Validation of Copernicus Sentinel-3/OLCI Level 2 Land Integrated Water Vapour product

Validation of the Integrated Water Vapour (IWV) from Sentinel-3 Ocean and Land Colour Instrument (OLCI) was performed as a part of the “ESA/Copernicus Space Component Validation for Land Surface Temperature, Aerosol Optical Depth and Water Vapour Sentinel-3 Products” (LAW) project. High-spatial-resolution IWV observations in the near-infrared spectral region from the OLCI instruments aboard the Sentinel-3A and Sentinel-3B satellites provide continuity with observations from MERIS (Medium Resolution Imaging Spectrometer). The IWV was compared with reference observations from two networks: GNSS (Global Navigation Satellite System) precipitable water vapour from the SuomiNet network and integrated lower tropospheric columns from radio-soundings from the IGRA (Integrated Radiosonde Archive) database. Results for cloud-free matchups over land show a wet bias of 7 %–10 % for OLCI, with a high correlation against the reference observations (0.98 against SuomiNet and 0.90 against IGRA). Both OLCI-A and OLCI-B instruments show almost identical results, apart from an anomaly observed in camera 3 of the OLCI-B instrument, where observed biases are lower than in other cameras in either instrument. The wavelength drift in sensors was investigated, and biases in different cameras were found to be independent of wavelength. Effect of cloud proximity was found to have almost no effect on observed biases, indicating that cloud flagging in the OLCI IWV product is sufficiently reliable. We performed validation of random uncertainty estimates and found them to be consistent with the statistical a posteriori estimates, but somewhat higher

A method for random uncertainties validation and probing the natural variability with application to TROPOMI on board Sentinel-5P total ozone measurements

In this paper, we discuss the method for validation of random uncertainties in the remote sensing measurements based on evaluation of the structure function, i.e., root-mean-square differences as a function of increasing spatiotemporal separation of the measurements. The limit at the zero mismatch provides the experimental estimate of random noise in the data. At the same time, this method allows probing of the natural variability of the measured parameter. As an illustration, we applied this method to the clear-sky total ozone measurements by the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5P satellite. We found that the random uncertainties reported by the TROPOMI inversion algorithm, which are in the range 1–2 DU, agree well with the experimental uncertainty estimates by the structure function. Our analysis of the structure function has shown the expected results on total ozone variability: it is significantly smaller in the tropics compared to mid-latitudes. At mid-latitudes, ozone variability is much larger in winter than in summer. The ozone structure function is anisotropic (being larger in the latitudinal direction) at horizontal scales larger than 10–20 km. The structure function rapidly grows with the separation distance. At mid-latitudes in winter, the ozone values can differ by 5 % at separations 300–500 km. The method discussed is a powerful tool in experimental estimates of the random noise in data and studies of natural variability, and it can be used in various applications.Peer reviewe

MIPAS observations of ozone in the middle atmosphere

This work is distributed under the Creative Commons Attribution 4.0 License.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 from 2005 until April 2012. O is retrieved from microwindows in the 14.8 and 10 μm spectral regions and requires non-local thermodynamic equilibrium (non-LTE) modelling of the O and 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 O 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 O 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 O air-broadened half-widths of the 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 O 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 O has a positive bias of ∼10 %, which is possibly caused in part by O spectroscopic errors in the 10 μm region. Between 75 and 90 km, MIPAS nighttime O is in agreement with other instruments by 10 %, but for daytime the agreement is slightly larger, ∼10-20 %. Above 90 km, MIPAS daytime O 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 O distributions as function of altitude, latitude, and time, showing the major O 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 O at 90 km shows a solar signature in phase with the solar cycle. © Author(s) 2018.The IAA team was supported by the Spanish MICINN under the project ESP2014-54362-P and EC FEDER funds. The IAA and IMK teams were partially supported by ESA O3-CCI and MesosphEO projects. Maya Garcia-Comas was financially supported by MINECO through its >Ramon y Cajal> subprogram. Funding for the Atmospheric Chemistry Experiment comes primarily from the Canadian Space Agency. Work at the Jet Propulsion Laboratory was performed under contract with the National Aeronautics and Space Administration

Updated merged SAGE-CCI-OMPS+ dataset for the evaluation of ozone trends in the stratosphere

In this paper, we present the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments – SAGE II (Stratospheric Aerosol and Gases Experiment II), OSIRIS (Optical Spectrograph and InfraRed Imaging System), MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), SCIAMACHY (SCanning Imaging Spectrometer for Atmospheric CHartographY), GOMOS (Global Ozone Monitoring by Occultation of Stars), ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer), OMPS-LP (Ozone Monitor Profiling Suite Limb Profiler), POAM (Polar Ozone and Aerosol Measurement) III, and SAGE III/ISS (Stratospheric Aerosol and Gases Experiment III on the International Space Station). Compared to the original version of the SAGE-CCI-OMPS dataset (Sofieva et al., 2017b), the update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP). In this paper, we show detailed intercomparisons of ozone profiles from different instruments and data versions, with a focus on the detection of possible drifts in the datasets. The SAGE-CCI-OMPS+ dataset has a better coverage of polar regions and of the upper troposphere and the lower stratosphere (UTLS) than the previous dataset. We also studied the influence of including new datasets on ozone trends, which are estimated using multiple linear regression. The changes in the merged dataset do not change the overall morphology of post-1997 ozone trends; statistically significant trends are observed in the upper stratosphere. The largest changes in ozone trends are observed in polar regions, especially in the Southern Hemisphere

Updated trends of the stratospheric ozone vertical distribution in the 60° S–60° N latitude range based on the LOTUS regression model

This study presents an updated evaluation of stratospheric ozone profile trends in the 60° S–60° N latitude range over the 2000–2020 period using an updated version of the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) regression model that was used to evaluate such trends up to 2016 for the last WMO Ozone Assessment (2018). In addition to the derivation of detailed trends as a function of latitude and vertical coordinates, the regressions are performed with the datasets averaged over broad latitude bands, i.e. 60–35° S, 20° S–20° N and 35–60° N. The same methodology as in the last assessment is applied to combine trends in these broad latitude bands in order to compare the results with the previous studies. Longitudinally resolved merged satellite records are also considered in order to provide a better comparison with trends retrieved from ground-based records, e.g. lidar, ozonesondes, Umkehr, microwave and Fourier transform infrared (FTIR) spectrometers at selected stations where long-term time series are available. The study includes a comparison with trends derived from the REF-C2 simulations of the Chemistry Climate Model Initiative (CCMI-1). This work confirms past results showing an ozone increase in the upper stratosphere, which is now significant in the three broad latitude bands. The increase is largest in the Northern and Southern Hemisphere midlatitudes, with ∼2.2 ± 0.7 % per decade at ∼2.1 hPa and ∼2.1 ± 0.6 % per decade at ∼3.2 hPa respectively compared to ∼1.6 ± 0.6 % per decade at ∼2.6 hPa in the tropics. New trend signals have emerged from the records, such as a significant decrease in ozone in the tropics around 35 hPa and a non-significant increase in ozone in the southern midlatitudes at about 20 hPa. Non-significant negative ozone trends are derived in the lowermost stratosphere, with the most pronounced trends in the tropics. While a very good agreement is obtained between trends from merged satellite records and the CCMI-1 REF-C2 simulation in the upper stratosphere, observed negative trends in the lower stratosphere are not reproduced by models at southern and, in particular, at northern midlatitudes, where models report an ozone increase. However, the lower-stratospheric trend uncertainties are quite large, for both measured and modelled trends. Finally, 2000–2020 stratospheric ozone trends derived from the ground-based and longitudinally resolved satellite records are in reasonable agreement over the European Alpine and tropical regions, while at the Lauder station in the Southern Hemisphere midlatitudes they show some differences

Updated trends of the stratospheric ozone vertical distribution in the 60° S–60° N latitude range based on the LOTUS regression model

peer reviewedAbstract. This study presents an updated evaluation of stratospheric ozone profile trends in the 60∘ S–60º N latitude range over the 2000–2020 period using an updated version of the Long-term Ozone Trends and Uncertainties in the Stratosphere (LOTUS) regression model that was used to evaluate such trends up to 2016 for the last WMO Ozone Assessment (2018). In addition to the derivation of detailed trends as a function of latitude and vertical coordinates, the regressions are performed with the datasets averaged over broad latitude bands, i.e. 60–35º S, 20º S–20º N and 35–60º N. The same methodology as in the last assessment is applied to combine trends in these broad latitude bands in order to compare the results with the previous studies. Longitudinally resolved merged satellite records are also considered in order to provide a better comparison with trends retrieved from ground-based records, e.g. lidar, ozonesondes, Umkehr, microwave and Fourier transform infrared (FTIR) spectrometers at selected stations where long-term time series are available. The study includes a comparison with trends derived from the REF-C2 simulations of the Chemistry Climate Model Initiative (CCMI-1). This work confirms past results showing an ozone increase in the upper stratosphere, which is now significant in the three broad latitude bands. The increase is largest in the Northern and Southern Hemisphere midlatitudes, with ∼2.2 ± 0.7 % per decade at ∼2.1 hPa and ∼2.1 ± 0.6 % per decade at ∼3.2 hPa respectively compared to ∼1.6 ± 0.6 % per decade at ∼2.6 hPa in the tropics. New trend signals have emerged from the records, such as a significant decrease in ozone in the tropics around 35 hPa and a non-significant increase in ozone in the southern midlatitudes at about 20 hPa. Non-significant negative ozone trends are derived in the lowermost stratosphere, with the most pronounced trends in the tropics. While a very good agreement is obtained between trends from merged satellite records and the CCMI-1 REF-C2 simulation in the upper stratosphere, observed negative trends in the lower stratosphere are not reproduced by models at southern and, in particular, at northern midlatitudes, where models report an ozone increase. However, the lower-stratospheric trend uncertainties are quite large, for both measured and modelled trends. Finally, 2000–2020 stratospheric ozone trends derived from the ground-based and longitudinally resolved satellite records are in reasonable agreement over the European Alpine and tropical regions, while at the Lauder station in the Southern Hemisphere midlatitudes they show some differences

State of the climate in 2018

In 2018, the dominant greenhouse gases released into Earth’s atmosphere—carbon dioxide, methane, and nitrous oxide—continued their increase. The annual global average carbon dioxide concentration at Earth’s surface was 407.4 ± 0.1 ppm, the highest in the modern instrumental record and in ice core records dating back 800 000 years. Combined, greenhouse gases and several halogenated gases contribute just over 3 W m−2 to radiative forcing and represent a nearly 43% increase since 1990. Carbon dioxide is responsible for about 65% of this radiative forcing. With a weak La Niña in early 2018 transitioning to a weak El Niño by the year’s end, the global surface (land and ocean) temperature was the fourth highest on record, with only 2015 through 2017 being warmer. Several European countries reported record high annual temperatures. There were also more high, and fewer low, temperature extremes than in nearly all of the 68-year extremes record. Madagascar recorded a record daily temperature of 40.5°C in Morondava in March, while South Korea set its record high of 41.0°C in August in Hongcheon. Nawabshah, Pakistan, recorded its highest temperature of 50.2°C, which may be a new daily world record for April. Globally, the annual lower troposphere temperature was third to seventh highest, depending on the dataset analyzed. The lower stratospheric temperature was approximately fifth lowest. The 2018 Arctic land surface temperature was 1.2°C above the 1981–2010 average, tying for third highest in the 118-year record, following 2016 and 2017. June’s Arctic snow cover extent was almost half of what it was 35 years ago. Across Greenland, however, regional summer temperatures were generally below or near average. Additionally, a satellite survey of 47 glaciers in Greenland indicated a net increase in area for the first time since records began in 1999. Increasing permafrost temperatures were reported at most observation sites in the Arctic, with the overall increase of 0.1°–0.2°C between 2017 and 2018 being comparable to the highest rate of warming ever observed in the region. On 17 March, Arctic sea ice extent marked the second smallest annual maximum in the 38-year record, larger than only 2017. The minimum extent in 2018 was reached on 19 September and again on 23 September, tying 2008 and 2010 for the sixth lowest extent on record. The 23 September date tied 1997 as the latest sea ice minimum date on record. First-year ice now dominates the ice cover, comprising 77% of the March 2018 ice pack compared to 55% during the 1980s. Because thinner, younger ice is more vulnerable to melting out in summer, this shift in sea ice age has contributed to the decreasing trend in minimum ice extent. Regionally, Bering Sea ice extent was at record lows for almost the entire 2017/18 ice season. For the Antarctic continent as a whole, 2018 was warmer than average. On the highest points of the Antarctic Plateau, the automatic weather station Relay (74°S) broke or tied six monthly temperature records throughout the year, with August breaking its record by nearly 8°C. However, cool conditions in the western Bellingshausen Sea and Amundsen Sea sector contributed to a low melt season overall for 2017/18. High SSTs contributed to low summer sea ice extent in the Ross and Weddell Seas in 2018, underpinning the second lowest Antarctic summer minimum sea ice extent on record. Despite conducive conditions for its formation, the ozone hole at its maximum extent in September was near the 2000–18 mean, likely due to an ongoing slow decline in stratospheric chlorine monoxide concentration. Across the oceans, globally averaged SST decreased slightly since the record El Niño year of 2016 but was still far above the climatological mean. On average, SST is increasing at a rate of 0.10° ± 0.01°C decade−1 since 1950. The warming appeared largest in the tropical Indian Ocean and smallest in the North Pacific. The deeper ocean continues to warm year after year. For the seventh consecutive year, global annual mean sea level became the highest in the 26-year record, rising to 81 mm above the 1993 average. As anticipated in a warming climate, the hydrological cycle over the ocean is accelerating: dry regions are becoming drier and wet regions rainier. Closer to the equator, 95 named tropical storms were observed during 2018, well above the 1981–2010 average of 82. Eleven tropical cyclones reached Saffir–Simpson scale Category 5 intensity. North Atlantic Major Hurricane Michael’s landfall intensity of 140 kt was the fourth strongest for any continental U.S. hurricane landfall in the 168-year record. Michael caused more than 30 fatalities and $25 billion (U.S. dollars) in damages. In the western North Pacific, Super Typhoon Mangkhut led to 160 fatalities and$6 billion (U.S. dollars) in damages across the Philippines, Hong Kong, Macau, mainland China, Guam, and the Northern Mariana Islands. Tropical Storm Son-Tinh was responsible for 170 fatalities in Vietnam and Laos. Nearly all the islands of Micronesia experienced at least moderate impacts from various tropical cyclones. Across land, many areas around the globe received copious precipitation, notable at different time scales. Rodrigues and Réunion Island near southern Africa each reported their third wettest year on record. In Hawaii, 1262 mm precipitation at Waipā Gardens (Kauai) on 14–15 April set a new U.S. record for 24-h precipitation. In Brazil, the city of Belo Horizonte received nearly 75 mm of rain in just 20 minutes, nearly half its monthly average. Globally, fire activity during 2018 was the lowest since the start of the record in 1997, with a combined burned area of about 500 million hectares. This reinforced the long-term downward trend in fire emissions driven by changes in land use in frequently burning savannas. However, wildfires burned 3.5 million hectares across the United States, well above the 2000–10 average of 2.7 million hectares. Combined, U.S. wildfire damages for the 2017 and 2018 wildfire seasons exceeded $40 billion (U.S. dollars)

Anisotropy of small-scale stratospheric irregularities retrieved from scintillations of a double star α-Cru observed by GOMOS/ENVISAT

In this paper, we discuss estimating anisotropy of air density irregularities (ratio of characteristic horizontal and vertical scales) from satellite observations of bi-chromatic scintillations of a double star whose components are not resolved by the detector. The analysis is based on fitting experimental auto- and cross-spectra of scintillations by those computed using the 3-D spectral model of atmospheric irregularities consisting of anisotropic and isotropic components. Application of the developed method to the scintillation measurements of the double star α-Cru by GOMOS (Global Ozone Monitoring by Occultation of Stars) fast photometers results in estimates of anisotropy coefficient of ~15-20 at altitudes 30-38 km, as well as other parameters of atmospheric irregularities. The obtained estimates of the anisotropy coefficient correspond to small-scale irregularities, close to the buoyancy scale

Variable anisotropy of small-scale stratospheric irregularities retrieved from stellar scintillation measurements by GOMOS/Envisat

In this paper, we consider possibilities for studying the anisotropy of small-scale air density irregularities using satellite observations of bi-chromatic stellar scintillations during tangential occultations. Estimation of the anisotropy coefficient (the ratio of the characteristic horizontal to vertical scales) and other atmospheric parameters is based on the comparison of simulated/theoretical and experimental auto-spectra and coherency spectra of scintillation. Our analyses exploit a 3-D model of the spectrum of atmospheric inhomogeneities, which consists of anisotropic and isotropic components. For the anisotropic component, a spectral model with variable anisotropy is used. Using stellar scintillation measurements by GOMOS (Global Ozone Monitoring by Occultation of Stars) fast photometers, estimates of the anisotropy coefficient are obtained for atmospheric irregularities with vertical scales of 8-55 m at altitudes of 43-30 km. It is shown that the anisotropy increases from about 10 to 50 with increasing vertical scales