Retrieval of Metop-A/IASI N2O Profiles and Validation with NDACC FTIR Data

A Comparative Analysis of Satellite-Derived CO Retrievals During the 2020 Wildfires in North America

In September 2020, the Western United States experienced anomalously severe wildfires that resulted in carbon monoxide (CO) emissions almost three times the 2001-2019 average. In this study, we investigate the influence of wildfires on atmospheric carbon monoxide (CO) variability through a comparative analysis of observations from the Measurements of Pollution in the Troposphere (MOPITT), the Infrared Atmospheric Sounding Interferometer (IASI), and the Tropospheric Monitoring Instrument (TROPOMI). Our focus is on the North American domain, aiming to understand the differences among these products. In general, all instruments show excellent agreement under typical atmospheric CO conditions. However, notable discrepancies were observed in the CO data from the three sensors, particularly in regions with elevated CO total column (TC) values. IASI and TROPOMI consistently showed higher CO values over the western U.S. compared to MOPITT. During the fire episodes, we found that the IASI retrievals suggested higher CO abundances near the surface than the MOPITT thermal infrared retrievals that are probably the result of the differences in the covariance matrices used in IASI and MOPITT retrievals. We also found that the high IASI and TROPOMI CO observations over the western U.S. coincided with high values of the TROPOMI aerosol index (AI), suggesting the presence of absorbing aerosols. The analysis exhibited better agreement between TROPOMI and MOPITT CO TC when the AI values were low. Our results suggest that appropriate quality filtering should be employed when analyzing pollution events with these data. In particular, utilizing the AI for quality filtering may be useful when analyzing extreme pollution events with these satellite products.

A 1-D model to retrieve the vertical profiles of minor atmospheric constituents for cloud microphysical modelling: III. Disturbed weather situations

A hybrid Monte-Carlo Gear solver developed earlier has been improvised to retrieve the vertical profiles of CH4 and N2O during disturbed weather situations such as western disturbances, tropical cyclones, and heavy rainfall events over the megacities: Delhi, Kolkata, Chennai, and Mumbai. Due to rapid changes in the temperature during the passage of these systems over megacities, the percentage differences of CH4 and N2O number concentrations were more compared to the Community Long-term Infrared Microwave Coupled Atmospheric Product System (CLIMCAPS). Therefore, the hybrid solver has been modified by improving maximum likelihood estimates of vertical temperature profiles. The number concentrations of CH4 and N2O during these weather events since 2012 are obtained from the CLIMCAPS dataset for bias correction. It is found that the modified methodology has improved the retrieval of CH4 and N2O vertical profiles by reducing the error percentages during daytime and nighttime over these megacities. The percentage error in estimated number concentrations of CH4 and N2O significantly reduced during (i) the passage of the western disturbance and rainy days of August 2020 over Delhi; (ii) the rainy days of June 2020 over Kolkata; (iii) the influence of supercyclonic storm Amphan (24 and 25 Nov 2020) over Chennai and (iv) rainy days of July 2020 over Mumbai. Implementing this solver in the global model may retrieve the number concentrations more accurately.

Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm Description, Application to 10 Years of IASI Observations and Quality Assessment

Nitrous oxide (N2O) is the third most abundant anthropogenous greenhouse gas (after carbon dioxide and methane), with a long atmospheric lifetime and a continuously increasing concentration due to human activities, making it an important gas to monitor. In this work, we present a new method to retrieve N2O concentration profiles (with up to two degrees of freedom) from each cloud-free satellite observation by the Infrared Atmospheric Sounding Interferometer (IASI), using spectral micro-windows in the N2O ν3 band, the Radiative Transfer for TOVS (RTTOV) tools and the Tikhonov regularization scheme. A time series of ten years (2011–2020) of IASI N2O profiles and integrated partial columns has been produced and validated with collocated ground-based Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) data. The importance of consistency in the ancillary data used for the retrieval for generating consistent time series has been demonstrated. The Nitrous Oxide Profiling from Infrared Radiances (NOPIR) N2O partial columns are of very good quality, with a positive bias of 1.8 to 4% with respect to the ground-based data, which is less than the sum of uncertainties of the compared values. At high latitudes, the comparisons are a bit worse, due to either a known bias in the ground-based data, or to a higher uncertainty in both ground-based and satellite retrievals.

Evaluation and Global-Scale Observation of Nitrous Oxide from IASI on Metop-A

Nitrous oxide (N2O) is a greenhouse gas difficult to estimate by satellite because of its weak spectral signature in the infra-red band and its low variability in the troposphere. Nevertheless, this study presents the evaluation of new tropospheric N2O observations from the Infrared Atmospheric Sounder Interferometer (IASI) on Metop-A using the Toulouse N2O Retrieval Version 2.0 tool. This tool is based on the Radiative Transfer for Tiros Operational Vertical sounder (RTTOV) model version 12.3 coupled to the Levenberg-Marquardt optimal estimation method enabling the simultaneous retrieval of methane, water vapour, temperature profiles together with surface temperature and emissivity within the 1240–1350 cm−1 window. In this study, we focused on the upper troposphere (300 hPa) where the sensitivity of IASI is significant. The IASI N2O data has been evaluated using aircraft N2O observations from the High-performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations (HIPPO) campaigns in 2009, 2010, and 2011 and from the National Oceanic and Atmospheric Administration’s (NOAA) Global Greenhouse Gas Reference Network (GGGRN) in 2011. In addition, we evaluated the IASI N2O using ground-based N2O measurements from 9 stations belonging to the Network for the Detection of Atmospheric Composition Change (NDACC). We found a total random error of ∼2 ppbv (0.6%) for one single retrieval at 300 hPa. Under favorable conditions, this error is also found in the vertical level pressure range 300–500 hPa. It decreases rapidly to ∼0.4 ppbv (0.1%) when we average on a 1° × 1° box. In addition, independent observations allows the estimation of bias with the IASI TN2OR v2.0 N2O. The bias between IASI and aircraft N2O data at 300 hPa is ∼1.0 ppbv (∼0.3%). We found an estimated random error of ∼2.3 ppbv (∼0.75%). This study also shows relatively high correlations between IASI data and aircraft in situ profiles but more varying correlations over the year 2011 depending on the location between IASI and NDACC remote sensing data. Finally, we present daily, monthly, and seasonal IASI N2O horizontal distributions in the upper troposphere as well as cross sections for different seasons that exhibit maxima in the Tropical band especially over Africa and South America.