WRF-Chem simulations in the Amazon region during wet and dry season transitions: evaluation of methane models and wetland inundation maps

Beck, Veronika; Gerbig, Christoph; Koch, Thomas; Béla, M.; Longo, Karla M.; Freitas, Saulo R.; Kaplan, Jed O.; Prigent, Catherine; Bergamaschi, P.; Heimann, Martin

doi:10.5194/acp-13-7961-2013

Cited by 36 publications

(33 citation statements)

References 56 publications

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“…We attribute the underprediction to a faster fall-off in modelled methane concentrations with altitude than that observed. To test this, we initially replaced the HadGEM2 model outputs above 400 hPa with methane mixing ratios derived from the thermal infrared (TIR) channel of the Tropospheric Emission Spectrometer (TES, AURA, 2004: Beer, 2006, because of its availability and ease of use. As discussed by Worden et al (2012), the CH 4 in the upper troposphere is biased high relative to the lower troposphere by 4 % on average.…”

Section: Initial Comparisonmentioning

confidence: 99%

Comparison of the HadGEM2 climate-chemistry model against in-situ and SCIAMACHY atmospheric methane data

Hayman¹,

O’Connor²,

Dalvi³

et al. 2014

Preprint

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Abstract. Wetlands are a major emission source of methane (CH4) globally. In this study, we have evaluated wetland emission estimates derived using the UK community land surface model (JULES, the Joint UK Land Earth Simulator) against atmospheric observations of methane, including, for the first time, total methane columns derived from the SCIAMACHY instrument on board the ENVISAT satellite. Two JULES wetland emission estimates were investigated: (a) from an offline run driven with CRU-NCEP meteorological data and (b) from the same offline run in which the modelled wetland fractions were replaced with those derived from the Global Inundation Extent from Multi-Satellites (GIEMS) remote sensing product. The mean annual emission assumed for each inventory (181 Tg CH4 per annum over the period 1999–2007) is in line with other recently-published estimates. There are regional differences as the unconstrained JULES inventory gave significantly higher emissions in the Amazon and lower emissions in other regions compared to the JULES estimates constrained with the GIEMS product. Using the UK Hadley Centre's Earth System model with atmospheric chemistry (HadGEM2), we have evaluated these JULES wetland emissions against atmospheric observations of methane. We obtained improved agreement with the surface concentration measurements, especially at northern high latitudes, compared to previous HadGEM2 runs using the wetland emission dataset of Fung (1991). Although the modelled monthly atmospheric methane columns reproduced the large–scale patterns in the SCIAMACHY observations, they were biased low by 50 part per billion by volume (ppb). Replacing the HadGEM2 modelled concentrations above 300 hPa with HALOE–ACE assimilated TOMCAT output resulted in a significantly better agreement with the SCIAMACHY observations. The use of the GIEMS product to constrain JULES-derived wetland fraction improved the description of the wetland emissions in JULES and gave a good description of the seasonality observed at surface sites influenced by wetlands, especially at high latitudes. We found that the annual cycles observed in the SCIAMACHY measurements and at many of the surface sites influenced by non-wetland sources could not be reproduced in these HadGEM2 runs. This suggests that the emissions over certain regions (e.g., India and China) are possibly too high and/or the monthly emission patterns for specific sectors are incorrect. The comparisons presented in this paper have shown that the performance of the JULES wetland scheme is comparable to that of other process-based land surface models. We have identified areas for improvement in this and the atmospheric chemistry components of the HadGEM Earth System model. The Earth Observation datasets used here will be of continued value in future evaluations of JULES and the HadGEM family of models.

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Section: Initial Comparisonmentioning

confidence: 99%

Comparison of the HadGEM2 climate-chemistry model against in-situ and SCIAMACHY atmospheric methane data

Hayman¹,

O’Connor²,

Dalvi³

et al. 2014

Preprint

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“…Therefore, models are essential tools for understanding the interactions of physical and chemical processes that contribute to O 3 formation, as well as monitoring and predicting atmospheric chemistry composition, weather, and climate at local, regional, and global scales. In turn, the observations help constrain uncertainties in the model representations of parameterized convection, turbulence, land surface, and other subgrid scale processes that affect the simulated transport and chemical transformation of the atmospheric composition (Beck et al, 2013).…”

Section: M Bela Et Al: Ozone Production and Transport Over The Amentioning

confidence: 99%

“…However, the probability densities were consistent with observations in the boundary layer, indicating that horizontal dispersion was reasonable. Beck et al (2013) evaluated different CH 4 wetland emissions schemes and maps using WRF-GHG. They found the best agreement with BARCA CH 4 data for days when convective transport, as evaluated by comparison of upstream Tropical Rainfall Monitoring Mission (TRMM) and WRF precipitation amounts, was well represented in the model.…”

Section: Barca Aircraft Campaignsmentioning

confidence: 99%

Ozone production and transport over the Amazon Basin during the dry-to-wet and wet-to-dry transition seasons

et al. 2015

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Abstract. The Regional Carbon Balance in Amazonia (BARCA) campaign provided the first Amazon Basin-wide aircraft measurements of ozone (O 3 ) during both the dry-towet (November and December 2008) and wet-to-dry (May 2009) transition seasons. Extremely low background values (< 20 ppb) were observed to the west and north of Manaus in both seasons and in all regions during the wet-to-dry transition. On the other hand, elevated O 3 levels (40-60 ppb) were seen during the dry-to-wet transition to the east and south of Manaus, where biomass burning emissions of O 3 precursors were present. Chemistry simulations with the CCATT-BRAMS and WRF-Chem models are within the error bars of the observed O 3 profiles in the boundary layer (0-3 km a.s.l.) in polluted conditions. However, the models overestimate O 3 in the boundary layer in clean conditions, despite lacking the predominant NO source from soil. In addition, O 3 simulated by the models was either within the error bars or lower than BARCA observations in mid-levels (3-5 km a.s.l.), and lower than total tropospheric O 3 retrieved from the OMI/MLS instruments, which is primarily comprised of middle troposphere O 3 and thus reflects long-range transport processes. Therefore, the models do a relatively poor job of representing the free troposphere-boundary layer gradient in O 3 compared with aircraft and satellite observations, which could be due to missing long-range and convective transport of O 3 at mid-levels. Additional simulations with WRF-Chem showed that the model O 3 production is very sensitive to both the O 3 deposition velocities and the NO x emissions, which were both about one-half of observed values. These results indicate the necessity of more realistic model representations of emissions, deposition, and convective processes for accurate monitoring and prediction of increases in O 3 production in the Amazon Basin as the regional population grows.

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“…A modelling study using synthetic CO 2 data by Mueller et al (2018) showed, that for the Baltimore-Washington area a substantial fraction of ~3 5% of the CO 2 background variability is caused by biogenic sources and sinks in July. Therefore, we simulate the biogenic CO 2 flux with the Vegetation Photosynthesis and Respiration Model (VPRM, Mahadevan et al, 2008) coupled with WRF-GHG (Beck et al, 2013) in order to estimate the influence of the photosynthetic uptake and respiration on our assessment of the anthropogenic flux. According to our analysis, the maximum daytime photosynthetic uptake predicted over the footprint area is at most 12% of the estimated anthropogenic flux.…”

Section: Discussion On Emission Fluxesmentioning

confidence: 99%

Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and CH4 in situ observations in summer 2018

Klausner¹,

Mertens²,

Huntrieser³

et al. 2020

Elem Sci Anth

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Urban areas are recognised as a significant source of greenhouse gas emissions (GHG), such as carbon dioxide (CO 2 ) and methane (CH 4 ). The total amount of urban GHG emissions, especially for CH 4 , however, is not well quantified. Here we report on airborne in situ measurements using a Picarro G1301-m analyser aboard the DLR Cessna Grand Caravan to study GHG emissions downwind of the German capital Berlin. In total, five aircraft-based mass balance experiments were conducted in July 2018 within the Urban Climate Under Change [UC] 2 project. The detection and isolation of the Berlin plume was often challenging because of comparatively small GHG signals above variable atmospheric background concentrations. However, on July 20 th enhancements of up to 4 ppm CO 2 and 21 ppb CH 4 were observed over a horizontal extent of roughly 45 to 65 km downwind of Berlin. These enhanced mixing ratios are clearly distinguishable from the background and can partly be assigned to city emissions. The estimated CO 2 emission flux of 1.39 ± 0.76 t s -1 is in agreement with current inventories, while the CH 4 emission flux of 5.20 ± 1.70 kg s -1 is almost two times larger than the highest reported value in the inventories. We localized the source area with HYSPLIT trajectory calculations and the global/regional nested chemistry climate model MECO(n) (down to ~1 km), and investigated the contribution from sewage-treatment plants and waste deposition to CH 4 , which are treated differently by the emission inventories. Our work highlights the importance of strong CH 4 sources in the vicinity of Berlin and shows, that there is limited understanding of CH 4 emissions from urban regions, even for major cities in highly developed countries like Germany. Furthermore, we show that a detailed knowledge of GHG inflow mixing ratios is necessary to suitably estimate emission rates for Berlin.

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WRF-Chem simulations in the Amazon region during wet and dry season transitions: evaluation of methane models and wetland inundation maps

Cited by 36 publications

References 56 publications

Comparison of the HadGEM2 climate-chemistry model against in-situ and SCIAMACHY atmospheric methane data

Comparison of the HadGEM2 climate-chemistry model against in-situ and SCIAMACHY atmospheric methane data

Ozone production and transport over the Amazon Basin during the dry-to-wet and wet-to-dry transition seasons

Urban greenhouse gas emissions from the Berlin area: A case study using airborne CO2 and CH4 in situ observations in summer 2018

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