich substructure in the footprint tails of Io, Europa, and Ganymede, which appear as a trail of quasi-regularly spaced bright sub-dots whose intensity fades away along the emission trail as the spatial separation from the footprint increases. The fine structure of the Europa and Ganymede footprint tails is reported in this work for the first time. We will also show that the typical distance between subsequent sub-dots is the same for all three moons at JIRAM resolution in both hemispheres. In addition, the sub-dots observed by JIRAM are static in a frame corotating with Jupiter. A feedback mechanism between the ionosphere and the magnetosphere is suggested as a potential candidate to explain the morphology of the footprint tails

An Optimized Forward Model And Retrieval Scheme For Mipas Near Real Time Data Processing

The infrared emission limb sounder MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) will be operated as an ESA core instrument on the ENVISAT-1 satellite. Near real time retrieval of pressure, temperature (p,T) and volume mixing ratio (VMR) of six key species (O 3 , H 2 O, HNO 3 , CH 4 , N 2 O and NO 2 ) from calibrated spectra will be performed in the Level 2 processor of the ENVISAT Payload Data Segment