scholarly journals Tropospheric Ozone Assessment Report: Assessment of global-scale model performance for global and regional ozone distributions, variability, and trends

Elem Sci Anth ◽  
2018 ◽  
Vol 6 ◽  
Author(s):  
P. J. Young ◽  
V. Naik ◽  
A. M. Fiore ◽  
A. Gaudel ◽  
J. Guo ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Tropospheric Ozone ◽  
Model Performance ◽  
Temporal Distribution ◽  
Temporal Variations ◽  
Global Scale ◽  
Scale Model ◽  
Significant Information ◽  
Assessment Report ◽  
Spatio Temporal

The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for the problem being addressed, whether biases can be tolerated or corrected, whether the model is appropriately constituted, and whether there is a way to satisfactorily quantify the uncertainty.

scholarly journals 8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale

2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Air Temperature ◽  
Spatial Scales ◽  
Model Performance ◽  
Global Scale ◽  
Scale Model ◽  
Validation Dataset ◽  
Daily Maximum ◽  
Climate Zone ◽  
Temporal And Spatial

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.

Spatio-temporal variations of caddisfly assemblages in a chalk stream, Balaton Upland, Hungary

Zoosymposia ◽  
2011 ◽  
Vol 5 (1) ◽  
pp. 439-452
Author(s):  
ILDIKÓ SZIVÁK ◽  
ARNOLD MÓRA ◽  
JÚLIA KATALIN TÖRÖK
Keyword(s):  
Indicator Species ◽  
Cold Water ◽  
Human Impacts ◽  
Temporal Structure ◽  
Temporal Distribution ◽  
Weather Conditions ◽  
Temporal Variations ◽  
Aquatic Habitats ◽  
Indicator Value ◽  
Spatio Temporal

In 2006–2007 larval caddisfly assemblages of a semi-natural calcareous stream (Örvényesi Creek) were studied. Characteristic sections can be detected along the whole length of the stream, which passes through diverse types of vegetation, resulting in highly heterogeneous aquatic habitats. Based on an annual survey of different aquatic habitats, our aims were to give an overview of the spatio-temporal distribution of the larval caddisfly assemblages in the Örvényesi Creek and to find indicator species characterizing different sections of the stream. In order to show the spatio-temporal patterns, samples were collected at 7 locations with different streambed morphology, from spring to the mouth of the stream. Caddisfly larvae were collected in every 3rd week during a 1 year period using the “kick and sweep” method. Multivariate analyses were carried out to explore the spatio-temporal structure of caddisfly assemblages. The indicator value method was applied to detect indicator species for different sections of the stream. A rich caddisfly fauna (20 taxa) was found in the Örvényesi Creek. Fast-running and relatively cold-water hypocrenal sections were characterized by Beraea maurus and Apatania muliebris at high indicator value. Three Limnephilidae species (Limnephilus rhombicus, Limnephilus lunatus and Glyphotaelius pellucidus) were identified as significant indicator species for slow flowing, lentic habitats. Along the length of the stream, distinctive spatial and temporal changes were detected in the distribution of the caddisfly assemblages. These changes were mainly connected to variations in morphology of the streambed, phenology of individual taxa, extreme weather conditions and human impacts.

scholarly journals From biota to chemistry and climate: towards a comprehensive description of trace gas exchange between the biosphere and atmosphere

2009 ◽  
Vol 6 (4) ◽  
pp. 7717-7788 ◽  
Author(s):  
A. Arneth ◽  
S. Sitch ◽  
A. Bondeau ◽  
K. Butterbach-Bahl ◽  
P. Foster ◽  
...  
Keyword(s):  
Gas Exchange ◽  
Atmospheric Chemistry ◽  
Land Surface ◽  
Climate Science ◽  
Temporal Variations ◽  
Scale Model ◽  
Trace Gas ◽  
Gas Emissions ◽  
Abstract Exchange ◽  
Trace Gas Emissions

Abstract. Exchange of non-CO2 trace gases between the land surface and the atmosphere plays an important role in atmospheric chemistry and climate. Recent studies have highlighted its importance for interpretation of glacial-interglacial ice-core records, the simulation of the pre-industrial and present atmosphere, and the potential for large climate-chemistry and climate-aerosol feedbacks in the coming century. However, spatial and temporal variations in trace gas emissions and the magnitude of future feedbacks are a major source of uncertainty in atmospheric chemistry, air quality and climate science. To reduce such uncertainties Dynamic Global Vegetation Models (DGVMs) are currently being expanded to mechanistically represent processes relevant to non-CO2 trace gas exchange between land biota and the atmosphere. In this paper we present a review of important non-CO2 trace gas emissions, the state-of-the-art in DGVM modelling of processes regulating these emissions, identify key uncertainties for global scale model applications, and discuss a methodology for model integration and evaluation.

scholarly journals Process-based modelling of biogenic monoterpene emissions combining production and release from storage

2009 ◽  
Vol 9 (10) ◽  
pp. 3409-3423 ◽  
Author(s):  
G. Schurgers ◽  
A. Arneth ◽  
R. Holzinger ◽  
A. H. Goldstein
Keyword(s):  
Atmospheric Chemistry ◽  
Ponderosa Pine ◽  
Temporal Distribution ◽  
Global Scale ◽  
Terrestrial Vegetation ◽  
Temperature Dependent ◽  
Short Term ◽  
Specific Storage ◽  
Production Capacities

Abstract. Monoterpenes, primarily emitted by terrestrial vegetation, can influence atmospheric ozone chemistry, and can form precursors for secondary organic aerosol. The short-term emissions of monoterpenes have been well studied and understood, but their long-term variability, which is particularly important for atmospheric chemistry, has not. This understanding is crucial for the understanding of future changes. In this study, two algorithms of terrestrial biogenic monoterpene emissions, the first one based on the short-term volatilization of monoterpenes, as commonly used for temperature-dependent emissions, and the second one based on long-term production of monoterpenes (linked to photosynthesis) combined with emissions from storage, were compared and evaluated with measurements from a Ponderosa pine plantation (Blodgett Forest, California). The measurements were used to parameterize the long-term storage of monoterpenes, which takes place in specific storage organs and which determines the temporal distribution of the emissions over the year. The difference in assumptions between the first (emission-based) method and the second (production-based) method, which causes a difference in upscaling from instantaneous to daily emissions, requires roughly a doubling of emission capacities to bridge the gap to production capacities. The sensitivities to changes in temperature and light were tested for the new methods, the temperature sensitivity was slightly higher than that of the short-term temperature dependent algorithm. Applied on a global scale, the first algorithm resulted in annual total emissions of 29.6 Tg C a−1, the second algorithm resulted in 31.8 Tg C a−1 when applying the correction factor 2 between emission capacities and production capacities. However, the exact magnitude of such a correction is spatially varying and hard to determine as a global average.

scholarly journals Global-scale combustion sources of organic aerosols: sensitivity to formation and removal mechanisms

2017 ◽  
Vol 17 (12) ◽  
pp. 7345-7364 ◽  
Author(s):  
Alexandra P. Tsimpidi ◽  
Vlassis A. Karydis ◽  
Spyros N. Pandis ◽  
Jos Lelieveld
Keyword(s):  
Organic Compounds ◽  
Atmospheric Chemistry ◽  
Climate Model ◽  
Hybrid Approach ◽  
Model Performance ◽  
Organic Aerosols ◽  
Global Scale ◽  
Emission Rates ◽  
Combustion Sources ◽  
Scavenging Efficiency

Abstract. Organic compounds from combustion sources such as biomass burning and fossil fuel use are major contributors to the global atmospheric load of aerosols. We analyzed the sensitivity of model-predicted global-scale organic aerosols (OA) to parameters that control primary emissions, photochemical aging, and the scavenging efficiency of organic vapors. We used a computationally efficient module for the description of OA composition and evolution in the atmosphere (ORACLE) of the global chemistry–climate model EMAC (ECHAM/MESSy Atmospheric Chemistry). A global dataset of aerosol mass spectrometer (AMS) measurements was used to evaluate simulated primary (POA) and secondary (SOA) OA concentrations. Model results are sensitive to the emission rates of intermediate-volatility organic compounds (IVOCs) and POA. Assuming enhanced reactivity of semi-volatile organic compounds (SVOCs) and IVOCs with OH substantially improved the model performance for SOA. The use of a hybrid approach for the parameterization of the aging of IVOCs had a small effect on predicted SOA levels. The model performance improved by assuming that freshly emitted organic compounds are relatively hydrophobic and become increasingly hygroscopic due to oxidation.

scholarly journals Process-based modelling of biogenic monoterpene emissions: sensitivity to temperature and light

2009 ◽  
Vol 9 (1) ◽  
pp. 271-307 ◽  
Author(s):  
G. Schurgers ◽  
A. Arneth ◽  
R. Holzinger ◽  
A. Goldstein
Keyword(s):  
Atmospheric Chemistry ◽  
Ponderosa Pine ◽  
Temporal Distribution ◽  
Global Scale ◽  
Terrestrial Vegetation ◽  
Temperature Dependent ◽  
Short Term ◽  
Specific Storage ◽  
Production Capacities

Abstract. Monoterpenes, primarily emitted by terrestrial vegetation, can influence atmospheric ozone chemistry, and can form precursors for secondary organic aerosol. The short-term emissions of monoterpenes have been well studied and understood, but their long-term variability, which is particularly important for atmospheric chemistry, has not. This understanding is crucial for the understanding of future changes. In this study, two algorithms of terrestrial biogenic monoterpene emissions, the first one based on the short-term volatilization of monoterpenes, as commonly used for temperature-dependent emissions, and the second one based on long-term production of monoterpenes (linked to photosynthesis) combined with emissions from storage, were compared and evaluated with measurements from a Ponderosa pine plantation (Blodgett Forest, California). The measurements were used to parameterize the long-term storage of monoterpenes, which takes place in specific storage organs and which determines the temporal distribution of the emissions over the year. The difference in assumptions between the first (emission-based) method and the second (production-based) method, which causes a difference in upscaling from instantaneous to daily emissions, requires roughly a doubling of emission capacities to bridge the gap to production capacities. The sensitivities to changes in temperature and light were tested for the new methods, the temperature sensitivity was slightly higher than that of the short-term temperature dependent algorithm. Applied on a global scale, the first algorithm resulted in annual total emissions of 29.6 Tg C a−1, the second algorithm resulted in 31.8 Tg C a−1 when applying the correction factor 2 between emission capacities and production capacities. However, the exact magnitude of such a correction is spatially varying and hard to determine as a global average.

scholarly journals The effect of using limited scene-dependent averaging kernels approximations for the implementation of fast observing system simulation experiments targeted on lower tropospheric ozone

2013 ◽  
Vol 6 (8) ◽  
pp. 1869-1881 ◽  
Author(s):  
P. Sellitto ◽  
G. Dufour ◽  
M. Eremenko ◽  
J. Cuesta ◽  
V.-H. Peuch ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Tropospheric Ozone ◽  
System Simulation ◽  
Temporal Variations ◽  
Ozone Pollution ◽  
Simulation Experiments ◽  
Atmospheric Species ◽  
Radiative Transfer Calculation ◽  
Pollution Event ◽  
Spatio Temporal

Abstract. Practical implementations of chemical OSSEs (Observing System Simulation Experiments) usually rely on approximations of the pseudo-observations by means of a predefined parametrization of the averaging kernels, which describe the sensitivity of the observing system to the target atmospheric species. This is intended to avoid the use of a computationally expensive pseudo-observations simulator, that relies on full radiative transfer calculations. Here we present an investigation on how no, or limited, scene dependent averaging kernels parametrizations may misrepresent the sensitivity of an observing system. We carried out the full radiative transfer calculation for a three-days period over Europe, to produce reference pseudo-observations of lower tropospheric ozone, as they would be observed by a concept geostationary observing system called MAGEAQ (Monitoring the Atmosphere from Geostationary orbit for European Air Quality). The selected spatio-temporal interval is characterised by an ozone pollution event. We then compared our reference with approximated pseudo-observations, following existing simulation exercises made for both the MAGEAQ and GEOstationary Coastal and Air Pollution Events (GEO-CAPE) missions. We found that approximated averaging kernels may fail to replicate the variability of the full radiative transfer calculations. In addition, we found that the approximations substantially overestimate the capability of MAGEAQ to follow the spatio-temporal variations of the lower tropospheric ozone in selected areas, during the mentioned pollution event. We conclude that such approximations may lead to false conclusions if used in an OSSE. Thus, we recommend to use comprehensive scene-dependent approximations of the averaging kernels, in cases where the full radiative transfer is computationally too costly for the OSSE being investigated.

scholarly journals Spatio-temporal variations of NO<sub>y</sub> species in the northern latitudes stratosphere measured with the balloon-borne MIPAS instrument

2009 ◽  
Vol 9 (4) ◽  
pp. 1151-1163 ◽  
Author(s):  
A. Wiegele ◽  
A. Kleinert ◽  
H. Oelhaf ◽  
R. Ruhnke ◽  
G. Wetzel ◽  
...  
Keyword(s):  
Continuous Measurement ◽  
Temporal Distribution ◽  
Polar Vortex ◽  
Temporal Variations ◽  
Model Calculations ◽  
Mixing Ratios ◽  
Northern Latitudes ◽  
Photolysis Rates ◽  
Spatio Temporal ◽  
Good Agreement

Abstract. This paper presents the spatio-temporal distribution of NOy species at altitudes between 14 and 31 km as measured with the MIPAS-B instrument on the morning of 21 March 2003 in northern Scandinavia. At lower altitudes (below about 22 km), temperature variations, the distribution of ClONO2, and the tracer N2O reveal the dynamics through the edge of the late arctic polar vortex. At higher altitudes, continuous measurement before, during, and after sunrise provides information about photochemistry illustrating the evolution of the photochemically active gases NO2 and N2O5 around sunrise. The measured temporal evolution of NO2 and N2O5 is compared to box modelling that is run along backward calculated trajectories. While the comparison of measured and modelled N2O5 reveals significant differences, there is a good agreement between the model and observations for NO2 in terms of volume mixing ratios but the simulated decrease shortly after sunrise is underestimated compared to the measurements. The differences are attributed to the photolysis rates used in the box model calculations.

scholarly journals Modelling the high-resolution dynamic exposure to flood in city-region

2018 ◽  
Author(s):  
Xuehong Zhu ◽  
Qiang Dai ◽  
Dawei Han ◽  
Lu Zhuo ◽  
Shaonan Zhu ◽  
...  
Keyword(s):  
Population Distribution ◽  
Temporal Distribution ◽  
Temporal Variations ◽  
Urban Flooding ◽  
City Region ◽  
Loss Assessment ◽  
Urban Flood ◽  
Flood Exposure ◽  
Spatio Temporal ◽  
Dynamic Exposure

Abstract. Urban flooding exposure is generally investigated with the assumption of stationary disasters and disaster-bearing bodies within an event, and thus cannot satisfy the increasingly elaborative modelling and management of urban flood. In this study, a comprehensive method was developed to simulate dynamic exposure to urban flooding considering residents’ travel behavior. First, a flood simulation was conducted using the LISFLOOD-FP model to predict the spatio-temporal distribution of flooding. Second, an agent-based model was used to simulate residents’ movements during the period of urban flooding. Finally, to study the evolution and patterns of urban flooding exposure, the exposure of population, roads, and buildings to urban flooding was simulated using Lishui, China as the case study. The results indicated evident spatio-temporal variations in urban flooding and population distribution. Additionally, the exposure increased with increasing rainfall and flooding severity. The urban area near the Oujiang River was the most severely flooded and indicated the largest amount of exposure of population, roads, and buildings. Furthermore, the impacts of flooding on roads were greater than those on population and on buildings. This study presents the first fully formulated method for dynamic urban flood exposure simulation at high spatio-temporal resolution. The results of this study can provide baseline data for determining urban flood disaster vulnerability, socioeconomic loss assessment, urban disaster risk management, and for establishing emergency response plans.

scholarly journals Sea-crossing along migratory flyways is limited more strongly by wind than by lack of uplift

2020 ◽  
Author(s):  
Elham Nourani ◽  
Paolo Becciu ◽  
Richard O. Bierregaard ◽  
Olivier Duriez ◽  
Sinos Giokas ◽  
...  
Keyword(s):  
Animal Movement ◽  
Migratory Birds ◽  
Bird Species ◽  
Temporal Distribution ◽  
Global Scale ◽  
Route Selection ◽  
Atmospheric Conditions ◽  
Ecological Barriers ◽  
Open Sea ◽  
Spatio Temporal

AbstractThe open sea is considered an ecological barrier to terrestrial bird movement. However, over-water journeys of many terrestrial birds, sometimes hundreds of kilometers long, are being uncovered by bio-logging technology. To understand how these birds afford their flights over the open sea, we investigated the role of atmospheric conditions in subsidizing sea-crossing behavior at the global scale. By analyzing forty years of temperature data, we show that the spatio-temporal patterns of sea-crossing in terrestrial migratory birds correspond to favorable uplift conditions. We then analyzed route selection over the open sea for four bird species with varying levels of dependence on soaring flight, representing all major migratory flyways worldwide. Our results showed that favorable uplift conditions, albeit not as common and powerful as over land, are not rare over the open seas and oceans. Moreover, wind, which is more variable than uplift in its spatio-temporal distribution, is the determining factor in the birds’ route selection over the open sea. Our findings suggest a need for revisiting how ecological barriers are defined, to reflect what we know of animal movement in the era of bio-logging.

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