119 results found
Wells CD, Kasoar M, Ezzati M, et al., 2024, Significant human health co-benefits of mitigating African emissions., Atmospheric Chemistry and Physics, Vol: 24, Pages: 1025-1039, ISSN: 1680-7316
Future African aerosol emissions, and therefore air pollution levels and health outcomes, are uncertain and understudied. Understanding the future health impacts of pollutant emissions from this region is crucial. Here, this research gap is addressed by studying the range in the future health impacts of aerosol emissions from Africa in the Shared Socioeconomic Pathway (SSP) scenarios, using the UK Earth System Model version 1 (UKESM1), along with human health concentration-response functions. The effects of Africa following a high-pollution aerosol pathway are studied relative to a low-pollution control, with experiments varying aerosol emissions from industry and biomass burning. Using present-day demographics, annual deaths within Africa attributable to ambient particulate matter are estimated to be lower by 150 000 (5th-95th confidence interval of 67 000-234 000) under stronger African aerosol mitigation by 2090, while those attributable to O3 are lower by 15 000 (5th-95th confidence interval of 9000-21 000). The particulate matter health benefits are realised predominantly within Africa, with the O3-driven benefits being more widespread - though still concentrated in Africa - due to the longer atmospheric lifetime of O3. These results demonstrate the important health co-benefits from future emission mitigation in Africa.
Perkins O, Kasoar M, Voulgarakis A, et al., 2023, Supplementary material to "A global behavioural model of human fire use and management: WHAM! v1.0"
Blackford KR, Kasoar M, Burton C, et al., 2023, Supplementary material to "INFERNO-peat v1.0.0: A representation of northern high latitude peat fires in the JULES-INFERNO global fire model"
Rosu I-A, Grillakis M, Papadopoulos A, et al., 2023, Fractal and Spectral Analysis of Recent Wildfire Scars in Greece, FIRE TECHNOLOGY, ISSN: 0015-2684
Chatoutsidou SE, Saridaki A, Raisi L, et al., 2023, Variations, seasonal shifts and ambient conditions affecting airborne microorganisms and particles at a southeastern Mediterranean site, SCIENCE OF THE TOTAL ENVIRONMENT, Vol: 892, ISSN: 0048-9697
Wells CD, Kasoar M, Ezzati M, et al., 2023, Supplementary material to "Significant human health co-benefits of African emissions mitigation"
Misal H, Varela E, Voulgarakis A, et al., 2023, Assessing public preferences for a wildfire mitigation policy in Crete, Greece, Forest Policy and Economics, Vol: 153, Pages: 1-16, ISSN: 1389-9341
The increased frequency and severity of wildfires in the Mediterranean region generates significant damages in ecosystems and landscapes while harming human populations. Institutional complexities, along with socioeconomic and demographic changes encouraging development into the wildland-urban interface, rural abandonment, and focus on fire suppression, are increasing the vulnerability and flammability of Mediterranean ecosystems. Developing effective strategies for managing wildfire incidence and its aftermath requires understanding of the public preferences for wildfire policy characteristics. Here we elicit public preferences for wildfire mitigation policies employing a stated choice experiment applied in Crete, Greece. A region with typical Mediterranean landscape experiencing significant development and rural-to-urban migration that disrupts existing fire regimes. We estimate conditional logit, mixed logit and latent class models to study the general public's preferences and willingness to pay for limiting wildfire frequency and agricultural land burnt, maintaining landscape features, and managing post-wildfire recovery. Results of our study show that measures to manage post-wildfire damage are consistently valued as the most positive amongst the sampled respondents, achieving values that range between €25.92 in conditional logit model to €46 in one of the latent classes identified. Improving the landscape quality follows in importance, although it shows more heterogeneity in the responses. The latent class approach allowed to identify that those associated with either the agricultural or the tourism sector of the sampled individuals, displayed significantly different preferences for the proposed attributes. Overall, our findings indicate that there is a strong preference amongst the general public to shift current policies based on suppression towards more integrated approaches dealing both with prevention and post-fire management. The outcomes of th
Stjern CW, Forster PM, Jia H, et al., 2023, The Time Scales of Climate Responses to Carbon Dioxide and Aerosols, JOURNAL OF CLIMATE, Vol: 36, Pages: 3537-3551, ISSN: 0894-8755
Blackford K, Voulgarakis A, Prentice C, et al., 2023, Representing Northern High Latitude Peat Fires in the JULES-INFERNO Fire Model
<jats:p>Anthropogenic activities and climate change are increasing the vulnerability of carbon rich peatlands to wildfires. Peat fires, which are dominated by smouldering combustion, are some of the largest and most persistent wildfires on Earth. Across the northern high latitudes, peat fires have the potential to release vast amounts of long term stored carbon and other greenhouse gases and aerosols. Consequently, peat fires can have huge implications on the carbon cycle and result in a positive feedback effect on the climate system. Peat fires also impact air quality and can lead to haze events, with major impacts on human health. Despite the importance of peat fires they are currently not represented in most fire models, leading to large underestimations of burnt area and carbon emissions in the high latitudes. Here, I present a representation of peat fires in the JULES-INFERNO fire model (INFERNO-peat). INFERNO-peat improves the representation of burnt area across the high latitudes, with notable areas of improvement in Canada and Siberia. INFERNO-peat also highlights a large amount of interannual variability in carbon emissions from peat fires. The inclusion of peat fires into JULES-INFERNO demonstrates the importance of representing peat fires in models, and not doing so may heavily restrict our ability to model present and future fires and their impacts across the northern high latitudes.</jats:p>
Teixeira J, Burton C, Kelley DI, et al., 2023, Impact of socio-economic factors in burnt area for future climate scenarios
<jats:p>Fire processes are a complex component of the Earth System processes and their full representation has proven to be difficult to represent Earth System Models (ESM). Because of this, these processes are often simplified in fire enabled ESMs, for instance ignitions are usually modelled to increase at low population densities up to a threshold, and reduce thereafter, as suppression effects become dominant with the increase of population density. However, socio-economic, and cultural factors can play a significant role in shaping the behaviour of fire ignitions. This study aims to address this by implementing a socio-economic factor in the fire ignition and suppression parametrisation in the INteractive Fire and Emission algoRithm for Natural envirOnments (INFERNO) based on the Human Development Index (HDI). The inclusion of this factor reduced a large long-standing positive bias found in regions of Temperate North America, Central America, Europe, and Southern Hemisphere South America. This change also leads to improvements in the model representation of fire weather and anthropogenic drivers in tropical regions, by reducing the influence of population density changes. Therefore, this framework can be used to improve understanding of the anthropogenic impacts of fire in future scenarios based on different Shared Socioeconomic Pathways.</jats:p>
Wells C, Kasoar M, Bellouin N, et al., 2023, Local and remote climate impacts of future African aerosol emissions, Atmospheric Chemistry and Physics, Vol: 23, Pages: 3575-3593, ISSN: 1680-7316
The potential future trend in African aerosol emissions is uncertain, with a large range found in future scenarios used to drive climate projections. The future climate impact of these emissions is therefore uncertain. Using the Shared Socioeconomic Pathway (SSP) scenarios, transient future experiments were performed with the UK Earth System Model (UKESM1) to investigate the effect of African emissions following the high emission SSP370 scenario as the rest of the world follows the more sustainable SSP119, relative to a global SSP119 control. This isolates the effect of Africa following a relatively more polluted future emissions pathway. Compared to SSP119, SSP370 projects higher non-biomass-burning (non-BB) aerosol emissions, but lower biomass burning emissions, over Africa. Increased shortwave (SW) absorption by black carbon aerosol leads to a global warming, but the reduction in the local incident surface radiation close to the emissions is larger, causing a local cooling effect. The local cooling persists even when including the higher African CO2 emissions under SSP370 than SSP119. The global warming is significantly higher by 0.07 K when including the non-BB aerosol increases and higher still (0.22 K) when including all aerosols and CO2. Precipitation also exhibits complex changes. Northward shifts in the Inter-tropical Convergence Zone (ITCZ) occur under relatively warm Northern Hemisphere land, and local rainfall is enhanced due to mid-tropospheric instability from black carbon absorption. These results highlight the importance of future African aerosol emissions for regional and global climate and the spatial complexity of this climate influence.
Xie X, Myhre G, Shindell D, et al., 2022, Anthropogenic sulfate aerosol pollution in South and East Asia induces increased summer precipitation over arid Central Asia, COMMUNICATIONS EARTH & ENVIRONMENT, Vol: 3
Kourgialas NN, Hliaoutakis A, Argyriou AV, et al., 2022, A web-based GIS platform supporting innovative irrigation management techniques at farm-scale for the Mediterranean island of Crete., Sci Total Environ, Vol: 842
The aim of this paper is the creation of an integrated and free-access web platform for parcel irrigation water management on a large spatial scale (Water District of Crete, in Greece) in order to: a) accurately determine the irrigation needs of the main crops for Crete such as olives, citrus, avocados and vineyards, b) design strategies, for optimal adaptation of the agricultural sector in the context of climate change, and c) incorporate the dynamic integration of the above information through the creation of a digital platform. In the proposed decision-making system, essential factors are taken into account, such as real-time meteorological data, information about the type and spatial distribution of the agricultural parcels in Crete, algorithms for calculation crop evapotranspiration per development stage and age of the crops, satellite remote sensing techniques in combination with field surveys to depict accurate soil texture map for the whole island of Crete as well as sustainable cultivation practices for saving water per crop and parcel geomorphology. Based on the proposed decision-making system, users will have the opportunity in any specific location/farm in Crete to know the irrigation needs of the crops in real-time and obtain information about proper climate-water adaptation practices. The main novelty points of the proposed platform include the derivation of parcel-level soil texture data from Sentinel-2 satellite imagery and field samples, the comprehensiveness of the irrigation management information, the relatively low data requirements and the application interface simplicity provided to the end-user.
Wells CD, Kasoar M, Bellouin N, et al., 2022, Supplementary material to "Local and remote climate impacts of future African aerosol emissions"
Rovithakis A, Grillakis MG, Seiradakis KD, et al., 2022, Future climate change impact on wildfire danger over the Mediterranean: the case of Greece, Environmental Research Letters, Vol: 17, ISSN: 1748-9326
Recent studies have shown that temperature and precipitation in the Mediterranean are expected to change, contributing to longer and more intense summer droughts that even extend out of season. In connection to this, the frequency of forest fire occurrence and intensity will likely increase. In the present study, the changes in future fire danger conditions are assessed for the different regions of Greece using the Canadian fire weather index (FWI). Gridded future climate output as estimated from three regional climate models from the Coordinated Regional Downscaling Experiment are utilized. We use three representative concentration pathways (RCPs) consisting of an optimistic emissions scenario where emissions peak and decline beyond 2020 (RCP2.6), a middle-of-the-road scenario (RCP4.5) and a pessimistic scenario, in terms of mitigation where emissions continue to rise throughout the century (RCP8.5). Based on established critical fire FWI threshold values for Greece, the future change in days with critical fire danger were calculated for different areas of Greece domains. The results show that fire danger is expected to progressively increase in the future especially in the high-end climate change scenario with southern and eastern regions of Greece expected to have up to 40 additional days of high fire danger relative to the late 20th century, on average. Crete, the Aegean Islands, the Attica region, as well as parts of Peloponnese are predicted to experience a stronger increase in fire danger.
Wildfire is an integral part of the Earth system, but at the same time it can pose serious threats to human society and to certain types of terrestrial ecosystems. Meteorological conditions are a key driver of wildfire activity and extent, which led to the emergence of the use of fire danger indices that depend solely on weather conditions. The Canadian Fire Weather Index (FWI) is a widely used fire danger index of this kind. Here, we evaluate how well the FWI, its components, and the climate variables from which it is derived, correlate with observation-based burned area (BA) for a variety of world regions. We use a novel technique, according to which monthly BA are grouped by size for each Global Fire Emissions Database (GFED) pyrographic region. We find strong correlations of BA anomalies with the FWI anomalies, as well as with the underlying deviations from their climatologies for the four climate variables from which FWI is estimated, namely, temperature, relative humidity, precipitation, and wind. We quantify the relative sensitivity of the observed BA to each of the four climate variables, finding that this relationship strongly depends on the pyrographic region and land type. Our results indicate that the BA anomalies strongly correlate with FWI anomalies at a GFED region scale, compared to the strength of the correlation with individual climate variables. Additionally, among the individual climate variables that comprise the FWI, relative humidity and temperature are the most influential factors that affect the observed BA. Our results support the use of the composite fire danger index FWI, as well as its sub-indices, the Build-Up Index (BUI) and the Initial Spread Index (ISI), comparing to single climate variables, since they are found to correlate better with the observed forest or non-forest BA, for the most regions across the globe.
Myhre G, Samset B, Forster PM, et al., 2022, Scientific data from precipitation driver response model intercomparison project, Scientific Data, Vol: 9, Pages: 123-123, ISSN: 2052-4463
This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth's radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project.
Kasoar M, Corsaro C, Voulgarakis A, 2022, Metrics for Regional Climate Responses to Regional Pollutant Emissions
<jats:p>&lt;p&gt;The Absolute Global Temperature change Potential (AGTP) and Absolute Global Precipitation change Potential (AGPP) are widely used climate change indices.&amp;#160; They can be applied quickly and easily to estimate the global mean temperature and precipitation responses to a pulse emission of a long-lived climate pollutant at a given time horizon, making them invaluable policy-relevant metrics.&amp;#160; They can also be extended to short-lived climate pollutants - where a sustained emission is more useful to consider than a pulse emission - by using their time-integrated forms (iAGTP and iAGPP).&lt;/p&gt;&lt;p&gt;However, these metrics are only useful when taking a global-average perspective, and do not allow us to account for the regional nature of either emissions or their climate response.&amp;#160; Although long-lived greenhouse gases induce a relatively homogeneous radiative forcing (RF) which is not sensitive to emission location, nonetheless due to transport of heat there is not a one-to-one correspondence between the RF in a region and the local temperature response.&amp;#160; Moreover when considering short-lived pollutants such as aerosols, the region of emission is potentially critical because the short lifetime of such pollutants results in an inhomogeneous distribution of RF.&amp;#160; Therefore, for both long-lived and short-lived pollutants the AGTP/AGPP (or iAGTP/iAGPP) are not adequate when looking at climate responses on a regional scale, even though this would be the most relevant when evaluating different policy scenarios or climate change impacts.&lt;/p&gt;&lt;p&gt;Here, we combine the results of simulations from the Precipitation Driver Response Model Intercomparison Project (PDRMIP) where emissions (or concentrations) of multiple long- and short-lived climate pollutants were perturbed globally in nine
Misal H, Kountouris I, Voulgarakis A, et al., 2022, Eliciting public preferences for wildfire management policies in Crete, Greece
<jats:p>&lt;p&gt;Fire regimes form an integral part of terrestrial biomes in the Mediterranean region as they provide essential disturbances which change&amp;#160;the&amp;#160;structure and function of plants that favour Mediterranean type climates. Fire is inextricably linked to such ecosystems and cannot be excluded from them. However, the intensification of human activities in Greece, coupled with increasingly unpredictable wildfires has created huge imbalances and jeopardised the ecological integrity of ecosystems. Expansions into the wildland urban interface, rural abandonment, and the focus on fire suppression are increasing the vulnerability and flammability of the Greek environment. The duality of fire is delicate, both at local and national level, catastrophic wildfires singe deeply on landscapes and economies, social burns can take just as long to heal. In Greece, this is further exacerbated by the burgeoning socio-economic and political complexities that have catalysed the current ineffective and unsustainable fire management strategies. Damages from wildfires affect ecosystem services which can lead to a reduction in human wellbeing. Understanding the interactions between ecosystems and humans through environmental valuation is key to implementing effective policy. This study uses economic valuation methods in the form of a choice experiment to elicit public preference for a wildfire management policy in Crete. A survey was deployed around the island, with respondents asked about their preferences between different management strategies. The policies outlined in the survey are made up of the following attributes: risk of fire, agricultural production, landscape quality and post-wildfire damage mitigation. Results from this study indicate a positive preference by the public for a new proposed policy. The findings from this study can be used for decision making in Crete and other similar southern European environments
Teixeira J, Burton C, Kelley DI, et al., 2022, Representing socio-economic factors in INFERNO using the Human Development Index
<jats:p>&lt;p&gt;INFERNO human fire ignitions and fire suppression functions excluded the representation of socio-economic factors (aside population density) that can affect anthropogenic behaviour regarding fire ignitions. To address this, we implement a socio-economic factor in the fire ignition and suppression parametrisation in INFERNO based on an Human Development Index (HDI) term. The HDI is calculated based on three indicators designed to capture the income, health, and education dimensions of human development. Therefore, we assume this leads to a representation where if there is more effort in improving human development, there is also investment on higher fire suppression by the population. Including this representation of socio-economic factors in INFERNO we were able to reduce large positive biases that were found for the regions of Temperate North America, Central America, Europe and Southern Hemisphere South America without significant impact to other regions, improving the model performance at a regional level and better representing processes that drive fire behaviour in the Earth System.&lt;/p&gt;</jats:p>
Myhre G, Stjern C, Samset B, et al., 2022, The timescales of climate responses to carbon dioxide and aerosols
<jats:p>&lt;p&gt;Enhanced emissions of both greenhouse gases and aerosols generate climate responses on a wide range of time scales. An initial radiative response triggers a set of rapid adjustments, which are eventually followed by surface-temperature-driven feedbacks. While a lot happens during the first days and months after a perturbation, the monthly mean data typically used in climate studies are too coarse to show the temporal evolution of responses. In these analyses, we take a closer look at how the climate system responds during the very first hours and days after a sudden increase in carbon dioxide (CO2), in black carbon (BC) or in sulfate (SO4). Five models have performed PDRMIP simulations with hourly output, and we also compare results to monthly PDRMIP and CMIP6 results. We find that the effect of increasing ocean temperatures kicks in after a couple of months. Rapid precipitation reductions are for all three climate perturbations established after just a couple of days, and does for BC not differ much from the full-time response. &amp;#160;For CO2 and SO4, the magnitude of the precipitation response gradually increases with surface warming, and for CO2 the sign of the response changes for negative to positive after two years. Rapid cloud adjustments are typically established within the first 24 hours and while the magnitude of cloud feedbacks for CO2 and SO4 increases over time, the latitude-height pattern of the total cloud changes is clearly present after one year. While previously known that climate responses to BC are dominated by rapid adjustments, this work underlines the swiftness of the processes involved.&lt;/p&gt;</jats:p>
Teixeira JC, Folberth GA, O'Connor FM, et al., 2021, Coupling interactive fire with atmospheric composition and climate in the UK Earth System Model, Geoscientific Model Development, Vol: 14, Pages: 6515-6539, ISSN: 1991-959X
Fire constitutes a key process in the Earth system (ES), being driven by climate as well as affecting the climate by changing atmospheric composition and impacting the terrestrial carbon cycle. However, studies on the effects of fires on atmospheric composition, radiative forcing and climate have been limited to date, as the current generation of ES models (ESMs) does not include fully atmosphere–composition–vegetation coupled fires feedbacks. The aim of this work is to develop and evaluate a fully coupled fire–composition–climate ES model. For this, the INteractive Fires and Emissions algoRithm for Natural envirOnments (INFERNO) fire model is coupled to the atmosphere-only configuration of the UK's Earth System Model (UKESM1). This fire–atmosphere interaction through atmospheric chemistry and aerosols allows for fire emissions to influence radiation, clouds and generally weather, which can consequently influence the meteorological drivers of fire. Additionally, INFERNO is updated based on recent developments in the literature to improve the representation of human and/or economic factors in the anthropogenic ignition and suppression of fire. This work presents an assessment of the effects of interactive fire coupling on atmospheric composition and climate compared to the standard UKESM1 configuration that uses prescribed fire emissions. Results show a similar performance when using the fire–atmosphere coupling (the “online” version of the model) when compared to the offline UKESM1 that uses prescribed fire. The model can reproduce observed present-day global fire emissions of carbon monoxide (CO) and aerosols, despite underestimating the global average burnt area. However, at a regional scale, there is an overestimation of fire emissions over Africa due to the misrepresentation of the underlying vegetation types and an underestimation over equatorial Asia due to a lack of representation of peat fires. Despite this, co
Tang T, Shindell D, Zhang Y, et al., 2021, Distinct surface response to black carbon aerosols, Atmospheric Chemistry and Physics, Vol: 21, Pages: 13797-13809, ISSN: 1680-7316
For the radiative impact of individual climate forcings, most previous studies focused on the global mean values at the top of the atmosphere (TOA), and less attention has been paid to surface processes, especially for black carbon (BC) aerosols. In this study, the surface radiative responses to five different forcing agents were analyzed by using idealized model simulations. Our analyses reveal that for greenhouse gases, solar irradiance, and scattering aerosols, the surface temperature changes are mainly dictated by the changes of surface radiative heating, but for BC, surface energy redistribution between different components plays a more crucial role. Globally, when a unit BC forcing is imposed at TOA, the net shortwave radiation at the surface decreases by −5.87±0.67 W m−2 (W m−2)−1 (averaged over global land without Antarctica), which is partially offset by increased downward longwave radiation (2.32±0.38 W m−2 (W m−2)−1 from the warmer atmosphere, causing a net decrease in the incoming downward surface radiation of −3.56±0.60 W m−2 (W m−2)−1. Despite a reduction in the downward radiation energy, the surface air temperature still increases by 0.25±0.08 K because of less efficient energy dissipation, manifested by reduced surface sensible (−2.88±0.43 W m−2 (W m−2)−1) and latent heat flux (−1.54±0.27 W m−2 (W m−2)−1), as well as a decrease in Bowen ratio (−0.20±0.07 (W m−2)−1). Such reductions of turbulent fluxes can be largely explained by enhanced air stability (0.07±0.02 K (W m−2)−1), measured as the difference of the potential temperature between 925 hPa and surface, and reduc
Thomas C, Voulgarakis A, Lim G, et al., 2021, An unsupervised learning approach to identifying blocking events:the case of European summer, Weather and Climate Dynamics, Vol: 2, ISSN: 2698-4016
Atmospheric blocking events are mid-latitudeweather patterns, which obstruct the usual path of the polar jet streams. They are often associated with heat wavesin summer and cold snaps in winter. Despite being centralfeatures of mid-latitude synoptic-scale weather, there is nowell-defined historical dataset of blocking events. Variousblocking indices (BIs) have thus been suggested for automatically identifying blocking events in observational and inclimate model data. However, BIs show significant regionaland seasonal differences so that several indices are typicallyapplied in combination to ensure scientific robustness. Here,we introduce a new BI using self-organizing maps (SOMs),an unsupervised machine learning approach, and compare itsdetection skill to some of the most widely applied BIs. Toenable this intercomparison, we first create a new groundtruth time series classification of European blocking basedon expert judgement. We then demonstrate that our method(SOM-BI) has several key advantages over previous BIs because it exploits all of the spatial information provided in theinput data and reduces the dependence on arbitrary thresholds. Using ERA5 reanalysis data (1979–2019), we find thatthe SOM-BI identifies blocking events with a higher precision and recall than other BIs. In particular, SOM-BI alreadyperforms well using only around 20 years of training data sothat observational records are long enough to train our newmethod. We present case studies of the 2003 and 2019 European heat waves and highlight that well-defined groups ofSOM nodes can be an effective tool to diagnose such weatherevents, although the domain-based approach can still lead toerrors in the identification of certain events in a fashion similar to the other BIs. We further test the red blocking detectionskill of SOM-BI depending on the meteorological variableused to study blocking, including geopotential height, sealevel pressure and four variables related to potential vorticity,and t
Thomas C, Voulgarakis A, Lim G, et al., 2021, An unsupervised learning approach to identifying blocking events: the case of European summer, Weather and Climate Dynamics, Vol: 2, Pages: 581-608, ISSN: 2698-4016
Atmospheric blocking events are mid-latitude weather patterns, which obstruct the usual path of the polar jet streams. They are often associated with heat waves in summer and cold snaps in winter. Despite being central features of mid-latitude synoptic-scale weather, there is no well-defined historical dataset of blocking events. Various blocking indices (BIs) have thus been suggested for automatically identifying blocking events in observational and in climate model data. However, BIs show significant regional and seasonal differences so that several indices are typically applied in combination to ensure scientific robustness. Here, we introduce a new BI using self-organizing maps (SOMs), an unsupervised machine learning approach, and compare its detection skill to some of the most widely applied BIs. To enable this intercomparison, we first create a new ground truth time series classification of European blocking based on expert judgement. We then demonstrate that our method (SOM-BI) has several key advantages over previous BIs because it exploits all of the spatial information provided in the input data and reduces the dependence on arbitrary thresholds. Using ERA5 reanalysis data (1979–2019), we find that the SOM-BI identifies blocking events with a higher precision and recall than other BIs. In particular, SOM-BI already performs well using only around 20 years of training data so that observational records are long enough to train our new method. We present case studies of the 2003 and 2019 European heat waves and highlight that well-defined groups of SOM nodes can be an effective tool to diagnose such weather events, although the domain-based approach can still lead to errors in the identification of certain events in a fashion similar to the other BIs. We further test the red blocking detection skill of SOM-BI depending on the meteorological variable used to study blocking, including geopotential height, sea level pressure and four variables related to
Kuhn-Régnier A, Voulgarakis A, Nowack P, et al., 2021, Quantifying the Importance of antecedent fuel-related vegetationproperties for burnt area using random forests, Biogeosciences, Vol: 8, ISSN: 1726-4170
The seasonal and longer-term dynamics of fuel accumulation affect fire seasonality and the occurrence of extreme wildfires. Failure to account for their influence mayhelp to explain why state-of-the-art fire models do not simulate the length and timing of the fire season or interannual variability in burnt area well. We investigated the impact of accounting for different timescales of fuel production and accumulation on burnt area using a suite of random forest regression models that included the immediateimpact of climate, vegetation, and human influences in agiven month and tested the impact of various combinationsof antecedent conditions in four productivity-related vegetation indices and in antecedent moisture conditions. Analyses were conducted for the period from 2010 to 2015 inclusive. Inclusion of antecedent vegetation conditions representing fuel build-up led to an improvement of the global,climatological out-of-sample R2from 0.579 to 0.701, but theinclusion of antecedent vegetation conditions on timescales≥ 1 year had no impact on simulated burnt area. Currentmoisture levels were the dominant influence on fuel drying. Additionally, antecedent moisture levels were importantfor fuel build-up. The models also enabled the visualisationof interactions between variables, such as the importanceof antecedent productivity coupled with instantaneous drying. The length of the period which needs to be consideredvaries across biomes; fuel-limited regions are sensitive to antecedent conditions that determine fuel build-up over longertime periods (∼ 4 months), while moisture-limited regionsare more sensitive to current conditions that regulate fuel drying.
Kuhn- Regnier A, Voulgarakis A, Nowack P, et al., 2021, The importance of antecedent vegetation and drought conditions as global drivers of burnt areas, Biogeosciences, Vol: 18, Pages: 3861-3879, ISSN: 1726-4170
The seasonal and longer-term dynamics of fuel accumulation affect fire seasonality and the occurrence of extreme wildfires. Failure to account for their influence may help to explain why state-of-the-art fire models do not simulate the length and timing of the fire season or interannual variability in burnt area well. We investigated the impact of accounting for different timescales of fuel production and accumulation on burnt area using a suite of random forest regression models that included the immediate impact of climate, vegetation, and human influences in a given month and tested the impact of various combinations of antecedent conditions in four productivity-related vegetation indices and in antecedent moisture conditions. Analyses were conducted for the period from 2010 to 2015 inclusive. Inclusion of antecedent vegetation conditions representing fuel build-up led to an improvement of the global, climatological out-of-sample R2 from 0.579 to 0.701, but the inclusion of antecedent vegetation conditions on timescales ≥ 1 year had no impact on simulated burnt area. Current moisture levels were the dominant influence on fuel drying. Additionally, antecedent moisture levels were important for fuel build-up. The models also enabled the visualisation of interactions between variables, such as the importance of antecedent productivity coupled with instantaneous drying. The length of the period which needs to be considered varies across biomes; fuel-limited regions are sensitive to antecedent conditions that determine fuel build-up over longer time periods (∼ 4 months), while moisture-limited regions are more sensitive to current conditions that regulate fuel drying.
Kuhn-Régnier A, Voulgarakis A, Nowack P, et al., 2021, Supplementary material to "Quantifying the Importance of Antecedent Fuel-Related VegetationProperties for Burnt Area using Random Forests", Biogeosciences, ISSN: 1726-4170
Qu Y, Voulgarakis A, Wang T, et al., 2021, A study of the effect of aerosols on surface ozone through meteorology feedbacks over China, Atmospheric Chemistry and Physics, Vol: 21, Pages: 5705-5718, ISSN: 1680-7316
Interactions between aerosols and gases in the atmosphere have been the focus of an increasing number of studies in recent years. Here, we focus on aerosol effects on tropospheric ozone that involve meteorological feedbacks induced by aerosol–radiation interactions. Specifically, we study the effects that involve aerosol influences on the transport of gaseous pollutants and on atmospheric moisture, both of which can impact ozone chemistry. For this purpose, we use the UK Earth System Model (UKESM1), with which we performed sensitivity simulations including and excluding the aerosol direct radiative effect (ADE) on atmospheric chemistry, and focused our analysis on an area with a high aerosol presence, namely China. By comparing the simulations, we found that ADE reduced shortwave radiation by 11 % in China and consequently led to lower turbulent kinetic energy, weaker horizontal winds and a shallower boundary layer (with a maximum of 102.28 m reduction in north China). On the one hand, the suppressed boundary layer limited the export and diffusion of pollutants and increased the concentration of CO, SO2, NO, NO2, PM2.5 and PM10 in the aerosol-rich regions. The NO/NO2 ratio generally increased and led to more ozone depletion. On the other hand, the boundary layer top acted as a barrier that trapped moisture at lower altitudes and reduced the moisture at higher altitudes (the specific humidity was reduced by 1.69 % at 1493 m on average in China). Due to reduced water vapour, fewer clouds were formed and more sunlight reached the surface, so the photolytical production of ozone increased. Under the combined effect of the two meteorology feedback methods, the annual average ozone concentration in China declined by 2.01 ppb (6.2 %), which was found to bring the model into closer agreement with surface ozone measurements from different parts of China.
Millington J, Perkins O, Kasoar M, et al., 2021, Advancing representation of anthropogenic fire in dynamic global vegetation models
<jats:p>&lt;div&gt;&lt;p&gt;It is now commonly-understood that improved understanding of global fire regimes demands better representation of anthropogenic fire in dynamic global vegetation models (DGVMs). However, currently there is no clear agreement on how human activity should be incorporated into fire-enabled DGVMs and existing models exhibit large differences in the sensitivities of socio-economic variables. Furthermore, existing approaches are limited to empirical statistical relations between fire regime variables and globally available socio-economic indicators such as population density or GDP. Although there has been some limited representation in global models of the contrasting ways in which different classes of actors use or manage fires, we argue that fruitful progress in advancing representation of anthropogenic fire in DGVMs will come by building on agent-based modelling approaches. Here, we report on our progress developing a global agent-based representation of anthropogenic fire and its coupling with the JULES-INFERNO fire-enabled DGVM.&amp;#160;&amp;#160;&lt;/p&gt;&lt;/div&gt;&lt;div&gt;&lt;p&gt;Our modelling of anthropogenic fire adopts an approach that classifies &amp;#8216;agent functional types&amp;#8217; (AFTs) to represent human fire activity based on land use/cover and Stephen Pyne&amp;#8217;s fire development stages. For example, the &amp;#8216;swidden&amp;#8217; AFT represents shifting cultivation farmers managing cropland and secondary vegetation in a pre-industrial development setting. This approach is based on the assumption that anthropogenic fire use and management is primarily a function of land use but influenced by socio-economic context, leading different AFTs to produce qualitatively distinct fire regimes. The literature empirically supports this assumption, however data
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