ALBERT

Description: Observational studies of stratospheric ozone often involve data from multiple instruments that measure the ozone at different times of day. There has been an increased awareness of the potential impact of the diurnal cycle when interpreting measurements of stratospheric ozone at altitudes in the mid- to upper stratosphere. To address this issue, we present a climatological representation of diurnal variations in ozone with a 30 min temporal resolution as a function of latitude, pressure and month, based on output from the Goddard Earth Observing System (GEOS) general circulation model coupled to the NASA Global Modeling Initiative (GMI) chemistry package (known as the GEOS-GMI chemistry model). This climatology can be applied to a wide range of ozone data analyses, including data intercomparisons, data merging and the analysis of data from a single platform in a non-sun-synchronous orbit. We evaluate the diurnal climatology by comparing mean differences between ozone measurements made at different local solar times to the differences predicted by the diurnal model. The ozone diurnal cycle is a complicated function of latitude, pressure and season, with variations of less than 5 % in the tropics and subtropics, increasing to more than 15 % near the polar day terminator in the upper stratosphere. These results compare well with previous modeling simulations and are supported by similar size variations in satellite observations. We present several example applications of the climatology in currently relevant data studies. We also compare this diurnal climatology to the diurnal signal from a previous iteration of the free-running GEOS Chemistry Climate Model (GEOSCCM) and to the ensemble runs of GEOS-GMI to test the sensitivity of the model diurnal cycle to changes in model formulation and simulated time period.

Description: In this study we compare the satellite-based Global Ozone Monitoring Experiment (GOME)-type Total Ozone Essential Climate Variable (GTO-ECV) record, generated as part of the European Space Agency's Climate Change Initiative (ESA-CCI) ozone project, with the adjusted total ozone product from the Modern Era Retrospective Analysis for Research and Applications version 2 (adjusted MERRA-2) reanalysis, produced at the National Aeronautics and Space Administration (NASA) Global Modeling and Assimilation Office (GMAO). Total ozone columns and associated standard deviations show a very good agreement in terms of both spatial and temporal patterns during their 23-year overlap period from July 1995 to December 2018. The mean difference between adjusted MERRA-2 and GTO-ECV 5∘×5∘ monthly mean total ozone columns is -0.9±1.5 %. A small discontinuity in the deviations is detected in October 2004, when data from the Ozone Monitoring Instrument (OMI) were ingested in the GTO-ECV and adjusted MERRA-2 data records. This induces a small overall negative drift in the differences for almost all latitude bands, which, however, does not exceed 1 % per decade. The mean difference for the period prior to October 2004 is -0.5±1.7 %, whereas the difference is -1.0±1.1 % for the period from October 2004 to December 2018. The variability in the differences is considerably reduced in the period after 2004 due to a significant increase in data coverage and sampling. In the tropical region, the differences indicate a slight zonal variability with negative deviations over the Atlantic, Africa, and the Indian Ocean and positive deviations over the Pacific. Ozone anomalies and the distribution of their statistical moments indicate a very high correlation among both data records as to the temporal and spatial structures. Furthermore, we evaluate the consistency of the data sets by means of an empirical orthogonal function (EOF) analysis. The interannual variability is assessed in the tropics, and both GTO-ECV and adjusted MERRA-2 exhibit a remarkable agreement with respect to the derived patterns. The first four EOFs can be attributed to different modes of interannual climate variability, and correlations with the Quasi-Biennial Oscillation (QBO), the El Niño–Southern Oscillation (ENSO) signal, and the solar cycle were found.

Description: We report on updated trends using different merged datasets from satellite and ground-based observations for the period from 1979 to 2016. Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. Merged datasets used here include NASA MOD v8.6 and National Oceanic and Atmospheric Administration (NOAA) merge v8.6, both based on data from the series of Solar Backscatter UltraViolet (SBUV) and SBUV-2 satellite instruments (1978–present) as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone (GTO) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (1995–present), mainly comprising satellite data from GOME, the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and GOME-2A. The fifth dataset consists of the monthly mean zonal mean data from ground-based measurements collected at World Ozone and UV Data Center (WOUDC). The addition of four more years of data since the last World Meteorological Organization (WMO) ozone assessment (2013–2016) shows that for most datasets and regions the trends since the stratospheric halogen reached its maximum (∼ 1996 globally and ∼ 2000 in polar regions) are mostly not significantly different from zero. However, for some latitudes, in particular the Southern Hemisphere extratropics and Northern Hemisphere subtropics, several datasets show small positive trends of slightly below +1 % decade−1 that are barely statistically significant at the 2σ uncertainty level. In the tropics, only two datasets show significant trends of +0.5 to +0.8 % decade−1, while the others show near-zero trends. Positive trends since 2000 have been observed over Antarctica in September, but near-zero trends are found in October as well as in March over the Arctic. Uncertainties due to possible drifts between the datasets, from the merging procedure used to combine satellite datasets and related to the low sampling of ground-based data, are not accounted for in the trend analysis. Consequently, the retrieved trends can be only considered to be at the brink of becoming significant, but there are indications that we are about to emerge into the expected recovery phase. However, the recent trends are still considerably masked by the observed large year-to-year dynamical variability in total ozone.

Description: The combined record of total and profile ozone measurements from the solar backscatter ultraviolet (SBUV) and SBUV/2 series of instruments, known as the SBUV Merged Ozone Data (MOD) product, constitutes the longest satellite-based ozone time series from a single instrument type and as such plays a key role in ozone trend analyses.Following the approach documented in Frith et al. (2014) to analyze the merging uncertainties in the MOD total ozone record, we use Monte Carlo simulations to estimate the potential for uncertainties in the calibration and drift of individual instruments in the profile ozone merged data set. We focus our discussion on the trends and associated merging uncertainty since 2001 in an effort to verify the start of ozone recovery as predicted by chemistry climate models. We find that merging uncertainty dominates the overall estimated uncertainty when considering only the 15 years of data since 2001. We derive trends versus pressure level for the MOD data set that are positive in the upper stratosphere as expected for ozone recovery. These trends appear to be significant when only statistical uncertainties are included but become not significant at the 2σ level when instrument uncertainties are accounted for. However, when we use the entire data set from 1979 through 2015 and fit to the EESC (equivalent effective stratospheric chlorine) we find statistically significant fits throughout the upper stratosphere at all latitudes. This implies that the ozone profile data remain consistent with our expectation that chlorine is the dominant ozone forcing term.

Description: Past studies have suggested that ozone in the troposphere has increased globally throughout much of the 20th century due to increases in anthropogenic emissions and transport. We show, by combining satellite measurements with a chemical transport model, that during the last four decades tropospheric ozone does indeed indicate increases that are global in nature, yet still highly regional. Satellite ozone measurements from Nimbus-7 and Earth Probe Total Ozone Mapping Spectrometer (TOMS) are merged with ozone measurements from the Aura Ozone Monitoring Instrument/Microwave Limb Sounder (OMI/MLS) to determine trends in tropospheric ozone for 1979–2016. Both TOMS (1979–2005) and OMI/MLS (2005–2016) depict large increases in tropospheric ozone from the Near East to India and East Asia and further eastward over the Pacific Ocean. The 38-year merged satellite record shows total net change over this region of about +6 to +7 Dobson units (DU) (i.e., ∼15 %–20 % of average background ozone), with the largest increase (∼4 DU) occurring during the 2005–2016 Aura period. The Global Modeling Initiative (GMI) chemical transport model with time-varying emissions is used to aid in the interpretation of tropospheric ozone trends for 1980–2016. The GMI simulation for the combined record also depicts the greatest increases of +6 to +7 DU over India and East Asia, very similar to the satellite measurements. In regions of significant increases in tropospheric column ozone (TCO) the trends are a factor of 2–2.5 larger for the Aura record when compared to the earlier TOMS record; for India and East Asia the trends in TCO for both GMI and satellite measurements are ∼+3 DU decade−1 or greater during 2005–2016 compared to about +1.2 to +1.4 DU decade−1 for 1979–2005. The GMI simulation and satellite data also reveal a tropospheric ozone increases in ∼+4 to +5 DU for the 38-year record over central Africa and the tropical Atlantic Ocean. Both the GMI simulation and satellite-measured tropospheric ozone during the latter Aura time period show increases of ∼+3 DU decade−1 over the N Atlantic and NE Pacific.

Description: The quasi-biennial oscillation (QBO) is a quasiperiodic alternation between easterly and westerly zonal winds in the tropical stratosphere, propagating downward from the middle stratosphere to the tropopause with a period that varies from 24 to 32 months ( ∼  28 months on average). The QBO wind oscillations affect the distribution of chemical constituents, such as ozone (O3), water vapor (H2O), nitrous oxide (N2O), and hydrochloric acid (HCl), through the QBO-induced meridional circulation. In the 2015–2016 winter, radiosonde observations revealed an anomaly in the downward propagation of the westerly phase, which was disrupted by the upward displacement of the westerly phase from  ∼  30 hPa up to 15 hPa and the sudden appearance of easterlies at 40 hPa. Such a disruption is unprecedented in the observational record from 1953 to the present. In this study we show the response of trace gases to this QBO disruption using O3, HCl, H2O, and temperature from the Aura Microwave Limb Sounder (MLS) and total ozone measurements from the Solar Backscatter Ultraviolet (SBUV) Merged Ozone Data Set (MOD). Results reveal the development of positive anomalies in stratospheric equatorial O3 and HCl over  ∼  50–30 hPa in May–September of 2016 and a substantial decrease in O3 in the subtropics of both hemispheres. The SBUV observations show near-record low levels of column ozone in the subtropics in 2016, resulting in an increase in the surface UV index during northern summer. Furthermore, cold temperature anomalies near the tropical tropopause result in a global decrease in stratospheric water vapor.

Description: In this work we present evidence that quasi-cyclical perturbations in total ozone (quasi-biennial oscillation – QBO, El Niño–Southern Oscillation – ENSO, and North Atlantic Oscillation – NAO) can be used as independent proxies in evaluating Global Ozone Monitoring Experiment (GOME) 2 aboard MetOp A (GOME-2A) satellite total ozone data, using ground-based (GB) measurements, other satellite data, and chemical transport model calculations. The analysis is performed in the frame of the validation strategy on longer time scales within the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Atmospheric Composition Monitoring (AC SAF) project, covering the period 2007–2016. Comparison of GOME-2A total ozone with ground observations shows mean differences of about -0.7±1.4 % in the tropics (0–30∘), about +0.1±2.1 % in the mid-latitudes (30–60∘), and about +2.5±3.2 % and 0.0±4.3 % over the northern and southern high latitudes (60–80∘), respectively. In general, we find that GOME-2A total ozone data depict the QBO–ENSO–NAO natural fluctuations in concurrence with the co-located solar backscatter ultraviolet radiometer (SBUV), GOME-type Total Ozone Essential Climate Variable (GTO-ECV; composed of total ozone observations from GOME, SCIAMACHY – SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY, GOME-2A, and OMI – ozone monitoring instrument, combined into one homogeneous time series), and ground-based observations. Total ozone from GOME-2A is well correlated with the QBO (highest correlation in the tropics of +0.8) in agreement with SBUV, GTO-ECV, and GB data which also give the highest correlation in the tropics. The differences between deseazonalized GOME-2A and GB total ozone in the tropics are within ±1 %. These differences were tested further as to their correlations with the QBO. The differences had practically no QBO signal, providing an independent test of the stability of the long-term variability of the satellite data. Correlations between GOME-2A total ozone and the Southern Oscillation Index (SOI) were studied over the tropical Pacific Ocean after removing seasonal, QBO, and solar-cycle-related variability. Correlations between ozone and the SOI are on the order of +0.5, consistent with SBUV and GB observations. Differences between GOME-2A and GB measurements at the station of Samoa (American Samoa; 14.25∘ S, 170.6∘ W) are within ±1.9 %. We also studied the impact of the NAO on total ozone in the northern mid-latitudes in winter. We find very good agreement between GOME-2A and GB observations over Canada and Europe as to their NAO-related variability, with mean differences reaching the ±1 % levels. The agreement and small differences which were found between the independently produced total ozone datasets as to the influence of the QBO, ENSO, and NAO show the importance of these climatological proxies as additional tool for monitoring the long-term stability of satellite–ground-truth biases.

Description: Sensors on satellites provide unprecedented understanding of the Earth's climate system by measuring incoming solar radiation, as well as both passive and active observations of the entire Earth with outstanding spatial and temporal coverage. A common challenge with satellite observations is to quantify their ability to provide well-calibrated, long-term, stable records of the parameters they measure. Ground-based intercomparisons offer some insight, while reference observations and internal calibrations give further assistance for understanding long-term stability. A valuable tool for evaluating and developing long-term records from satellites is the examination of data from overlapping satellite missions. This paper addresses how the length of overlap affects the ability to identify an offset or a drift in the overlap of data between two sensors. Ozone and temperature data sets are used as examples showing that overlap data can differ by latitude and can change over time. New results are presented for the general case of sensor overlap by using Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) solar irradiance data as an example. To achieve a 1 % uncertainty in estimating the offset for these two instruments' measurement of the Mg II core (280 nm) requires approximately 5 months of overlap. For relative drift to be identified within 0.1 % yr−1 uncertainty (0.00008 W m−2 nm−1 yr−1), the overlap for these two satellites would need to be 2.5 years. Additional overlap of satellite measurements is needed if, as is the case for solar monitoring, unexpected jumps occur adding uncertainty to both offsets and drifts; the additional length of time needed to account for a single jump in the overlap data may be as large as 50 % of the original overlap period in order to achieve the same desired confidence in the stability of the merged data set. Results presented here are directly applicable to satellite Earth observations. Approaches for Earth observations offer additional challenges due to the complexity of the observations, but Earth observations may also benefit from ancillary observations taken from ground-based and in situ sources. Difficult choices need to be made when monitoring approaches are considered; we outline some attempts at optimizing networks based on economic principles. The careful evaluation of monitoring overlap is important to the appropriate application of observational resources and to the usefulness of current and future observations.