scholarly journals Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements

2021 ◽  
Vol 14 (7) ◽  
pp. 5241-5269
Author(s):  
Vinod Kumar ◽  
Julia Remmers ◽  
Steffen Beirle ◽  
Joachim Fallmann ◽  
Astrid Kerkweg ◽  
...  
Keyword(s):  
High Resolution ◽  
Atmospheric Chemistry ◽  
Temporal Variability ◽  
Model System ◽  
West Germany ◽  
Optical Absorption Spectroscopy ◽  
Anthropogenic Emissions ◽  
Spatial And Temporal Variability ◽  
Daily Variability

Abstract. We present high spatial resolution (up to 2.2×2.2 km2) simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n) (MESSy-fied ECHAM and COSMO models nested n times). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMRs) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly-resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS (Multiple AXis Differential Optical Absorption Spectroscopy) measurements performed at Mainz (49.99∘ N, 8.23∘ E) were used to evaluate the simulated tropospheric vertical column densities (VCDs) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles (≤8∘), small biases in the range of −14 % to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases, indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly-resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when vertical mixing is suppressed, and the atmospheric lifetime of NO2 is relatively long.

scholarly journals Evaluation of the coupled high-resolution atmospheric chemistry model system MECO(n) using in situ and MAX-DOAS NO<sub>2</sub> measurements

2021 ◽  
Author(s):  
Vinod Kumar ◽  
Julia Remmers ◽  
Steffen Beirle ◽  
Joachim Fallmann ◽  
Astrid Kerkweg ◽  
...  
Keyword(s):  
High Resolution ◽  
Atmospheric Chemistry ◽  
Temporal Variability ◽  
Pearson Correlation ◽  
Model System ◽  
West Germany ◽  
Anthropogenic Emissions ◽  
Spatial And Temporal Variability ◽  
Daily Variability

Abstract. We present high spatial resolution (up to 2.2 × 2.2 km2 simulations focussed over south-west Germany using the online coupled regional atmospheric chemistry model system MECO(n). Numerical simulation of nitrogen dioxide (NO2) surface volume mixing ratios (VMR) are compared to in situ measurements from a network with 193 locations including background, traffic-adjacent and industrial stations to investigate the model's performance in simulating the spatial and temporal variability of short-lived chemical species. We show that the use of a high-resolution and up-to-date emission inventory is crucial for reproducing the spatial variability, and resulted in good agreement with the measured VMRs at the background and industrial locations with an overall bias of less than 10 %. We introduce a computationally efficient approach that simulates diurnal and daily variability in monthly resolved anthropogenic emissions to resolve the temporal variability of NO2. MAX-DOAS measurements performed at Mainz (49.99° N, 8.23° E) were used to evaluate the simulated tropospheric vertical column densities (VCD) of NO2. We propose a consistent and robust approach to evaluate the vertical distribution of NO2 in the boundary layer by comparing the individual differential slant column densities (dSCDs) at various elevation angles. This approach considers details of the spatial heterogeneity and sensitivity volume of the MAX-DOAS measurements while comparing the measured and simulated dSCDs. The effects of clouds on the agreement between MAX-DOAS measurements and simulations have also been investigated. For low elevation angles ≤ 8°), small biases in the range of −14 to +7 % and Pearson correlation coefficients in the range of 0.5 to 0.8 were achieved for different azimuth directions in the cloud-free cases indicating good model performance in the layers close to the surface. Accounting for diurnal and daily variability in the monthly resolved anthropogenic emissions was found to be crucial for the accurate representation of time series of measured NO2 VMR and dSCDs and is particularly critical when the atmospheric lifetime of NO2 is relatively long.

scholarly journals Multiscale observations of NH<sub>3</sub> around Toronto, Canada

2021 ◽  
Vol 14 (2) ◽  
pp. 905-921
Author(s):  
Shoma Yamanouchi ◽  
Camille Viatte ◽  
Kimberly Strong ◽  
Erik Lutsch ◽  
Dylan B. A. Jones ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Grid Point ◽  
Regional Scale ◽  
Model Performance ◽  
In Situ Measurements ◽  
Coefficient Of Determination ◽  
Spatial And Temporal Variability ◽  
Predictive Capacity ◽  
Total Column

Abstract. Ammonia (NH3) is a major source of nitrates in the atmosphere and a major source of fine particulate matter. As such, there have been increasing efforts to measure the atmospheric abundance of NH3 and its spatial and temporal variability. In this study, long-term measurements of NH3 derived from multiscale datasets are examined. These NH3 datasets include 16 years of total column measurements using Fourier transform infrared (FTIR) spectroscopy, 3 years of surface in situ measurements, and 10 years of total column measurements from the Infrared Atmospheric Sounding Interferometer (IASI). The datasets were used to quantify NH3 temporal variability over Toronto, Canada. The multiscale datasets were also compared to assess the representativeness of the FTIR measurements. All three time series showed positive trends in NH3 over Toronto: 3.34 ± 0.89 %/yr from 2002 to 2018 in the FTIR columns, 8.88 ± 5.08 %/yr from 2013 to 2017 in the surface in situ data, and 8.38 ± 1.54 %/yr from 2008 to 2018 in the IASI columns. To assess the representative scale of the FTIR NH3 columns, correlations between the datasets were examined. The best correlation between FTIR and IASI was obtained with coincidence criteria of ≤25 km and ≤20 min, with r=0.73 and a slope of 1.14 ± 0.06. Additionally, FTIR column and in situ measurements were standardized and correlated. Comparison of 24 d averages and monthly averages resulted in correlation coefficients of r=0.72 and r=0.75, respectively, although correlation without averaging to reduce high-frequency variability led to a poorer correlation, with r=0.39. The GEOS-Chem model, run at 2∘ × 2.5∘ resolution, was compared to FTIR and IASI to assess model performance and investigate the correlation of observational data and model output, both with local column measurements (FTIR) and measurements on a regional scale (IASI). Comparisons on a regional scale (a domain spanning 35 to 53∘ N and 93.75 to 63.75∘ W) resulted in r=0.57 and thus a coefficient of determination, which is indicative of the predictive capacity of the model, of r2=0.33, but comparing a single model grid point against the FTIR resulted in a poorer correlation, with r2=0.13, indicating that a finer spatial resolution is needed for modeling NH3.

scholarly journals Effects of high spatial and temporal resolution Earth observations on simulated hydrometeorological variables in a cropland (southwestern France)

2017 ◽  
Vol 21 (11) ◽  
pp. 5693-5708 ◽  
Author(s):  
Jordi Etchanchu ◽  
Vincent Rivalland ◽  
Simon Gascoin ◽  
Jérôme Cros ◽  
Tiphaine Tallec ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Surface ◽  
Agricultural Landscapes ◽  
Surface Model ◽  
Spatial And Temporal Variability ◽  
Area Index ◽  
The Impact ◽  
Sentinel 2

Abstract. Agricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. This temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. The Sentinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. Here, we evaluate the impact of Sentinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the Interactions between the Surface Biosphere Atmosphere (ISBA) land surface model included in the EXternalized SURface (SURFEX) modeling platform. The study focuses on the effect of the leaf area index (LAI) spatial and temporal variability on these fluxes. We compare the use of the LAI climatology from ECOCLIMAP-II, used by default in SURFEX-ISBA, and time series of LAI derived from the high-resolution Formosat-2 satellite data (8 m). The study area is an agricultural zone in southwestern France covering 576 km2 (24 km  ×  24 km). An innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. Evaluation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux (LE). Our results show that the use of LAI derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to ECOCLIMAP-II, especially when the surface is covered with summer crops. The comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30 % of the root mean square error (RMSE) in the simulated evapotranspiration. This finding is attributable to a better description of LAI evolution processes with Formosat-2 data, which further modify soil water content and drainage of soil reservoirs. Effects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4 % of annual precipitation levels with simulations using Formosat-2 data in comparison to the reference simulation values. This study illustrates the potential for the Sentinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.

scholarly journals Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data

2020 ◽  
Vol 12 (15) ◽  
pp. 2415
Author(s):  
Tuuli Soomets ◽  
Kristi Uudeberg ◽  
Kersti Kangro ◽  
Dainis Jakovels ◽  
Agris Brauns ◽  
...  
Keyword(s):  
Primary Production ◽  
Temporal Variability ◽  
Carbon Fixation ◽  
Remote Sensing Data ◽  
Spatial And Temporal Variation ◽  
Spatial And Temporal Variability ◽  
Phytoplankton Primary Production ◽  
Spatio Temporal ◽  
Lake Size

Phytoplankton primary production (PP) in lakes play an important role in the global carbon cycle. However, monitoring the PP in lakes with traditional complicated and costly in situ sampling methods are impossible due to the large number of lakes worldwide (estimated to be 117 million lakes). In this study, bio-optical modelling and remote sensing data (Sentinel-3 Ocean and Land Colour Instrument) was combined to investigate the spatial and temporal variation of PP in four Baltic lakes during 2018. The model used has three input parameters: concentration of chlorophyll-a, the diffuse attenuation coefficient, and incident downwelling irradiance. The largest of our studied lakes, Võrtsjärv (270 km2), had the highest total yearly estimated production (61 Gg C y−1) compared to the smaller lakes Lubans (18 Gg C y−1) and Razna (7 Gg C y−1). However, the most productive was the smallest studied, Lake Burtnieks (40.2 km2); although the total yearly production was 13 Gg C y−1, the daily average areal production was 910 mg C m−2 d−1 in 2018. Even if lake size plays a significant role in the total PP of the lake, the abundance of small and medium-sized lakes would sum up to a significant contribution of carbon fixation. Our method is applicable to larger regions to monitor the spatial and temporal variability of lake PP.

scholarly journals Implementation of electrochemical, optical and denuder-based sensors and sampling techniques on UAV for volcanic gas measurements: examples from Masaya, Turrialba and Stromboli volcanoes

2018 ◽  
Vol 11 (4) ◽  
pp. 2441-2457 ◽  
Author(s):  
Julian Rüdiger ◽  
Jan-Lukas Tirpitz ◽  
J. Maarten de Moor ◽  
Nicole Bobrowski ◽  
Alexandra Gutmann ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Compositional Analysis ◽  
Optical Absorption Spectroscopy ◽  
Stromboli Volcano ◽  
Volcanic Gas ◽  
Airborne Measurements ◽  
Masaya Volcano ◽  
Custom Made ◽  
Turrialba Volcano

Abstract. Volcanoes are a natural source of several reactive gases (e.g., sulfur and halogen containing species) and nonreactive gases (e.g., carbon dioxide) to the atmosphere. The relative abundance of carbon and sulfur in volcanic gas as well as the total sulfur dioxide emission rate from a volcanic vent are established parameters in current volcano-monitoring strategies, and they oftentimes allow insights into subsurface processes. However, chemical reactions involving halogens are thought to have local to regional impact on the atmospheric chemistry around passively degassing volcanoes. In this study we demonstrate the successful deployment of a multirotor UAV (quadcopter) system with custom-made lightweight payloads for the compositional analysis and gas flux estimation of volcanic plumes. The various applications and their potential are presented and discussed in example studies at three volcanoes encompassing flight heights of 450 to 3300 m and various states of volcanic activity. Field applications were performed at Stromboli volcano (Italy), Turrialba volcano (Costa Rica) and Masaya volcano (Nicaragua). Two in situ gas-measuring systems adapted for autonomous airborne measurements, based on electrochemical and optical detection principles, as well as an airborne sampling unit, are introduced. We show volcanic gas composition results including abundances of CO2, SO2 and halogen species. The new instrumental setups were compared with established instruments during ground-based measurements at Masaya volcano, which resulted in CO2 ∕ SO2 ratios of 3.6 ± 0.4. For total SO2 flux estimations a small differential optical absorption spectroscopy (DOAS) system measured SO2 column amounts on transversal flights below the plume at Turrialba volcano, giving 1776 ± 1108 T d−1 and 1616 ± 1007 T d−1 of SO2 during two traverses. At Stromboli volcano, elevated CO2 ∕ SO2 ratios were observed at spatial and temporal proximity to explosions by airborne in situ measurements. Reactive bromine to sulfur ratios of 0.19 × 10−4 to 9.8 × 10−4 were measured in situ in the plume of Stromboli volcano, downwind of the vent.

scholarly journals Technical note: A high-resolution inverse modelling technique for estimating surface CO<sub>2</sub> fluxes based on the NIES-TM – FLEXPART coupled transport model and its adjoint

2020 ◽  
Author(s):  
Shamil Maksyutov ◽  
Tomohiro Oda ◽  
Makoto Saito ◽  
Rajesh Janardanan ◽  
Dmitry Belikov ◽  
...  
Keyword(s):  
High Resolution ◽  
Transport Model ◽  
Dispersion Model ◽  
Surface Flux ◽  
Particle Dispersion ◽  
Anthropogenic Emissions ◽  
Coupled Transport ◽  
Tracer Transport ◽  
Flux Corrections

Abstract. We developed a high-resolution surface flux inversion system based on the global Lagrangian–Eulerian coupled tracer transport model composed of National Institute for Environmental Studies Transport Model (NIES-TM) and FLEXible PARTicle dispersion model (FLEXPART). The inversion system is named NTFVAR (NIES-TM-FLEXPART-variational) as it applies variational optimisation to estimate surface fluxes. We tested the system by estimating optimized corrections to natural surface CO2 fluxes to achieve best fit to atmospheric CO2 data collected by the global in-situ network, as a necessary step towards capability of estimating anthropogenic CO2 emissions. We employ the Lagrangian particle dispersion model (LPDM) FLEXPART to calculate the surface flux footprints of CO2 observations at a 0.1° × 0.1° spatial resolution. The LPDM is coupled to a global atmospheric tracer transport model (NIES-TM). Our inversion technique uses an adjoint of the coupled transport model in an iterative optimization procedure. The flux error covariance operator is being implemented via implicit diffusion. Biweekly flux corrections to prior flux fields were estimated for the years 2010–2012 from in-situ CO2 data included in the Observation Package (ObsPack) dataset. High-resolution prior flux fields were prepared using Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) for fossil fuel combustion, Global Fire Assimilation System (GFAS) for biomass burning, the Vegetation Integrative SImulator for Trace gases (VISIT) model for terrestrial biosphere exchange and Ocean Tracer Transport Model (OTTM) for oceanic exchange. The terrestrial biospheric flux field was constructed using a vegetation mosaic map and separate simulation of CO2 fluxes at daily time step by the VISIT model for each vegetation type. The prior flux uncertainty for terrestrial biosphere was scaled proportionally to the monthly mean Gross Primary Production (GPP) by the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD17 product. The inverse system calculates flux corrections to the prior fluxes in the form of a relatively smooth field multiplied by high-resolution patterns of the prior flux uncertainties for land and ocean, following the coastlines and vegetation productivity gradients. The resulting flux estimates improve fit to the observations at continuous observations sites, reproducing both the seasonal variation and short-term concentration variability, including high CO2 concentration events associated with anthropogenic emissions. The use of high-resolution atmospheric transport in global CO2 flux inversion has the advantage of better resolving the transport from the mix of the anthropogenic and biospheric sources in densely populated continental regions and shows potential for better separation between fluxes from terrestrial ecosystems and strong localised sources such as anthropogenic emissions and forest fires. Further improvements in the modelling system are needed as the posterior fit is better than that by the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker only for a fraction of the monitoring sites, mostly at coastal and island locations experiencing mix of background and local flux signals.

scholarly journals The 1-way on-line coupled model system MECO(n) – Part 4: Chemical evaluation (based on MESSy v2.52)

2016 ◽  
Author(s):  
Mariano Mertens ◽  
Astrid Kerkweg ◽  
Patrick Jöckel ◽  
Holger Tost ◽  
Christiane Hofmann
Keyword(s):  
Atmospheric Chemistry ◽  
Coupled Model ◽  
Ground Level ◽  
Global Scale ◽  
Model System ◽  
Scale Down ◽  
On Line ◽  
In Situ Observations ◽  
Line Coupling

Abstract. For the first time a simulation incorporating tropospheric and stratospheric chemistry using the newly developed MECO(n) model system is performed. MECO(n) is short for MESSyfied ECHAM and COSMO model nested n-times. It features an on-line coupling of the COSMO-CLM model, equipped with the Modular Earth Submodel System (MESSy) interface (called COSMO/MESSy), with the global atmospheric chemistry model ECHAM5/MESSy for Atmospheric Chemistry (EMAC). This on-line coupling allows a consistent model chain with respect to chemical and meteorological boundary conditions from the global scale down to the regional kilometre scale. A MECO(2) simulation incorporating one regional instance over Europe with 50 km resolution and a one instance over Germany with 12 km resolution is conducted for the evaluation of MECO(n) with respect to tropospheric gas-phase chemistry. The main goal of this evaluation is to ensure, that the chemistry related MESSy submodels and the on-line coupling with respect to the chemistry are correctly implemented. This evaluation is a prerequisite for the further usage of MECO(n) in atmospheric chemistry related studies. Results of EMAC and the two COSMO/MESSy instances are compared with satellite-, ground-based- and aircraft in situ observations, focusing on ozone, carbon monoxide and nitrogen dioxide. Further the methane lifetimes in EMAC and the two COSMO/MESSy instances are analysed in view of the tropospheric oxidation capacity. From this evaluation we conclude that the chemistry related submodels and the on-line coupling with respect to the chemistry are correctly implemented. In comparison with observations both, EMAC and COSMO/MESSy, show strengths and weaknesses. Especially in comparison to aircraft in situ observations COSMO/MESSy shows very promising results. However, the amplitude of the diurnal cycle of ground-level ozone measurements is underestimated. Most of the differences between COSMO/MESSy and EMAC can be attributed to differences in the dynamics of both models, which is subject to further model developments.

Sign in / Sign up

Export Citation Format

Share Document