Evaluating the Performance of Ozone Products Derived from CrIS/NOAA20, AIRS/Aqua and ERA5 Reanalysis in the Polar Regions in 2020 Using Ground-Based Observations

Quantifying spatiotemporal polar ozone changes can promote our understanding of global stratospheric ozone depletion, polar ozone-related chemical processes, and atmospheric dynamics. By means of ground-level measurements, satellite observations, and re-analyzed meteorology, the global spatial and temporal distribution characteristics of the total column ozone (TCO) and ozone profile can be quantitatively described. In this study, we evaluated the ozone datasets from CrIS/NOAA20, AIRS/Aqua, and ERA5/ECWMF for their performance in polar regions in 2020, along with the in situ observations of the Dobson, Brewer, and ozonesonde instruments, which are regarded as benchmarks. The results showed that the ERA5 reanalysis ozone field had good consistency with the ground observations (R > 0.95) and indicated whether the TCO or ozone profile was less affected by the site location. In contrast, both CrIS and AIRS could capture the ozone loss process resulting from the Antarctic/Arctic ozone hole at a monthly scale, but their ability to characterize the Arctic ozone hole was weaker than in the Antarctic. Specifically, the TCO values derived from AIRS were apparently higher in March 2020 than those of ERA5, which made it difficult to assess the area and depth of the ozone hole during this period. Moreover, the pattern of CrIS TCO was abnormal and tended to deviate from the pattern that characterized ERA5 and AIRS at the Alert site during the Arctic ozone loss process in 2020, which demonstrates that CrIS ozone products have limited applicability at this ground site. Furthermore, the validation of the ozone profile shows that AIRS and CrIS do not have good vertical representation in the polar regions and are not able to characterize the location and depth of ozone depletion. Overall, the results reveal the shortcomings of the ozone profiles derived from AIRS and CrIS observations and the reliability of the ERA5 reanalysis ozone field in polar applications. A more suitable prior method and detection sensitivity improvement on CrIS and AIRS ozone products would improve their reliability and applicability in polar regions.

A STATISTICAL MODEL OF WINTER/SPRING POLAR OZONE

Satellite measurements provided by NASA (USA) at http://ozonewatch.gsfc.nasa.gov are used to study the variability and interdependence of polar ozone, polar temperature, and mean zonal wind. A model of winter/spring polar ozone in the Arctic and Antarctic is constructed using data on polar temperatures at 30, 70, and 100 hPa levels and mean zonal wind at 10 and 70 hPa levels in the latitude zone of 45°-75°. The results of the statistical analysis of the 1979-2020 polar ozone calculation errors are presented.

Polar Stratospheric Clouds: Satellite Observations, Processes, and Role in Ozone Depletion

<p>The important role of polar stratospheric clouds (PSCs) in stratospheric ozone depletion during winter and spring at high latitudes has been known since the 1980s. However, contemporary observations by the spaceborne instruments MIPAS (Michelson Interferometer for Passive Atmospheric Sounding), MLS (Microwave Limb Sounder), and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) have brought about a comprehensive and clearer understanding of PSC spatial and temporal distributions, their conditions of existence, and the processes through which they impact polar ozone. Within the SPARC (Stratosphere-troposphere Processes And their Role in Climate) PSC initiative (PSCi), those datasets have been synthesized and discussed in depth with the result of a new vortex-wide climatology of PSC occurrence and composition. We will present our results within this vPICO together with a review of the significant progress that has been made in our understanding of PSC nucleation, related dynamical processes, and heterogeneous chlorine activation. Moreover, we have compiled different techniques for parameterizing PSCs and we will show their effects in global models.</p>

Ozone super recovery cancelled in the Antarctic upper stratosphere

<p>Ozone is expected to fully recover from the CFC-era by the end of the 21st century. Furthermore, because of the anthropogenic climate change, cooler stratosphere accelerates the ozone production and is projected to lead to a super recovery. We investigate the ozone distribution over the 21st century with four different future scenarios using simulations of the Whole Atmosphere Community Climate Model (WACCM). At the end of the 21st century, higher polar ozone levels than pre CFC-era are obtained in scenarios that have highest atmospheric radiative forcing. This is true in the Arctic stratosphere and the Antarctic lower stratosphere. The Antarctic upper stratosphere forms an exception, where different scenarios have similar level of ozone during winter. This results from excess nitrogen oxides (NOx) descending from above in stronger future scenarios. NOx is formed by energetic electron precipitation (EEP) in the thermosphere and the upper mesosphere, and descends faster through the mesosphere in stronger scenarios. This indicates that the EEP indirect effect will be important factor for the future Antarctic ozone evolution, and is potentially able to prevent the super recovery in the upper stratosphere.</p>

Exploration of machine learning methods for the classification of infrared limb spectra of polar stratospheric clouds

Polar stratospheric clouds (PSCs) play a key role in polar ozone depletion in the stratosphere. Improved observations and continuous monitoring of PSCs can help to validate and improve chemistry–climate models that are used to predict the evolution of the polar ozone hole. In this paper, we explore the potential of applying machine learning (ML) methods to classify PSC observations of infrared limb sounders. Two datasets were considered in this study. The first dataset is a collection of infrared spectra captured in Northern Hemisphere winter 2006/2007 and Southern Hemisphere winter 2009 by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument on board the European Space Agency's (ESA) Envisat satellite. The second dataset is the cloud scenario database (CSDB) of simulated MIPAS spectra. We first performed an initial analysis to assess the basic characteristics of the CSDB and to decide which features to extract from it. Here, we focused on an approach using brightness temperature differences (BTDs). From both the measured and the simulated infrared spectra, more than 10 000 BTD features were generated. Next, we assessed the use of ML methods for the reduction of the dimensionality of this large feature space using principal component analysis (PCA) and kernel principal component analysis (KPCA) followed by a classification with the support vector machine (SVM). The random forest (RF) technique, which embeds the feature selection step, has also been used as a classifier. All methods were found to be suitable to retrieve information on the composition of PSCs. Of these, RF seems to be the most promising method, being less prone to overfitting and producing results that agree well with established results based on conventional classification methods.

Magnetic local time dependency of radiation belt electron precipitation: impact on polar ozone

The radiation belts are regions in the near-Earth space where solar wind electrons are captured by the Earth's magnetic field. A portion of these electrons is continuously lost into the atmosphere where they cause ionisation and chemical changes. Driven by solar activity, electron forcing leads to ozone variability in the polar regions. Understanding possible dynamical connections to regional climate is an on-going research activity which supports the assessment of greenhouse gas driven climate change by better definition of the solar-driven variability. In the context of the Coupled Model Intercomparison Project Phase 6 (CMIP6), energetic electron and proton precipitation is included in the solar forcing recommendation for the first time. For radiation belt electrons, CMIP6 forcing is from a daily, zonal mean proxy model. This zonal mean model ignores the well-known dependency of precipitation on magnetic local time (MLT), i.e. its diurnal variability. Here we use the Whole Atmosphere Community Climate Model with lower ionospheric chemistry extension (WACCM-D) to study the effect of MLT dependency of electron forcing on the polar ozone response. We analyse simulations applying MLT-dependent and MLT-independent forcings, and contrast ozone responses in monthly mean data as well as in monthly means of individual local time sectors. We consider two cases: 1) year 2003 and 2) extreme, long-duration forcing. Our results indicate that the ozone responses to MLT-dependent and MLT-independent forcings are very similar, and the differences found are small compared to those related to overall uncertainties in electron forcing. We conclude that electron forcing that ignores the MLT dependency will still provide an accurate ozone response in long-term climate simulations.