Comprehensive evaluation of the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis against independent observations: Reactive gases

The Copernicus Atmosphere Monitoring Service (CAMS) is operationally providing forecast and reanalysis products of air quality and atmospheric composition. In this article, we present an extended evaluation of the CAMS global reanalysis data set of four reactive gases, namely, ozone (O-3), carbon monoxide (CO), nitrogen dioxide (NO2), and formaldehyde (HCHO), using multiple independent observations. Our results show that the CAMS model system mostly provides a stable and accurate representation of the global distribution of reactive gases over time. Our findings highlight the crucial impact of satellite data assimilation and emissions, investigated through comparison with a model run without assimilated data. Stratospheric and tropospheric O-3 are mostly well constrained by the data assimilation, except over Antarctica after 2012/2013 due to changes in the assimilated data. Challenges remain for O-3 in the Tropics and high-latitude regions during winter and spring. At the surface and for short-lived species (NO2), data assimilation is less effective. Total column CO in the CAMS reanalysis is well constrained by the assimilated satellite data. The control run, however, shows large overestimations of total column CO in the Southern Hemisphere and larger year-to-year variability in all regions. Concerning the long-term stability of the CAMS model, we note drifts in the time series of biases for surface O-3 and CO in the Northern midlatitudes and Tropics and for NO2 over East Asia, which point to biased emissions. Compared to the previous Monitoring Atmospheric Composition and Climate reanalysis, changes in the CAMS chemistry module and assimilation system helped to reduce biases and enhance the long-term temporal consistency of model results for the CAMS reanalysis

Solar UV irradiance in a changing climate: Trends in europe and the significance of spectral monitoring in Italy

Review of the existing bibliography shows that the direction and magnitude of the long-term trends of UV irradiance, and their main drivers, vary significantly throughout Europe. Analysis of total ozone and spectral UV data recorded at four European stations during 1996–2017 reveals that long-term changes in UV are mainly driven by changes in aerosols, cloudiness, and surface albedo, while changes in total ozone play a less significant role. The variability of UV irradiance is large throughout Italy due to the complex topography and large latitudinal extension of the country. Analysis of the spectral UV records of the urban site of Rome, and the alpine site of Aosta reveals that differences between the two sites follow the annual cycle of the differences in cloudiness and surface albedo. Comparisons between the noon UV index measured at the ground at the same stations and the corresponding estimates from the Deutscher Wetterdienst (DWD) forecast model and the ozone monitoring instrument (OMI)/Aura observations reveal differences of up to 6 units between individual measurements, which are likely due to the different spatial resolution of the different datasets, and average differences of 0.5–1 unit, possibly related to the use of climatological surface albedo and aerosol optical properties in the retrieval algorithms

Ozone, DNA-active UV radiation, and cloud changes for the near-global mean and at high latitudes due to enhanced greenhouse gas concentrations

This study analyses the variability and trends of ultraviolet-B (UV-B, wavelength 280–320 nm) radiation that can cause DNA damage. The variability and trends caused by climate change due to enhanced greenhouse gas (GHG) concentrations. The analysis is based on DNA-active irradiance, total ozone, total cloud cover, and surface albedo calculations with the European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) chemistry–climate model (CCM) free-running simulations following the RCP 6.0 climate scenario for the period 1960–2100. The model output is evaluated with DNA-active irradiance ground-based measurements, satellite SBUV (v8.7) total-ozone measurements, and satellite MODerate-resolution Imaging Spectroradiometer (MODIS) Terra cloud cover data. The results show that the model reproduces the observed variability and change in total ozone, DNA-active irradiance, and cloud cover for the period 2000–2018 quite well according to the statistical comparisons. Between 50∘ N–50∘ S, the DNA-damaging UV radiation is expected to decrease until 2050 and to increase thereafter, as was shown previously by Eleftheratos et al. (2020). This change is associated with decreases in the model total cloud cover and negative trends in total ozone after about 2050 due to increasing GHGs. The new study confirms the previous work by adding more stations over low latitudes and mid-latitudes (13 instead of 5 stations). In addition, we include estimates from high-latitude stations with long-term measurements of UV irradiance (three stations in the northern high latitudes and four stations in the southern high latitudes greater than 55∘). In contrast to the predictions for 50∘ N–50∘ S, it is shown that DNA-active irradiance will continue to decrease after the year 2050 over high latitudes because of upward ozone trends. At latitudes poleward of 55∘ N, we estimate that DNA-active irradiance will decrease by 8.2 %±3.8 % from 2050 to 2100. Similarly, at latitudes poleward of 55∘ S, DNA-active irradiance will decrease by 4.8 % ± 2.9 % after 2050. The results for the high latitudes refer to the summer period and not to the seasons when ozone depletion occurs, i.e. in late winter and spring. The contributions of ozone, cloud, and albedo trends to the DNA-active irradiance trends are estimated and discussed.</p

Chapter 4: The LOTUS regression model

One of the primary motivations of the LOTUS effort is to attempt to reconcile the discrepancies in ozone trend results from the wealth of literature on the subject. Doing so requires investigating the various methodologies employed to derive long-term trends in ozone as well as to examine the large array of possible variables that feed into those methodologies and analyse their impacts on potential trend results. Given the limited amount of time, the LOTUS group focused on the most common methodology of multiple linear regression and performed a number of sensitivity tests with the goal of trying to establish best practices and come to a consensus on a single regression model to use for this study. This chapter discusses the details and results of the sensitivity tests before describing the components of the final single model that was chosen and the reasons for that choice

The use of QBO, ENSO, and NAO perturbations in the evaluation of GOME-2 MetOp A total ozone measurements

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&thinsp;% in the tropics (0–30∘), about +0.1±2.1&thinsp;% in the mid-latitudes (30–60∘), and about +2.5±3.2&thinsp;% and 0.0±4.3&thinsp;% 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&thinsp;%. 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∘&thinsp;S, 170.6∘&thinsp;W) are within ±1.9&thinsp;%. 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&thinsp;% 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.</p

Regional climate model simulations of extreme air temperature in Greece. Abnormal or common records in the future climate?

The aim of this study is to analyze and quantify the future projections of heat waves in Greece. For this reason, specific climatic indices were used in the analysis concerning absolute, percentile and duration indices defined by the CCl/CLIVAR/JCOMM Expert Team (ET) on Climate Change Detection and Indices (ETCCDI). The future projections (SRES A1B) of these indices such as summer days, tropical days, maximum daily maximum air temperature, warm days, tropical nights, maximum daily minimum air temperature, warm nights and warm spell duration were carried out using six regional climate models from the ENSEMBLES project, concerning the near future 2031-2050 and the far future 2071-2100 compared to the reference period 1961-1990. The ensemble means along with the inter-model-standard deviations of the examined extreme indices for the future model projections are presented and analyzed. Further, the findings of this analysis are discussed against recent recorded heat waves during 2007, in order to understand if such events are even more extreme or common in the future climate. It is very likely, that the anomalies observed in 2007, especially for extreme indices of minimum air temperature, could be more frequent considered as typical events by the end of the 21th century. © 2014 Elsevier B.V

Analysis of precipitation extremes based on satellite and high-resolution gridded data set over Mediterranean basin

The objective of this study is to compare and analyze satellite precipitation extremes of Tropical Rainfall Measuring Mission level 3 output (TRMM 3B42) over Mediterranean region against the respective high resolution gridded precipitation datasets (0.25. ×. 0.25) based on the E-OBS project, for the period 2000-2011.The Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating. The E-OBS data set (a European daily high-resolution gridded dataset of surface temperature and precipitation) was developed as part of the European Union Framework 6 ENSEMBLES project, with the aim being to use it for validation of Regional Climate Models (RCMs) and for climate change studies.The indices used in the analysis can be divided in three categories: percentile, absolute and duration indices. The percentile indices concern: very wet days (the number of days with daily precipitation amount above the 95th percentile from the examined period) and extremely wet days (the number of days with daily precipitation amount above the 99th percentile from the examined period). The absolute threshold indices concern: number of heavy precipitation days (number of days with daily precipitation amount above 10. mm), number of very heavy precipitation days (number of days with daily precipitation amount above 20. mm) and simple daily intensity index (daily precipitation amount on wet days in a period per number of wet days in the period). The duration indices concern consecutive dry days (the largest number of consecutive days with daily precipitation amount below 1. mm) and consecutive wet days (the largest number of consecutive days with daily precipitation amount above 1. mm).The spatial distribution of the differences between the two datasets along with the spatial distribution of the correlation coefficients are presented and analyzed. Results show considerable regional differences of precipitation indices over the Mediterranean Region. © 2013 Elsevier B.V