The Michelson Interferometer for Passive Atmospheric Sounding global climatology of BrONO₂ 2002–2012: a test for stratospheric bromine chemistry

We present the first observational dataset of vertically resolved global stratospheric BrONO2 distributions from July 2002 until April 2012 and compare them to results of the atmospheric chemical climate model ECHAM/MESSy Atmospheric Chemistry (EMAC). The retrieved distributions are based on space-borne measurements of infrared limb-emission spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat. The derived vertical profiles of BrONO2 volume mixing ratios represent 10∘ latitude bins and 3 d means, separated into sunlit observations and observations in the dark. The estimated uncertainties are around 1–4 pptv, caused by spectral noise for single profiles as well as for further parameter and systematic errors which may not improve by averaging. Vertical resolutions range from 3 to 8 km between 15 and 35 km altitude. All leading modes of spatial and temporal variability of stratospheric BrONO2 in the observations are well replicated by the model simulations: the large diurnal variability, the low values during polar winter as well as the maximum values at mid and high latitudes during summer. Three major differences between observations and model results are observed: (1) a model underestimation of enhanced BrONO2 in the polar winter stratosphere above about 30 km of up to 15 pptv, (2) up to 8 pptv higher modelled values than observed globally in the lower stratosphere up to 25 km, most obvious during night, and (3) up to 5 pptv lower modelled concentrations at tropical latitudes between 27 and 32 km during sunlit conditions. (1) is explained by the model missing enhanced NOx produced in the mesosphere and lower thermosphere subsiding at high latitudes in winter. This is the first time that observational evidence for enhancement of BrONO2 caused by mesospheric NOx production is reported. The other major inconsistencies (2, 3) between EMAC model results and observations are studied by sensitivity runs with a 1D model. These tentatively hint at a model underestimation of heterogeneous loss of BrONO2 in the lower stratosphere, a simulated production of BrONO2 that is too low during the day as well as strongly underestimated BrONO2 volume mixing ratios when loss via reaction with O(3P) is considered in addition to photolysis. However, considering the uncertainty ranges of model parameters and of measurements, an unambiguous identification of the causes of the differences remains difficult. The observations have also been used to derive the total stratospheric bromine content relative to years of stratospheric entry between 1997 and 2007. With an average value of 21.2±1.4 pptv of Bry at mid latitudes where the modelled adjustment from BrONO2 to Bry is smallest, the MIPAS data agree with estimates of Bry derived from observations of BrO as well as from MIPAS-Balloon measurements of BrONO2.

The global and multi-annual MUSICA IASI {H₂O, <i>δ</i>D} pair dataset

We present a global and multi-annual space-borne dataset of tropospheric {H2O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) on board the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in Schneider et al. (2021b). From the independently retrieved H2O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset, we generate an optimal estimation product for pairs of H2O and δD. Here, this standard MUSICA method for deriving {H2O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {H2O, δD} pair dataset for the whole period from October 2014 to December 2020 with global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1500 million individually processed observations. The retrievals are most sensitive to variations in {H2O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H2O, δD} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but higher latitudes also show a considerable amount of reliable data. Exemplary time series over the tropical Atlantic and West Africa are chosen to illustrate the potential of the MUSICA IASI {H2O, δD} pair data for atmospheric moisture pathway studies. Furthermore, in order to facilitate the application of this rather comprehensive MUSICA IASI {H2O, δD} pair dataset (referred to as Level-2), we additionally provide the data in a re-gridded and simplified format (Level-3) with focus on the quality-filtered {H2O, δD} pairs in the free troposphere. A technical documentation for guiding the use of both datasets is attached as the Supplement. Finally, the Level-2 dataset is referenced with the DOI https://doi.org/10.35097/415 (Diekmann et al., 2021a) and the Level-3 dataset with DOI https://doi.org/10.35097/495 (Diekmann et al., 2021b).

Research and Optimization of Meteo-Particle Model for Wind Retrieval

As the aviation industry has entered a critical period of development, the demand for Automatic Dependent Surveillance Broadcast (ADS-B) technology is becoming increasingly urgent. Real-time detection of aviation wind field information and the early warning of wind field shear by atmospheric sounding system are two important factors related to the safe operation of aviation and airport. According to the advantages of ADS-B and Mode S data, this paper uses the Meteo-Particle (MP) model proposed by Sun et al., in their previous research to retrieve high-altitude wind field. Comparing the precision and accuracy of wind field retrieved results, and the optimization parameters of MP model suitable for meteorological model are further studied. To solve the problem of incomplete wind field coverage obtained by retrieval, an extrapolation algorithm of wind field is proposed. The results show that: (1) a comprehensive evaluation index is introduced, which can more effectively evaluate the comprehensive difference of wind field retrieval results in wind speed and direction. (2) The adaptability results of MP model in different periods and altitudes provide some reference for the research of other scholars. (3) The new parameter setting can improve the accuracy of the retrieved results, and the appropriate extrapolation of wind field fills in the blank part of aviation and meteorology.

Quantification of CH₄ emissions from waste disposal sites near the city of Madrid using ground- and space-based observations of COCCON, TROPOMI and IASI

The objective is to derive methane (CH4) emissions of the metropolitan city Madrid Spain from the CH4 enhancements seen by the space-borne and the ground-based instruments. This study applies satellite-based measurements from the TROPOspheric Monitoring Instrument (TROPOMI) and the Infrared Atmospheric Sounding Interferometer (IASI) together with measurements from the ground-based COllaborative Carbon Column Observing Network (COCCON) instruments. In 2018, a two-week field campaign for measuring the atmospheric concentrations of greenhouse gases was performed in Madrid in the framework of Monitoring greenhousE Gas EmIssions of Madrid city (MEGEI-MAD) project. Five COCCON instruments were deployed at different locations around the Madrid city center enabling the observation of total column averaged CH4 mixing ratios (XCH4). Using available wind data, the differences between CH4 columns observed at these locations allow to estimate the emissions emerging from the surrounded area. In addition, based on the dominating wind direction in the Madrid region, we calculate the difference of the satellite data maps for two opposite wind regimes (northeast – southwest, NE – SW). In the following, we refer to the resultant signal as the wind-assigned anomaly. We use TROPOMI tropospheric nitrogen dioxide (NO2) observations as a test to verify our method of wind-assigned anomaly and its implementation, taking advantage of the much better detectability of the plume due to the short lifetime and low background concentrations of NO2. Pronounced bipolar plumes are found along NE and SW wind direction, which implies that our method of wind-assigned anomaly is working as expected. The wind-assigned TROPOMI XCH4 anomaly shows much weaker symmetric plumes than NO2 due to the long lifetime of CH4 and in consequence a high accumulated background of CH4 in the atmosphere. The wind-assigned plume method is also applied to the tropospheric and upper tropospheric/stratospheric column averaged CH4 mixing ratio products (in the following referred to as TXCH4 and UTSXCH4) derived from a-posteriori merged Infrared Atmospheric Sounding Interferometer (IASI) profile and TROPOMI total column data. Based on the NE and SW wind fields, we developed a simple plume model locating the source at three waste disposal sites east of Madrid for CH4. As CH4 emission strength we estimate 7.4 × 1025 ± 6.4 × 1024 molec s−1 from the TROPOMI XCH4 data and 7.1 × 1025 ± 1.0 × 1025 molec s−1 from the TROPOMI&amp;IASI merged TXCH4 data. The COCCON observations indicate a weaker CH4 emission strength of around 3.7 × 1025 molec s−1 from local source (near to the Valdemingómez waste plant) in accordance with observations in a single day and. All emission rates estimated from the different observations are significantly larger than the emission rates provided via the official Spanish Register of Emissions and Pollutant Sources.

Optimal ash particle refractive index model for simulating the brightness temperature spectrum of volcanic ash clouds from satellite infrared sounder measurements

Using data from the Infrared Atmospheric Sounding Interferometer (IASI) measurements of volcanic ash clouds and radiative transfer calculations, we identify the optimal refractive index model for simulating the measured brightness temperature spectrum of volcanic ash material. We assume that the optimal refractive index model has the smallest root mean square of the brightness temperature difference between measurements and simulations for channels in the wavenumber range of 750–1400 cm−1 and compare 21 refractive index models for optical properties of ash particles, including recently published models. From the results of numerical simulations for 164 pixels of IASI measurements for ash clouds from 11 volcanoes, we found that the measured brightness temperature spectrum could be well simulated using certain newly established refractive index models. In the cases of Eyjafjallajökull and Grímsvötn ash clouds, the optimal refractive index models determined through numerical simulation correspond to those deduced from the chemical composition of ash samples for the same volcanic eruption events. This finding suggests that infrared sounder measurement of volcanic ash clouds is an effective approach to estimating the optimal refractive index model. However, discrepancies between the estimated refractive index models based on satellite measurements and the associated volcanic rock types were observed for some volcanic events.

Comparison of annual changes of zenith tropospheric delay components, calculated according to the atmospheric sounding data and by analytical model

The aim of this work is to study the zenith tropospheric delay components fluctuations according to the atmospheric sounding data and analytical model in selected period and accuracy assessment of Saastamoinen model. Methodology. The main methods for calculation ZTD are atmospheric sounding and using analytical models. To study ZTD components we use atmospheric sounding data conducted at 4 Ukrainian upper air stations (Kyiv, Kharkiv, Lviv, Odesa) with 24 hours frequency, as well as near-surface atmospheric variables provided by weather stations with 3 hours frequency in the period from January 1 to December 31, 2019. ZTD components were calculated by integration using sounding data, and using Saastamoinen’s formulas. Based on the calculated data, created graphs comparing the values of sounding and model. Calculated the standard error of Saastamoinen model. Results. Compared ZTD components at points, located in different climatic zones, using the atmospheric pressure reduced to sea level. Both ZDD and ZWD are the largest at Odesa station. Annual fluctuation of ZDD are 8–20 mm and ZWD fluctuations are 75–95 mm. The daily amplitudes of ZDD are 5–6 mm in summer and 12–13 mm in winter. The daily amplitudes of ZWD are 20–30 mm in summer and 6–8 mm in winter. The standard error of Saastamoinen’s model is 7 mm for ZDD and 22 mm for ZWD. Scientific novelty and practical significance in that the study can improve accuracy and evaluate the feasibility of using different methods for calculating ZTD, see the dynamic of change ZDD and ZWD and their behavior over a long period. The results can be used for further studies of ZTD and improving the accuracy of satellite observations.

The MUSICA IASI {H₂O, δD} pair product

We present a global and multi-annual space-borne dataset of tropospheric {H2O, δD} pairs that is based on radiance measurements from the nadir thermal infrared sensor IASI (Infrared Atmospheric Sounding Interferometer) onboard the Metop satellites of EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites). This dataset is an a posteriori processed extension of the MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) IASI full product dataset as presented in Schneider et al. (2021b). From the independently retrieved H2O and δD proxy states, their a priori settings and constraints, and their error covariances provided by the IASI full product dataset we generate an optimal estimation product for pairs of H2O and δD. Here, this standard MUSICA method for deriving {H2O, δD} pairs is extended using an a posteriori reduction of the constraints for improving the retrieval sensitivity at dry conditions. By applying this improved water isotopologue post-processing for all cloud-free MUSICA IASI retrievals, this yields a {H2O, δD} pair dataset for the whole period from October 2014 to June 2019 with a global coverage twice per day (local morning and evening overpass times). In total, the dataset covers more than 1200 million individually processed observations. The retrievals are most sensitivity to variations of {H2O, δD} pairs within the free troposphere, with up to 30 % of all retrievals containing vertical profile information in the {H2O, δD} pair product. After applying appropriate quality filters, the largest number of reliable pair data arises for tropical and subtropical summer regions, but also for higher latitudes there is a considerable amount of reliable data. Exemplary time-series over the Tropical Atlantic and West Africa are chosen to illustrates the potential of the MUSICA IASI {H2O, δD} pair data for atmospheric moisture pathway studiess. Finally, the dataset is referenced with the DOI 10.35097/415 (Diekmann et al., 2021).

Change of CO Concentration Due to the COVID-19 Lockdown in China Observed by Surface and Satellite Observations

The nationwide lockdown due to the COVID-19 pandemic in 2020 reduced industrial and human activities in China. In this study, we investigate atmospheric carbon monoxide (CO) concentration changes during the lockdown from observations at the surface and from two satellites (TROPOspheric Monitoring Instrument (TROPOMI) and Infrared Atmospheric Sounding Interferometer (IASI)). It is found that the average CO surface concentration in 2020 was close to that in 2019 before the lockdown, and became 18.7% lower as compared to 2019 during the lockdown. The spatial variation of the change in the CO surface concentration is high, with an 8–27% reduction observed for Beijing, Shanghai, Chengdu, Zhengzhou, and Guangzhou, and almost no change in Wuhan. The TROPOMI and IASI satellite observations show that the CO columns decreased by 2–13% during the lockdown in most regions in China. However in South China, there was an 8.8% increase in the CO columns observed by TROPOMI and a 36.7% increase observed by IASI, which is contrary to the 23% decrease in the surface CO concentration. The enhancement of the CO column in South China is strongly affected by the fire emissions transported from Southeast Asia. This study provides an insight into the impact of COVID-19 on CO concentrations both at the surface and in the columns in China, and it can be extended to evaluate other areas using the same approach.