Wolfgang Lucht

Tipping elements in the Earth's climate system

The term “tipping point” commonly refers to a critical threshold at which a tiny perturbation can qualitatively alter the state or development of a system. Here we introduce the term “tipping element” to describe large-scale components of the Earth system that may pass a tipping point. We critically evaluate potential policy-relevant tipping elements in the climate system under anthropogenic forcing, drawing on the pertinent literature and a recent international workshop to compile a short list, and we assess where their tipping points lie. An expert elicitation is used to help rank their sensitivity to global warming and the uncertainty about the underlying physical mechanisms. Then we explain how, in principle, early warning systems could be established to detect the proximity of some tipping points.

First operational BRDF, albedo nadir reflectance products from MODIS

With the launch of NASA’s Terra satellite and the MODerate Resolution Imaging Spectroradiometer (MODIS), operational Bidirectional Reflectance Distribution Function (BRDF) and albedo products are now being made available to the scientific community. The MODIS BRDF/Albedo algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model and multidate, multispectral data to provide global 1-km gridded and tiled products of the land surface every 16 days. These products include directional hemispherical albedo (black-sky albedo), bihemispherical albedo (white-sky albedo), Nadir BRDF-Adjusted surface Reflectances (NBAR), model parameters describing the BRDF, and extensive quality assurance information. The algorithm has been consistently producing albedo and NBAR for the public since July 2000. Initial evaluations indicate a stable BRDF/Albedo Product, where, for example, the spatial and temporal progression of phenological characteristics is easily detected in the NBAR and albedo results. These early beta and provisional products auger well for the routine production of stable MODIS-derived BRDF parameters, nadir reflectances, and albedos for use by the global observation and modeling communities.

The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research

The first Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is planned for launch by NASA in 1998. This instrument will provide a new and improved capability for terrestrial satellite remote sensing aimed at meeting the needs of global change research. The MODIS standard products will provide new and improved tools for moderate resolution land surface monitoring. These higher order data products have been designed to remove the burden of certain common types of data processing from the user community and meet the more general needs of global-to-regional monitoring, modeling, and assessment. The near-daily coverage of moderate resolution data from MODIS, coupled with the planned increase in high-resolution sampling from Landsat 7, will provide a powerful combination of observations. The full potential of MODIS will be realized once a stable and well-calibrated time-series of multispectral data has been established. In this paper the proposed MODIS standard products for land applications are described along with the current plans for data quality assessment and product validation.

Quantifying and mapping the human appropriation of net primary production in earth's terrestrial ecosystems

Human appropriation of net primary production (HANPP), the aggregate impact of land use on biomass available each year in ecosystems, is a prominent measure of the human domination of the biosphere. We present a comprehensive assessment of global HANPP based on vegetation modeling, agricultural and forestry statistics, and geographical information systems data on land use, land cover, and soil degradation that localizes human impact on ecosystems. We found an aggregate global HANPP value of 15.6 Pg C/yr or 23.8% of potential net primary productivity, of which 53% was contributed by harvest, 40% by land-use-induced productivity changes, and 7% by human-induced fires. This is a remarkable impact on the biosphere caused by just one species. We present maps quantifying human-induced changes in trophic energy flows in ecosystems that illustrate spatial patterns in the human domination of ecosystems, thus emphasizing land use as a pervasive factor of global importance. Land use transforms earths terrestrial surface, resulting in changes in biogeochemical cycles and in the ability of ecosystems to deliver services critical to human well being. The results suggest that large-scale schemes to substitute biomass for fossil fuels should be viewed cautiously because massive additional pressures on ecosystems might result from increased biomass harvest.

An algorithm for the retrieval of albedo from space using semiempirical BRDF models

Spectral albedo may be derived from atmospherically corrected, cloud-cleared multiangular reflectance observations through the inversion of a bidirectional reflectance distribution function (BRDF) model and angular integration. This paper outlines an algorithm suitable for this task that makes use of kernel-based BRDF models. Intrinsic land surface albedos are derived, which may be used to derive actual albedo by taking into account the prevailing distribution of diffuse skylight. Spectral-to-broadband conversion is achieved using band-dependent weighting factors. The validation of a suitable BRDF model, the semiempirical Ross-Li (reciprocal RossThick-LiSparse) model and its performance under conditions of sparse angular sampling and noisy reflectances are discussed, showing that the retrievals obtained are generally reliable. The solar-zenith angle dependence of albedo may be parameterized by a simple polynomial that makes it unnecessary for the user to be familiar with the underlying BRDF model. The algorithm given is that used for the production of a BRDF/albedo standard data product from NASAs EOS-MODIS sensor, for which an at-launch status is provided. Finally, the algorithm is demonstrated on combined AVHRR and GOES observations acquired over New England, from which solar zenith angle-dependent albedo maps with a nominal spatial resolution of 1 km are derived in the visible band. The algorithm presented may be employed to derive albedo from space-based multiangular measurements and also serves as a guide for the use of the MODIS BRDF/albedo product.

Bioenergy production potential of global biomass plantations under environmental and agricultural constraints

We estimate the global bioenergy potential from dedicated biomass plantations in the 21st century under a range of sustainability requirements to safeguard food production, biodiversity and terrestrial carbon storage. We use a process‐based model of the land biosphere to simulate rainfed and irrigated biomass yields driven by data from different climate models and combine these simulations with a scenario‐based assessment of future land availability for energy crops. The resulting spatial patterns of large‐scale lignocellulosic energy crop cultivation are then investigated with regard to their impacts on land and water resources. Calculated bioenergy potentials are in the lower range of previous assessments but the combination of all biomass sources may still provide between 130 and 270 EJ yr−1 in 2050, equivalent to 15–25% of the Worlds future energy demand. Energy crops account for 20–60% of the total potential depending on land availability and share of irrigated area. However, a full exploitation of these potentials will further increase the pressure on natural ecosystems with a doubling of current land use change and irrigation water demand. Despite the consideration of sustainability constraints on future agricultural expansion the large‐scale cultivation of energy crops is a threat to many areas that have already been fragmented and degraded, are rich in biodiversity and provide habitat for many endangered and endemic species.

Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2

Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510–758 ppm of CO2), vegetation carbon increases by 52–477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.

Dynamic global vegetation modelling: quantifying terrestrial ecosystem responses to large-scale environmental change

DGVMs exploit the power of modern computers and computational methods to yield a predictive description of land ecosystem processes that takes account of knowledge previously developed through long histories of separate disciplinary approaches to the study of the biosphere. The degree of interaction between the different scientific approaches still falls far short of optimal; thus, DGVM developers have a responsibility to be aware of progress in several disciplines in order to ensure that their models remain state-of-the-art. We have presented a series of case studies of the evaluation of DGVMs that demonstrate the predictive capability that current models have achieved. Nevertheless, there are plenty of unresolved issues — differences among models that are not well understood, important processes that are omitted or treated simplistically by some or all models, and sets of observations that are not satisfactorily reproduced by current models. More comprehensive “benchmarking” of DGVMs against multiple data sets is required and would be most effectively carried out through an international consortium, so as to avoid duplicating the large amount of work involved in selecting and processing data sets and model experiments. We have also presented a series of case studies that illustrate the power of DGVMs, even with their known limitations, in explaining a remarkable variety of Earth System phenomena and in addressing contemporary issues related to climate and land-use change. These case studies encourage us to believe that the continued development of DGVMs is a worthwhile enterprise. Finally, new directions in Earth System Science point to a range of aspects in which DGVMs could be improved so as to take account of recently acquired knowledge, such as experimental work on whole-ecosystem responses to environmental modification and new understanding of the functional basis of plant traits; complemented by an effort to represent semi-natural and agricultural ecosystems and the impacts of different management practices on these ecosystems; and extended to include processes such as trace-gas emissions, which are important in order to understand the functional role of the terrestrial biosphere in the Earth System. Together, these potential developments add up to an ambitious research program, requiring the economies of scale that only an international collaborative effort can provide.

Causes of change in 20th century global river discharge

[1] A global vegetation and hydrology model (LPJmL) was applied to quantify the contributions of changing precipitation, temperature, atmospheric CO 2 content, land use and irrigation to worldwide trends in 20th century river discharge (Q). Consistently with observations, Q decreased in parts of Africa, central/southern Asia and south-eastern Europe, and increased especially in parts of North America and western Asia. Based on the CRU TS2.1 climatology, total global Q rose over 1901-2002 (trend, 30.8 km 3 a -2 , equaling 7.7%), due primarily to increasing precipitation (individual effect, +24.7 km 3 a -2 ). Global warming (-3.1), rising CO 2 (+4.4), land cover changes (+5.9) and irrigation (-1.1) also had discernible effects. However, sign and magnitude of trends exhibited pronounced decadal variability and differed among precipitation forcing datasets. Since recent trends in these and other drivers of Q are mainly anthropogenic, we conclude that humans exert an increasing influence on the global water cycle.

Spatial decoupling of agricultural production and consumption: quantifying dependences of countries on food imports due to domestic land and water constraints

In our globalizing world, the geographical locations of food production and consumption are becoming increasingly disconnected, which increases reliance on external resources and their trade. We quantified to what extent water and land constraints limit countries’ capacities, at present and by 2050, to produce on their own territory the crop products that they currently import from other countries. Scenarios of increased crop productivity and water use, cropland expansion (excluding areas prioritized for other uses) and population change are accounted for. We found that currently 16% of the world population use the opportunities of international trade to cover their demand for agricultural products. Population change may strongly increase the number of people depending on ex situ land and water resources up to about 5.2 billion (51% of world population) in the SRES A2r scenario. International trade will thus have to intensify if population growth is not accompanied by dietary change towards less resource-intensive products, by cropland expansion, or by productivity improvements, mainly in Africa and the Middle East. Up to 1.3 billion people may be at risk of food insecurity in 2050 in present low-income economies (mainly in Africa), if their economic development does not allow them to afford productivity increases, cropland expansion and/or imports from other countries.