scholarly journals Aerosol data assimilation in the MOCAGE chemical transport model during the TRAQA/ChArMEx campaign: lidar observations

2020 ◽  
Vol 13 (9) ◽  
pp. 4645-4667
Author(s):  
Laaziz El Amraoui ◽  
Bojan Sič ◽  
Andrea Piacentini ◽  
Virginie Marécal ◽  
Nicolas Frebourg ◽  
...  

Abstract. This paper presents the first results about the assimilation of CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) extinction coefficient measurements onboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite in the MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) chemistry transport model of Météo-France. This assimilation module is an extension of the aerosol optical depth (AOD) assimilation system already presented by Sič et al. (2016). We focus on the period of the TRAQA (TRAnsport à longue distance et Qualité de l’Air dans le bassin méditerranéen) field campaign that took place during summer 2012. This period offers the opportunity to have access to a large set of aerosol observations from instrumented aircraft, balloons, satellite and ground-based stations. We evaluate the added value of CALIOP assimilation with respect to the model free run by comparing both fields to independent observations issued from the TRAQA field campaign. In this study we focus on the desert dust outbreak which happened during late June 2012 over the Mediterranean Basin (MB) during the TRAQA campaign. The comparison with the AERONET (Aerosol Robotic Network) AOD measurements shows that the assimilation of CALIOP lidar observations improves the statistics compared to the model free run. The correlation between AERONET and the model (assimilation) is 0.682 (0.753); the bias and the root mean square error (RMSE), due to CALIOP assimilation, are reduced from −0.063 to 0.048 and from 0.183 to 0.148, respectively. Compared to MODIS (Moderate-resolution Imaging Spectroradiometer) AOD observations, the model free run shows an underestimation of the AOD values, whereas the CALIOP assimilation corrects this underestimation and shows a quantitative good improvement in terms of AOD maps over the MB. The correlation between MODIS and the model (assimilation) during the dust outbreak is 0.47 (0.52), whereas the bias is −0.18 (−0.02) and the RMSE is 0.36 (0.30). The comparison of in situ aircraft and balloon measurements to both modelled and assimilated outputs shows that the CALIOP lidar assimilation highly improves the model aerosol field. The evaluation with the LOAC (Light Optical Particle Counter) measurements indicates that the aerosol vertical profiles are well simulated by the direct model but with a general underestimation of the aerosol number concentration, especially in the altitude range 2–5 km. The CALIOP assimilation improves these results by a factor of 2.5 to 5. Analysis of the vertical distribution of the desert aerosol concentration shows that the aerosol dust transport event is well captured by the model but with an underestimated intensity. The assimilation of CALIOP observations allows the improvement of the geographical representation of the event within the model as well as its intensity by a factor of 2 in the altitude range 1–5 km.

2020 ◽  
Author(s):  
Laaziz El Amraoui ◽  
Bojan Sič ◽  
Andrea Piacentini ◽  
Virginie Marécal ◽  
Jean-Luc Attié ◽  
...  

Abstract. This paper presents the first results about the assimilation of CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) extinction coefficient measurements on-board the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite in the chemistry transport model MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle) of Météo-France. This assimilation module is an extension of the Aerosol Optical Depth (AOD) assimilation system already presented by Sic et al. (2016). We focus on the period of TRAQA (TRAnsport à longue distance et Qualité de l’Air dans le bassin méditerranéen) field campaign that took place during the summer 2012. This period offers the opportunity to have access to a large set of aerosol observations from instrumented aircraft, balloons, satellite and ground-based stations. We evaluate the added value of CALIOP assimilation with respect to the model free run by comparing both fields to independent observations issued from the TRAQA field campaign. In this study we focus on the desert dust outbreak which happened during late June 2012 over the Mediterranean Basin (MB) during TRAQA campaign. The comparison with the AERONET (Aerosol Robotic Network) AOD measurements shows that the assimilation of CALIOP lidar observations improves the statistics compared to the model free run. The correlation between AERONET and the model (assimilation) is 0.682 (0.753), the bias and the RMSE, due to CALIOP assimilation, are reduced from −0.063 to 0.048 and from 0.183 to 0.148, respectively. Compared to MODIS (Moderate-resolution Imaging Spectroradiometer) AOD observations, the model free run shows an underestimation of the AOD values whereas the CALIOP assimilation corrects this underestimation and shows a quantitative good improvement in terms of AOD maps over the MB. The correlation between MODIS and the model (assimilation) during the dust outbreak is 0.47 (0.52), whereas the bias is −0.18 (−0.02) and the RMSE is 0.36 (0.30). The comparison of in-situ aircraft and balloon measurements to both modelled and assimilated outputs shows that the CALIOP lidar assimilation highly improves themodel aerosol field. The evaluation with the LOAC (Light Optical Particle Counter) measurements indicates that the aerosol vertical profiles are well simulated by the direct model but with a general underestimation of the aerosol number concentration especially in the altitude range 2–5 km. The CALIOP assimilation improves these results by a factor of 2.5 to 5. Analysis of the vertical distribution of the desert aerosol concentration shows that the aerosol dust transport event is well captured by the model but with an underestimated intensity. The assimilation of CALIOP observations allows the improvement of the geographical representation of the event within the model as well as its intensity by a factor of two in the altitude range 1–5 km.


2014 ◽  
Vol 14 (7) ◽  
pp. 3511-3532 ◽  
Author(s):  
Y. Wang ◽  
K. N. Sartelet ◽  
M. Bocquet ◽  
P. Chazette

Abstract. In this study, we investigate the ability of the chemistry transport model (CTM) Polair3D of the air quality modelling platform Polyphemus to simulate lidar backscattered profiles from model aerosol concentration outputs. This investigation is an important preprocessing stage of data assimilation (validation of the observation operator). To do so, simulated lidar signals are compared to hourly lidar observations performed during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009, when a ground-based mobile lidar was deployed around Paris on-board a van. The comparison is performed for six different measurement days, 1, 4, 16, 21, 26 and 29 July 2009, corresponding to different levels of pollution and different atmospheric conditions. Overall, Polyphemus well reproduces the vertical distribution of lidar signals and their temporal variability, especially for 1, 16, 26 and 29 July 2009. Discrepancies on 4 and 21 July 2009 are due to high-altitude aerosol layers, which are not well modelled. In the second part of this study, two new algorithms for assimilating lidar observations based on the optimal interpolation method are presented. One algorithm analyses PM10 (particulate matter with diameter less than 10 μm) concentrations. Another analyses PM2.5 (particulate matter with diameter less than 2.5 μm) and PM2.5–10 (particulate matter with a diameter higher than 2.5 μm and lower than 10 μm) concentrations separately. The aerosol simulations without and with lidar data assimilation (DA) are evaluated using the Airparif (a regional operational network in charge of air quality survey around the Paris area) database to demonstrate the feasibility and usefulness of assimilating lidar profiles for aerosol forecasts. The evaluation shows that lidar DA is more efficient at correcting PM10 than PM2.5, probably because PM2.5 is better modelled than PM10. Furthermore, the algorithm which analyses both PM2.5and PM2.5–10 provides the best scores for PM10. The averaged root-mean-square error (RMSE) of PM10 is 11.63 μg m−3 with DA (PM2.5 and PM2.5–10), compared to 13.69 μg m−3 with DA (PM10) and 17.74 μg m−3 without DA on 1 July 2009. The averaged RMSE of PM10 is 4.73 μg m−3 with DA (PM2.5 and PM2.5–10), against 6.08 μg m−3 with DA (PM10) and 6.67 μg m−3 without DA on 26 July 2009.


2013 ◽  
Vol 13 (10) ◽  
pp. 27115-27161
Author(s):  
Y. Wang ◽  
K. N. Sartelet ◽  
M. Bocquet ◽  
P. Chazette

Abstract. In this study, we investigate the ability of the chemistry transport model (CTM) Polair3D of the air quality modelling platform Polyphemus of simulating lidar backscattered profiles from model aerosol concentration outputs. To do so, simulated lidar signals are compared to hourly lidar observations performed during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009, where a ground-based mobile lidar was deployed around Paris on-board a van. The comparison is performed for six different measurement days, 1, 4, 16, 21, 26 and 29 July 2009, corresponding to different levels of pollution and different atmospheric conditions. Polyphemus correctly reproduces the vertical distribution of aerosol optical properties and their temporal variability. In the second part of this study, two new algorithms for assimilating lidar observations are presented. The aerosol simulations without and with lidar data assimilation are evaluated using the Airparif (a regional operational network in charge of air quality survey around the Paris area) database to demonstrate the feasibility and the usefulness of assimilating lidar profiles for aerosol forecasts.


2012 ◽  
Vol 12 (15) ◽  
pp. 7073-7085 ◽  
Author(s):  
J. Kuttippurath ◽  
S. Godin-Beekmann ◽  
F. Lefèvre ◽  
G. Nikulin ◽  
M. L. Santee ◽  
...  

Abstract. We present a detailed discussion of the chemical and dynamical processes in the Arctic winters 1996/1997 and 2010/2011 with high resolution chemical transport model (CTM) simulations and space-based observations. In the Arctic winter 2010/2011, the lower stratospheric minimum temperatures were below 195 K for a record period of time, from December to mid-April, and a strong and stable vortex was present during that period. Simulations with the Mimosa-Chim CTM show that the chemical ozone loss started in early January and progressed slowly to 1 ppmv (parts per million by volume) by late February. The loss intensified by early March and reached a record maximum of ~2.4 ppmv in the late March–early April period over a broad altitude range of 450–550 K. This coincides with elevated ozone loss rates of 2–4 ppbv sh−1 (parts per billion by volume/sunlit hour) and a contribution of about 30–55% and 30–35% from the ClO-ClO and ClO-BrO cycles, respectively, in late February and March. In addition, a contribution of 30–50% from the HOx cycle is also estimated in April. We also estimate a loss of about 0.7–1.2 ppmv contributed (75%) by the NOx cycle at 550–700 K. The ozone loss estimated in the partial column range of 350–550 K exhibits a record value of ~148 DU (Dobson Unit). This is the largest ozone loss ever estimated in the Arctic and is consistent with the remarkable chlorine activation and strong denitrification (40–50%) during the winter, as the modeled ClO shows ~1.8 ppbv in early January and ~1 ppbv in March at 450–550 K. These model results are in excellent agreement with those found from the Aura Microwave Limb Sounder observations. Our analyses also show that the ozone loss in 2010/2011 is close to that found in some Antarctic winters, for the first time in the observed history. Though the winter 1996/1997 was also very cold in March–April, the temperatures were higher in December–February, and, therefore, chlorine activation was moderate and ozone loss was average with about 1.2 ppmv at 475–550 K or 42 DU at 350–550 K, as diagnosed from the model simulations and measurements.


2014 ◽  
Vol 7 (2) ◽  
pp. 1645-1689
Author(s):  
E. Hache ◽  
J.-L. Attié ◽  
C. Tourneur ◽  
P. Ricaud ◽  
L. Coret ◽  
...  

Abstract. Ozone is a tropospheric pollutant and plays a key role in determining the air quality that affects human wellbeing. In this study, we compare the capability of two hypothetical grating spectrometers onboard a geostationary (GEO) satellite to sense ozone in the lowermost troposphere (surface and the 0–1 km column). We consider one week during the Northern Hemisphere summer simulated by a chemical transport model, and use the two GEO instrument configurations to measure ozone concentration (1) in the thermal infrared (GEO TIR) and (2) in the thermal infrared and the visible (GEO TIR+VIS). These configurations are compared against each other, and also against an ozone reference state and a priori ozone information. In a first approximation, we assume clear sky conditions neglecting the influence of aerosols and clouds. A number of statistical tests are used to assess the performance of the two GEO configurations. We consider land and sea pixels and whether differences between the two in the performance are significant. Results show that the GEO TIR+VIS configuration provides a better representation of the ozone field both for surface ozone and the 0–1 km ozone column during the daytime especially over land.


2018 ◽  
Author(s):  
Pascal O. Title ◽  
Daniel L. Rabosky

AbstractSpecies-specific diversification rates, or “tip rates”, can be computed quickly from phylogenies and are widely used to study diversification rate variation in relation to geography, ecology, and phenotypes. These tip rates provide a number of theoretical and practical advantages, such as the relaxation of assumptions of rate homogeneity in trait-dependent diversification studies. However, there is substantial confusion in the literature regarding whether these metrics estimate speciation or net diversification rates. Additionally, no study has yet compared the relative performance and accuracy of tip rate metrics across simulated diversification scenarios.We compared the statistical performance of three model-free rate metrics (inverse terminal branch lengths; node density metric; DR statistic) and a model-based approach (BAMM). We applied each method to a large set of simulated phylogenies that had been generated under different diversification processes; scenarios included multi-regime time-constant and diversity-dependent trees, as well as trees where the rate of speciation evolves under a diffusion process. We summarized performance in relation to the type of rate variation, the magnitude of rate heterogeneity and rate regime size. We also compared the ability of the metrics to estimate both speciation and net diversification rates.We show decisively that model-free tip rate metrics provide a better estimate of the rate of speciation than of net diversification. Error in net diversification rate estimates increases as a function of the relative extinction rate. In contrast, error in speciation rate estimates is low and relatively insensitive to extinction. Overall, and in particular when relative extinction was high, BAMM inferred the most accurate tip rates and exhibited lower error than non-model-based approaches. DR was highly correlated with true speciation rates but exhibited high error variance, and was the best metric for very small rate regimes.We found that, of the metrics tested, DR and BAMM are the most useful metrics for studying speciation rate dynamics and trait-dependent diversification. Although BAMM was more accurate than DR overall, the two approaches have complementary strengths. Because tip rate metrics are more reliable estimators of speciation rate, we recommend that empirical studies using these metrics exercise caution when drawing biological interpretations in any situation where the distinction between speciation and net diversification is important.


2019 ◽  
Vol 19 (19) ◽  
pp. 12811-12833 ◽  
Author(s):  
Renske Timmermans ◽  
Arjo Segers ◽  
Lyana Curier ◽  
Rachid Abida ◽  
Jean-Luc Attié ◽  
...  

Abstract. We present an Observing System Simulation Experiment (OSSE) dedicated to the evaluation of the added value of the Sentinel-4 and Sentinel-5P missions for tropospheric nitrogen dioxide (NO2). Sentinel-4 is a geostationary (GEO) mission covering the European continent, providing observations with high temporal resolution (hourly). Sentinel-5P is a low Earth orbit (LEO) mission providing daily observations with a global coverage. The OSSE experiment has been carefully designed, with separate models for the simulation of observations and for the assimilation experiments and with conservative estimates of the total observation uncertainties. In the experiment we simulate Sentinel-4 and Sentinel-5P tropospheric NO2 columns and surface ozone concentrations at 7 by 7 km resolution over Europe for two 3-month summer and winter periods. The synthetic observations are based on a nature run (NR) from a chemistry transport model (MOCAGE) and error estimates using instrument characteristics. We assimilate the simulated observations into a chemistry transport model (LOTOS-EUROS) independent of the NR to evaluate their impact on modelled NO2 tropospheric columns and surface concentrations. The results are compared to an operational system where only ground-based ozone observations are ingested. Both instruments have an added value to analysed NO2 columns and surface values, reflected in decreased biases and improved correlations. The Sentinel-4 NO2 observations with hourly temporal resolution benefit modelled NO2 analyses throughout the entire day where the daily Sentinel-5P NO2 observations have a slightly lower impact that lasts up to 3–6 h after overpass. The evaluated benefits may be even higher in reality as the applied error estimates were shown to be higher than actual errors in the now operational Sentinel-5P NO2 products. We show that an accurate representation of the NO2 profile is crucial for the benefit of the column observations on surface values. The results support the need for having a combination of GEO and LEO missions for NO2 analyses in view of the complementary benefits of hourly temporal resolution (GEO, Sentinel-4) and global coverage (LEO, Sentinel-5P).


2016 ◽  
Author(s):  
Kathleen Sell ◽  
Erik-H. Saenger ◽  
Andrzej Falenty ◽  
Marwen Chaouachi ◽  
David Haberthür ◽  
...  

Abstract. To date, very little is known about the distribution of gas hydrates in sedimentary matrices and the resulting matrix-pore network affecting the seismic properties at low hydrate concentration. Digital rock physics offers a unique solution to this issue yet requires good quality, high resolution 3D representations for the accurate modelling of petrophysical and transport properties. Although such models are readily available via in-situ synchrotron radiation X-ray tomography the analysis of such data asks for complex workflows and high computational power to maintain valuable results. Here, we present a best-practise procedure complementing data from Chaouachi et al. (Geochemistry, Geophysics, Geosystems 2015, 16 (6), 1711–1722) with data post-processing, including image enhancement and segmentation as well as numerical simulations in 3D using the derived results as a direct model input. The method presented opens a path to a model-free deduction of the properties of gas hydrate bearing sediments when aiming for in-situ experiments linked to synchrotron-based tomography and 3D modelling.


2019 ◽  
Vol 19 (21) ◽  
pp. 13445-13467 ◽  
Author(s):  
Yueming Cheng ◽  
Tie Dai ◽  
Daisuke Goto ◽  
Nick A. J. Schutgens ◽  
Guangyu Shi ◽  
...  

Abstract. Aerosol vertical information is critical to quantify the influences of aerosol on the climate and environment; however, large uncertainties still persist in model simulations. In this study, the vertical aerosol extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) are assimilated to optimize the hourly aerosol fields of the Non-hydrostatic ICosahedral Atmospheric Model (NICAM) online coupled with the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) using a four-dimensional local ensemble transform Kalman filter (4-D LETKF). A parallel assimilation experiment using bias-corrected aerosol optical thicknesses (AOTs) from the Moderate Resolution Imaging Spectroradiometer (MODIS) is conducted to investigate the effects of assimilating the observations (and whether to include vertical information) on the model performances. Additionally, an experiment simultaneously assimilating both CALIOP and MODIS observations is conducted. The assimilation experiments are successfully performed for 1 month, making it possible to evaluate the results in a statistical sense. The hourly analyses are validated via both the CALIOP-observed aerosol vertical extinction coefficients and the AOT observations from MODIS and the AErosol RObotic NETwork (AERONET). Our results reveal that both the CALIOP and MODIS assimilations can improve the model simulations. The CALIOP assimilation is superior to the MODIS assimilation in modifying the incorrect aerosol vertical distributions and reproducing the real magnitudes and variations, and the joint CALIOP and MODIS assimilation can further improve the simulated aerosol vertical distribution. However, the MODIS assimilation can better reproduce the AOT distributions than the CALIOP assimilation, and the inclusion of the CALIOP observations has an insignificant impact on the AOT analysis. This is probably due to the nadir-viewing CALIOP having much sparser coverage than MODIS. The assimilation efficiencies of CALIOP decrease with increasing distances of the overpass time, indicating that more aerosol vertical observation platforms are required to fill the sensor-specific observation gaps and hence improve the aerosol vertical data assimilation.


2009 ◽  
Vol 9 (20) ◽  
pp. 8105-8120 ◽  
Author(s):  
A. T. J. de Laat ◽  
R. J. van der A ◽  
M. van Weele

Abstract. Tropospheric O3 column estimates are produced and evaluated from spaceborne O3 observations by the subtraction of assimilated O3 profile observations from total column observations, the so-called Tropospheric O3 ReAnalysis or TORA method. Here we apply the TORA method to six years (1996–2001) of ERS-2 GOME/TOMS total O3 and ERS-2 GOME O3 profile observations using the TM5 global chemistry-transport model with a linearized O3 photochemistry parameterization scheme. Free running TM5 simulations show good agreement with O3 sonde observations in the upper-tropospheric and lower stratospheric region (UTLS), both for short day-to-day variability as well as for monthly means. The assimilation of GOME O3 profile observations counteracts the mid-latitude stratospheric O3 drift caused by the overstrong stratospheric meridional circulation in TM5. Assimilation of GOME O3 profile observations also improves the bias and correlations in the tropical UTLS region but slightly degrades the model-to-sonde correlations and bias of extra-tropical UTLS. We suggest that this degradation is related to the large ground pixel size of the GOME O3 measurements (960×100 km) in combination with retrieval and calibration errors. The added value of the assimilation of GOME O3 profiles compared to stand-alone model simulations lays in the long term variations of stratospheric O3, not in short term synoptic variations. The evaluation of daily and monthly tropospheric O3 columns obtained from total column observations and using the TORA methodology shows that the use of GOME UV-VIS nadir O3 profiles in combination with the spatial resolution of the model does not result in satisfactory residual tropospheric ozone columns.


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