The UARS microwave limb sounder version 5 data set: Theory, characterization, and validation

Nitric acid (HNO3) is a major player in processes controlling the springtime depletion of polar ozone. It is the main constituent of the Polar Stratospheric Clouds (PSCs) and a primary reservoir for reactive nitrogen. Potential variations in the stratospheric circulation and temperature may alter the extent and duration of PSCs activity, influencing the future ozone levels significantly. Monitoring HNO3 and its long-term variability, especially in polar region, is then crucial for better understanding issues related to ozone decline and expected recovery. In this study we present an intercomparison between ground based HNO3 measurements, carried out by means of the Ground-Based Millimeter-wave Spectrometer (GBMS), and two satellite data sets produced by the two NASA/JPL Microwave Limb Sounder (MLS) experiments. In particular, we compare UARS MLS measurements (1991-1999) with those carried out by the GBMS at South Pole, Antarctica (90°S), Fall of 1993 and 1995. A similar intercomparison is made between Aura MLS HNO3 observations (2004 - to date) and GBMS measurements obtained during the period February 2004 - March 2007, at the mid-latitudes/high altitudes station of Testa Grigia (45.9° N, 7.7° E, elev. 3500 m), and during polar winters 2008/09 and 2009/2010 at Thule Air Base (76.5°N 68.8°W), Greenland. We assess systematic differences between GBMS and both UARS and Aura HNO3 data sets at seven potential temperature levels (θ) spanning the range 465 – 960 K. The UARS data set advected to the South Pole shows a low bias, within 20% for all θ levels but the 960 K, with respect to GBMS measurements. A very good agreement, within 5%, is obtained between Aura and GBMS observations at Testa Grigia, while larger differences, possibly due to latitude dependent effects, are observed over Thule. These differences are under further investigations but a preliminary comparison over Thule among MLS v3, GBMS, and ACE-FTS measurements suggests that GBMS measurements carried out during winter 2009 might not be reliable. These comparisons have been performed in the framework of the NASA JPL GOZCARDS project, which is aimed at developing a long-term, global data record of the relevant stratospheric constituents in the context of ozone decline. GBMS has been selected in GOZCARDS since its HNO3 dataset, although sampling different latitudes in different years, is the only one spanning a sufficiently long time interval for cross-calibrating HNO3 measurements by the UARS and Aura MLS experiments

A linear CO chemistry parameterization in a chemistry-transport model: evaluation and application to data assimilation

This paper presents an evaluation of a new linear parameterization valid for the troposphere and the stratosphere, based on a first order approximation of the carbon monoxide (CO) continuity equation. This linear scheme (hereinafter noted LINCO) has been implemented in the 3-D Chemical Transport Model (CTM) MOCAGE (MOdèle de Chimie Atmospherique Grande Echelle). First, a one and a half years of LINCO simulation has been compared to output obtained from a detailed chemical scheme output. The mean differences between both schemes are about ±25 ppbv (part per billion by volume) or 15% in the troposphere and ±10 ppbv or 100% in the stratosphere. Second, LINCO has been compared to diverse observations from satellite instruments covering the troposphere (Measurements Of Pollution In The Troposphere: MOPITT) and the stratosphere (Microwave Limb Sounder: MLS) and also from aircraft (Measurements of ozone and water vapour by Airbus in-service aircraft: MOZAIC programme) mostly flying in the upper troposphere and lower stratosphere (UTLS). In the troposphere, the LINCO seasonal variations as well as the vertical and horizontal distributions are quite close to MOPITT CO observations. However, a bias of ~−40 ppbv is observed at 700 Pa between LINCO and MOPITT. In the stratosphere, MLS and LINCO present similar large-scale patterns, except over the poles where the CO concentration is underestimated by the model. In the UTLS, LINCO presents small biases less than 2% compared to independent MOZAIC profiles. Third, we assimilated MOPITT CO using a variational 3D-FGAT (First Guess at Appropriate Time) method in conjunction with MOCAGE for a long run of one and a half years. The data assimilation greatly improves the vertical CO distribution in the troposphere from 700 to 350 hPa compared to independent MOZAIC profiles. At 146 hPa, the assimilated CO distribution is also improved compared to MLS observations by reducing the bias up to a factor of 2 in the tropics. This study confirms that the linear scheme is able to simulate reasonably well the CO distribution in the troposphere and in the lower stratosphere. Therefore, the low computing cost of the linear scheme opens new perspectives to make free runs and CO data assimilation runs at high resolution and over periods of several years

Comparing learned predictiveness effects within and across compound discriminations

In four human learning experiments, we examined the extent to which learned predictiveness depends upon direct comparison between relatively good and poor predictors. Participants initially solved (1) linear compound discriminations in which one or both of the stimuli in each compound were predictive of the correct outcome, (2) biconditional discriminations where only the configurations of the stimuli were predictive of the correct outcome, or (3) pseudo-discriminations in which no stimulus features were predictive. In each experiment, subsequent learning and test stages were used to assay changes in the associability of each stimulus brought about by its role in the initial discriminations. Although learned predictiveness effects were observed in all experiments (i.e. previously predictive cues were more readily associated with a new outcome than previously non-predictive cues), the same changes in associability were observed regardless of whether the stimulus was initially learned about in the presence of an equally predictive, more predictive, or less predictive stimulus. The results suggest that learned associability is not controlled by competitive allocation of attention, but rather by the absolute predictiveness of each individual cue.Australian Research Council, and the German Academic Exchange Service (DAAD

Characterizing sampling and quality screening biases in infrared and microwave limb sounding

This study investigates orbital sampling biases and evaluates the additional impact caused by data quality screening for the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and the Aura Microwave Limb Sounder (MLS). MIPAS acts as a proxy for typical infrared limb emission sounders, while MLS acts as a proxy for microwave limb sounders. These biases were calculated for temperature and several trace gases by interpolating model fields to real sampling patterns and, additionally, screening those locations as directed by their corresponding quality criteria. Both instruments have dense uniform sampling patterns typical of limb emission sounders, producing almost identical sampling biases. However, there is a substantial difference between the number of locations discarded. MIPAS, as a mid-infrared instrument, is very sensitive to clouds, and measurements affected by them are thus rejected from the analysis. For example, in the tropics, the MIPAS yield is strongly affected by clouds, while MLS is mostly unaffected. The results show that upper-tropospheric sampling biases in zonally averaged data, for both instruments, can be up to 10 to 30 %, depending on the species, and up to 3 K for temperature. For MIPAS, the sampling reduction due to quality screening worsens the biases, leading to values as large as 30 to 100 % for the trace gases and expanding the 3 K bias region for temperature. This type of sampling bias is largely induced by the geophysical origins of the screening (e.g. clouds). Further, analysis of long-term time series reveals that these additional quality screening biases may affect the ability to accurately detect upper-tropospheric long-term changes using such data. In contrast, MLS data quality screening removes sufficiently few points that no additional bias is introduced, although its penetration is limited to the upper troposphere, while MIPAS may cover well into the mid-troposphere in cloud-free scenarios. We emphasize that the results of this study refer only to the representativeness of the respective data, not to their intrinsic quality

Validation of Aura Microwave Limb Sounder O-3 and CO observations in the upper troposphere and lower stratosphere

International audienceGlobal satellite observations of ozone and carbon monoxide from the Microwave Limb Sounder (MLS) on the EOS Aura spacecraft are discussed with emphasis on those observations in the 215–100 hPa region (the upper troposphere and lower stratosphere). The precision, resolution and accuracy of the data produced by the MLS “version 2.2” processing algorithms are discussed and quantified. O3 accuracy is estimated at ~40 ppbv +5% (~20 ppbv +20% at 215 hPa) while the CO accuracy is estimated at ~30 ppbv +30% for pressures of 147 hPa and less. Comparisons with expectations and other observations show good agreements for the O3 product, generally consistent with the systematic errors quoted above. In the case of CO, a persistent factor of ~2 high bias is seen at 215 hPa. However, the morphology is shown to be realistic, consistent with raw MLS radiance data, and useful for scientific study. The MLS CO data at higher altitudes are shown to be consistent with other observations

Microwave Limb Sounder (MLS) observations of biomass burning products in the stratosphere from Canadian forest fires in August 2017

Forest fires in British Columbia in August 2017 caused a pyrocumulonimbus event that injected a polluted air mass into the lower stratosphere. The Microwave Limb Sounder (MLS) on the Aura satellite first observed the polluted air mass on 14 August 2017 and continued to observe it for 60 d (100 d in water vapour). We estimate the mass of CO injected into the stratosphere to be 2400 Gg. Events in which a fire injects its burning products directly into the stratosphere are rare: this is the third of four such events in the 16 years since the launch of Aura, the second largest of the four events, and the only one in the Northern Hemisphere. The other three events occurred in Australia in December 2006, February 2009 and from December 2019 to January 2020. Unlike the 2006 and 2009 events, but like the 2019–2020 event, the polluted air mass described here had a clearly elevated water vapour content: between 2.5 and 5 times greater than that in the surrounding atmosphere. We describe the evolution of the polluted air mass, showing that it rose to an altitude of about 24 km (31 hPa) and divided into several identifiable parts. In addition to CO and H2O, we observe enhanced amounts of HCN, CH3CN, CH3Cl and CH3OH with mixing ratios in the range to be expected from a variety of measurements in other biomass burning plumes. We use back trajectories and plume-dispersion modelling to demonstrate that the pollutants observed by MLS originated in the British Columbia fires, the likeliest source being at 53.2∘ N, 121.8∘ W at 05:20 UTC on 13 August 2017.</p

Accurate satellite-derived estimates of the tropospheric ozone impact on the global radiation budget

Estimates of the radiative forcing due to anthropogenically-produced tropospheric O3 are derived primarily from models. Here, we use tropospheric ozone and cloud data from several instruments in the A-train constellation of satellites as well as information from the GEOS-5 Data Assimilation System to accurately estimate the radiative effect of tropospheric O3 for January and July 2005. Since we cannot distinguish between natural and anthropogenic sources with the satellite data, our derived radiative effect reflects the unadjusted (instantaneous) effect of the total tropospheric O3 rather than the anthropogenic component. We improve upon previous estimates of tropospheric ozone mixing ratios from a residual approach using the NASA Earth Observing System (EOS) Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) by incorporating cloud pressure information from OMI. We focus specifically on the magnitude and spatial structure of the cloud effect on both the short- and long-wave radiative budget. The estimates presented here can be used to evaluate the various aspects of model-generated radiative forcing. For example, our derived cloud impact is to reduce the radiative effect of tropospheric ozone by ~16%. This is centered within the published range of model-produced cloud effect on unadjusted ozone radiative forcing

Northern Hemisphere mid-winter vortex-displacement and vortex-split stratospheric sudden warmings: Influence of the Madden-Julian Oscillation and Quasi-Biennial Oscillation

We investigate the connection between the equatorial Madden‐Julian Oscillation (MJO) and different types of the Northern Hemisphere mid‐winter major stratospheric sudden warmings (SSWs), i.e., vortex‐displacement and vortex‐split SSWs. The MJO‐SSW relationship for vortex‐split SSWs is stronger than that for vortex‐displacement SSWs, as a result of the stronger and more coherent eastward propagating MJOs before vortex‐split SSWs than those before vortex‐displacement SSWs. Composite analysis indicates that both the intensity and propagation features of MJO may influence the MJO‐related circulation pattern at high latitudes and the type of SSWs. A pronounced Quasi‐Biennial Oscillation (QBO) dependence is found for vortex‐displacement and vortex‐split SSWs, with vortex‐displacement (‐split) SSWs occurring preferentially in easterly (westerly) QBO phases. The lagged composites suggest that the MJO‐related anomalies in the Arctic are very likely initiated when the MJO‐related convection is active over the equatorial Indian Ocean (around the MJO phase 3). Further analysis suggests that the QBO may modulate the MJO‐related wave disturbances via its influence on the upper tropospheric subtropical jet. As a result, the MJO‐related circulation pattern in the Arctic tends to be wave number‐one/wave number‐two ~25–30 days following phase 3 (i.e., approximately phases 7–8, when the MJO‐related convection is active over the western Pacific) during easterly/westerly QBO phases, which resembles the circulation pattern associated with vortex‐displacement/vortex‐split SSWs