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Simulating the effect of tillage practices with the global ecosystem model LPJmL (version 5.0-tillage)
Lutz, Femke ; Herzfeld, Tobias ; Heinke, Jens ; Rolinski, Susanne ; Schaphoff, Sibyll ; Bloh, Werner Von; Stoorvogel, Jetse J. ; Müller, Christoph - \ 2019
Geoscientific Model Development 12 (2019)6. - ISSN 1991-959X - p. 2419 - 2440.
The effects of tillage on soil properties, crop productivity, and global greenhouse gas emissions have been discussed in the last decades. Global ecosystem models have limited capacity to simulate the various effects of tillage. With respect to the decomposition of soil organic matter, they either assume a constant increase due to tillage or they ignore the effects of tillage. Hence, they do not allow for analysing the effects of tillage and cannot evaluate, for example, reduced tillage or no tillage (referred to here as "no-till") practises as mitigation practices for climate change. In this paper, we describe the implementation of tillage-related practices in the global ecosystem model LPJmL. The extended model is evaluated against reported differences between tillage and no-till management on several soil properties. To this end, simulation results are compared with published meta-analyses on tillage effects. In general, the model is able to reproduce observed tillage effects on global, as well as regional, patterns of carbon and water fluxes. However, modelled N fluxes deviate from the literature values and need further study. The addition of the tillage module to LPJmL5 opens up opportunities to assess the impact of agricultural soil management practices under different scenarios with implications for agricultural productivity, carbon sequestration, greenhouse gas emissions, and other environmental indicators.
A generic pixel-to-point comparison for simulated large-scale ecosystem properties and ground-based observations : An example from the Amazon region
Rammig, Anja ; Heinke, Jens ; Hofhansl, Florian ; Verbeeck, Hans ; Baker, Timothy R. ; Christoffersen, Bradley ; Ciais, Philippe ; Deurwaerder, Hannes De; Fleischer, Katrin ; Galbraith, David ; Guimberteau, Matthieu ; Huth, Andreas ; Johnson, Michelle ; Krujit, Bart ; Langerwisch, Fanny ; Meir, Patrick ; Papastefanou, Phillip ; Sampaio, Gilvan ; Thonicke, Kirsten ; Randow, Celso von; Zang, Christian ; Rödig, Edna - \ 2018
Geoscientific Model Development 11 (2018)12. - ISSN 1991-959X - p. 5203 - 5215.
Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25% and up to 60%, respectively. Our comparison metrics provide a quantitative measure for model-data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products.
LPJmL4 model output for the publications in GMD: LPJmL4 - a dynamic global vegetation model with managed land: Part I – Model description and Part II – Model evaluation
Schaphoff, Sibyll ; Bloh, Werner von; Rammig, Anja ; Thonicke, Kirsten ; Biemans, H. ; Forkel, Matthias ; Gerten, Dieter ; Heinke, Jens ; Jägermeyr, Jonas ; Knauer, Jürgen ; Langerwisch, Fanny ; Lucht, Wolfgang ; Müller, Christoph ; Rolinski, Susanne ; Waha, Katharina - \ 2018
soil carbon - vegetation carbon - global carbon balance - permafrost distribution - discharge - fractional burned area - crop yields - global dynamic vegetation model - vegetation dynamics
LPJmL4 is a process-based model that simulates climate and land-use change impacts on the terrestrial biosphere, the water and carbon cycle and on agricultural production. The LPJmL4 model combines plant physiological relations, generalized empirically established functions and plant trait parameters. The model incorporates dynamic land use at the global scale and is also able to simulate the production of woody and herbaceous short-rotation bio-energy plantations. Grid cells may contain one or several types of natural or agricultural vegetation. A comprehensive description of the model is given by Schaphoff et al. (2017a, http://doi.org/10.5194/gmd-2017-145). The data presented here represent some standard LPJmL4 model results for the land surface described in Schaphoff et al. (2017a,). Additionally, these results are evaluated in the companion paper of Schaphoff et al. (2017b, http://doi.org/10.5194/gmd-2017-146). The data collection includes some key output variables made with different model setups described by Schaphoff et al. (2017b). The data cover the entire globe with a spatial resolution of 0.5° and temporal coverage from 1901-2011 on an annual basis for soil, vegetation, aboveground and litter carbon as well as for vegetation distribution, crop yields, sowing dates, maximum thawing depth, and fire carbon emissions. Vegetation distribution is given for each plant functional type (PFT), crop yields, and sowing dates are given for each crop functional type (CFT), respectively. Monthly data are provided for the carbon fluxes (net primary production, gross primary production, soil respiration) and the water fluxes (transpiration, evaporation, interception, runoff, and discharge) and for absorbed photosynthetically active radiation (FAPAR) and albedo.
LPJmL4 Model Code
Schaphoff, Sibyll ; Bloh, Werner von; Thonicke, Kirsten ; Biemans, H. ; Forkel, Matthias ; Gerten, Dieter ; Heinke, Jens ; Jägermeyr, Jonas ; Müller, Christoph ; Rolinski, Susanne ; Waha, Katharina ; Stehfest, Elke ; Waal, Liesbeth de; Heyder, Ursula ; Gumpenberger, Marlies ; Beringer, Tim - \ 2018
Potsdam Institute for Climate Impact Research (PIK)
soil carbon - vegetation carbon - global carbon balance - permafrost distribution - discharge - fractional burned area - crop yields - global dynamic vegetation model - vegetation dynamics
LPJmL4 is a process-based model that simulates climate and land-use change impacts on the terrestrial biosphere, the water and carbon cycle and on agricultural production. The LPJmL4 model combines plant physiological relations, generalized empirically established functions and plant trait parameters. The model incorporates dynamic land use at the global scale and is also able to simulate the production of woody and herbaceous short-rotation bio-energy plantations. Grid cells may contain one or several types of natural or agricultural vegetation.
Pyridine Nucleotide Coenzyme Specificity of p-Hydroxybenzoate Hydroxylase and Related Flavoprotein Monooxygenases
Westphal, A.H. ; Tischler, Dirk ; Heinke, Florian ; Hofmann, Sarah ; Gröning, Janosch ; Labudde, Dirk ; Berkel, W.J.H. van - \ 2018
Frontiers in Microbiology 9 (2018). - ISSN 1664-302X - 17 p.
p-Hydroxybenzoate hydroxylase (PHBH; EC 220.127.116.11) is a microbial group A flavoprotein monooxygenase that catalyzes the ortho-hydroxylation of 4-hydroxybenzoate to 3,4-dihydroxybenzoate with the stoichiometric consumption of NAD(P)H and oxygen. PHBH and related enzymes lack a canonical NAD(P)H-binding domain and the way they interact with the pyridine nucleotide coenzyme has remained a conundrum. Previously, we identified a surface exposed protein segment of PHBH from Pseudomonas fluorescens involved in NADPH binding. Here, we report the first amino acid sequences of NADH-preferring PHBHs and a phylogenetic analysis of putative PHBHs identified in currently available bacterial genomes. It was found that PHBHs group into three clades consisting of NADPH-specific, NAD(P)H-dependent and NADH-preferring enzymes. The latter proteins frequently occur in Actinobacteria. To validate the results, we produced several putative PHBHs in Escherichia coli and confirmed their predicted coenzyme preferences. Based on phylogeny, protein energy profiling and lifestyle of PHBH harboring bacteria we propose that the pyridine nucleotide coenzyme specificity of PHBH emerged through adaptive evolution and that the NADH-preferring enzymes are the older versions of PHBH. Structural comparison and distance tree analysis of group A flavoprotein monooxygenases indicated that a similar protein segment as being responsible for the pyridine nucleotide coenzyme specificity of PHBH is involved in determining the pyridine nucleotide coenzyme specificity of the other group A members.
LPJmL4 - A dynamic global vegetation model with managed land - Part 1 : Model description
Schaphoff, Sibyll ; Bloh, Werner von; Rammig, Anja ; Thonicke, Kirsten ; Biemans, Hester ; Forkel, Matthias ; Gerten, Dieter ; Heinke, Jens ; Jägermeyr, Jonas ; Knauer, Jürgen ; Langerwisch, Fanny ; Lucht, Wolfgang ; Müller, Christoph ; Rolinski, Susanne ; Waha, Katharina - \ 2018
Geoscientific Model Development 11 (2018)4. - ISSN 1991-959X - p. 1343 - 1375.
This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.
Modeling vegetation and carbon dynamics of managed grasslands at the global scale with LPJmL 3.6
Rolinski, Susanne ; Müller, Christoph ; Heinke, Jens ; Weindl, Isabelle ; Biewald, Anne ; Leon Bodirsky, Benjamin ; Bondeau, Alberte ; Boons-Prins, Eltje R. ; Bouwman, Alexander F. ; Leffelaar, Peter A. ; Roller, Johnny A. te; Schaphoff, Sibyll ; Thonicke, Kirsten - \ 2018
Geoscientific Model Development 11 (2018)1. - ISSN 1991-959X - p. 429 - 451.
Grassland management affects the carbon fluxes of one-third of the global land area and is thus an important factor for the global carbon budget. Nonetheless, this aspect has been largely neglected or underrepresented in global carbon cycle models. We investigate four harvesting schemes for the managed grassland implementation of the dynamic global vegetation model (DGVM) Lund-Potsdam-Jena managed Land (LPJmL) that facilitate a better representation of actual management systems globally. We describe the model implementation and analyze simulation results with respect to harvest, net primary productivity and soil carbon content and by evaluating them against reported grass yields in Europe.We demonstrate the importance of accounting for differences in grassland management by assessing potential livestock grazing densities as well as the impacts of grazing, grazing intensities and mowing systems on soil carbon stocks. Grazing leads to soil carbon losses in polar or arid regions even at moderate livestock densities ( < 0.4 livestock units per hectare-LSUha -1 ) but not in temperate regions even at much higher densities (0.4 to 1.2 LSUha -1 ). Applying LPJmL with the new grassland management options enables assessments of the global grassland production and its impact on the terrestrial biogeochemical cycles but requires a global data set on current grassland management.
Resilience of Amazon forests emerges from plant trait diversity
Sakschewski, Boris ; Bloh, Werner Von; Boit, Alice ; Poorter, Lourens ; Peña-Claros, Marielos ; Heinke, Jens ; Joshi, Jasmin ; Thonicke, Kirsten - \ 2016
Nature Climate Change 6 (2016)11. - ISSN 1758-678X - p. 1032 - 1036.
Climate change threatens ecosystems worldwide, yet their potential future resilience remains largely unquantified. In recent years many studies have shown that biodiversity, and in particular functional diversity, can enhance ecosystem resilience by providing a higher response diversity. So far these insights have been mostly neglected in large-scale projections of ecosystem responses to climate change. Here we show that plant trait diversity, as a key component of functional diversity, can have a strikingly positive effect on the Amazon forests' biomass under future climate change. Using a terrestrial biogeochemical model that simulates diverse forest communities on the basis of individual tree growth, we show that plant trait diversity may enable the Amazon forests to adjust to new climate conditions via a process of ecological sorting, protecting the Amazon's carbon sink function. Therefore, plant trait diversity, and biodiversity in general, should be considered in large-scale ecosystem projections and be included as an integral part of climate change research and policy.
Multimodel assessment of water scarcity under climate change
Schellnhuber, H.J. ; Heinke, J. ; Gerten, D. ; Haddeland, I. ; Arnell, N.W. ; Clark, D.B. ; Dankers, R. ; Eisner, S. ; Kabat, P. - \ 2014
Proceedings of the National Academy of Sciences of the United States of America 111 (2014)9. - ISSN 0027-8424 - p. 3245 - 3250.
future food-production - model description - bias correction - river runoff - resources - availability - vulnerability - uncertainty - scenarios - trends
Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 °C above present (approximately 2.7 °C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (
Global water resources affected by human interventionss and climate change
Haddeland, I. ; Heinke, J. ; Biemans, H. ; Eisner, S. ; Florke, M.F. ; Hanasaki, N. ; Konzmann, M. ; Ludwig, F. - \ 2014
Proceedings of the National Academy of Sciences of the United States of America 111 (2014)9. - ISSN 0027-8424 - p. 3251 - 3256.
integrated model - bias correction - surface-water - validation - fluxes - scheme
Humans directly change the dynamics of the water cycle through dams constructed for water storage, and through water withdrawals for industrial, agricultural, or domestic purposes. Climate change is expected to additionally affect water supply and demand. Here, analyses of climate change and direct human impacts on the terrestrial water cycle are presented and compared using a multimodel approach. Seven global hydrological models have been forced with multiple climate projections, and with and without taking into account impacts of human interventions such as dams and water withdrawals on the hydrological cycle. Model results are analyzed for different levels of global warming, allowing for analyses in line with temperature targets for climate change mitigation. The results indicate that direct human impacts on the water cycle in some regions, e.g., parts of Asia and in the western United States, are of the same order of magnitude, or even exceed impacts to be expected for moderate levels of global warming (+2 K). Despite some spread in model projections, irrigation water consumption is generally projected to increase with higher global mean temperatures. Irrigation water scarcity is particularly large in parts of southern and eastern Asia, and is expected to become even larger in the future.
Climate change impact on available water resources obtained using multiple global climate and hydrology models
Hagemann, S. ; Chen, Cui ; Clark, D.B. ; Folwell, S. ; Gosling, S. ; Haddeland, I. ; Hanasaki, N. ; Heinke, J. ; Ludwig, F. - \ 2013
Earth System dynamics 4 (2013). - ISSN 2190-4979 - p. 129 - 144.
Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological 5 models (eight) were used to systematically assess the hydrological response to climate change and project the future state of global water resources. The results show a large spread in projected changes in water resources within the climate–hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change. But there are also areas 10 showing a robust change signal, such as at high latitudes and in some mid-latitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence. In many catchments an increase of available water resources is expected but there are some severe decreases in central and Southern Europe, the Middle East, the Mississippi river basin, Southern Africa, Southern China and south 15 eastern Australia.
Anthropogenic impacts on the global water cycle-a multi model approach
Ludwig, F. ; Biemans, H. ; Clark, D. ; Franssen, W.H.P. ; Voss, F. ; Heinke, J. ; Hagemann, S. - \ 2012
In: European Geosciences Union, EGU General Assembly 2012, Wenen, Austria, 22 - 27 April, 2012. - - p. 10273 - 10273.
Humans activities have a large impact on the global water cycle. Through the building of dams and irrigation schemes large amounts of water are diverted from river systems. Through the emission of greenhouse gases causing global warming, also the rainfall and evaporation patterns are changed across the globe. It is, however, still difficult to quantify current and future impacts on the global water cycle due to limited data availability, model imperfections and large uncertainties in climate change projections. To partly overcome these limitations we used a multi-model approach to study anthropogenic impacts on the global water cycle. Four different global hydrological models (H08, VIC, WaterGAP and LPJml) were forced with an historical climate dataset (Watch Forcing Data) and bias corrected output of three different global climate models (Echam, IPSL and CNRM) using two emission scenarios (A2 and B1). In addition the LPJml model was also run with two different land use change scenarios. Combining the water availability simulations with the water demand scenarios developed within the Watch project we also analyzed current and future water scarcity. The analyses show that current human impacts and on the water cycle are especially high in Central Asia, parts of Europe, the Southwestern US and the Murray-Darling Basin in Australia. The model comparison of agricultural water use and demand showed that the differences in total global agricultural demand and water use were relatively smaller than the differences in simulated water availability. All models showed agricultural water extractions are high in South and East Asia in particular in Northern India and Pakistan and in Northeast China. The most important spatial differences between the different models was observed for Northern China where H08 showed much higher water demands than VIC. Future analyses showed that climate change impacts on the global water cycle are potentially high especially in the semi-arid regions. Although there were considerable differences in the four hydrological models in general all models predicted the same direction of change. In conclusion the analyses showed that both under the B1 and the A2 scenarios the percentage of agricultural water demand than cannot be fulfilled by surface and ground-water will increase. Water shortages will be much higher under the A2 than under the B1 scenario. In conclusion using a multi model approach gives a more robust quantification of possible future anthropogenic impacts on the global water cycle.
Effects of climate model radiation, humidity and wind estimates on hydrological simulations
Haddeland, I. ; Heinke, J. ; Eisner, S. ; Chen, C. ; Hagemann, S. ; Ludwig, F. - \ 2012
Hydrology and Earth System Sciences 16 (2012)2. - ISSN 1027-5606 - p. 305 - 318.
Due to biases in the output of climate models, a bias correction is often needed to make the output suitable for use in hydrological simulations. In most cases only the temperature and precipitation values are bias corrected. However, often there are also biases in other variables such as radiation, humidity and wind speed. In this study we tested to what extent it is also needed to bias correct these variables. Responses to radiation, humidity and wind estimates from two climate models for four large-scale hydrological models are analysed. For the period 1971–2000 these hydrological simulations are compared to simulations using meteorological data based on observations and reanalysis; i.e. the baseline simulation. In both forcing datasets originating from climate models precipitation and temperature are bias corrected to the baseline forcing dataset. Hence, it is only effects of radiation, humidity and wind estimates that are tested here. The direct use of climate model outputs result in substantial different evapotranspiration and runoff estimates, when compared to the baseline simulations. A simple bias correction method is implemented and tested by rerunning the hydrological models using bias corrected radiation, humidity and wind values. The results indicate that bias correction can successfully be used to match the baseline simulations. Finally, historical (1971–2000) and future (2071–2100) model simulations resulting from using bias corrected forcings are compared to the results using non-bias corrected forcings. The relative changes in simulated evapotranspiration and runoff are relatively similar for the bias corrected and non bias corrected hydrological projections, although the absolute evapotranspiration and runoff numbers are often very different. The simulated relative and absolute differences when using bias corrected and non bias corrected climate model radiation, humidity and wind values are, however, smaller than literature reported differences resulting from using bias corrected and non bias corrected climate model precipitation and temperature values.
Global Water Availability and Requirements for Future Food Production
Gerten, D. ; Heinke, J. ; Hoff, H. ; Biemans, H. ; Fader, M. ; Waha, K. - \ 2011
Journal of Hydrometeorology 12 (2011)5. - ISSN 1525-755X - p. 885 - 899.
high-resolution - climate-change - fresh-water - resources - agriculture - vegetation - scenarios - nations - balance - trade
This study compares, spatially explicitly and at global scale, per capita water availability and water requirements for food production presently (1971-2000) and in the future given climate and population change (2070-99). A vegetation and hydrology model Lund-Potsdam-Jena managed Land (LPJmL) was used to calculate green and blue water availability per capita, water requirements to produce a balanced diet representing a benchmark for hunger alleviation [3000 kilocalories per capita per day (1 kilocalorie = 4184 joules), here assumed to consist of 80% vegetal food and 20% animal products], and a new water scarcity indicator that relates the two at country scale. A country was considered water-scarce if its water availability fell below the water requirement for the specified diet, which is presently the case especially in North and East Africa and in southwestern Asia. Under climate (derived from 17 general circulation models) and population change (A2 and B1 emissions and population scenarios), water availability per person will most probably diminish in many regions. At the same time the calorie-specific water requirements tend to decrease, due mainly to the positive effect of rising atmospheric CO(2) concentration on crop water productivity which, however, is very uncertain to be fully realized in most regions. As a net effect of climate, CO(2), and population change, water scarcity will become aggravated in many countries, and a number of additional countries are at risk of losing their present capacity to produce a balanced diet for their inhabitants.
|Projected hydrological changes in the 21st century and related uncertainties obtained from a multi-model ensemble
Chen, C. ; Hagemann, S. ; Clark, D. ; Folwell, S. ; Gosling, S. ; Haddeland, I. ; Hanasaki, N. ; Heinke, J. ; Ludwig, F. ; Voss, F. ; Wiltshire, A. - \ 2011
Wageningen : Wageningen Universiteit
Multimodel estimate of the global terrestrial water balance: Setup and first results
Haddeland, I. ; Clark, D. ; Franssen, W.H.P. ; Ludwig, F. ; Voss, F. ; Arnell, N.W. ; Bertrand, N. ; Best, M. ; Folwell, S. ; Gerten, D. ; Gomes, S. ; Gosling, S. ; Hagemann, S. ; Hanasaki, N. ; Harding, R. ; Heinke, J. ; Kabat, P. ; Koirala, S. ; Oki, T. ; Polcher, J. ; Stacke, T. ; Viterbo, P. ; Weedon, G.P. ; Yeh, P. - \ 2011
Journal of Hydrometeorology 12 (2011)5. - ISSN 1525-755X - p. 869 - 884.
land-surface scheme - space-time climate - parameterization schemes - integrated model - project - simulation - resources - runoff - gcm - precipitation
Six land surface models and five global hydrological models participate in a model intercomparison project [Water Model Intercomparison Project (WaterMIP)], which for the first time compares simulation results of these different classes of models in a consistent way. In this paper, the simulation setup is described and aspects of the multimodel global terrestrial water balance are presented. All models were run at 0.5° spatial resolution for the global land areas for a 15-yr period (1985–99) using a newly developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm yr-1 (from 60 000 to 85 000 km3 yr-1), and simulated runoff ranges from 290 to 457 mm yr-1 (from 42 000 to 66 000 km3 yr-1). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degree-day approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between models are a major source of uncertainty. Climate change impact studies thus need to use not only multiple climate models but also some other measure of uncertainty (e.g., multiple impact models).
Drought at the global scale in the 2nd part of the 20th century (1963-2001)
Huijgevoort, M.H.J. van; Hazenberg, P. ; Lanen, H.A.J. van; Bertrand, N. ; Clark, D. ; Folwell, S. ; Gosling, S. ; Hanasaki, N. ; Heinke, J. ; Stacke, T. ; Voss, F. - \ 2011
Brussel : European Commission (Technical report / WATCH no. 42) - 40
droogte - hydrologische gegevens - aardoppervlak - modellen - hydrologie - klimatologie - geschiedenis - drought - hydrological data - land surface - models - hydrology - climatology - history
The large impacts of drought on society, economy and environment urge for a thorough investigation. A good knowledge of past drought events is important for both understanding of the processes causing drought, as well as to provide reliability assessments for drought projections for the future. Preferably, the investigation of historic drought events should rely on observations. Unfortunately, for a global scale these detailed observations are often not available. Therefore, the outcome of global hydrological models (GHMs) and off-line land surface models (LSMs) is used to assess droughts. In this study we have investigated to what extent simulated gridded time series from these large-scale models capture historic hydrological drought events. Results of ten different models, both GHMs and LSMs, made available by the WATCH project, were compared. All models are run on a global 0.5 degree grid for the period 1963-2000 with the same meteorological forcing data (WATCH forcing data). To identify hydrological drought events, the monthly aggregated total runoff values were used. Different methods were developed to identify spatio-temporal drought characteristics. General drought characteristics for each grid cell, as for example the average drought duration, were compared. These characteristics show that when comparing absolute values the models give substantially different results, whereas relative values lead to more or less the same drought pattern. Next to the general drought characteristics, some documented major historical drought events (one for each continent) were selected and described in more detail. For each drought event, the simulated drought clusters (spatial events) and their characteristics are given for one month during the event. It can be concluded that most major drought events are captured by all models. However, the spatial extent of the drought events differ substantially between the models. In general the models show a fast reaction to rainfall and therefore also capture drought events caused by large rainfall anomalies. More research is still needed, since here we only looked at a few selected number of documented drought events spread over the globe. To assess more in detail if these large-scale models are able to capture drought, additional quantitative analyses are needed together with a more elaborated comparison against observed drought events.
Drought at the global scale in the 21st Century
Corzo Perez, G. ; Lanen, H.A.J. van; Bertrand, N. ; Chen, C. ; Clark, D. ; Folwell, S. ; Gosling, S. ; Hanasaki, N. ; Heinke, J. ; Voss, F. - \ 2011
Brussel : European Commission (Technical report / WATCH no. 43) - 117