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Two types of particles exist in the atmosphere, primary and secondary particles. While primary particles such as soot, mineral dust, sea salt particles or pollen are introduced directly as particles into the atmosphere, secondary particles are formed in the atmosphere by condensation of gases. The formation of such new aerosol particles takes place frequently and at a broad variety of atmospheric conditions and geographic locations. A considerable fraction of the atmospheric particles is formed by such nucleation processes. The newly formed particles may grow by condensation to sizes where they are large enough to act as cloud condensation nuclei and therefore may affect cloud properties. The fundamental processes of aerosol nucleation are described and typical atmospheric observations are discussed. Two recent studies are introduced that potentially change our current understanding of atmospheric nucleation substantially.
This study examines the urban heat island (UHI) of Brussels, for both current (2000–2009) and projected future (2060–2069) climate conditions, by employing very high resolution (250 m) modelling experiments, using the urban boundary layer climate model UrbClim. Meteorological parameters that are related to the intensity of the UHI are identified and it is investigated how these parameters and the magnitude of the UHI evolve for two plausible trajectories for future climate conditions. UHI intensity is found to be strongly correlated to the inversion strength in the lowest 100 m of the atmosphere. The results for the future scenarios indicate that the magnitude of the UHI is expected to decrease slightly due to global warming. This can be attributed to the increased incoming longwave radiation, caused by higher air temperature and humidity values. The presence of the UHI also has a significant impact on the frequency of extreme temperature events in the city area, both in present and future climates, and exacerbates the impact of climate change on the urban population as the amount of heat wave days in the city increases twice as fast as in the rural surroundings.
Quantification of spatially and temporally resolved water flows and water storage variations for all land areas of the globe is required to assess water resources, water scarcity and flood hazards, and to understand the Earth system. This quantification is done with the help of global hydrological models (GHMs). What are the challenges and prospects in the development and application of GHMs? Seven important challenges are presented. (1) Data scarcity makes quantification of human water use difficult even though significant progress has been achieved in the last decade. (2) Uncertainty of meteorological input data strongly affects model outputs. (3) The reaction of vegetation to changing climate and CO2 concentrations is uncertain and not taken into account in most GHMs that serve to estimate climate change impacts. (4) Reasons for discrepant responses of GHMs to changing climate have yet to be identified. (5) More accurate estimates of monthly time series of water availability and use are needed to provide good indicators of water scarcity. (6) Integration of gradient-based groundwater modelling into GHMs is necessary for a better simulation of groundwater–surface water interactions and capillary rise. (7) Detection and attribution of human interference with freshwater systems by using GHMs are constrained by data of insufficient quality but also GHM uncertainty itself. Regarding prospects for progress, we propose to decrease the uncertainty of GHM output by making better use of in situ and remotely sensed observations of output variables such as river discharge or total water storage variations by multi-criteria validation, calibration or data assimilation. Finally, we present an initiative that works towards the vision of hyperresolution global hydrological modelling where GHM outputs would be provided at a 1-km resolution with reasonable accuracy.
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making.
Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
Profiles of CFC-11 (CCl3F) and CFC-12 (CCl2F2) of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard the European satellite Envisat have been retrieved from versions MIPAS/4.61 to MIPAS/4.62 and MIPAS/5.02 to MIPAS/5.06 level-1b data using the scientific level-2 processor run by Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK) and Consejo Superior de Investigaciones Científicas (CSIC), Instituto de Astrofísica de Andalucía (IAA). These profiles have been compared to measurements taken by the balloon-borne cryosampler, Mark IV (MkIV) and MIPAS-Balloon (MIPAS-B), the airborne MIPAS-STRatospheric aircraft (MIPAS-STR), the satellite-borne Atmospheric Chemistry Experiment Fourier transform spectrometer (ACE-FTS) and the High Resolution Dynamic Limb Sounder (HIRDLS), as well as the ground-based Halocarbon and other Atmospheric Trace Species (HATS) network for the reduced spectral resolution period (RR: January 2005–April 2012) of MIPAS. ACE-FTS, MkIV and HATS also provide measurements during the high spectral resolution period (full resolution, FR: July 2002–March 2004) and were used to validate MIPAS CFC-11 and CFC-12 products during that time, as well as profiles from the Improved Limb Atmospheric Spectrometer, ILAS-II. In general, we find that MIPAS shows slightly higher values for CFC-11 at the lower end of the profiles (below ∼ 15 km) and in a comparison of HATS ground-based data and MIPAS measurements at 3 km below the tropopause. Differences range from approximately 10 to 50 pptv ( ∼ 5–20 %) during the RR period. In general, differences are slightly smaller for the FR period. An indication of a slight high bias at the lower end of the profile exists for CFC-12 as well, but this bias is far less pronounced than for CFC-11 and is not as obvious in the relative differences between MIPAS and any of the comparison instruments. Differences at the lower end of the profile (below ∼ 15 km) and in the comparison of HATS and MIPAS measurements taken at 3 km below the tropopause mainly stay within 10–50 pptv (corresponding to ∼ 2–10 % for CFC-12) for the RR and the FR period. Between ∼ 15 and 30 km, most comparisons agree within 10–20 pptv (10–20 %), apart from ILAS-II, which shows large differences above ∼ 17 km. Overall, relative differences are usually smaller for CFC-12 than for CFC-11. For both species – CFC-11 and CFC-12 – we find that differences at the lower end of the profile tend to be larger at higher latitudes than in tropical and subtropical regions. In addition, MIPAS profiles have a maximum in their mixing ratio around the tropopause, which is most obvious in tropical mean profiles. Comparisons of the standard deviation in a quiescent atmosphere (polar summer) show that only the CFC-12 FR error budget can fully explain the observed variability, while for the other products (CFC-11 FR and RR and CFC-12 RR) only two-thirds to three-quarters can be explained. Investigations regarding the temporal stability show very small negative drifts in MIPAS CFC-11 measurements. These instrument drifts vary between ∼ 1 and 3 % decade−1. For CFC-12, the drifts are also negative and close to zero up to ∼ 30 km. Above that altitude, larger drifts of up to ∼ 50 % decade−1 appear which are negative up to ∼ 35 km and positive, but of a similar magnitude, above.
Reconstructions of biomass burning from sediment charcoal records to improve data–model comparisons
(2015)
The location, timing, spatial extent, and frequency of wildfires are changing rapidly in many parts of the world, producing substantial impacts on ecosystems, people, and potentially climate. Paleofire records based on charcoal accumulation in sediments enable modern changes in biomass burning to be considered in their long-term context. Paleofire records also provide insights into the causes and impacts of past wildfires and emissions when analyzed in conjunction with other paleoenvironmental data and with fire models. Here we present new 1000-year and 22 000-year trends and gridded biomass burning reconstructions based on the Global Charcoal Database version 3 (GCDv3), which includes 736 charcoal records (57 more than in version 2). The new gridded reconstructions reveal the spatial patterns underlying the temporal trends in the data, allowing insights into likely controls on biomass burning at regional to global scales. In the most recent few decades, biomass burning has sharply increased in both hemispheres but especially in the north, where charcoal fluxes are now higher than at any other time during the past 22 000 years. We also discuss methodological issues relevant to data–model comparisons and identify areas for future research. Spatially gridded versions of the global data set from GCDv3 are provided to facilitate comparison with and validation of global fire simulations.
Amines are potentially important for atmospheric new particle formation, but their concentrations are usually low with typical mixing ratios in the pptv range or even smaller. Therefore, the demand for highly sensitive gas-phase amine measurements has emerged in the last several years. Nitrate chemical ionization mass spectrometry (CIMS) is routinely used for the measurement of gas-phase sulfuric acid in the sub-pptv range. Furthermore, extremely low volatile organic compounds (ELVOCs) can be detected with a nitrate CIMS. In this study we demonstrate that a nitrate CIMS can also be used for the sensitive measurement of dimethylamine (DMA, (CH3)2NH) using the NO3−•(HNO3)1 − 2• (DMA) cluster ion signal. Calibration measurements were made at the CLOUD chamber during two different measurement campaigns. Good linearity between 0 and ∼ 120 pptv of DMA as well as a sub-pptv detection limit of 0.7 pptv for a 10 min integration time are demonstrated at 278 K and 38 % RH.
MIPAS-Envisat is a satellite-borne sensor which measured vertical profiles of a wide range of trace gases from 2002 to 2012 using IR emission spectroscopy. We present geophysical validation of the MIPAS-Envisat operational retrieval (version 6.0) of N2O, CH4, CFC-12, and CFC-11 by the European Space Agency (ESA). The geophysical validation data are derived from measurements of samples collected by a cryogenic whole air sampler flown to altitudes of up to 34 km by means of large scientific balloons. In order to increase the number of coincidences between the satellite and the balloon observations, we applied a trajectory matching technique. The results are presented for different time periods due to a change in the spectroscopic resolution of MIPAS in early 2005. Retrieval results for N2O, CH4, and CFC-12 show partly good agreement for some altitude regions, which differs for the periods with different spectroscopic resolution. The more recent low spectroscopic resolution data above 20 km altitude show agreement with the combined uncertainties, while there is a tendency of the earlier high spectral resolution data set to underestimate these species above 25 km. The earlier high spectral resolution data show a significant overestimation of the mixing ratios for N2O, CH4, and CFC-12 below 20 km. These differences need to be considered when using these data. The CFC-11 results from the operation retrieval version 6.0 cannot be recommended for scientific studies due to a systematic overestimation of the CFC-11 mixing ratios at all altitudes.
Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest
(2015)
The vegetation–atmosphere carbon and water exchange at one particular site can strongly vary from year to year, and understanding this interannual variability in carbon and water exchange (IAVcw) is a critical factor in projecting future ecosystem changes. However, the mechanisms driving this IAVcw are not well understood. We used data on carbon and water fluxes from a multi-year eddy covariance study (1997–2009) in a Dutch Scots pine forest and forced a process-based ecosystem model (Lund–Potsdam–Jena General Ecosystem Simulator; LPJ-GUESS) with local data to, firstly, test whether the model can explain IAVcw and seasonal carbon and water exchange from direct environmental factors only. Initial model runs showed low correlations with estimated annual gross primary productivity (GPP) and annual actual evapotranspiration (AET), while monthly and daily fluxes showed high correlations. The model underestimated GPP and AET during winter and drought events. Secondly, we adapted the temperature inhibition function of photosynthesis to account for the observation that at this particular site, trees continue to assimilate at very low atmospheric temperatures (up to daily averages of −10 °C), resulting in a net carbon sink in winter. While we were able to improve daily and monthly simulations during winter by lowering the modelled minimum temperature threshold for photosynthesis, this did not increase explained IAVcw at the site. Thirdly, we implemented three alternative hypotheses concerning water uptake by plants in order to test which one best corresponds with the data. In particular, we analyse the effects during the 2003 heatwave. These simulations revealed a strong sensitivity of the modelled fluxes during dry and warm conditions, but no single formulation was consistently superior in reproducing the data for all timescales and the overall model–data match for IAVcw could not be improved. Most probably access to deep soil water leads to higher AET and GPP simulated during the heatwave of 2003. We conclude that photosynthesis at lower temperatures than assumed in most models can be important for winter carbon and water fluxes in pine forests. Furthermore, details of the model representations of water uptake, which are often overlooked, need further attention, and deep water access should be treated explicitly.
Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest
(2015)
The vegetation–atmosphere carbon and water exchange at one particular site can strongly vary from year to year, and understanding this interannual variability in carbon and water exchange (IAVcw) is a critical factor in projecting future ecosystem changes. However, the mechanisms driving this IAVcw are not well understood. We used data on carbon and water fluxes from a multi-year eddy covariance study (1997–2009) in a Dutch Scots pine forest and forced a process-based ecosystem model (Lund–Potsdam–Jena General Ecosystem Simulator; LPJ-GUESS) with local data to, firstly, test whether the model can explain IAVcw and seasonal carbon and water exchange from direct environmental factors only. Initial model runs showed low correlations with estimated annual gross primary productivity (GPP) and annual actual evapotranspiration (AET), while monthly and daily fluxes showed high correlations. The model underestimated GPP and AET during winter and drought events. Secondly, we adapted the temperature inhibition function of photosynthesis to account for the observation that at this particular site, trees continue to assimilate at very low atmospheric temperatures (up to daily averages of −10 °C), resulting in a net carbon sink in winter. While we were able to improve daily and monthly simulations during winter by lowering the modelled minimum temperature threshold for photosynthesis, this did not increase explained IAVcw at the site. Thirdly, we implemented three alternative hypotheses concerning water uptake by plants in order to test which one best corresponds with the data. In particular, we analyse the effects during the 2003 heatwave. These simulations revealed a strong sensitivity of the modelled fluxes during dry and warm conditions, but no single formulation was consistently superior in reproducing the data for all timescales and the overall model–data match for IAVcw could not be improved. Most probably access to deep soil water leads to higher AET and GPP simulated during the heatwave of 2003. We conclude that photosynthesis at lower temperatures than assumed in most models can be important for winter carbon and water fluxes in pine forests. Furthermore, details of the model representations of water uptake, which are often overlooked, need further attention, and deep water access should be treated explicitly.