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- ItemTrend detection in river flow indices in Poland(Heidelberg : Springer, 2018) Piniewski, Mikołaj; Marcinkowski, Paweł; Kundzewicz, Zbigniew W.The issue of trend detection in long time series of river flow records is of vast theoretical interest and considerable practical relevance. Water management is based on the assumption of stationarity; hence, it is crucial to check whether taking this assumption is justified. The objective of this study is to analyse long-term trends in selected river flow indices in small- and medium-sized catchments with relatively unmodified flow regime (semi-natural catchments) in Poland. The examined indices describe annual and seasonal average conditions as well as annual extreme conditions—low and high flows. The special focus is on the spatial analysis of trends, carried out on a comprehensive, representative data set of flow gauges. The present paper is timely, as no spatially comprehensive studies (i.e. covering the entire Poland or its large parts) on trend detection in time series of river flow have been done in the recent 15 years or so. The results suggest that there is a strong random component in the river flow process, the changes are weak and the spatial pattern is complex. Yet, the results of trend detection in different indices of river flow in Poland show that there exists a spatial divide that seems to hold quite generally for various indices (annual, seasonal, as well as low and high flow). Decreases of river flow dominate in the northern part of the country and increases usually in the southern part. Stations in the central part show mostly ‘no trend’ results. However, the spatial gradient is apparent only for the data for the period 1981–2016 rather than for 1956–2016. It seems also that the magnitude of increases of river flow is generally lower than that of decreases.
- ItemChanges of snow cover in Poland(Heidelberg : Springer, 2017) Szwed, Małgorzata; Pin´skwar, Iwona; Kundzewicz, Zbigniew W.; Graczyk, Dariusz; Mezghani, AbdelkaderThe present paper examines variability of characteristics of snow cover (snow cover depth, number of days with snow cover and dates of beginning and end of snow cover) in Poland. The study makes use of a set of 43 long time series of observation records from the stations in Poland, from 1952 to 2013. To describe temporal changes in snow cover characteristics, the intervals of 1952–1990 and of 1991–2013 are compared and trends in analysed data are sought (e.g., using the Mann–Kendall test). Observed behaviour of time series of snow-related variables is complex and not easy to interpret, for instance because of the location of the research area in the zone of transitional moderate climate, where strong variability of climate events is one of the main attributes. A statistical link between the North Atlantic Oscillation (NAO) index and the snow cover depth, as well as the number of snow cover days is found.
- ItemWhat can we learn from the projections of changes of flow patterns? Results from Polish case studies(Heidelberg : Springer, 2017) Piniewski, Mikołaj; Meresa, Hadush Kidane; Romanowicz, Renata; Osuch, Marzena; Szczes´niak, Mateusz; Kardel, Ignacy; Okruszko, Tomasz; Mezghani, Abdelkader; Kundzewicz, Zbigniew W.River flow projections for two future time horizons and RCP 8.5 scenario, generated by two projects (CHASE-PL and CHIHE) in the Polish-Norwegian Research Programme, were compared. The projects employed different hydrological models over different spatial domains. The semi-distributed, process-based, SWAT model was used in the CHASE-PL project for the entire Vistula and Odra basins area, whilst the lumped, conceptual, HBV model was used in the CHIHE project for eight Polish catchments, for which the comparison study was made. Climate projections in both studies originated from the common EURO-CORDEX dataset, but they were different, e.g. due to different bias correction approaches. Increases in mean annual and seasonal flows were projected in both studies, yet the magnitudes of changes were largely different, in particular for the lowland catchments in the far future. The HBV-based increases were significantly higher in the latter case than the SWAT-based increases in all seasons except winter. Uncertainty in projections is high and creates a problem for practitioners.
- ItemImpact of temperature and precipitation extremes on the flowering dates of four German wildlife shrub species(München : European Geopyhsical Union, 2016) Siegmund, Jonatan F.; Wiedermann, Marc; Donges, Jonathan F.; Donner, Reik V.Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions have already been shown to strongly influence plant flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. Studying this question calls for the application of statistical methods that are tailored to the specific properties of event time series. Here, we employ event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences of occurrences in order to systematically quantify simultaneities between meteorological extremes and the timing of the flowering of four shrub species across Germany. Our study confirms previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of the investigated plants. However, previous studies solely based on correlation analysis do not allow deriving explicit estimates of the strength of such interdependencies without further assumptions, a gap that is closed by our analysis. In addition to direct impacts of extremely warm and cold spring temperatures, our analysis reveals statistically significant indications of an influence of temperature extremes in the autumn preceding the flowering.
- ItemDetecting impacts of extreme events with ecological in situ monitoring networks(München : European Geopyhsical Union, 2017) Mahecha, Miguel D.; Gans, Fabian; Sippel, Sebastian; Donges, Jonathan F.; Kaminski, Thomas; Metzger, Stefan; Migliavacca, Mirco; Papale, Dario; Rammig, Anja; Zscheischler, Jakob; Arneth, AlmutExtreme hydrometeorological conditions typically impact ecophysiological processes on land. Satellite-based observations of the terrestrial biosphere provide an important reference for detecting and describing the spatiotemporal development of such events. However, in-depth investigations of ecological processes during extreme events require additional in situ observations. The question is whether the density of existing ecological in situ networks is sufficient for analysing the impact of extreme events, and what are expected event detection rates of ecological in situ networks of a given size. To assess these issues, we build a baseline of extreme reductions in the fraction of absorbed photosynthetically active radiation (FAPAR), identified by a new event detection method tailored to identify extremes of regional relevance. We then investigate the event detection success rates of hypothetical networks of varying sizes. Our results show that large extremes can be reliably detected with relatively small networks, but also reveal a linear decay of detection probabilities towards smaller extreme events in log–log space. For instance, networks with  ≈  100 randomly placed sites in Europe yield a  ≥  90 % chance of detecting the eight largest (typically very large) extreme events; but only a  ≥  50 % chance of capturing the 39 largest events. These findings are consistent with probability-theoretic considerations, but the slopes of the decay rates deviate due to temporal autocorrelation and the exact implementation of the extreme event detection algorithm. Using the examples of AmeriFlux and NEON, we then investigate to what degree ecological in situ networks can capture extreme events of a given size. Consistent with our theoretical considerations, we find that today's systematically designed networks (i.e. NEON) reliably detect the largest extremes, but that the extreme event detection rates are not higher than would be achieved by randomly designed networks. Spatio-temporal expansions of ecological in situ monitoring networks should carefully consider the size distribution characteristics of extreme events if the aim is also to monitor the impacts of such events in the terrestrial biosphere.
- ItemRole of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis(München : European Geopyhsical Union, 2016) Zhao, Fang; Zeng, Ning; Asrar, Ghassem; Friedlingstein, Pierre; Ito, Akihiko; Jain, Atul; Kalnay, Eugenia; Kato, Etsushi; Koven, Charles D.; Poulter, Ben; Rafique, Rashid; Sitch, Stephen; Shu, Shijie; Stocker, Beni; Viovy, Nicolas; Wiltshire, Andy; Zaehle, SonkeWe examined the net terrestrial carbon flux to the atmosphere (FTA) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961–2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40 % compared to atmospheric inversions. Global FTA amplitude increase (19 ± 8 %) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56 %, −3 ± 74 and 20 ± 30 % to rising CO2, climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO2 fertilization is the strongest control – with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global FTA: some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between FTA amplitude increase and increase in land carbon sink (R2 =  0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO2 fertilization, climate change and land use/cover changes are crucial in determining the right mechanisms in seasonal carbon cycle change as well as mean sink change.
- ItemImproving the use of crop models for risk assessment and climate change adaptation(Amsterdam : Elsevier, 2017) Challinor, Andrew J.; Müller, Christoph; Asseng, Senthold; Deva, Chetan; Nicklin, Kathryn Jane; Wallach, Daniel; Vanuytrecht, Eline; Whitfield, Stephen; Ramirez-Villegas, Julian; Koehler, Ann-KristinCrop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1. Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk? 2. Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output. 3. Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper.
- ItemThe role of bioenergy in enhancing energy, food and ecosystem sustainability based on societal perceptions and preferences in Asia(Basel : MDPI, 2016) Acosta, Lilibeth A.; Magcale-Macandog, Damasa B.; Kavi Kumar, K.S.; Cui, Xuefeng; Eugenio, Elena A.; Macandog, Paula Beatrice M.; Salvacion, Arnold R.; Eugenio, Jemimah Mae A.This paper discussed the analysis of the survey on sustainability of bioenergy conducted in the Philippines, India and China. It acquired general perceptions of the people by asking them (a) specific questions about their level of familiarity with bioenergy; (b) relationship of their work to bioenergy; and (c) their opinion on contribution of various feedstock on the economy and impact of bioenergy production on food security. In addition to these questions, we estimated preference weights of various feedstock based on the conjoint choices on bioenergy’s contribution to social stability, social welfare and ecological balance. The estimates revealed significant trade-offs not only among these three dimensions of sustainability but also the relative importance of energy security, food security and ecosystem capacity to other economic, social and environmental objectives. The types of first generation feedstock that are currently used for biofuel production in the respective countries and those that offer alternative household use are perceived as important to the economy and preferred bioenergy feedstock. Based on the results of the study, the preferred role of bioenergy for sustainable development reflects the social and economic concerns in the respective Asian countries, e.g., energy security in China, food security in India, and ecosystem degradation in the Philippines.
- ItemOn deeper human dimensions in Earth system analysis and modelling(München : European Geopyhsical Union, 2018) Gerten, Dieter; Schönfeld, Martin; Schauberger, BernhardWhile humanity is altering planet Earth at unprecedented magnitude and speed, representation of the cultural driving factors and their dynamics in models of the Earth system is limited. In this review and perspectives paper, we argue that more or less distinct environmental value sets can be assigned to religion – a deeply embedded feature of human cultures, here defined as collectively shared belief in something sacred. This assertion renders religious theories, practices and actors suitable for studying cultural facets of anthropogenic Earth system change, especially regarding deeper, non-materialistic motivations that ask about humans' self-understanding in the Anthropocene epoch. We sketch a modelling landscape and outline some research primers, encompassing the following elements: (i) extensions of existing Earth system models by quantitative relationships between religious practices and biophysical processes, building on databases that allow for (mathematical) formalisation of such knowledge; (ii) design of new model types that specifically represent religious morals, actors and activities as part of co-evolutionary human–environment dynamics; and (iii) identification of research questions of humanitarian relevance that are underrepresented in purely economic–technocratic modelling and scenario paradigms. While this analysis is by necessity heuristic and semi-cohesive, we hope that it will act as a stimulus for further interdisciplinary and systematic research on the immaterial dimension of humanity's imprint on the Earth system, both qualitatively and quantitatively.
- ItemEstimating global cropland production from 1961 to 2010(München : European Geopyhsical Union, 2017) Han, Pengfei; Zeng, Ning; Zhao, Fang; Lin, XiaohuiGlobal cropland net primary production (NPP) has tripled over the last 50 years, contributing 17–45 % to the increase in global atmospheric CO2 seasonal amplitude. Although many regional-scale comparisons have been made between statistical data and modeling results, long-term national comparisons across global croplands are scarce due to the lack of detailed spatiotemporal management data. Here, we conducted a simulation study of global cropland NPP from 1961 to 2010 using a process-based model called Vegetation–Global Atmosphere–Soil (VEGAS) and compared the results with Food and Agriculture Organization of the United Nations (FAO) statistical data on both continental and country scales. According to the FAO data, the global cropland NPP was 1.3, 1.8, 2.2, 2.6, 3.0, and 3.6 PgC yr−1 in the 1960s, 1970s, 1980s, 1990s, 2000s, and 2010s, respectively. The VEGAS model captured these major trends on global and continental scales. The NPP increased most notably in the US Midwest, western Europe, and the North China Plain and increased modestly in Africa and Oceania. However, significant biases remained in some regions such as Africa and Oceania, especially in temporal evolution. This finding is not surprising as VEGAS is the first global carbon cycle model with full parameterization representing the Green Revolution. To improve model performance for different major regions, we modified the default values of management intensity associated with the agricultural Green Revolution differences across various regions to better match the FAO statistical data at the continental level and for selected countries. Across all the selected countries, the updated results reduced the RMSE from 19.0 to 10.5 TgC yr−1 (∼  45 % decrease). The results suggest that these regional differences in model parameterization are due to differences in socioeconomic development. To better explain the past changes and predict the future trends, it is important to calibrate key parameters on regional scales and develop data sets for land management history.