Dieter Gerten

Multimodel estimate of the global terrestrial water balance: setup and first results

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 0.58 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 21 (from 60 000 to 85 000 km 3 yr 21 ), and simulated runoff ranges from 290 to 457 mm yr 21 (from 42 000 to 66 000 km 3 yr 21 ). 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 degreeday 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

Effects of Precipitation Uncertainty on Discharge Calculations for Main River Basins

This study quantifies the uncertainty in discharge calculations caused by uncertainty in precipitation input for 294 river basins worldwide. Seven global gridded precipitation datasets are compared at river basin scale in terms of mean annual and seasonal precipitation. The representation of seasonality is similar in all datasets, but the uncertainty in mean annual precipitation is large, especially in mountainous, arctic, and small basins. The average precipitation uncertainty in a basin is 30%, but there are strong differences between basins. The effect of this precipitation uncertainty on mean annual and seasonal discharge was assessed using the uncalibrated dynamic global vegetation and hydrology model Lund‐Potsdam‐Jena managed land (LPJmL), yielding even larger uncertainties in discharge (average 90%). For 95 basins (out of 213 basins for which measurements were available) calibration of model parameters is problematic because the observed discharge falls within the uncertainty of the simulated discharge. A method is presented to account for precipitation uncertainty in discharge simulations.

Comparing large-scale hydrological models to observed runoff percentiles in Europe

Large-scalehydrologicalmodelsdescribingtheterrestrialwaterbalanceat continentalandglobalscalesare increasingly being used in earth system modeling and climate impact assessments. However, because of incomplete process understanding and limits of the forcing data, model simulations remain uncertain. To quantify this uncertainty a multimodel ensemble of nine large-scale hydrological models was compared to observed runoff from 426 small catchments in Europe. The ensemble was built within the framework of the European Union Water and Global Change (WATCH) project. The models were driven with the same atmospheric forcing data. Models were evaluated with respect to their ability to capture the interannual variability of spatially aggregated annual time series of five runoff percentiles—derived from daily time series—including annual low and high flows. Overall, the models capture the interannual variability of low, mean, and high flows well. However, errors in the mean and standard deviation, as well as differences in performance between the models, became increasingly pronounced for low runoff percentiles, reflecting the uncertaintyassociatedwiththerepresentationofhydrologicalprocesses,suchasthedepletionofsoilmoisture stores.Thelargespreadin modelperformanceimpliesthatany singlemodelshouldbeappliedwithcautionas there is a great risk of biased conclusions. However, this large spread is contrasted by the good overall performance of the ensemble mean. It is concluded that the ensemble mean is a pragmatic and reliable estimator of spatially aggregated time series of annual low, mean, and high flows across Europe.

Integrated crop water management might sustainably halve the global food gap

As planetary boundaries are rapidly being approached, humanity has little room for additional expansion and conventional intensification of agriculture, while a growing world population further spreads the food gap. Ample evidence exists that improved on-farm water management can close water-related yield gaps to a considerable degree, but its global significance remains unclear. In this modeling study we investigate systematically to what extent integrated crop water management might contribute to closing the global food gap, constrained by the assumption that pressure on water resources and land does not increase. Using a process-based bio-/agrosphere model, we simulate the yield-increasing potential of elevated irrigation water productivity (including irrigation expansion with thus saved water) and optimized use of in situ precipitation water (alleviated soil evaporation, enhanced infiltration, water harvesting for supplemental irrigation) under current and projected future climate (from 20 climate models, with and without beneficial CO2 effects). Results show that irrigation efficiency improvements can save substantial amounts of water in many river basins (globally 48% of non-productive water consumption in an ambitious scenario), and if rerouted to irrigate neighboring rainfed systems, can boost kcal production significantly (26% global increase). Low-tech solutions for small-scale farmers on water-limited croplands show the potential to increase rainfed yields to a similar extent. In combination, the ambitious yet achievable integrated water management strategies explored in this study could increase global production by 41% and close the water-related yield gap by 62%. Unabated climate change will have adverse effects on crop yields in many regions, but improvements in water management as analyzed here can buffer such effects to a significant degree.

Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

The limits to global-warming mitigation by terrestrial carbon removal

Massive near-term greenhouse gas emissions reduction is a precondition for staying “well below 2°C” global warming as envisaged by the Paris Agreement. Furthermore, extensive terrestrial carbon dioxide removal (tCDR) through managed biomass growth and subsequent carbon capture and storage is required to avoid temperature “overshoot” in most pertinent scenarios. Here, we address two major issues: First, we calculate the extent of tCDR required to “repair” delayed or insufficient emissions reduction policies unable to prevent global mean temperature rise of 2.5°C or even 4.5°C above pre-industrial level. Our results show that those tCDR measures are unable to counteract “business-as-usual” emissions without eliminating virtually all natural ecosystems. Even if considerable (Representative Concentration Pathway 4.5 [RCP4.5]) emissions reductions are assumed, tCDR with 50% storage efficiency requires >1.1u2009Gha of the most productive agricultural areas or the elimination of >50% of natural forests. In addition, >100u2009MtN/yr fertilizers would be needed to remove the roughly 320u2009GtC foreseen in these scenarios. Such interventions would severely compromise food production and/or biosphere functioning. Second, we reanalyze the requirements for achieving the 160–190u2009GtC tCDR that would complement strong mitigation action (RCP2.6) in order to avoid 2°C overshoot anytime. We find that a combination of high irrigation water input and/or more efficient conversion to stored carbon is necessary. In the face of severe trade-offs with society and the biosphere, we conclude that large-scale tCDR is not a viable alternative to aggressive emissions reduction. However, we argue that tCDR might serve as a valuable “supporting actor” for strong mitigation if sustainable schemes are established immediately.

Two-thirds of global cropland area impacted by climate oscillations

The El Niño Southern Oscillation (ENSO) peaked strongly during the boreal winter 2015–2016, leading to food insecurity in many parts of Africa, Asia and Latin America. Besides ENSO, the Indian Ocean Dipole (IOD) and the North Atlantic Oscillation (NAO) are known to impact crop yields worldwide. Here we assess for the first time in a unified framework the relationships between ENSO, IOD and NAO and simulated crop productivity at the sub-country scale. Our findings reveal that during 1961–2010, crop productivity is significantly influenced by at least one large-scale climate oscillation in two-thirds of global cropland area. Besides observing new possible links,xa0especially for NAO in Africa and the Middle East, our analyses confirm several known relationships between crop productivity and these oscillations. Our results improve the understanding of climatological crop productivity drivers, which is essential for enhancing food security in many of the most vulnerable places on the planet.Climate oscillations such as El Niño Southern Oscillation may impact global crop production. Here, the authors, using a unified framework of multiple climate oscillations, find that from 1961 to 2010 over two-thirds of the global cropland is located where crop productivity is influenced by climate oscillations.

Towards a comprehensive climate impacts assessment of solar geoengineering

Despite a growing literature on the climate response to solar geoengineering – proposals to cool the planet by increasing the planetary albedo – there has been little published on the impacts of solar geoengineering on natural and human systems such as agriculture, health, water resources, and ecosystems. An understanding of the impacts of different scenarios of solar geoengineering deployment will be crucial for informing decisions on whether and how to deploy it. Here we review the current state of knowledge about impacts of a solar geoengineered climate and identify major research gaps. We suggest that a thorough assessment of the climate impacts of a range of scenarios of solar geoengineering deployment is needed and can build upon existing frameworks. However, solar geoengineering poses a novel challenge for climate impacts research as the manner of deployment could be tailored to pursue different objectives making possible a wide range of climate outcomes. We present a number of ideas for approaches to extend the survey of climate impacts beyond standard scenarios of solar geoengineering deployment to address this challenge. Reducing the impacts of climate change is the fundamental motivator for emissions reductions and for considering whether and how to deploy solar geoengineering. This means that the active engagement of the climate impacts research community will be important for improving the overall understanding of the opportunities, challenges and risks presented by solar geoengineering.

Biomass-based negative emissions difficult to reconcile with planetary boundaries

Under the Paris Agreement, 195 nations have committed to holding the increase in the global average temperature to well below 2u2009°C above pre-industrial levels and to strive to limit the increase to 1.5u2009°C (ref. 1). It is noted that this requires a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of the century1. This either calls for zero greenhouse gas (GHG) emissions or a balance between positive and negative emissions (NE)2,3. Roadmaps and socio-economic scenarios compatible with a 2u2009°C or 1.5u2009°C goal depend upon NE via bioenergy with carbon capture and storage (BECCS) to balance remaining GHG emissions4–7. However, large-scale deployment of BECCS would imply significant impacts on many Earth system components besides atmospheric CO2 concentrations8,9. Here we explore the feasibility of NE via BECCS from dedicated plantations and potential trade-offs with planetary boundaries (PBs)10,11 for multiple socio-economic pathways. We show that while large-scale BECCS is intended to lower the pressure on the PB for climate change, it would most likely steer the Earth system closer to the PB for freshwater use and lead to further transgression of the PBs for land-system change, biosphere integrity and biogeochemical flows.Biomass-based negative emissions can help to address the planetary boundary (PB) for climate change. However, side-effects likely include pushing us closer to the PBs for freshwater use and further transgression of the PBs for biosphere integrity, land-system change, and biogeochemical flows.

Impacts devalue the potential of large-scale terrestrial CO2 removal through biomass plantations

Many integrated assessmentmodels (IAMs) rely on the availability and extensive use of biomass energywith carbon capture and storage (BECCS) to deliver emissions scenarios consistent with limiting climate change to below 2 °Caverage temperature rise. BECCS has the potential to remove carbon dioxide (CO2) from the atmosphere, delivering ‘negative emissions’. The deployment of BECCS at the scale assumed in IAM scenarios is highly uncertain: biomass energy is commonly used but not at such a scale, andCCS technologies have been demonstrated but not commercially established.Herewe present the results of an expert elicitation process that explores the explicit and implicit assumptions underpinning the feasibility of BECCS in IAM scenarios. Our results show that the assumptions are considered realistic regarding technical aspects of CCS but unrealistic regarding the extent of bioenergy deployment, and development of adequate societal support and governance structures for BECCS. The results highlight concerns about the assumedmagnitude of carbon dioxide removal achieved across a full BECCS supply chain, with the greatest uncertainty in bioenergy production. Unrealistically optimistic assumptions regarding the future availability of BECCS in IAM scenarios could lead to the overshoot of critical warming limits and have significant impacts on neartermmitigation options.