Scale interactions on diurnal toseasonal timescales and their relevanceto model systematic errors

Examples of current research into systematic errors in climate models are used to demonstrate the importance of scale interactions on diurnal,intraseasonal and seasonal timescales for the mean and variability of the tropical climate system. It has enabled some conclusions to be drawn about possible processes that may need to be represented, and some recommendations to be made regarding model improvements. It has been shown that the Maritime Continent heat source is a major driver of the global circulation but yet is poorly represented in GCMs. A new climatology of the diurnal cycle has been used to provide compelling evidence of important land-sea breeze and gravity wave effects, which may play a crucial role in the heat and moisture budget of this key region for the tropical and global circulation. The role of the diurnal cycle has also been emphasized for intraseasonal variability associated with the Madden Julian Oscillation (MJO). It is suggested that the diurnal cycle in Sea Surface Temperature (SST) during the suppressed phase of the MJO leads to a triggering of cumulus congestus clouds, which serve to moisten the free troposphere and hence precondition the atmosphere for the next active phase. It has been further shown that coupling between the ocean and atmosphere on intraseasonal timescales leads to a more realistic simulation of the MJO. These results stress the need for models to be able to simulate firstly, the observed tri-modal distribution of convection, and secondly, the coupling between the ocean and atmosphere on diurnal to intraseasonal timescales. It is argued, however, that the current representation of the ocean mixed layer in coupled models is not adequate to represent the complex structure of the observed mixed layer, in particular the formation of salinity barrier layers which can potentially provide much stronger local coupling between the atmosphere and ocean on diurnal to intraseasonal timescales

Shipborne measurements of XCO2, XCH4, and XCO above the Pacific Ocean and comparison to CAMS atmospheric analyses and S5P/TROPOMI

Measurements of atmospheric column-averaged dry-air mole fractions of carbon dioxide (XCO2), methane (XCH4), and carbon monoxide (XCO) have been collected across the Pacific Ocean during the Measuring Ocean REferences 2 (MORE-2) campaign in June 2019.We deployed a shipborne variant of the EM27/SUN Fourier transform spectrometer (FTS) on board the German R/V Sonne which, during MORE-2, crossed the Pacific Ocean from Vancouver, Canada, to Singapore. Equipped with a specially manufactured fast solar tracker, the FTS operated in direct-sun viewing geometry during the ship cruise reliably delivering solar absorption spectra in the shortwave infrared spectral range (4000 to 11000 cm-1). After filtering and bias correcting the dataset, we report on XCO2, XCH4, and XCO measurements for 22 d along a trajectory that largely aligns with 30° N of latitude between 140°W and 120° E of longitude. The dataset has been scaled to the Total Carbon Column Observing Network (TCCON) station in Karlsruhe, Germany, before and after the MORE-2 campaign through side-by-side measurements. The 1σ repeatability of hourly means of XCO2, XCH4, and XCO is found to be 0.24 ppm, 1.1 ppb, and 0.75 ppb, respectively. The Copernicus Atmosphere Monitoring Service (CAMS) models gridded concentration fields of the atmospheric composition using assimilated satellite observations, which show excellent agreement of 0:52-0:31 ppm for XCO2, 0:9±4:1 ppb for XCH4, and 3:2-3:4 ppb for XCO (mean difference ± SD, standard deviation, of differences for entire record) with our observations. Likewise, we find excellent agreement to within 2:2±6:6 ppb with the XCO observations of the TROPOspheric MOnitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite (S5P). The shipborne measurements are accessible at https://doi.org/10.1594/PANGAEA.917240 (Knapp et al., 2020). © Author(s) 2021

Trace gas/aerosol boundary concentrations and their impacts on continental-scale AQMEII modeling domains

Copyright 2011 Elsevier B.V., All rights reserved.Over twenty modeling groups are participating in the Air Quality Model Evaluation International Initiative (AQMEII) in which a variety of mesoscale photochemical and aerosol air quality modeling systems are being applied to continental-scale domains in North America and Europe for 2006 full-year simulations for model inter-comparisons and evaluations. To better understand the reasons for differences in model results among these participating groups, each group was asked to use the same source of emissions and boundary concentration data for their simulations. This paper describes the development and application of the boundary concentration data for this AQMEII modeling exercise. The European project known as GEMS (Global and regional Earth-system Monitoring using Satellite and in-situ data) has produced global-scale re-analyses of air quality for several years, including 2006 (http://gems.ecmwf.int). The GEMS trace gas and aerosol data were made available at 3-hourly intervals on a regular latitude/longitude grid of approximately 1.9° resolution within 2 "cut-outs" from the global model domain. One cut-out was centered over North America and the other over Europe, covering sufficient spatial domain for each modeling group to extract the necessary time- and space-varying (horizontal and vertical) concentrations for their mesoscale model boundaries. Examples of the impact of these boundary concentrations on the AQMEII continental simulations are presented to quantify the sensitivity of the simulations to boundary concentrations. In addition, some participating groups were not able to use the GEMS data and instead relied upon other sources for their boundary concentration specifications. These are noted, and the contrasting impacts of other data sources for boundary data are presented. How one specifies four-dimensional boundary concentrations for mesoscale air quality simulations can have a profound impact on the model results, and hence, this aspect of data preparation must be performed with considerable care.Peer reviewedFinal Accepted Versio

Detecting volcanic sulfur dioxide plumes in the Northern Hemisphere using the Brewer spectrophotometer, other networks, and satellite observations

This paper demonstrates that SO 2 columnar amounts have significantly increased following the five largest volcanic eruptions of the past decade in the Northern Hemisphere. A strong positive signal was detected by all the existing networks either ground based (Brewer, EARLINET, AirBase) or from satellites (OMI, GOME-2). The study particularly examines the adequacy of the existing Brewer network to detect SO 2 plumes of volcanic origin in comparison to other networks and satellite platforms. The comparison with OMI and 45 GOME-2 SO 2 space-borne retrievals shows statistically significant agreement between the Brewer network data and the collocated satellite overpasses. It is shown that the Brewer instrument is capable of detecting significant columnar SO 2 increases following large volcanic eruptions, when SO 2 levels rise well above the instrumental noise of daily observations, estimated to be of the order of 2 DU. A model exercise from the MACC project shows that the large increases of SO 2 over Europe following the Bárðarbunga eruption in Iceland were not caused by local sources or ship emissions but are clearly linked to the eruption. We propose that by combining Brewer data with that from other networks and satellites, a useful tool aided by trajectory analyses and modeling could be created which can be used to forecast high SO 2 values both at ground level and in air flight corridors following future eruptions

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

Ocean temperature and salinity components of the Madden-Julian oscillation observed by Argo floats

New diagnostics of the Madden-Julian Oscillation (MJO) cycle in ocean temperature and, for the first time, salinity are presented. The MJO composites are based on 4 years of gridded Argo float data from 2003 to 2006, and extend from the surface to 1,400 m depth in the tropical Indian and Pacific Oceans. The MJO surface salinity anomalies are consistent with precipitation minus evaporation fluxes in the Indian Ocean, and with anomalous zonal advection in the Pacific. The Argo sea surface temperature and thermocline depth anomalies are consistent with previous studies using other data sets. The near-surface density changes due to salinity are comparable to, and partially offset, those due to temperature, emphasising the importance of including salinity as well as temperature changes in mixed-layer modelling of tropical intraseasonal processes. The MJO-forced equatorial Kelvin wave that propagates along the thermocline in the Pacific extends down into the deep ocean, to at least 1,400 m. Coherent, statistically significant, MJO temperature and salinity anomalies are also present in the deep Indian Ocean

Global model simulations of air pollution during the 2003 European heat wave

Three global Chemistry Transport Models – MOZART, MOCAGE, and TM5 – as well as MOZART coupled to the IFS meteorological model including assimilation of ozone (O<sub>3</sub>) and carbon monoxide (CO) satellite column retrievals, have been compared to surface measurements and MOZAIC vertical profiles in the troposphere over Western/Central Europe for summer 2003. The models reproduce the meteorological features and enhancement of pollution during the period 2–14 August, but not fully the ozone and CO mixing ratios measured during that episode. Modified normalised mean biases are around −25% (except ~5% for MOCAGE) in the case of ozone and from −80% to −30% for CO in the boundary layer above Frankfurt. The coupling and assimilation of CO columns from MOPITT overcomes some of the deficiencies in the treatment of transport, chemistry and emissions in MOZART, reducing the negative biases to around 20%. The high reactivity and small dry deposition velocities in MOCAGE seem to be responsible for the overestimation of O<sub>3</sub> in this model. Results from sensitivity simulations indicate that an increase of the horizontal resolution to around 1°×1° and potential uncertainties in European anthropogenic emissions or in long-range transport of pollution cannot completely account for the underestimation of CO and O<sub>3</sub> found for most models. A process-oriented TM5 sensitivity simulation where soil wetness was reduced results in a decrease in dry deposition fluxes and a subsequent ozone increase larger than the ozone changes due to the previous sensitivity runs. However this latest simulation still underestimates ozone during the heat wave and overestimates it outside that period. Most probably, a combination of the mentioned factors together with underrepresented biogenic emissions in the models, uncertainties in the modelling of vertical/horizontal transport processes in the proximity of the boundary layer as well as limitations of the chemistry schemes are responsible for the underestimation of ozone (overestimation in the case of MOCAGE) and CO found in the models during this extreme pollution event

Nutritional Geometry Provides Food for Thought

Dietary Restriction extends lifespan in a diverse range of animals, but this often comes at a cost to reproduction. While a number of molecular pathways integral to these relationships have been characterised, we still do not fully understand whether restriction of specific nutrients or calories is responsible. Two recent studies on insects have offered novel insights into this longstanding issue via the application of Nutritional Geometry. This technique promises to significantly advance our understanding of how nutrition influences reproduction and longevity

Analysis of meteorology-chemistry interactions during air pollution episodes using online coupled models within AQMEII Phase-2

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).This study reviews the top ranked meteorology and chemistry interactions in online coupled models recommended by an experts’ survey conducted in COST Action EuMetChem and examines the sensitivity of those interactions during two pollution episodes: the Russian forest fires 25 Jul -15 Aug 2010 and a Saharan dust transport event from 1 Oct -31 Oct 2010 as a part of the AQMEII phase-2 exercise. Three WRF-Chem model simulations were performed for the forest fire case for a baseline without any aerosol feedback on meteorology, a simulation with aerosol direct effects only and a simulation including both direct and indirect effects. For the dust case study, eight WRF-Chem and one WRF-CMAQ simulations were selected from the set of simulations conducted in the framework of AQMEII. Of these two simulations considered no feedbacks, two included direct effects only and five simulations included both direct and indirect effects. The results from both episodes demonstrate that it is important to include the meteorology and chemistry interactions in online-coupled models. Model evaluations using routine observations collected in AQMEII phase-2 and observations from a station in Moscow show that for the fire case the simulation including only aerosol direct effects has better performance than the simulations with no aerosol feedbacks or including both direct and indirect effects. The normalized mean biases are significantly reduced by 10-20% for PM10 when including aerosol direct effects. The analysis for the dust case confirms that models perform better when including aerosol direct effects, but worse when including both aerosol direct and indirect effects, which suggests that the representation of aerosol indirect effects needs to be improved in the model.Peer reviewedFinal Published versio