Trends in tropospheric nitrogen dioxide (NO sub(2)) columns over 66 large urban agglomerations worldwide have been computed using data from the SCanning Imaging Absorption spectroMeter for ...Atmospheric CHartographY (SCIAMACHY) instrument onboard the Envisat platform for the period August 2002 to March 2012. A seasonal model including a linear trend was fitted to the satellite-based time series over each site. The results indicate distinct spatial patterns in trends. While agglomerations in Europe, North America, and some locations in East Asia/Oceania show decreasing tropospheric NO sub(2) levels on the order of -5% yr super(-1), rapidly increasing levels of tropospheric NO sub(2) are found for agglomerations in large parts of Asia, Africa, and South America. The site with the most rapidly increasing absolute levels of tropospheric NO sub(2) was found to be Tianjin in China with a trend of 3.04 ( plus or minus 0.47) x 10 super(15) molecules cm super(-2)yr super(-1), whereas the site with the most rapidly increasing relative trend was Kabul in Afghanistan with 14.3 ( plus or minus 2.2) % yr super(-1). In total, 34 sites exhibited increasing trends of tropospheric NO sub(2) throughout the study period, 24 of which were found to be statistically significant. A total of 32 sites showed decreasing levels of tropospheric NO sub(2) during the study period, of which 20 sites did so at statistically significant magnitudes. Overall, going beyond the relatively small set of megacities investigated previously, this study provides the first consistent analysis of recent changes in tropospheric NO sub(2) levels over most large urban agglomerations worldwide, and indicates that changes in urban NO sub(2) levels are subject to substantial regional differences as well as influenced by economic and demographic factors.
Stratospheric ozone profiles from MLS and tropospheric ozone columns from IASI have been assimilated into the MOCAGE model during the month of July 2009, using a variational (3D‐FGAT) technique. This ...study compares the separate and combined analysis of IASI tropospheric columns and MLS stratospheric profiles, in order to investigate possible synergistic effects. The contributions on the ozone distribution of each data assimilation experiment are discussed and self‐consistency is evaluated via χ2 test, Observations minus Analyses and Observations minus Forecasts diagnostics. The results show that MLS assimilation has a significant impact on the model troposphere. An evaluation of the stratospheric distribution is made using independent MIPAS stratospheric profiles. IAGOS flights are used to evaluate the impact of the dataset assimilated in the troposphere and in the UTLS region. Comparisons to MIPAS independent observations show an improvement of the ozone vertical profile in the stratosphere and in the UTLS due to the assimilation of MLS observations. The IASI analyses show the strongest improvements on ozone distributions in the free troposphere. The combined assimilation shows the most realistic ozone fields overall in the stratosphere, UTLS and troposphere. Though neither instrument covers the entire atmospheric column alone, the combined MLS and IASI analyses show also the best agreement with the independent total ozone columns data from the OMI dataset. Bias, RMSE and correlation are significantly improved compared to the free running model. This set of validations show that the vertical structure of the ozone fields is strongly improved by assimilation. By combining the pieces of information brought by IASI and MLS in the analyses, combined assimilation provides highly realistic ozone fields.
We assimilate stratospheric ozone profiles from MLS (Microwave Limb Sounder) into the MOCAGE Chemistry Transport Model (CTM) to study Stratosphere-Troposphere Exchange (STE). This study uses two ...horizontal grid resolutions of 2° and 0.2°. The combined impacts of MLS ozone assimilation and high horizontal resolution are illustrated in two case studies where STE events occurred (23 June 2009 and 17 July 2009). At high resolution the filamentary structures of stratospheric air which characterise STE events are captured by the model. To test the impact of the assimilation and the resolution, we compare model outputs from different experiments (high resolution and low resolution; MLS assimilation run and free run) with independent data (MOZAIC aircraft ozone data; WOUDC ozone sonde network data). MLS ozone analyses show a better description of the Upper Troposphere Lower Stratosphere (UTLS) region and the stratospheric intrusions than the free model run. In particular, at high horizontal resolution the MLS ozone analyses present realistic filamentary ozone structures in the UTLS and laminae structures in the ozone profile. Despite a low aspect ratio between horizontal resolution and vertical resolution in the UTLS at high horizontal resolution, MLS ozone analyses improve the vertical structures of the ozone fields. Results from backward trajectories and ozone forecasts show that assimilation at high horizontal resolution of MLS ozone profiles between 10 hPa and 215 hPa has an impact on tropospheric ozone.
This paper discusses the global analyses of stratospheric ozone (O3) and nitrogen dioxide (NO2) obtained by the Belgian Assimilation System for Chemical Observations from Envisat (BASCOE). Based on a ...chemistry transport model (CTM) and the 4-dimensional variational (4D-Var) method, BASCOE has assimilated chemical observations of O3, NO2, HNO3, N2O, CH4 and H2O, made between July 2002 and March 2004 by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) onboard the European Space Agency (ESA) Environment Satellite (ENVISAT). This corresponds to the entire period during which MIPAS was operating at its nominal resolution. Our analyses are evaluated against assimilated MIPAS data and independent HALOE (HALogen Occultation Experiment) and POAM-III (Polar Ozone and Aerosol Measurement) satellite data. A good agreement is generally found between the analyses and these datasets, in both cases within the estimated error bars of the observations. The benefit of data assimilation is also evaluated by comparing a BASCOE free model run with MIPAS observations. For O3, the gain from the assimilation is significant during ozone hole conditions, and in the lower stratosphere. Elsewhere, the assimilation does not provide significant improvement. For NO2, the gain from the assimilation is realized through most of the stratosphere. Using the BASCOE analyses, we estimate the differences between MIPAS data and independent data from HALOE and POAM-III, and find results close to those obtained by classical validation methods involving only direct measurement-to-measurement comparisons. Our results extend and reinforce previous MIPAS data validation efforts by taking into account a much larger variety of atmospheric states and measurement conditions. This study discusses possible further developments of the BASCOE data assimilation system; these concern the horizontal resolution, a better filtering of NO2 observations, and the photolysis calculation near the lid of the model. The ozone analyses are part of the PROMOTE project and are publicly available via the BASCOE website (http://www.bascoe.oma.be/promote/).
Model averaging in ecology Dormann, Carsten F.; Calabrese, Justin M.; Guillera-Arroita, Gurutzeta ...
Ecological monographs,
November 2018, Letnik:
88, Številka:
4
Journal Article
Recenzirano
Odprti dostop
In ecology, the true causal structure for a given problem is often not known, and several plausible models and thus model predictions exist. It has been claimed that using weighted averages of these ...models can reduce prediction error, as well as better reflect model selection uncertainty. These claims, however, are often demonstrated by isolated examples. Analysts must better understand under which conditions model averaging can improve predictions and their uncertainty estimates. Moreover, a large range of different model averaging methods exists, raising the question of how they differ in their behaviour and performance. Here, we review the mathematical foundations of model averaging along with the diversity of approaches available. We explain that the error in model-averaged predictions depends on each model's predictive bias and variance, as well as the covariance in predictions between models, and uncertainty about model weights. We show that model averaging is particularly useful if the predictive error of contributing model predictions is dominated by variance, and if the covariance between models is low. For noisy data, which predominate in ecology, these conditions will often be met. Many different methods to derive averaging weights exist, from Bayesian over information-theoretical to cross-validation optimized and resampling approaches. A general recommendation is difficult, because the performance of methods is often context dependent. Importantly, estimating weights creates some additional uncertainty. As a result, estimated model weights may not always outperform arbitrary fixed weights, such as equal weights for all models. When averaging a set of models with many inadequate models, however, estimating model weights will typically be superior to equal weights. We also investigate the quality of the confidence intervals calculated for model-averaged predictions, showing that they differ greatly in behaviour and seldom manage to achieve nominal coverage. Our overall recommendations stress the importance of non-parametric methods such as cross-validation for a reliable uncertainty quantification of model-averaged predictions.
This paper aims to summarise the current performance of ozone data assimilation (DA) systems, to show where they can be improved, and to quantify their errors. It examines 11 sets of ozone analyses ...from 7 different DA systems. Two are numerical weather prediction (NWP) systems based on general circulation models (GCMs); the other five use chemistry transport models (CTMs). The systems examined contain either linearised or detailed ozone chemistry, or no chemistry at all. In most analyses, MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) ozone data are assimilated; two assimilate SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) observations instead. Analyses are compared to independent ozone observations covering the troposphere, stratosphere and lower mesosphere during the period July to November 2003. Biases and standard deviations are largest, and show the largest divergence between systems, in the troposphere, in the upper-troposphere/lower-stratosphere, in the upper-stratosphere and mesosphere, and the Antarctic ozone hole region. However, in any particular area, apart from the troposphere, at least one system can be found that agrees well with independent data. In general, none of the differences can be linked to the assimilation technique (Kalman filter, three or four dimensional variational methods, direct inversion) or the system (CTM or NWP system). Where results diverge, a main explanation is the way ozone is modelled. It is important to correctly model transport at the tropical tropopause, to avoid positive biases and excessive structure in the ozone field. In the southern hemisphere ozone hole, only the analyses which correctly model heterogeneous ozone depletion are able to reproduce the near-complete ozone destruction over the pole. In the upper-stratosphere and mesosphere (above 5 hPa), some ozone photochemistry schemes caused large but easily remedied biases. The diurnal cycle of ozone in the mesosphere is not captured, except by the one system that includes a detailed treatment of mesospheric chemistry. These results indicate that when good observations are available for assimilation, the first priority for improving ozone DA systems is to improve the models. The analyses benefit strongly from the good quality of the MIPAS ozone observations. Using the analyses as a transfer standard, it is seen that MIPAS is ~5% higher than HALOE (Halogen Occultation Experiment) in the mid and upper stratosphere and mesosphere (above 30 hPa), and of order 10% higher than ozonesonde and HALOE in the lower stratosphere (100 hPa to 30 hPa). Analyses based on SCIAMACHY total column are almost as good as the MIPAS analyses; analyses based on SCIAMACHY limb profiles are worse in some areas, due to problems in the SCIAMACHY retrievals.
MONITORING AIR QUALITY FROM SPACE Lahoz, W. A.; Peuch, V.-H.; Orphal, J. ...
Bulletin of the American Meteorological Society,
02/2012, Letnik:
93, Številka:
2
Journal Article
Recenzirano
Odprti dostop
Air quality (AQ) is defined by the atmospheric composition of gases and particulates near the Earth's surface. This composition depends on local emissions of pollutants, chemistry, and transport ...processes; it is highly variable in space and time. Key lower-tropospheric pollutants include ozone, aerosols, and the ozone precursors NOₓ and volatile organic compounds. Information on the transport of pollutants is provided by carbon monoxide measurements. Air quality impacts human society, because high concentrations of pollutants can have adverse effects on human health; health costs attributable to AQ are high. The ability to monitor, forecast, and manage AQ is thus crucial for human society. In this paper we identify the observational requirements needed to undertake this task, discuss the advantages of the geostationary platform for monitoring AQ from space, and indicate important challenges to overcome. We present planned geostationary missions to monitor AQ in Europe, the United States, and Asia, and advocate for the usefulness of such a constellation in addition to the current global observing system of tropospheric composition.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We present an observing simulated system experiment (OSSE) dedicated to evaluate the potential added value from the Sentinel-4 and the Sentinel-5P observations on tropospheric ozone composition. For ...this purpose, the ozone data of Sentinel-4 (Ultraviolet Visible Near-infrared) and Sentinel-5P (TROPOspheric Monitoring Instrument) on board a geostationary (GEO) and a low-Earth-orbit (LEO) platform, respectively, have been simulated
using the DISAMAR inversion package
for the summer 2003. To ensure the robustness of the results, the OSSE has been configured with conservative assumptions. We simulate the reality by combining two chemistry transport models (CTMs): the LOng Term Ozone Simulation – EURopean Operational Smog (LOTOS-EUROS) and the Transport Model version 5 (TM5). The assimilation system is based on a different CTM, the MOdèle de Chimie Atmosphérique à Grande Echelle (MOCAGE), combined with the 3-D variational technique. The background error covariance matrix does not evolve in time and its variance is proportional to the field values. The simulated data are formed of six eigenvectors to minimize the size of the dataset by removing the noise-dominated part of the observations. The results show that the satellite data clearly bring direct added value around 200 hPa for the whole assimilation period and for the whole European domain, while a likely indirect added value is identified but not for the whole period and domain at 500 hPa, and to a lower extent at 700 hPa. In addition, the ozone added value from Sentinel-5P (LEO) appears close to that from Sentinel-4 (GEO) in the free troposphere (200–500 hPa) in our OSSE.
The outcome of our study is a result of the OSSE design and the choice within each of the components of the system.
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