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Fire is the primary disturbance factor in many terrestrial ecosystems. Wildfire alters vegetation structure and composition, affects carbon storage and biogeochemical cycling, and results in the release of climatically relevant trace gases including CO2, CO, CH4, NOx, and aerosols. One way of assessing the impacts of global wildfire on centennial to multi-millennial timescales is to use process-based fire models linked to dynamic global vegetation models (DGVMs). Here we present an update to the LPJ-DGVM and a new fire module based on SPITFIRE that includes several improvements to the way in which fire occurrence, behaviour, and the effects of fire on vegetation are simulated. The new LPJ-LMfire model includes explicit calculation of natural ignitions, the representation of multi-day burning and coalescence of fires, and the calculation of rates of spread in different vegetation types. We describe a new representation of anthropogenic biomass burning under preindustrial conditions that distinguishes the different relationships between humans and fire among hunter-gatherers, pastoralists, and farmers. We evaluate our model simulations against remote-sensing-based estimates of burned area at regional and global scale. While wildfire in much of the modern world is largely influenced by anthropogenic suppression and ignitions, in those parts of the world where natural fire is still the dominant process (e.g. in remote areas of the boreal forest and subarctic), our results demonstrate a significant improvement in simulated burned area over the original SPITFIRE. The new fire model we present here is particularly suited for the investigation of climate–human–fire relationships on multi-millennial timescales prior to the Industrial Revolution.
This study presents a method for adjusting long-term climate data records (CDRs) for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS). Recently, a 23-year long (1983–2005) continuous SIS CDR has been generated based on the visible channel (0.45–1 μm) of the MVIRI radiometers onboard the geostationary Meteosat First Generation Platform. The CDR is available from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). Here, it is assessed whether a homogeneous extension of the SIS CDR to the present is possible with operationally generated surface radiation data provided by CM SAF using the SEVIRI and GERB instruments onboard the Meteosat Second Generation satellites. Three extended CM SAF SIS CDR versions consisting of MVIRI-derived SIS (1983–2005) and three different SIS products derived from the SEVIRI and GERB instruments onboard the MSG satellites (2006 onwards) were tested. A procedure to detect shift inhomogeneities in the extended data record (1983–present) was applied that combines the Standard Normal Homogeneity Test (SNHT) and a penalized maximal T-test with visual inspection. Shift detection was done by comparing the SIS time series with the ground stations mean, in accordance with statistical significance. Several stations of the Baseline Surface Radiation Network (BSRN) and about 50 stations of the Global Energy Balance Archive (GEBA) over Europe were used as the ground-based reference. The analysis indicates several breaks in the data record between 1987 and 1994 probably due to artefacts in the raw data and instrument failures. After 2005 the MVIRI radiometer was replaced by the narrow-band SEVIRI and the broadband GERB radiometers and a new retrieval algorithm was applied. This induces significant challenges for the homogenisation across the satellite generations. Homogenisation is performed by applying a mean-shift correction depending on the shift size of any segment between two break points to the last segment (2006–present). Corrections are applied to the most significant breaks that can be related to satellite changes. This study focuses on the European region, but the methods can be generalized to other regions. To account for seasonal dependence of the mean-shifts the correction was performed independently for each calendar month. In comparison to the ground-based reference the homogenised data record shows an improvement over the original data record in terms of anomaly correlation and bias. In general the method can also be applied for the adjustment of satellite datasets addressing other variables to bridge the gap between CDRs and near-real-time data.
In this study we show how size-resolved measurements of aerosol particles and cloud condensation nuclei (CCN) can be used to characterize the supersaturation of water vapor in a cloud. The method was developed and applied for the investigation of a cloud event during the ACRIDICON-Zugspitze campaign (17 September to 4 October 2012) at the high-alpine research station Schneefernerhaus (German Alps, 2650 m a.s.l.). Number size distributions of total and interstitial aerosol particles were measured with a scanning mobility particle sizer (SMPS), and size-resolved CCN efficiency spectra were recorded with a CCN counter system operated at different supersaturation levels.
During the evolution of a cloud, aerosol particles are exposed to different supersaturation levels. We outline and compare different estimates for the lower and upper bounds (Slow, Shigh) and the average value (Savg) of peak supersaturation encountered by the particles in the cloud. For the investigated cloud event, we derived Slow ≈ 0.19–0.25%, Shigh ≈ 0.90–1.64% and Savg ≈ 0.38–0.84%. Estimates of Slow, Shigh and Savg based on aerosol size distribution data require specific knowledge or assumptions of aerosol hygroscopicity, which are not required for the derivation of Slow and Savg from the size-resolved CCN efficiency spectra.
Projections of future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Intercomparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed. Projections of change from the baseline period (1981–2010) to the future (2070–2099) from a number of different ecosystems and hydrological models were studied. The differences between projections from the two types of model were looked at globally and regionally. Typically, across different regions the ecosystem models tended to project larger increases and smaller decreases in runoff than the hydrological models. However, the differences varied both regionally and seasonally. Sensitivity experiments were also used to investigate the contributions of varying CO2 and allowing vegetation distribution to evolve on projected changes in runoff. In two out of four models which had data available from CO2 sensitivity experiments, allowing CO2 to vary was found to increase runoff more than keeping CO2 constant, while in two models runoff decreased. This suggests more uncertainty in runoff responses to elevated CO2 than previously considered. As CO2 effects on evapotranspiration via stomatal conductance and leaf-area index are more commonly included in ecosystems models than in hydrological models, this may partially explain some of the difference between model types. Keeping the vegetation distribution static in JULES runs had much less effect on runoff projections than varying CO2, but this may be more pronounced if looked at over a longer timescale as vegetation changes may take longer to reach a new state.
Comparing projections of future changes in runoff from hydrological and biome models in ISI-MIP
(2013)
Future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Intercomparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed for differences between impact models. Projections of change from a baseline period (1981–2010) to the future (2070–2099) from 12 impacts models which contributed to the hydrological and biomes sectors of ISI-MIP were studied. The biome models differed from the hydrological models by the inclusion of CO2 impacts and most also included a dynamic vegetation distribution. The biome and hydrological models agreed on the sign of runoff change for most regions of the world. However, in West Africa, the hydrological models projected drying, and the biome models a moistening. The biome models tended to produce larger increases and smaller decreases in regionally averaged runoff than the hydrological models, although there is large inter-model spread. The timing of runoff change was similar, but there were differences in magnitude, particularly at peak runoff. The impact of vegetation distribution change was much smaller than the projected change over time, while elevated CO2 had an effect as large as the magnitude of change over time projected by some models in some regions. The effect of CO2 on runoff was not consistent across the models, with two models showing increases and two decreases. There was also more spread in projections from the runs with elevated CO2 than with constant CO2. The biome models which gave increased runoff from elevated CO2 were also those which differed most from the hydrological models. Spatially, regions with most difference between model types tended to be projected to have most effect from elevated CO2, and seasonal differences were also similar, so elevated CO2 can partly explain the differences between hydrological and biome model runoff change projections. Therefore, this shows that a range of impact models should be considered to give the full range of uncertainty in impacts studies.
In this study we report the set-up of a novel twin chamber technique that uses the comparative method and establishes an appropriate connection of atmospheric and laboratory methods to broaden the tools for investigations. It is designed to study the impact of certain parameters and gases on ambient processes, such as particle formation online, and can be applied in a large variety of conditions. The characterisation of both chambers proved that both chambers operate identically, with a residence time xT (COMPASS1) = 26.5 ± 0.3 min and xT (COMPASS2) = 26.6 ± 0.4 min, at a typical flow rate of 15 L min−1 and a gas leak rate of (1.6 ± 0.8) × 10−5 s−1. Particle loss rates were found to be larger (due to the particles' stickiness to the chamber walls), with an extrapolated maximum of 1.8 × 10−3 s−1 at 1 nm, i.e. a hundredfold of the gas leak rate. This latter value is associated with sticky non-volatile gaseous compounds, too. Comparison measurement showed no significant differences. Therefore operation under atmospheric conditions is trustworthy. To indicate the applicability and the benefit of the system, a set of experiments was conducted under different conditions, i.e. urban and remote, enhanced ozone and terpenes as well as reduced sunlight. In order to do so, an ozone lamp was applied to enhance ozone in one of two chambers; the measurement chamber was protected from radiation by a first-aid cover and volatile organic compounds (VOCs) were added using a small additional flow and a temperature-controlled oven. During the elevated ozone period, ambient particle number and volume increased substantially at urban and remote conditions, but by a different intensity. Protection of solar radiation displayed a clear negative effect on particle number, while terpene addition did cause a distinct daily pattern. E.g. adding β pinene particle number concentration rose by 13% maximum at noontime, while no significant effect was observable during darkness. Therefore, the system is a useful tool for investigating local precursors and the details of ambient particle formation at surface locations as well as potential future feedback processes.
The anthropogenic influence on climate and environment has increased strongly since industrialization about 150 yr ago. The consequences for the atmosphere became more and more apparent and nowadays affect our life quality on Earth progressively. Because of that it is very important to understand the atmospheric processes, on which these effects are based on, in detail. In this study we report the set-up of a novel twin chamber technique that uses the comparative method and establishes an appropriate connection of atmospheric and laboratory methods to broaden the tools for investigations. It is designed to study the impact of certain parameters and gases on ambient processes such as particle formation online and can be applied in a large variety of conditions. The characterisation of both chambers proved that both chambers operate identically with a residence time (xT (COMPASS 1) = 26.5 ± 0.3 min and xT (COMPASS 2) = 26.6 ± 0.4 min) at a typical flow rate of 15 L min−1 and a deposition rate (1.6 ± 0.8) × 10−5 s−1. Comparison measurement showed no significant differences. Therefore operation under atmospheric conditions is trustworthy. To indicate the applicability and the benefit of the system a set of experiments was conducted at different conditions, i.e. urban and remote, enhancing ozone and terpenes as well as reducing sunlight. In the ozone enhanced ambient particle number and volume increased substantially at urban and remote conditions in a different strength. Solar radiation displayed a clear positive effect on particle number as well as terpene addition did at remote conditions. Therefore the system is a useful tool to investigate local precursors, the details of ambient particle formation at surface locations as well as future feedback processes.
Tropical forest soils are a significant source for the greenhouse gas N2O as well as for NO, a precursor of tropospheric ozone. However, current estimates are uncertain due to the limited number of field measurements. Furthermore, there is considerable spatial and temporal variability of N2O and NO emissions due to the variation of environmental conditions such as soil properties, vegetation characteristics and meteorology. In this study we used a process-based model (ForestDNDC-tropica) to estimate N2O and NO emissions from tropical highland forest (Nyungwe) soils in southwestern Rwanda. To extend the model inputs to regional scale, ForestDNDC-tropica was linked to an exceptionally large legacy soil dataset. There was agreement between N2O and NO measurements and the model predictions though the ForestDNDC-tropica resulted in considerable lower emissions for few sites. Low similarity was specifically found for acidic soil with high clay content and reduced metals, indicating that chemo-denitrification processes on acidic soils might be under-represented in the current ForestDNDC-tropica model. The results showed that soil bulk density and pH are the most influential factors driving spatial variations in soil N2O and NO emissions for tropical forest soils. The area investigated (1113 km2) was estimated to emit ca. 439 ± 50 t N2O-N yr−1 (2.8–5.5 kg N2O-N ha−1 yr−1) and 244 ± 16 t NO-N yr−1 (0.8–5.1 kg N ha−1 yr−1). Consistent with less detailed studies, we confirm that tropical highland rainforest soils are a major source of atmospheric N2O and NO.
Global climate change is one of the major driving forces for adaptive shifts in migration and breeding phenology and possibly impacts demographic changes if a species fails to adapt sufficiently. In Western Europe, pied flycatchers (Ficedula hypoleuca) have insufficiently adapted their breeding phenology to the ongoing advance of food peaks within their breeding area and consequently suffered local population declines. We address the question whether this population decline led to a loss of genetic variation, using two neutral marker sets (mitochondrial control region and microsatellites), and one potentially selectively non-neutral marker (avian Clock gene). We report temporal changes in genetic diversity in extant populations and biological archives over more than a century, using samples from sites differing in the extent of climate change. Comparing genetic differentiation over this period revealed that only the recent Dutch population, which underwent population declines, showed slightly lower genetic variation than the historic Dutch population. As that loss of variation was only moderate and not observed in all markers, current gene flow across Western and Central European populations might have compensated local loss of variation over the last decades. A comparison of genetic differentiation in neutral loci versus the Clock gene locus provided evidence for stabilizing selection. Furthermore, in all genetic markers, we found a greater genetic differentiation in space than in time. This pattern suggests that local adaptation or historic processes might have a stronger effect on the population structure and genetic variation in the pied flycatcher than recent global climate changes.
State-of-the-art general circulation models (GCMs) are tested and challenged by the ability to reproduce paleoclimate key intervals. In order to account for climate changes associated with soil dynamics we have developed a soil scheme, which is asynchronously coupled to a state-of-the-art atmosphere ocean GCM with dynamic vegetation. We test the scheme for conditions representative of a warmer (mid-Holocene, 6 kyr before present, BP) and colder (Last Glacial Maximum, 21 kyr BP) than pre-industrial climate. The computed change of physical soil properties (i.e. albedo, water storage capacity, and soil texture) for these different climates leads to amplified global climate anomalies. Especially regions like the transition zone of desert/savannah and taiga/tundra, exhibit an increased response as a result of the modified soil treatment. In comparison to earlier studies, the inclusion of the soil feedback pushes our model simulations towards the warmer end in the range of mid-Holocene studies and beyond current estimates of global cooling during the Last Glacial Maximum based on PMIP2 (Paleoclimate Modelling Intercomparison Project 2) studies. The main impact of the interactive soil scheme on the climate response is governed by positive feedbacks, including dynamics of vegetation, snow, sea ice, local water recycling, which might amplify forcing factors ranging from orbital to tectonic timescales.