scholarly journals Methodology for evaluating lateral boundary conditions in the regional chemical transport model MATCH (v5.5.0) using combined satellite and ground-based observations

2015 ◽  
Vol 8 (11) ◽  
pp. 3747-3763 ◽  
Author(s):  
E. Andersson ◽  
M. Kahnert ◽  
A. Devasthale
Keyword(s):  
Air Pollutants ◽  
Domain Boundary ◽  
A Priori ◽  
Satellite Observations ◽  
Global Model ◽  
Lateral Boundary ◽  
Model Domain ◽  
Lateral Boundary Conditions ◽  
Satellite Retrievals

Abstract. Hemispheric transport of air pollutants can have a significant impact on regional air quality, as well as on the effect of air pollutants on regional climate. An accurate representation of hemispheric transport in regional chemical transport models (CTMs) depends on the specification of the lateral boundary conditions (LBCs). This study focuses on the methodology for evaluating LBCs of two moderately long-lived trace gases, carbon monoxide (CO) and ozone (O3), for the European model domain and over a 7-year period, 2006–2012. The method is based on combining the use of satellite observations at the lateral boundary with the use of both satellite and in situ ground observations within the model domain. The LBCs are generated by the global European Monitoring and Evaluation Programme Meteorological Synthesizing Centre – West (EMEP MSC-W) model; they are evaluated at the lateral boundaries by comparison with satellite observations of the Terra-MOPITT (Measurements Of Pollution In The Troposphere) sensor (CO) and the Aura-OMI (Ozone Monitoring Instrument) sensor (O3). The LBCs from the global model lie well within the satellite uncertainties for both CO and O3. The biases increase below 700 hPa for both species. However, the satellite retrievals below this height are strongly influenced by the a priori data; hence, they are less reliable than at, e.g. 500 hPa. CO is, on average, underestimated by the global model, while O3 tends to be overestimated during winter, and underestimated during summer. A regional CTM is run with (a) the validated monthly climatological LBCs from the global model; (b) dynamical LBCs from the global model; and (c) constant LBCs based on in situ ground observations near the domain boundary. The results are validated against independent satellite retrievals from the Aqua-AIRS (Atmospheric InfraRed Sounder) sensor at 500 hPa, and against in situ ground observations from the Global Atmospheric Watch (GAW) network. It is found that (i) the use of LBCs from the global model gives reliable in-domain results for O3 and CO at 500 hPa. Taking AIRS retrievals as a reference, the use of these LBCs substantially improves spatial pattern correlations in the free troposphere as compared to results obtained with fixed LBCs based on ground observations. Also, the magnitude of the bias is reduced by the new LBCs for both trace gases. This demonstrates that the validation methodology based on using satellite observations at the domain boundary is sufficiently robust in the free troposphere. (ii) The impact of the LBCs on ground concentrations is significant only at locations in close proximity to the domain boundary. As the satellite data near the ground mainly reflect the a priori estimate used in the retrieval procedure, they are of little use for evaluating the effect of LBCs on ground concentrations. Rather, the evaluation of ground-level concentrations needs to rely on in situ ground observations. (iii) The improvements of dynamic over climatological LBCs become most apparent when using accumulated ozone over threshold 40 ppb (AOT40) as a metric. Also, when focusing on ground observations taken near the inflow boundary of the model domain, one finds that the use of dynamical LBCs yields a more accurate representation of the seasonal variation, as well as of the variability of the trace gas concentrations on shorter timescales.

scholarly journals Evaluation of lateral boundary conditions in a regional chemical transport model

2015 ◽  
Vol 8 (7) ◽  
pp. 5763-5808
Author(s):  
E. Andersson ◽  
M. Kahnert ◽  
A. Devasthale
Keyword(s):  
Boundary Conditions ◽  
Air Pollutants ◽  
Trace Gases ◽  
Chemical Transport ◽  
Lateral Boundary ◽  
Free Troposphere ◽  
Accurate Representation ◽  
Model Domain ◽  
Lateral Boundary Conditions ◽  
Match Model

Abstract. Hemispheric transport of air pollutants can have a significant impact on regional air quality, as well as on the effect of air pollutants on regional climate. An accurate representation of hemispheric transport in regional chemical transport models (CTMs) depends on the specification of the lateral boundary conditions (LBCs). This study investigates the use of new LBCs of two moderately long-lived trace gases, CO and O3, for the European model domain. The LBCs are generated by use of the global EMEP MSC-W model; they are evaluated at the lateral boundaries by comparison with satellite observations of the Terra/MOPITT sensor (CO) and the Aura/OMI sensor (O3) for use with European domain calculations with the Swedish Multi-scale Atmospheric Transport and CHemistry (MATCH) model. The LBCs from the global EMEP model lie well within the satellite uncertainties for both CO and O3. The biases increase below 700 hPa for both species, although it should be noted that satellite data below this height are more influenced by a priori data and hence less reliable than at e.g. 500 hPa. CO is, on average, underestimated by the global model, while O3 tends to be overestimated during winter, and underestimated during summer. Next, the validated LBCs are applied in a dynamical and climatological setup, respectively, to the MATCH model, set up over the European domain. The MATCH results obtained with climatological and dynamic LBCs are then validated against independent satellite retrievals from the Aqua/AIRS sensor at 500 hPa, and against in situ ground observations from the Global Atmospheric Watch (GAW) network. The application of the EMEP LBCs in the regional MATCH model greatly impacted the model results. The direct impact on ground-level concentrations strongly depends on the distance from the inflow boundary. The improvements of dynamic over climatological LBCs become most apparent when using AOT40 as a metric. Also, when focusing at ground observations taken near the inflow boundary of the model domain, one finds that the use of dynamical LBCs yields a more accurate representation of the seasonal variation, as well as of the variability of the trace gas concentrations on shorter time scales. The greatest impact from the new LBCs, was seen aloft in the free troposphere. Taking AIRS retrievals as a reference, the use of LBCs substantially improves spatial pattern correlations in the free troposphere as compared to results obtained with the LBCs that were originally used in MATCH. Also, the magnitude of the bias is reduced by the new LBCs for both trace gases.

scholarly journals Regional data assimilation of multi-spectral MOPITT observations of CO over North America

2015 ◽  
Vol 15 (12) ◽  
pp. 6801-6814 ◽  
Author(s):  
Z. Jiang ◽  
D. B. A. Jones ◽  
J. Worden ◽  
H. M. Worden ◽  
D. K. Henze ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Boundary Conditions ◽  
North American ◽  
A Priori ◽  
Sensitivity Analyses ◽  
Small Scale ◽  
Lateral Boundary ◽  
Free Troposphere ◽  
Lateral Boundary Conditions

Abstract. Chemical transport models (CTMs) driven with high-resolution meteorological fields can better resolve small-scale processes, such as frontal lifting or deep convection, and thus improve the simulation and emission estimates of tropospheric trace gases. In this work, we explore the use of the GEOS-Chem four-dimensional variational (4D-Var) data assimilation system with the nested high-resolution version of the model (0.5° × 0.67°) to quantify North American CO emissions during the period of June 2004–May 2005. With optimized lateral boundary conditions, regional inversion analyses can reduce the sensitivity of the CO source estimates to errors in long-range transport and in the distributions of the hydroxyl radical (OH), the main sink for CO. To further limit the potential impact of discrepancies in chemical aging of air in the free troposphere, associated with errors in OH, we use surface-level multispectral MOPITT (Measurement of Pollution in The Troposphere) CO retrievals, which have greater sensitivity to CO near the surface and reduced sensitivity in the free troposphere, compared to previous versions of the retrievals. We estimate that the annual total anthropogenic CO emission from the contiguous US 48 states was 97 Tg CO, a 14 % increase from the 85 Tg CO in the a priori. This increase is mainly due to enhanced emissions around the Great Lakes region and along the west coast, relative to the a priori. Sensitivity analyses using different OH fields and lateral boundary conditions suggest a possible error, associated with local North American OH distribution, in these emission estimates of 20 % during summer 2004, when the CO lifetime is short. This 20 % OH-related error is 50 % smaller than the OH-related error previously estimated for North American CO emissions using a global inversion analysis. We believe that reducing this OH-related error further will require integrating additional observations to provide a strong constraint on the CO distribution across the domain. Despite these limitations, our results show the potential advantages of combining high-resolution regional inversion analyses with global analyses to better quantify regional CO source estimates.

Satellite-based observations of ground-level fine particulate matter and comparison to a regional air quality model

2020 ◽  
Author(s):  
Jana Handschuh ◽  
Frank Baier ◽  
Thilo Erbertseder ◽  
Martijn Schaap
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Air Pollutants ◽  
Fine Particulate Matter ◽  
Ground Level ◽  
In Situ Measurements ◽  
Satellite Observations ◽  
Optical Parameters ◽  
Fine Particulate

<p>Particulate matter and other air pollutants have become an increasing burden on the environment and human health. Especially in metropolitan and high-traffic areas, air quality is often remarkably reduced. For a better understanding of the air quality in specific areas, which is of great environment-political interest, data with high resolution in space and time is required. The combination of satellite observations and chemistry-transport-modelling has proven to give a good database for assessments and analyses of air pollution. In contrast to sample in-situ measurements, satellite observations provide area-wide coverage ​​of measurements and thus the possibility for an almost gapless mapping of actual air pollutants. For a high temporal resolution, chemistry-transport-models are needed, which calculate concentrations of specific pollutants in continuous time steps. Satellite observations can thus be used to improve model performances.</p><p>There are no direct satellite-measurements of fine particulate matter (PM2.5) but ground-level concentrations of PM2.5 can be derived from optical parameters such as aerosol optical depth (AOD). A wide range of methods for the determination of PM2.5 concentrations from AOD measurements has been developed so far, but it is still a big challenge. In this study a semi-empirical approach based on the physical relationships between meteorological and optical parameters was applied to determine a first-guess of ground-level PM2.5 concentrations for the year 2018 and the larger Germany region. Therefor AOD observations of MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the NASA Aqua satellite were used in a spatial resolution of 3km. First results showed an overestimation of ground-level aerosols and quiet low correlations with in-situ station measurements from the European Environmental Agency (EEA). To improve the results, correction factors were calculated using the coefficients of linear regression between satellite-based and in-situ measured particulate matter concentrations. Spatial and seasonal dependencies were taken into account with it. Correlations between satellite and in-situ measurements could be improved applying this method.</p><p>The MODIS 3km AOD product was found to be a good base for area-wide calculations of ground-level PM2.5 concentrations. First comparisons to the calculated PM2.5 concentrations from chemistry-transport-model POLYPHEMUS/DLR showed significant differences though. Satellite observations will now be used to improve the general model performance, first by helping to find and understand regional and temporal dependencies in the differences. As part of the German project S-VELD funded by the Federal Ministry of Transport and Digital Infrastructure BMVI, it will help for example to adjust the derivation of particle emissions within the model.</p>

scholarly journals Satellite Observations of NO2Trend over Romania

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Daniel-Eduard Constantin ◽  
Mirela Voiculescu ◽  
Lucian Georgescu
Keyword(s):  
Atmospheric Pollution ◽  
Trace Gases ◽  
Satellite Observations ◽  
Major City ◽  
Satellite Retrievals ◽  
Urban Level ◽  
Realistic Image ◽  
National Industry ◽  
Made In

Satellite-based measurements of atmospheric trace gases loading give a realistic image of atmospheric pollution at global, regional, and urban level. The aim of this paper is to investigate the trend of atmospheric NO2content over Romania for the period 1996–2010 for several regions which are generally characterized by different pollutant loadings, resulting from GOME-1, SCIAMACHY, OMI, and GOME-2 instruments. Satellite results are then compared with ground-based in situ measurements made in industrial and relatively clean areas of one major city in Romania. This twofold approach will help in estimating whether the trend of NO2obtained by means of data satellite retrievals can be connected with the evolution of national industry and transportation.

scholarly journals Soil Initialization Strategy for Use in Limited-Area Weather Prediction Systems

2011 ◽  
Vol 139 (6) ◽  
pp. 1844-1860 ◽  
Author(s):  
Francesca Di Giuseppe ◽  
Davide Cesari ◽  
Giovanni Bonafé
Keyword(s):  
Soil Moisture ◽  
Boundary Conditions ◽  
Weather Prediction ◽  
Global Model ◽  
Limited Area ◽  
Lateral Boundary ◽  
Prognostic Variables ◽  
Lateral Boundary Conditions ◽  
Local Soil ◽  
Analysis System

Abstract Three diverse methods of initializing soil moisture and temperature in limited-area numerical weather prediction models are compared and assessed through the use of nonstandard surface observations to identify the approach that best combines ease of implementation, improvement in forecast skill, and realistic estimations of soil parameters. The first method initializes the limited-area model soil prognostic variables by a simple interpolation from a parent global model that is used to provide the lateral boundary conditions for the forecasts, thus ensuring that the limited-area model’s soil field cannot evolve far from the host model. The second method uses the soil properties generated by a previous limited-area model forecast, allowing the soil moisture to evolve over time to a new equilibrium consistent with the regional model’s hydrological cycle. The third method implements a new local soil moisture variational analysis system that uses screen-level temperature to adjust the soil water content, allowing the use of high-resolution station data that may be available to a regional meteorological service. The methods are tested in a suite of short-term weather forecasts performed with the Consortium for Small Scale Modeling (COSMO) model over the period September–November 2008, using the ECMWF Integrated Forecast System (IFS) model to provide the lateral boundary conditions. Extensive comparisons to observations show that substantial improvements in forecast skills are achievable with improved soil temperature initialization while a smaller additional benefit in the prediction of surface fluxes is possible with the soil moisture analysis. The analysis suggests that keeping the model prognostic variables close to equilibrium with the soil state, especially for temperature, is more relevant than correcting the soil moisture initial values. In particular, if a local soil analysis system is not available, it seems preferable to adopt an “open loop” strategy rather than the interpolation from the host global model analysis. This appears to be especially true for the COSMO model in its current operational configuration since the soil–vegetation–atmosphere transfer (SVAT) scheme of the ECMWF global host model and that of COSMO are radically diverse.

scholarly journals Regional data assimilation of multi-spectral MOPITT observations of CO over North America

2015 ◽  
Vol 15 (4) ◽  
pp. 5327-5358 ◽  
Author(s):  
Z. Jiang ◽  
D. B. A. Jones ◽  
J. Worden ◽  
H. M. Worden ◽  
D. K. Henze ◽  
...  
Keyword(s):  
High Resolution ◽  
North America ◽  
Data Assimilation ◽  
Boundary Conditions ◽  
North American ◽  
A Priori ◽  
Small Scale ◽  
Lateral Boundary ◽  
Free Troposphere ◽  
Lateral Boundary Conditions

Abstract. Chemical transport models (CTMs) driven with high-resolution meteorological fields can better resolve small-scale processes, such as frontal lifting or deep convection, and thus improve the simulation and emission estimates of tropospheric trace gases. In this work, we explore the use of the GEOS-Chem four-dimensional variational (4-D-Var) data assimilation system with the nested high-resolution version of the model (0.5° × 0.67°) to quantify North American CO emissions during the period of June 2004 – May 2005. With optimized lateral boundary conditions, regional inversion analyses can reduce the sensitivity of the CO source estimates to errors in long-range transport and in the distributions of the hydroxyl radical (OH), the main sink for CO. To further limit the potential impact of discrepancies in chemical aging of air in the free troposphere, associated with errors in OH, we use surface level multispectral MOPITT CO retrievals, which have greater sensitivity to CO near the surface and reduced sensitivity in the free troposphere, compared to previous versions of the retrievals. We estimate that the annual total anthropogenic CO emission from the contiguous US 48 states was 97 Tg CO, a 14% increase from the 85 Tg CO in the a priori. This increase is mainly due to enhanced emissions around the Great Lakes region and along the west coast, relative to the a priori. Sensitivity analyses using different OH fields and lateral boundary conditions suggest a possible error, associated with local North America OH distribution, in these emission estimates of 20% during summer 2004, when the CO lifetime is short. This 20% OH-related error is 50% smaller than the OH-related error previously estimated for North American CO emissions using a global inversion analysis. We believe that reducing this OH-related error further will require integrating additional observations to provide a strong constraint on the CO distribution across the domain. Despite these limitations, our results show the potential advantages of combining high-resolution regional inversion analyses with global analyses to better quantify regional CO source estimates.

scholarly journals Uncertainty assessment and applicability of an inversion method for volcanic ash forecasting

2017 ◽  
Vol 17 (14) ◽  
pp. 9205-9222 ◽  
Author(s):  
Birthe Marie Steensen ◽  
Arve Kylling ◽  
Nina Iren Kristiansen ◽  
Michael Schulz
Keyword(s):  
Satellite Data ◽  
Volcanic Ash ◽  
A Priori ◽  
Satellite Observations ◽  
Inversion Method ◽  
A Posteriori ◽  
Satellite Retrieval ◽  
Mass Load ◽  
Satellite Retrievals ◽  
Emission Estimate

Abstract. Significant improvements in the way we can observe and model volcanic ash clouds have been obtained since the 2010 Eyjafjallajökull eruption. One major development has been the application of data assimilation techniques, which combine models and satellite observations such that an optimal understanding of ash clouds can be gained. Still, questions remain regarding the degree to which the forecasting capabilities are improved by inclusion of such techniques and how these improvements depend on the data input. This study explores how different satellite data and different uncertainty assumptions of the satellite and a priori emissions affect the calculated volcanic ash emission estimate, which is computed by an inversion method that couples the satellite retrievals and a priori emissions with dispersion model data. Two major ash episodes over 4 days in April and May of the 2010 Eyjafjallajökull eruption are studied. Specifically, inversion calculations are done for four different satellite data sets with different size distribution assumptions in the retrieval. A reference satellite data set is chosen, and the range between the minimum and maximum 4-day average load of hourly retrieved ash is 121 % in April and 148 % in May, compared to the reference. The corresponding a posteriori maximum and minimum emission sum found for these four satellite retrievals is 26 and 47 % of the a posteriori reference estimate for the same two periods, respectively. Varying the assumptions made in the satellite retrieval is seen to affect the a posteriori emissions and modelled ash column loads, and modelled column loads therefore have uncertainties connected to them depending on the uncertainty in the satellite retrieval. By further exploring our uncertainty estimates connected to a priori emissions and the mass load uncertainties in the satellite data, the uncertainty in the a priori estimate is found in this case to have an order-of-magnitude-greater impact on the a posteriori solution than the mass load uncertainties in the satellite. Part of this is explained by a too-high a priori estimate used in this study that is reduced by around half in the a posteriori reference estimate. Setting large uncertainties connected to both a priori and satellite mass load shows that they compensate each other, but the a priori uncertainty is found to be most sensitive. Because of this, an inversion-based emission estimate in a forecasting setting needs well-tested and well-considered assumptions on uncertainties for the a priori emission and satellite data. The quality of using the inversion in a forecasting environment is tested by adding gradually, with time, more observations to improve the estimated height versus time evolution of Eyjafjallajökull ash emissions. We show that the initially too-high a priori emissions are reduced effectively when using just 12 h of satellite observations. More satellite observations (> 12 h), in the Eyjafjallajökull case, place the volcanic injection at higher altitudes. Adding additional satellite observations (> 36 h) changes the a posteriori emissions to only a small extent for May and minimal for the April period, because the ash is dispersed and transported effectively out of the domain after 1–2 days. A best-guess emission estimate for the forecasting period was constructed by averaging the last 12 h of the a posteriori emission. Using this emission for a forecast simulation leads to better performance, especially compared to model simulations with no further emissions over the forecast period in the case of a continued volcanic eruption activity. Because of undetected ash in the satellite retrieval and diffusion in the model, the forecast simulations generally contain more ash than the observed fields, and the model ash is more spread out. Overall, using the a posteriori emissions in our model reduces the uncertainties in the ash plume forecast, because it corrects effectively for false-positive satellite retrievals, temporary gaps in observations, and false a priori emissions in the window of observation.

Impact of non-Arctic observations on the AROME-Arctic regional model

2020 ◽  
Author(s):  
Rogerr Randriamampianina
Keyword(s):  
Regional Model ◽  
Satellite Observations ◽  
Lateral Boundary ◽  
Regional Data ◽  
Weather Forecasts ◽  
Lateral Boundary Conditions ◽  
Skill Scores ◽  
Medium Range ◽  
Considerable Impact ◽  
The Impact

<p>In the framework of the Applicate project (https://applicate.eu), ECMWF (European Centre for Medium-Range Weather Forecasts) performed global (Bormann et al. 2019) and Arctic (Lawrence et al. 2019) observing system experiments. Use of the results of these experiments as lateral boundary conditions (LBC) for our regional model opens opportunity to study the following: 1) the impact of observations through regional data assimilation (DA); 2) the impact of observations that are assimilated in a global model through LBC in a regional model; 3) the impact of global loss of observations in a regional model; and 4) the impact of non-Arctic observations in an Arctic regional model.</p><p>In the framework of the Alertness project, we performed experiments for the two special observation periods (SOP) 1 and 2 and found considerable impact (significant for some cases) of both conventional and satellite observations through both regional DA and LBC. So far, the impact of non-Arctic observations on our Arctic regional model AROME-Arctic analyses and forecasts was checked during SOP1 with microwave radiance only. The impact was found to be positive, especially on day-2 forecasts.</p><p>In this presentation, the impact of other non-Arctic observations (conventional and satellite) on our regional model AROME-Arctic will be discussed through different forecast skill scores verification.</p>

scholarly journals The Influence of Lateral Boundary Conditions on the Asymptotics in Thin Elastic Plates

2000 ◽  
Vol 31 (2) ◽  
pp. 305-345 ◽  
Author(s):  
Monique Dauge ◽  
Isabelle Gruais ◽  
Andreas Rössle
Keyword(s):  
Boundary Conditions ◽  
Lateral Boundary ◽  
Elastic Plates ◽  
Lateral Boundary Conditions ◽  
Thin Elastic Plates
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