Reconciliation of essential process parameters for an enhanced predictability of Arctic stratospheric ozone loss and its climate interactions (RECONCILE): activities and results
Marc von Hobe
Guido Di Donfrancesco
Christopher R. Hoyle
Ivar S.A. Isaksen
David R. Jackson
Imre M. Jánosi
Rod L. Jones
Sergey M. Khaykin
Johannes Christian Laube
Beiping P. Luo
Michael C. Pitts
Lamont R. Poole
Francis D. Pope
Michelle L. Santee
Matteo Siciliani de Cumis
Ole Amund Søvde
Marcel vom Scheidt
Peter von der Gathen
Kaley A. Walker
Franck G. Wienhold
Isla A. K. Young
- The international research project RECONCILE has addressed central questions regarding polar ozone depletion, with the objective to quantify some of the most relevant yet still uncertain physical and chemical processes and thereby improve prognostic modelling capabilities to realistically predict the response of the ozone layer to climate change. This overview paper outlines the scope and the general approach of RECONCILE, and it provides a summary of observations and modelling in 2010 and 2011 that have generated an in many respects unprecedented dataset to study processes in the Arctic winter stratosphere. Principally, it summarises important outcomes of RECONCILE including (i) better constraints and enhanced consistency on the set of parameters governing catalytic ozone destruction cycles, (ii) a better understanding of the role of cold binary aerosols in heterogeneous chlorine activation, (iii) an improved scheme of polar stratospheric cloud (PSC) processes that includes heterogeneous nucleation of nitric acid trihydrate (NAT) and ice on non-volatile background aerosol leading to better model parameterisations with respect to denitrification, and (iv) long transient simulations with a chemistry-climate model (CCM) updated based on the results of RECONCILE that better reproduce past ozone trends in Antarctica and are deemed to produce more reliable predictions of future ozone trends. The process studies and the global simulations conducted in RECONCILE show that in the Arctic, ozone depletion uncertainties in the chemical and microphysical processes are now clearly smaller than the sensitivity to dynamic variability.
Statistical separation of observed global and European climate data into natural and anthropogenic signals
- Observed global and European spatiotemporal related fields of surface air temperature, mean-sea-level pressure and precipitation are analyzed statistically with respect to their response to external forcing factors such as anthropogenic greenhouse gases, anthropogenic sulfate aerosol, solar variations and explosive volcanism, and known internal climate mechanisms such as the El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). As a first step, a principal component analysis (PCA) is applied to the observed spatiotemporal related fields to obtain spatial patterns with linear independent temporal structure. In a second step, the time series of each of the spatial patterns is subject to a stepwise regression analysis in order to separate it into signals of the external forcing factors and internal climate mechanisms as listed above as well as the residuals. Finally a back-transformation leads to the spatiotemporally related patterns of all these signals being intercompared. Two kinds of significance tests are applied to the anthropogenic signals. First, it is tested whether the anthropogenic signal is significant compared with the complete residual variance including natural variability. This test answers the question whether a significant anthropogenic climate change is visible in the observed data. As a second test the anthropogenic signal is tested with respect to the climate noise component only. This test answers the question whether the anthropogenic signal is significant among others in the observed data. Using both tests, regions can be specified where the anthropogenic influence is visible (second test) and regions where the anthropogenic influence has already significantly changed climate (first test).
Statistical time series decomposition into significant components and application to European temperature
Nonlinear statistical attribution and detection of anthropogenic climate change using a simulated annealing algorithm
- The climate system can be regarded as a dynamic nonlinear system. Thus, traditional linear statistical methods fail to model the nonlinearities of such a system. These nonlinearities render it necessary to find alternative statistical techniques. Since artificial neural network models (NNM) represent such a nonlinear statistical method their use in analyzing the climate system has been studied for a couple of years now. Most authors use the standard Backpropagation Network (BPN) for their investigations, although this specific model architecture carries a certain risk of over-/underfitting. Here we use the so called Cauchy Machine (CM) with an implemented Fast Simulated Annealing schedule (FSA) (Szu, 1986) for the purpose of attributing and detecting anthropogenic climate change instead. Under certain conditions the CM-FSA guarantees to find the global minimum of a yet undefined cost function (Geman and Geman, 1986). In addition to potential anthropogenic influences on climate (greenhouse gases (GHG), sulphur dioxide (SO2)) natural influences on near surface air temperature (variations of solar activity, explosive volcanism and the El Nino = Southern Oscillation phenomenon) serve as model inputs. The simulations are carried out on different spatial scales: global and area weighted averages. In addition, a multiple linear regression analysis serves as a linear reference. It is shown that the adaptive nonlinear CM-FSA algorithm captures the dynamics of the climate system to a great extent. However, free parameters of this specific network architecture have to be optimized subjectively. The quality of the simulations obtained by the CM-FSA algorithm exceeds the results of a multiple linear regression model; the simulation quality on the global scale amounts up to 81% explained variance. Furthermore the combined anthropogenic effect corresponds to the observed increase in temperature Jones et al. (1994), updated by Jones (1999a), for the examined period 1856–1998 on all investigated scales. In accordance to recent findings of physical climate models, the CM-FSA succeeds with the detection of anthropogenic induced climate change on a high significance level. Thus, the CMFSA algorithm can be regarded as a suitable nonlinear statistical tool for modeling and diagnosing the climate system.
A Digital Global Map of Artificially Drained Agricultural Areas
- Artificial drainage of agricultural land, for example with ditches or drainage tubes, is used to avoid water logging and to manage high groundwater tables. Among other impacts it influences the nutrient balances by increasing leaching losses and by decreasing denitrification. To simulate terrestrial transport of nitrogen on the global scale, a digital global map of artificially drained agricultural areas was developed. The map depicts the percentage of each 5’ by 5’ grid cell that is equipped for artificial drainage. Information on artificial drainage in countries or sub-national units was mainly derived from international inventories. Distribution to grid cells was based, for most countries, on the "Global Croplands Dataset" of Ramankutty et al. (1998) and the "Digital Global Map of Irrigation Areas" of Siebert et al. (2005). For some European countries the CORINE land cover dataset was used instead of the both datasets mentioned above. Maps with outlines of artificially drained areas were available for 6 countries. The global drainage area on the map is 167 Mio hectares. For only 11 out of the 116 countries with information on artificial drainage areas, sub-national information could be taken into account. Due to this coarse spatial resolution of the data sources, we recommended to use the map of artificially drained areas only for continental to global scale assessments. This documentation describes the dataset, the data sources and the map generation, and it discusses the data uncertainty.
Impact of climate change on renewable groundwater resources: assessing the benefits of avoided greenhouse gas emissions using selected CMIP5 climate projections
Felix Theodor Portmann
- Reduction of greenhouse gas (GHG) emissions to minimize climate change requires very significant societal effort. To motivate this effort, it is important to clarify the benefits of avoided emissions. To this end, we analysed the impact of four emissions scenarios on future renewable groundwater resources, which range from 1600 GtCO2 during the 21st century (RCP2.6) to 7300 GtCO2 (RCP8.5). Climate modelling uncertainty was taken into account by applying the bias-corrected output of a small ensemble of five CMIP5 global climate models (GCM) as provided by the ISI-MIP effort to the global hydrological model WaterGAP. Despite significant climate model uncertainty, the benefits of avoided emissions with respect to renewable groundwater resources (i.e. groundwater recharge (GWR)) are obvious. The percentage of projected global population (SSP2 population scenario) suffering from a significant decrease of GWR of more than 10% by the 2080s as compared to 1971–2000 decreases from 38% (GCM range 27–50%) for RCP8.5 to 24% (11–39%) for RCP2.6. The population fraction that is spared from any significant GWR change would increase from 29% to 47% if emissions were restricted to RCP2.6. Increases of GWR are more likely to occur in areas with below average population density, while GWR decreases of more than 30% affect especially (semi)arid regions, across all GCMs. Considering change of renewable groundwater resources as a function of mean global temperature (GMT) rise, the land area that is affected by GWR decreases of more than 30% and 70% increases linearly with global warming from 0 to 3 ° C. For each degree of GMT rise, an additional 4% of the global land area (except Greenland and Antarctica) is affected by a GWR decrease of more than 30%, and an additional 1% is affected by a decrease of more than 70%.
High functional diversity is related to high nitrogen availability in a deciduous forest - evidence from a functional trait approach
Valério de Patta Pillar
- The current study tested the assumption that floristic and functional diversity patterns are negatively related to soil nitrogen content. We analyzed 20 plots with soil N-contents ranging from 0.63% to 1.06% in a deciduous forest near Munich (Germany). To describe species adaptation strategies to different nitrogen availabilities, we used a plant functional type (PFT) approach. Each identified PFT represents one realized adaptation strategy to the current environment. These were correlated, next to plant species richness and evenness, to soil nitrogen contents. We found that N-efficient species were typical for low soil nitrogen contents, while N-requiring species occur at high N-contents. In contrast to our initial hypotheses, floristic and functional diversity measures (number of PFTs) were positively related to nitrogen content in the soil. Every functional group has its own adaptation to the prevailing environmental conditions; in consequence, these functional groups can co-exist but do not out-compete one another. The increased number of functional groups at high N-contents leads to increased species richness. Hence, for explaining diversity patterns we need to consider species groups representing different adaptations to the current environmental conditions. Such co-existing ecological strategies may even overcome the importance of competition in their effect on biodiversity.
Satellite-based sunshine duration for Europe
- In this study, two different methods were applied to derive daily and monthly sunshine duration based on high-resolution satellite products provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Climate Monitoring using data from Meteosat Second Generation (MSG) SEVIRI (Spinning Enhanced Visible and Infrared Imager). The satellite products were either hourly cloud type or hourly surface incoming direct radiation. The satellite sunshine duration estimates were not found to be significantly different using the native 15-minute temporal resolution of SEVIRI. The satellite-based sunshine duration products give additional spatial information over the European continent compared with equivalent in situ-based products. An evaluation of the satellite sunshine duration by product intercomparison and against station measurements was carried out to determine their accuracy. The satellite data were found to be within ±1 h/day compared to high-quality Baseline Surface Radiation Network or surface synoptic observations (SYNOP) station measurements. The satellite-based products differ more over the oceans than over land, mainly because of the treatment of fractional clouds in the cloud type-based sunshine duration product. This paper presents the methods used to derive the satellite sunshine duration products and the performance of the different retrievals. The main benefits and disadvantages compared to station-based products are also discussed.
Stratigraphy and properties of soil profiles along transects in Burkina Faso and Benin and their influence on phytodiversity
Cheikh Amadou Tidiane Anne
- This thesis aims to analyse in a first step the physical and chemical properties of soil profiles along pedomorphological transects in different land used conditions (protected, partly protected as well as cultivated and pastured areas) in North West Benin and in South East Burkina Faso. The information about soils, which are carried out in consideration of the pedogenesis processes like weathering types, saprolitisation, formation of laterite crusts and denudation within the planation surfaces are therefore correlated in a second step with the structure and dynamic of woody plant around individual soil profiles. The relationship soil properties and woody plant is investigated in order to assess the reciprocal influence between the diversity of woody plants and soil characteristics within a small scale study and under different land use conditions.
A common vertical and lateral differentiation of physical and chemical properties regardless of the partly protected, protected and cultivated status of the sites can be noticed. Thus, in the cultivated site of Kikideni and in the partly protected zone of Natiabouani (South East Burkina Faso) sandy loam and sandy clay loam soil surfaces are widespread because of the occurrence of similar erosion processes like sheet wash, rill and gully erosion while in the central part of the Pendjari National Park loamy soil textures are prevailing. In fact, the steepness of the relief and the length of the slopes in the Pendjari Park seem to limit the development of some erosion forms as gully. Furthermore, the classification of soils reflects the variation of pedological processes along the transects and thus the occurrence of different soil types. The status of the sites may play an insignificant role in the differentiation of soil properties within the scale of small pedomorphological transects. A direct comparison of the vegetation type in the land use respectively partly protected and in the total protected sites (National Park of Pendjari) reveals a transition from the shrub savanna to the tree savanna. In conclusion it is important to insist on the fact that the variations of soil parameters within small slopes and the different sites are more conditioned by varying erosion processes and drainage conditions than the status protected or land use sites while the composition and diversity of plants is influenced by the status of the sites, the prevailing management tools, the pedogenetic conditions as well as the presence of wild animals like elephants. The ordination diagram shows that the organic matter is better correlated to the subgroup representing principally the sites of the hunting zone of the Pendjari Park and might be an explaining factor to the distribution of these sample sites groups. CEC ratios in the partly protected site of Natiabouani represent the highest measured in all sites. Nevertheless, statistical analysis of the CCA (canonical correspondence analysis) indicates generally a low correlation. This tendency is consolidated by the Monte Carlo test (p=0.14) which is a good indicator of species and environmental conditions. The detailed analysis of soil properties and the vegetation dynamic as well as their relationship within small pedomorphological transects represent an important pedological and botanical data collection involving different compartments. This thesis contributes to the better understanding of the savanna landscapes of West Africa and may provide essential scientific background for each development project directed towards interdisciplinary and integrative researches.
The Global Crop Water Model (GCWM) : documentation and first results for irrigated crops
- A new global crop water model was developed to compute blue (irrigation) water requirements and crop evapotranspiration from green (precipitation) water at a spatial resolution of 5 arc minutes by 5 arc minutes for 26 different crop classes. The model is based on soil water balances performed for each crop and each grid cell. For the first time a new global data set was applied consisting of monthly growing areas of irrigated crops and related cropping calendars. Crop water use was computed for irrigated land and the period 1998 – 2002. In this documentation report the data sets used as model input and methods used in the model calculations are described, followed by a presentation of the first results for blue and green water use at the global scale, for countries and specific crops. Additionally the simulated seasonal distribution of water use on irrigated land is presented. The computed model results are compared to census based statistical information on irrigation water use and to results of another crop water model developed at FAO.