Showing papers by "Kaley A. Walker published in 2018"

The SPARC water vapour assessment II: comparison of stratospheric and lower mesospheric water vapour time series observed from satellites

Abstract: . Time series of stratospheric and lower mesospheric water vapour using 33 data sets from 15 different satellite instruments were compared in the framework of the second SPARC (Stratosphere-troposphere Processes And their Role in Climate) water vapour assessment (WAVAS-II). This comparison aimed to provide a comprehensive overview of the typical uncertainties in the observational database that can be considered in the future in observational and modelling studies, e.g addressing stratospheric water vapour trends. The time series comparisons are presented for the three latitude bands, the Antarctic (80 ∘ –70 ∘ S), the tropics (15 ∘ S–15 ∘ N) and the Northern Hemisphere mid-latitudes (50 ∘ –60 ∘ N) at four different altitudes (0.1, 3, 10 and 80 hPa ) covering the stratosphere and lower mesosphere. The combined temporal coverage of observations from the 15 satellite instruments allowed the consideration of the time period 1986–2014. In addition to the qualitative comparison of the time series, the agreement of the data sets is assessed quantitatively in the form of the spread (i.e. the difference between the maximum and minimum volume mixing ratios among the data sets), the (Pearson) correlation coefficient and the drift (i.e. linear changes of the difference between time series over time). Generally, good agreement between the time series was found in the middle stratosphere while larger differences were found in the lower mesosphere and near the tropopause. Concerning the latitude bands, the largest differences were found in the Antarctic while the best agreement was found for the tropics. From our assessment we find that most data sets can be considered in future observational and modelling studies, e.g. addressing stratospheric and lower mesospheric water vapour variability and trends, if data set specific characteristics (e.g. drift) and restrictions (e.g. temporal and spatial coverage) are taken into account.

Stratospheric ozone loss in the Arctic winters between 2005 and 2013 derived with ACE-FTS measurements

Abstract: . Stratospheric ozone loss inside the Arctic polar vortex for the winters between 2004–2005 and 2012–2013 has been quantified using measurements from the space-borne Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS). For the first time, an evaluation has been performed of six different ozone loss estimation methods based on the same single observational dataset to determine the Arctic ozone loss (mixing ratio loss profiles and the partial-column ozone losses between 380 and 550 K). The methods used are the tracer-tracer correlation, the artificial tracer correlation, the average vortex profile descent, and the passive subtraction with model output from both Lagrangian and Eulerian chemical transport models (CTMs). For the tracer-tracer, the artificial tracer, and the average vortex profile descent approaches, various tracers have been used that are also measured by ACE-FTS. From these seven tracers investigated ( CH4 , N2O , HF , OCS , CFC-11, CFC-12, and CFC-113), we found that CH4 , N2O , HF , and CFC-12 are the most suitable tracers for investigating polar stratospheric ozone depletion with ACE-FTS v3.5. The ozone loss estimates (in terms of the mixing ratio as well as total column ozone) are generally in good agreement between the different methods and among the different tracers. However, using the average vortex profile descent technique typically leads to smaller maximum losses (by approximately 15–30 DU) compared to all other methods. The passive subtraction method using output from CTMs generally results in slightly larger losses compared to the techniques that use ACE-FTS measurements only. The ozone loss computed, using both measurements and models, shows the greatest loss during the 2010–2011 Arctic winter. For that year, our results show that maximum ozone loss (2.1–2.7 ppmv) occurred at 460 K. The estimated partial-column ozone loss inside the polar vortex (between 380 and 550 K) using the different methods is 66–103, 61–95, 59–96, 41–89, and 85–122 DU for March 2005, 2007, 2008, 2010, and 2011, respectively. Ozone loss is difficult to diagnose for the Arctic winters during 2005–2006, 2008–2009, 2011–2012, and 2012–2013, because strong polar vortex disturbance or major sudden stratospheric warming events significantly perturbed the polar vortex, thereby limiting the number of measurements available for the analysis of ozone loss.

MIPAS Observations of Ozone in the Middle Atmosphere

Abstract: . In this paper we describe the stratospheric and mesospheric ozone (version V5r_O3_m22) distributions retrieved from MIPAS observations in the three middle atmosphere modes (MA, NLC, and UA) taken with an unapodized spectral resolution of 0.0625 cm−1 from 2005 until April 2012. O3 is retrieved from microwindows in the 14.8 and 10 µm spectral regions and requires non-local thermodynamic equilibrium (non-LTE) modelling of the O3 v1 and v3 vibrational levels. Ozone is reliably retrieved from 20 km in the MA mode (40 km for UA and NLC) up to ∼ 105 km during dark conditions and up to ∼ 95 km during illuminated conditions. Daytime MIPAS O3 has an average vertical resolution of 3–4 km below 70 km, 6–8 km at 70–80 km, 8–10 km at 80–90, and 5–7 km at the secondary maximum (90–100 km). For nighttime conditions, the vertical resolution is similar below 70 km and better in the upper mesosphere and lower thermosphere: 4–6 km at 70–100 km, 4–5 km at the secondary maximum, and 6–8 km at 100–105 km. The noise error for daytime conditions is typically smaller than 2 % below 50 km, 2–10 % between 50 and 70 km, 10–20 % at 70–90 km, and ∼ 30 % above 95 km. For nighttime, the noise errors are very similar below around 70 km but significantly smaller above, being 10–20 % at 75–95 km, 20–30 % at 95–100 km, and larger than 30 % above 100 km. The additional major O3 errors are the spectroscopic data uncertainties below 50 km (10–12 %) and the non-LTE and temperature errors above 70 km. The validation performed suggests that the spectroscopic errors below 50 km, mainly caused by the O3 air-broadened half-widths of the v2 band, are overestimated. The non-LTE error (including the uncertainty of atomic oxygen in nighttime) is relevant only above ∼ 85 km with values of 15–20 %. The temperature error varies from ∼ 3 % up to 80 km to 15–20 % near 100 km. Between 50 and 70 km, the pointing and spectroscopic errors are the dominant uncertainties. The validation performed in comparisons with SABER, GOMOS, MLS, SMILES, and ACE-FTS shows that MIPAS O3 has an accuracy better than 5 % at and below 50 km, with a positive bias of a few percent. In the 50–75 km region, MIPAS O3 has a positive bias of ≈ 10 %, which is possibly caused in part by O3 spectroscopic errors in the 10 µm region. Between 75 and 90 km, MIPAS nighttime O3 is in agreement with other instruments by 10 %, but for daytime the agreement is slightly larger, ∼ 10–20 %. Above 90 km, MIPAS daytime O3 is in agreement with other instruments by 10 %. At night, however, it shows a positive bias increasing from 10 % at 90 km to 20 % at 95–100 km, the latter of which is attributed to the large atomic oxygen abundance used. We also present MIPAS O3 distributions as function of altitude, latitude, and time, showing the major O3 features in the middle and upper mesosphere. In addition to the rapid diurnal variation due to photochemistry, the data also show apparent signatures of the diurnal migrating tide during both day- and nighttime, as well as the effects of the semi-annual oscillation above ∼ 70 km in the tropics and mid-latitudes. The tropical daytime O3 at 90 km shows a solar signature in phase with the solar cycle.

On sampling bias adjustment for sparsely observing satellite instruments for the example of carbonyl sulfide (OCS)

Abstract: . When computing climatological averages of atmospheric trace gas mixing ratios obtained from satellite-based measurements, sampling biases arise if data coverage is not uniform in space and time. Complete homogeneous spatio-temporal coverage is essentially impossible to achieve. Solar occultation measurements, by virtue of satellite orbits and the requirement of direct observation of the sun through the atmosphere, result in particularly sparse spatial coverage. In this study, a method is presented to adjust for such sampling biases when calculating climatological means. The method is demonstrated using carbonyl sulfide (OCS) measurements at 16 km altitude from the ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform 15 Spectrometer). At this altitude, OCS mixing ratios show a steep gradient between the poles and equator. ACE-FTS measurements, which are provided as vertically resolved profiles, and integrated stratospheric OCS columns are used in this study. The bias adjustment procedure requires no additional observations other than the satellite data product itself and is expected to be generally applicable when constructing climatologies of long-lived tracers from sparsely and heterogeneously sampled satellite data. In a first step of the adjustment procedure, a regression model is used to fit a 2-D surface to all available ACE-FTS OCS measurements as a function of day-of-year and latitude. The regression model fit is used to calculate an adjustment factor, 20 which is then used to adjust each measurement individually. The mean of the adjusted measurement points of a chosen spatio-temporal frame is then used as the bias-free climatological value. When applying the adjustment factor to seasonal averages in 30° zones, the maximum spatio-temporal sampling bias adjustment was 11 % for OCS mixing ratios at 16 km and 5 % for the stratospheric OCS column. The adjustments were validated against the much denser and more homogeneous OCS data product from the limb-sounding MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument, and both the direction and sign of the adjustments were in agreement with the adjustment of the ACE-FTS data.

Long-term Validation for the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS)

Abstract: This paper will describe the current validation results for the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) with a focus on long-term validation efforts and overall mission status for this instrument.

Investigating N2O produced in the mesosphere – lower thermosphere and its transport to the middle atmosphere

Abstract: This paper will describe Atmospheric Chemistry – Experiment Fourier Transform Spectrometer (ACE-FTS) N2O measurements in the middle atmosphere along with its production mechanisms and long-term variation. Comparisons with model N2O simulations will also be discussed.