ALBERT

Description: The need for open science has been recognized by the communities of meteorology and climate science. While these domains are mature in terms of applying digital technologies, the implementation of open science methodologies is less advanced. In a session on “Weather and Climate Science in the Digital Era” at the 14th IEEE International eScience Conference domain specialists and data and computer scientists discussed the road towards open weather and climate science. Roughly 80 % of the studies presented in the conference session showed the added value of open data and software. These studies included open datasets from disparate sources in their analyses or developed tools and approaches that were made openly available to the research community. Furthermore, shared software is a prerequisite for the studies which presented systems like a model coupling framework or digital collaboration platform. Although these studies showed that sharing code and data is important, the consensus among the participants was that this is not sufficient to achieve open weather and climate science and that there are important issues to address. At the level of technology, the application of the findable, accessible, interoperable, and reusable (FAIR) principles to many datasets used in weather and climate science remains a challenge. This may be due to scalability (in the case of high-resolution climate model data, for example), legal barriers such as those encountered in using weather forecast data, or issues with heterogeneity (for example, when trying to make use of citizen data). In addition, the complexity of current software platforms often limits collaboration between researchers and the optimal use of open science tools and methods. The main challenges we observed, however, were non-technical and impact the practice of science as a whole. There is a need for new roles and responsibilities in the scientific process. People working at the interface of science and digital technology – e.g., data stewards and research software engineers – should collaborate with domain researchers to ensure the optimal use of open science tools and methods. In order to remove legal boundaries on sharing data, non-academic parties such as meteorological institutes should be allowed to act as trusted agents. Besides the creation of these new roles, novel policies regarding open weather and climate science should be developed in an inclusive way in order to engage all stakeholders. Although there is an ongoing debate on open science in the community, the individual aspects are usually discussed in isolation. Our approach in this paper takes the discourse further by focusing on “open science in weather and climate research” as a whole. We consider all aspects of open science and discuss the challenges and opportunities of recent open science developments in data, software, and hardware. We have compiled these into a list of concrete recommendations that could bring us closer to open weather and climate science. We acknowledge that the development of open weather and climate science requires effort to change, but the benefits are large. We have observed these benefits directly in the studies presented in the conference and believe that it leads to much faster progress in understanding our complex world.

Description: Abundance-based model evaluations with observations provide critical tests for the simulated mean state in models of intercontinental pollution transport, and under certain conditions may also offer constraints on model responses to emission changes. We compile multiyear measurements of peroxy acetyl nitrate (PAN) available from five mountaintop sites and apply them in a proof-of-concept approach that exploits an ensemble of global chemical transport models (HTAP1) to identify an observational “emergent constraint”. In April, when the signal from anthropogenic emissions on PAN is strongest, simulated PAN at northern midlatitude mountaintops correlates strongly with PAN source–receptor relationships (the response to 20 % reductions in precursor emissions within northern midlatitude continents; hereafter, SRRs). This finding implies that PAN measurements can provide constraints on PAN SRRs by limiting the SRR range to that spanned by the subset of models simulating PAN within the observed range. In some cases, regional anthropogenic volatile organic compound (AVOC) emissions, tracers of transport from different source regions, and SRRs for ozone also correlate with PAN SRRs. Given the large observed interannual variability in the limited available datasets, establishing strong constraints will require matching meteorology in the models to the PAN measurements. Application of this evaluation approach to the chemistry–climate models used to project changes in atmospheric composition will require routine, long-term mountaintop PAN measurements to discern both the climatological SRR signal and its interannual variability.

Description: Despite several studies on temperature trends in the tropopause region, a comprehensive understanding of the evolution of temperatures in this climate-sensitive region of the atmosphere remains elusive. Here we present a unique global-scale, long-term data set of high-resolution in situ temperature data measured aboard passenger aircraft within the European Research Infrastructure IAGOS (In-service Aircraft for a Global Observing System; http://www.iagos.org). This data set is used to investigate temperature trends within the global upper troposphere and lowermost stratosphere (UTLS,  

Description: Within the framework of the global chemistry climate model ECHAM-HAMMOZ a novel explicit coupling between the sectional aerosol model HAM-SALSA and the chemistry model MOZ was established to form isoprene derived secondary organic aerosol (iSOA). Isoprene oxidation in the chemistry model MOZ is described by a semi-explicit scheme consisting of 147 reactions, embedded in a detailed atmospheric chemical mechanism with a total of 779 reactions. Low volatile compounds (LVOC) produced during isoprene photooxidation are identified and explicitly partitioned by HAM-SALSA. A group contribution method was used to estimate their evaporation enthalpies and corresponding saturation vapor pressures, which are used by HAM-SALSA to calculate the saturation concentration of each LVOC. With this method, every single precursor is tracked in terms of condensation and evaporation in each aerosol size bin. This approach lead to the identification of ISOP(OOH)2 as a main contributor to iSOA formation. Further, reactive uptake of isoprene epoxidiols (IEPOX) and isoprene derived glyoxal were included as iSOA sources. The parameterization of IEPOX reactive uptake includes a dependency on aerosol pH value. This model framework connecting semi-explicit isoprene oxidation with explicit treatment of aerosol tracers leads to a global, annual isoprene SOA yield of 16 % relative to the primary oxidation of isoprene by OH, NO3, and ozone. With 445 Tg (392 TgC) isoprene emitted, an iSOA source of 148 Tg (61 TgC) is simulated. The major part of iSOA in ECHAM-HAMMOZ is produced by IEPOX (24.4 TgC) and ISOP(OOH)2 (28.3 TgC). The main sink process is particle wet deposition which removes 143 Tg (59 TgC). The iSOA burden reaches 1.6 Tg (0.7 TgC) in the year 2012.

Description: The chemistry climate model ECHAM-HAMMOZ contains a detailed representation of tropospheric and stratospheric reactive chemistry and state-of-the-art parametrisations of aerorols using either a modal scheme (M7) or a bin scheme (SALSA). This article describes and evaluates the model version ECHAM6.3-HAM2.3-MOZ1.0 with a focus on the tropospheric gas-phase chemistry. A ten-year model simulation was performed to test the stability of the model and provide data for its evaluation. The comparison to observations concentrates on the year 2008 and includes total column observations of ozone (O3) and carbon monoxide (CO) from Infrared Atmospheric Sounding Interferometer (IASI) and Ozone Monitoring Instrument (OMI), Microwave Limb Sounder (MLS) observations of temperature, nitric acid (HNO3), chlorine monoxide (ClO), and O3 for the evaluation of polar stratospheric processes, an ozone sonde climatology, surface ozone observations from the Tropospheric Ozone Assessment Report (TOAR) database, and surface CO data from the Global Atmosphere Watch network. Global budgets of ozone, hydroxide (OH), nitrogen oxides (NOx), aerosols, clouds, and radiation are analyzed and compared to the literature. ECHAM-HAMMOZ performs well in many aspects. However, in the base simulation, lightning NOx emissions are very low, and the impact of the heterogeneous reaction of HNO3 on dust and seasalt aerosol is too strong. Sensitivity simulations with increased lightning NOx or modified heterogeneous chemistry deteriorate the comparison with observations and yield excessively large ozone budget terms and too much OH. We hypothesize that this is an impact of potential issues with tropical convection in the ECHAM model.

Description: A biogenic emission scheme based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 (Guenther et al., 2012) has been integrated into the ECHAM6-HAMMOZ chemistry climate model in order to calculate the emissions from terrestrial vegetation of 32 compounds. The estimated annual global total for the reference simulation is 634 Tg C yr−1 (simulation period 2000–2012). Isoprene is the main contributor to the average emission total, accounting for 66 % (417 Tg C yr−1), followed by several monoterpenes (12 %), methanol (7 %), acetone (3.6 %), and ethene (3.6 %). Regionally, most of the high annual emissions are found to be associated with tropical regions and tropical vegetation types. In order to evaluate the implementation of the biogenic model in ECHAM-HAMMOZ, global and regional biogenic volatile organic compound (BVOC) emissions of the reference simulation were compared to previous published experiment results with MEGAN. Several sensitivity simulations were performed to study the impact of different model input and parameters related to the vegetation cover and the ECHAM6 climate. BVOC emissions obtained here are within the range of previous published estimates. The large range of emission estimates can be attributed to the use of different input data and empirical coefficients within different setups of MEGAN. The biogenic model shows a high sensitivity to the changes in plant functional type (PFT) distributions and associated emission factors for most of the compounds. The global emission impact for isoprene is about −9 %, but reaches +75 % for α-pinene when switching from global emission factor maps to PFT-specific emission factor distributions. The highest sensitivity of isoprene emissions is calculated when considering soil moisture impact, with a global decrease of 12.5 % when the soil moisture activity factor is included in the model parameterization. Nudging ECHAM6 climate towards ERA-Interim reanalysis has an impact on the biogenic emissions, slightly lowering the global total emissions and their interannual variability.

Description: Global tropospheric ozone reanalyses constructed using different state-of-the-art satellite data assimilation systems, prepared as part of the Copernicus Atmosphere Monitoring Service (CAMS-iRean and CAMS-Rean) as well as two fully independent reanalyses (TCR-1 and TCR-2, Tropospheric Chemistry Reanalysis), have been intercompared and evaluated for the past decade. The updated reanalyses (CAMS-Rean and TCR-2) generally show substantially improved agreements with independent ground and ozone-sonde observations over their predecessor versions (CAMS-iRean and TCR-1) for diurnal, synoptical, seasonal, and interannual variabilities. For instance, for the Northern Hemisphere (NH) mid-latitudes the tropospheric ozone columns (surface to 300 hPa) from the updated reanalyses show mean biases to within 0.8 DU (Dobson units, 3 % relative to the observed column) with respect to the ozone-sonde observations. The improved performance can likely be attributed to a mixture of various upgrades, such as revisions in the chemical data assimilation, including the assimilated measurements, and the forecast model performance. The updated chemical reanalyses agree well with each other for most cases, which highlights the usefulness of the current chemical reanalyses in a variety of studies. Meanwhile, significant temporal changes in the reanalysis quality in all the systems can be attributed to discontinuities in the observing systems. To improve the temporal consistency, a careful assessment of changes in the assimilation configuration, such as a detailed assessment of biases between various retrieval products, is needed. Our comparison suggests that improving the observational constraints, including the continued development of satellite observing systems, together with the optimization of model parameterizations such as deposition and chemical reactions, will lead to increasingly consistent long-term reanalyses in the future.

Description: Peroxy acetyl nitrate (PAN) is the most important reservoir species for nitrogen oxides (NOx) in the remote troposphere. Upon decomposition in remote regions, PAN promotes efficient ozone production. We evaluate monthly mean PAN abundances from global chemical transport model simulations (HTAP1) for 2001 with measurements from five northern mid-latitude mountain sites (four European and one North American). The multi-model mean generally captures the observed monthly mean PAN but individual models simulate a factor of ~4–8 range in monthly abundances. We quantify PAN source-receptor relationships at the measurement sites with sensitivity simulations that decrease regional anthropogenic emissions of PAN (and ozone) precursors by 20% from North America (NA), Europe (EU), and East Asia (EA). The HTAP1 models attribute more of the observed PAN at Jungfraujoch (Switzerland) to emissions in NA and EA, and less to EU, than a prior trajectory-based estimate. The trajectory-based and modeling approaches agree that EU emissions play a role in the observed springtime PAN maximum at Jungfraujoch. The signal from anthropogenic emissions on PAN is strongest at Jungfraujoch and Mount Bachelor (Oregon, U.S.A.) during April. In this month, PAN source-receptor relationships correlate both with model differences in regional anthropogenic volatile organic compound (AVOC) emissions and with ozone source-receptor relationships. PAN observations at mountaintop sites can thus provide key information for evaluating models, including links between PAN and ozone production and source-receptor relationships. Establishing routine, long-term, mountaintop measurements is essential given the large observed interannual variability in PAN.

Description: The high density of European surface ozone monitoring sites provides unique opportunities for the investigation of regional ozone representativeness and for the evaluation of chemistry climate models. The regional representativeness of European ozone measurements is investigated through a cluster analysis (CA) of 4 years of three-hourly ozone data from 1492 European surface monitoring stations in the Airbase database; the time resolution corresponds to the output frequency of the model that is compared to the data in this study. K-means clustering is implemented for seasonal-diurnal variations (i) in absolute mixing ratio units, and (ii) normalized by the overall mean ozone mixing ratio at each site. Statistical tests suggest that each CA can distinguish between 4 and 5 different ozone pollution regimes. The individual clusters reveal differences in seasonal-diurnal cycles, showing typical patterns of the ozone behavior for more polluted stations or more rural background. The robustness of the clustering was tested with a series of k-means runs decreasing randomly the size of the initial data set or lengths of the timeseries. Except for the Po Valley, the clustering does not provide a regional differentiation, as the member stations within each cluster are generally distributed all over Europe. The typical seasonal, diurnal, and weekly cycles of each cluster are compared to the output of the multi-year global reanalysis produced within the Monitoring of Atmospheric Composition and Climate (MACC) project. While the MACC reanalysis generally captures the shape of the diurnal cycles and the diurnal amplitudes it is not able to reproduce the seasonal cycles very well and it exhibits a high bias up to 12 nmol/mol. The bias decreases from more polluted clusters to cleaner ones. Also, the seasonal and weekly cycles and frequency distributions of ozone mixing ratios are better described for clusters with relatively clean signatures. Due to relative sparsity of CO and NOx measurements these were not included in the cluster analysis. However, simulated CO and NOx mixing ratios are consistent with the general classification into more polluted and more background sites. Mean CO mixing ratios are ≈ 140–145 nmol/mol (CL1 – CL3) and ≈ 130–135 nmol/mol (CL4 and CL5), and NOx mixing ratios are ≈ 4–6 nmol/mol and ≈ 2–3 nmol/mol, respectively. These results confirm that relatively coarse scale global models are more suitable for simulation of regional background concentrations, which are less variable in space and time. We conclude that cluster analysis of surface ozone observations provides a powerful and robust way to stratify sets of stations being thus more suitable for model evaluation.

Description: Despite several studies on temperature trends in the tropopause region, a comprehensive understanding of the evolution of temperatures in this climate-sensitive region of the atmosphere remains elusive. Here we present a unique global-scale, long-term data set of high-resolution in-situ temperature data measured aboard passenger aircraft within the European Research Infrastructure IAGOS (In-service Aircraft for a Global Observing System, www.iagos.org). This data set is used to investigate temperature trends within the global upper troposphere and lowermost stratosphere (UTLS) for the period 1995 to 2012 in different geographical regions and vertical layers of the UTLS. The largest amount of observations is available over the North Atlantic. Here, a neutral temperature trend is found within the lowermost stratosphere. This contradicts the temperature trend in the European Centre for Medium Range Weather Forecast (ECMWF) ERA-Interim reanalysis, where a significant (95 % confidence) temperature increase of +0.56 K/decade is obtained. Differences between trends derived from observations and reanalysis data can be traced back to changes in the temperature bias between observation and model data over the studied period. This study demonstrates the value of the IAGOS temperature observations as anchor point for the evaluation of reanalyses and its suitability for independent trend analyses.