scholarly journals Impact of Ragweed Pollen Daily Release Intensity on Long-Range Transport in Western Europe

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 693
Author(s):  
Laurent Menut ◽  
Dmitry Khvorostyanov ◽  
Florian Couvidat ◽  
Frédérik Meleux
Keyword(s):  
Western Europe ◽  
Transport Model ◽  
Temporal Correlation ◽  
Surface Fluxes ◽  
Ragweed Pollen ◽  
Specific Humidity ◽  
Limiting Factors ◽  
Shortwave Radiation ◽  
Release Formulation ◽  
Regional Modelling

This study is dedicated to improving the daily release of ragweed pollen emission in the context of deterministic regional modelling for analysis and forecast. First, correlations are calculated between daily modelled meteorological variables (wind speed, temperature, humidity, precipitation, surface fluxes) and daily pollen counts at nine stations in Hungary, Croatia and France between 2005 and 2011. The 2 m temperature is the most correlated parameter, followed by convective velocity and incoming shortwave radiation, while precipitation rate and 2 m specific humidity act as limiting factors. Using these results, a ragweed pollen daily release formulation is proposed. This formulation is implemented in the CHIMERE chemistry-transport model and tested during the whole year of 2010. Results are compared to observations, and it is shown that the new formulation provides a more realistic day-to-day variability: the spatio-temporal correlation between surface measurements and modelled concentrations is 0.77, greater than two other known emission schemes.

scholarly journals A new model of ragweed pollen release based on the analysis of meteorological conditions

2014 ◽  
Vol 14 (7) ◽  
pp. 10891-10927 ◽  
Author(s):  
L. Menut ◽  
R. Vautard ◽  
A. Colette ◽  
D. Khvorostyanov ◽  
A. Potier ◽  
...  
Keyword(s):  
Meteorological Conditions ◽  
Surface Fluxes ◽  
The Other ◽  
Ragweed Pollen ◽  
Specific Humidity ◽  
Limiting Factors ◽  
Shortwave Radiation ◽  
Convective Velocity ◽  
Pollen Emission ◽  
Pollen Release

Abstract. In order to propose a new deterministic ragweed pollen emission scheme, the meteorological conditions conducive to common ragweed pollen emission are studied over Europe between 2005 and 2011. Correlations are calculated between daily modelled meteorological variables (wind speed, temperature, humidity, precipitations rates, surface fluxes) and surface concentrations at nine stations in Hungary, Croatia and France. We found that the 2 m temperature is the most correlated parameter, followed by convective velocity and incoming shortwave radiation. On the other hand, the precipitation rate and the 2 m specific humidity act as limiting factors. A new emission scheme is designed. Compared to two existing schemes, we show that it is able to better estimate the daily release of ragweed pollen in 73% of modelled cases.

scholarly journals Technical note: A geostatistical fixed-lag Kalman smoother for atmospheric inversions

2008 ◽  
Vol 8 (2) ◽  
pp. 7755-7779
Author(s):  
A. M. Michalak
Keyword(s):  
Carbon Dioxide ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Correlation ◽  
Technical Note ◽  
Surface Fluxes ◽  
Carbon Dioxide Fluxes ◽  
Kalman Smoother ◽  
Geostatistical Approach ◽  
Flux Estimation

Abstract. Inverse modeling methods are now commonly used for estimating surface fluxes of carbon dioxide, using atmospheric mass fraction measurements combined with a numerical atmospheric transport model. The geostatistical approach to flux estimation takes advantage of the spatial and/or temporal correlation in fluxes and does not require prior flux estimates. In this work, a geostatistical implementation of a fixed-lag Kalman smoother is developed to improve the computational efficiency of the inverse problem. This method makes it feasible to perform multi-year inversions, at fine resolutions, and with large amounts of data. The new method is applied to the recovery of global gridscale carbon dioxide fluxes for 1997 to 2001 using pseudodata representative of a subset of the NOAA-ESRL Cooperative Air Sampling Network.

scholarly journals Technical Note: Adapting a fixed-lag Kalman smoother to a geostatistical atmospheric inversion framework

2008 ◽  
Vol 8 (22) ◽  
pp. 6789-6799 ◽  
Author(s):  
A. M. Michalak
Keyword(s):  
Carbon Dioxide ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Correlation ◽  
Technical Note ◽  
Surface Fluxes ◽  
Computationally Efficient ◽  
Carbon Dioxide Fluxes ◽  
Kalman Smoother ◽  
Geostatistical Approach

Abstract. Inverse modeling methods are now commonly used for estimating surface fluxes of carbon dioxide, using atmospheric mass fraction measurements combined with a numerical atmospheric transport model. The geostatistical approach to flux estimation takes advantage of the spatial and/or temporal correlation in fluxes and does not require prior flux estimates. In this work, a previously-developed, computationally-efficient, fixed-lag Kalman smoother is adapted for application with a geostatistical approach to atmospheric inversions. This method makes it feasible to perform multi-year geostatistical inversions, at fine resolutions, and with large amounts of data. The new method is applied to the recovery of global gridscale carbon dioxide fluxes for 1997 to 2001 using pseudodata representative of a subset of the NOAA-ESRL Cooperative Air Sampling Network.

scholarly journals Development of the city-scale chemistry transport model CityChem-EPISODE and its application to the city of Hamburg

2018 ◽  
Author(s):  
Matthias Karl
Keyword(s):  
Air Quality ◽  
Urban Area ◽  
Transport Model ◽  
Dispersion Model ◽  
Temporal Correlation ◽  
Urban Atmosphere ◽  
Aerosol Formation ◽  
Urban Background ◽  
New Model ◽  
The City

Abstract. This paper describes the City-scale Chemistry (CityChem) extension of the urban dispersion model EPISODE with the aim to enable chemistry/transport simulations of multiple reactive pollutants on urban scales. The new model is called CityChem-EPISODE. The primary focus is on the simulation of urban ozone concentrations. Ozone is produced in photochemical reaction cycles involving nitrogen oxides (NOx) and volatile organic compounds (VOC) emitted by various anthropogenic activities in the urban area. The performance of the new model was evaluated with a series of synthetic tests and with a first application to the air quality situation in the city of Hamburg, Germany. The model performs fairly well for ozone in terms of temporal correlation and bias at the air quality monitoring stations in Hamburg. In summer afternoons, when photochemical activity is highest, modelled median ozone at an inner-city urban background station was about 30 % lower than the observed median ozone. Inaccuracy of the computed photolysis frequency of nitrogen dioxide (NO2) is the most probable explanation for this. CityChem-EPISODE reproduces the spatial variation of annual mean NO2 concentrations between urban background, traffic and industrial stations. However, the temporal correlation between modelled and observed hourly NO2 concentrations is weak for some of the stations. For daily mean PM10, the performance of CityChem-EPISODE is moderate due to low temporal correlation. The low correlation is linked to uncertainties in the seasonal cycle of the anthropogenic particulate matter (PM) emissions within the urban area. Missing emissions from domestic heating might be an explanation for the too low modelled PM10 in winter months. Four areas of need for improvement have been identified: (1) dry and wet deposition fluxes; (2) treatment of photochemistry in the urban atmosphere; (3) formation of secondary inorganic aerosol (SIA); and (4) formation of biogenic and anthropogenic secondary organic aerosol (SOA). The inclusion of secondary aerosol formation will allow for a better sectorial attribution of observed PM levels. Envisaged applications of the CityChem-EPISODE model are urban air quality studies, environmental impact assessment, sensitivity analysis of sector-specific emission and the assessment of local and regional emission abatement policy options.

scholarly journals A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 2: Optimization scheme and identical twin experiment of atmospheric CO<sub>2</sub> inversion

2017 ◽  
Vol 10 (6) ◽  
pp. 2201-2219 ◽  
Author(s):  
Yosuke Niwa ◽  
Yosuke Fujii ◽  
Yousuke Sawa ◽  
Yosuke Iida ◽  
Akihiko Ito ◽  
...  
Keyword(s):  
Transport Model ◽  
Surface Fluxes ◽  
Identical Twin ◽  
Inversion Problem ◽  
Model Errors ◽  
Optimization Scheme ◽  
Error Covariance ◽  
Optimal Setting ◽  
Source Sink ◽  
Quasi Newton

Abstract. A four-dimensional variational method (4D-Var) is a popular technique for source/sink inversions of atmospheric constituents, but it is not without problems. Using an icosahedral grid transport model and the 4D-Var method, a new atmospheric greenhouse gas (GHG) inversion system has been developed. The system combines offline forward and adjoint models with a quasi-Newton optimization scheme. The new approach is then used to conduct identical twin experiments to investigate optimal system settings for an atmospheric CO2 inversion problem, and to demonstrate the validity of the new inversion system. In this paper, the inversion problem is simplified by assuming the prior flux errors to be reasonably well known and by designing the prior error correlations with a simple function as a first step. It is found that a system of forward and adjoint models with smaller model errors but with nonlinearity has comparable optimization performance to that of another system that conserves linearity with an exact adjoint relationship. Furthermore, the effectiveness of the prior error correlations is demonstrated, as the global error is reduced by about 15 % by adding prior error correlations that are simply designed when 65 weekly flask sampling observations at ground-based stations are used. With the optimal setting, the new inversion system successfully reproduces the spatiotemporal variations of the surface fluxes, from regional (such as biomass burning) to global scales. The optimization algorithm introduced in the new system does not require decomposition of a matrix that establishes the correlation among the prior flux errors. This enables us to design the prior error covariance matrix more freely.

scholarly journals Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 1: Model description and evaluation of meteorological predictions

2013 ◽  
Vol 13 (2) ◽  
pp. 3993-4058 ◽  
Author(s):  
Y. Zhang ◽  
K. Sartelet ◽  
S.-Y. Wu ◽  
C. Seigneur
Keyword(s):  
Western Europe ◽  
Model Comparison ◽  
Urban Canopy ◽  
Cloud Microphysics ◽  
Specific Humidity ◽  
Meteorological Variables ◽  
Background Information ◽  
Model Description ◽  
Subgrid Scale ◽  
Simulation Design

Abstract. Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e. the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID) are conducted over western Europe. Part 1 describes the background information for the model comparison and simulation design, as well as the application of WRF for January and July 2001 over triple-nested domains in western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°. Six simulated meteorological variables (i.e. temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients of major meteorological variables. While the domainwide performance of T2, Q2, RH2, and WD10 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in WS10 and Precip even at 0.025°. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g. lack of soil temperature and moisture nudging), limitations in the physical parameterizations of the planetary boundary layer (e.g. cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g. snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvement for WS10, Precip, and some mesoscale events (e.g. strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. These results indicate a need to further improve the model representations of the above parameterizations at all scales.

scholarly journals Estimating surface CO<sub>2</sub> fluxes from space-borne CO<sub>2</sub> dry air mole fraction observations using an ensemble Kalman Filter

2009 ◽  
Vol 9 (8) ◽  
pp. 2619-2633 ◽  
Author(s):  
L. Feng ◽  
P. I. Palmer ◽  
H. Bösch ◽  
S. Dance
Keyword(s):  
Kalman Filter ◽  
Mole Fraction ◽  
Ensemble Kalman Filter ◽  
Transport Model ◽  
Co2 Flux ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Co2 Fluxes ◽  
Dry Air ◽  
Geographical Regions

Abstract. We have developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2) and evaluate the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO). The 32-day duty cycle of OCO alternates every 16 days between nadir and glint measurements of backscattered solar radiation at short-wave infrared wavelengths. The EnKF uses an ensemble of states to represent the error covariances to estimate 8-day CO2 surface fluxes over 144 geographical regions. We use a 12×8-day lag window, recognising that XCO2 measurements include surface flux information from prior time windows. The observation operator that relates surface CO2 fluxes to atmospheric distributions of XCO2 includes: a) the GEOS-Chem transport model that relates surface fluxes to global 3-D distributions of CO2 concentrations, which are sampled at the time and location of OCO measurements that are cloud-free and have aerosol optical depths <0.3; and b) scene-dependent averaging kernels that relate the CO2 profiles to XCO2, accounting for differences between nadir and glint measurements, and the associated scene-dependent observation errors. We show that OCO XCO2 measurements significantly reduce the uncertainties of surface CO2 flux estimates. Glint measurements are generally better at constraining ocean CO2 flux estimates. Nadir XCO2 measurements over the terrestrial tropics are sparse throughout the year because of either clouds or smoke. Glint measurements provide the most effective constraint for estimating tropical terrestrial CO2 fluxes by accurately sampling fresh continental outflow over neighbouring oceans. We also present results from sensitivity experiments that investigate how flux estimates change with 1) bias and unbiased errors, 2) alternative duty cycles, 3) measurement density and correlations, 4) the spatial resolution of estimated flux estimates, and 5) reducing the length of the lag window and the size of the ensemble. At the revision stage of this manuscript, the OCO instrument failed to reach its orbit after it was launched on 24 February 2009. The EnKF formulation presented here is also applicable to GOSAT measurements of CO2 and CH4.

Evaluating the effects of lateral control surfaces failure on the generic transport model: a case study

2020 ◽  
Vol 124 (1277) ◽  
pp. 1016-1054
Author(s):  
R. Norouzi ◽  
A. Kosari ◽  
M. Hossein Sabour
Keyword(s):  
Path Planning ◽  
Transport Model ◽  
Control Surface ◽  
Limiting Factors ◽  
Lateral Control ◽  
Maneuvering Flight ◽  
Surface Failure ◽  
Flight Envelope ◽  
And Performance

ABSTRACTExtensive research in recent years has focused on improving the current loss-of-control prevention systems and developing new strategies for safe path planning of the impaired aircraft. Success in developing such systems requires a comprehensive perception of the influence of damage on the aircraft’s dynamic behaviour and performance, and the effect of various failure degrees on the flight envelope confinement and the remaining safe maneuvers. This paper comprehensively describes the effects of lateral control surface failure on the NASA Generic Transport Model (GTM) flight envelope, defined by a set of attainable steady-state maneuvers herein referred to as trim points. The study utilises a large database of high-fidelity maneuvering flight envelopes computed for the unimpaired case and wide ranges of the aileron and rudder failure cases at different flight conditions. Flight envelope boundary is rigorously investigated, and the key parameters confining the trim points at different boundary sections are identified. Trend analyses of the impaired flight envelopes and the corresponding limiting factors demonstrate the effect of various failure degrees on the remaining feasible trim points. Results can be employed in emergency path planning with potential uses in the development of aircraft resilient control and upset recovery systems.

scholarly journals Error correlation between CO<sub>2</sub> and CO as constraint for CO<sub>2</sub> flux inversions using satellite data

2009 ◽  
Vol 9 (19) ◽  
pp. 7313-7323 ◽  
Author(s):  
H. Wang ◽  
D. J. Jacob ◽  
M. Kopacz ◽  
D. B. A. Jones ◽  
P. Suntharalingam ◽  
...  
Keyword(s):  
Inverse Modeling ◽  
Large Scale ◽  
Transport Model ◽  
Meteorological Data ◽  
Correlation Coefficients ◽  
Surface Fluxes ◽  
Satellite Observations ◽  
Carbon Surface ◽  
Chemical Transport Model ◽  
Error Correlation

Abstract. Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h GEOS-5 CTM forecasts of CO2 and CO columns for the same forecast time). We find strong error correlations (r2>0.5) between CO2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. We present a simple inverse modeling application to demonstrate that CO2-CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2-CO inversion vs. a CO2-only inversion.

scholarly journals Trends in surface radiation and cloud radiative effect at four Swiss sites for the 1996–2015 period

2019 ◽  
Vol 19 (20) ◽  
pp. 13227-13241 ◽  
Author(s):  
Stephan Nyeki ◽  
Stefan Wacker ◽  
Christine Aebi ◽  
Julian Gröbner ◽  
Giovanni Martucci ◽  
...  
Keyword(s):  
Longwave Radiation ◽  
Ground Temperature ◽  
Surface Radiation ◽  
Specific Humidity ◽  
Shortwave Radiation ◽  
Radiative Effect ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
Downward Longwave Radiation ◽  
Integrated Water Vapour

Abstract. The trends of meteorological parameters and surface downward shortwave radiation (DSR) and downward longwave radiation (DLR) were analysed at four stations (between 370 and 3580 m a.s.l.) in Switzerland for the 1996–2015 period. Ground temperature, specific humidity, and atmospheric integrated water vapour (IWV) trends were positive during all-sky and cloud-free conditions. All-sky DSR and DLR trends were in the ranges of 0.6–4.3 W m−2 decade−1 and 0.9–4.3 W m−2 decade−1, respectively, while corresponding cloud-free trends were −2.9–3.3 W m−2 decade−1 and 2.9–5.4 W m−2 decade−1. Most trends were significant at the 90 % and 95 % confidence levels. The cloud radiative effect (CRE) was determined using radiative-transfer calculations for cloud-free DSR and an empirical scheme for cloud-free DLR. The CRE decreased in magnitude by 0.9–3.1 W m−2 decade−1 (only one trend significant at 90 % confidence level), which implies a change in macrophysical and/or microphysical cloud properties. Between 10 % and 70 % of the increase in DLR is explained by factors other than ground temperature and IWV. A more detailed, long-term quantification of cloud changes is crucial and will be possible in the future, as cloud cameras have been measuring reliably at two of the four stations since 2013.

Sign in / Sign up

Export Citation Format

Share Document