A comprehensive benchmarking system for evaluating global vegetation models.

We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover, composition and 5 height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, 10 and are compared to scores based on the temporal or spatial mean value of the observations and a “random” model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), and the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global 15 vegetation models (DGVMs). SDBM reproduces observed CO2 seasonal cycles, but its simulation of independent measurements of net primary production (NPP) is too high. The two DGVMs show little difference for most benchmarks (including the interannual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified 20 several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change 25 impacts and feedbacks.

Stable isotope and modelling evidence for CO2 as a driver of glacial–interglacial vegetation shifts in southern Africa

Atmospheric CO2 concentration is hypothesized to influence vegetation distribution via tree–grass competition, with higher CO2 concentrations favouring trees. The stable carbon isotope (δ13C) signature of vegetation is influenced by the relative importance of C4 plants (including most tropical grasses) and C3 plants (including nearly all trees), and the degree of stomatal closure – a response to aridity – in C3 plants. Compound-specific δ13C analyses of leaf-wax biomarkers in sediment cores of an offshore South Atlantic transect are used here as a record of vegetation changes in subequatorial Africa. These data suggest a large increase in C3 relative to C4 plant dominance after the Last Glacial Maximum. Using a process-based biogeography model that explicitly simulates 13C discrimination, it is shown that precipitation and temperature changes cannot explain the observed shift in δ13C values. The physiological effect of increasing CO2 concentration is decisive, altering the C3/C4 balance and bringing the simulated and observed δ13C values into line. It is concluded that CO2 concentration itself was a key agent of vegetation change in tropical southern Africa during the last glacial–interglacial transition. Two additional inferences follow. First, long-term variations in terrestrial δ13Cvalues are not simply a proxy for regional rainfall, as has sometimes been assumed. Although precipitation and temperature changes have had major effects on vegetation in many regions of the world during the period between the Last Glacial Maximum and recent times, CO2 effects must also be taken into account, especially when reconstructing changes in climate between glacial and interglacial states. Second, rising CO2 concentration today is likely to be influencing tree–grass competition in a similar way, and thus contributing to the "woody thickening" observed in savannas worldwide. This second inference points to the importance of experiments to determine how vegetation composition in savannas is likely to be influenced by the continuing rise of CO2 concentration.

Global vegetation and terrestrial carbon cycle changes after the last ice age

•In current models, the ecophysiological effects of CO2 create both woody thickening and terrestrial carbon uptake, as observed now, and forest cover and terrestrial carbon storage increases that took place after the last glacial maximum (LGM). Here, we aimed to assess the realism of modelled vegetation and carbon storage changes between LGM and the pre-industrial Holocene (PIH). •We applied Land Processes and eXchanges (LPX), a dynamic global vegetation model (DGVM), with lowered CO2 and LGM climate anomalies from the Palaeoclimate Modelling Intercomparison Project (PMIP II), and compared the model results with palaeodata. •Modelled global gross primary production was reduced by 27–36% and carbon storage by 550–694 Pg C compared with PIH. Comparable reductions have been estimated from stable isotopes. The modelled areal reduction of forests is broadly consistent with pollen records. Despite reduced productivity and biomass, tropical forests accounted for a greater proportion of modelled land carbon storage at LGM (28–32%) than at PIH (25%). •The agreement between palaeodata and model results for LGM is consistent with the hypothesis that the ecophysiological effects of CO2 influence tree–grass competition and vegetation productivity, and suggests that these effects are also at work today.

Exploring the climatic impact of the continental vegetation on the Mezosoic atmospheric CO2 and climate history

In this contribution, we continue our exploration of the factors defining the Mesozoic climatic history. We improve the Earth system model GEOCLIM designed for long term climate and geochemical reconstructions by adding the explicit calculation of the biome dynamics using the LPJ model. The coupled GEOCLIM-LPJ model thus allows the simultaneous calculation of the climate with a 2-D spatial resolution, the coeval atmospheric CO2, and the continental biome distribution. We found that accounting for the climatic role of the continental vegetation dynamics (albedo change, water cycle and surface roughness modulations) strongly affects the reconstructed geological climate. Indeed the calculated partial pressure of atmospheric CO2 over the Mesozoic is twice the value calculated when assuming a uniform constant vegetation. This increase in CO2 is triggered by a global cooling of the continents, itself triggered by a general increase in continental albedo owing to the development of desertic surfaces. This cooling reduces the CO2 consumption through silicate weathering, and hence results in a compensating increase in the atmospheric CO2 pressure. This study demonstrates that the impact of land plants on climate and hence on atmospheric CO2 is as important as their geochemical effect through the enhancement of chemical weathering of the continental surface. Our GEOCLIM-LPJ simulations also define a climatic baseline for the Mesozoic, around which exceptionally cool and warm events can be identified.

Last glacial vegetation of northern Eurasia

In order to investigate the potential role of vegetation changes in megafaunal extinctions during the later part of the last glacial stage and early Holocene (42–10 ka BP), the palaeovegetation of northern Eurasia and Alaska was simulated using the LPJ-GUESS dynamic vegetation model. Palaeoclimatic driving data were derived from simulations made for 22 time slices using the Hadley Centre Unified Model. Modelled annual net primary productivity (aNPP) of a series of plant functional types (PFTs) is mapped for selected time slices and summarised for major geographical regions for all time slices. Strong canonical correlations are demonstrated between model outputs and pollen data compiled for the same period and region. Simulated aNPP values, especially for tree PFTs and for a mesophilous herb PFT, provide evidence of the structure and productivity of last glacial vegetation. The mesophilous herb PFT aNPP is higher in many areas during the glacial than at present or during the early Holocene. Glacial stage vegetation, whilst open and largely treeless in much of Europe, thus had a higher capacity to support large vertebrate herbivore populations than did early Holocene vegetation. A marked and rapid decrease in aNPP of mesophilous herbs began shortly after the Last Glacial Maximum, especially in western Eurasia. This is likely implicated in extinction of several large herbivorous mammals during the latter part of the glacial stage and the transition to the Holocene.

Nature of vegetation and building morphology characteristics across a city: influence on shadow patterns and mean radiant temperatures in London

Vegetation and building morphology characteristics are investigated at 19 sites on a north-south LiDAR transect across the megacity of London. Local maxima of mean building height and building plan area density at the city centre are evident. Surprisingly, the mean vegetation height (zv3) is also found to be highest in the city centre. From the LiDAR data various morphological parameters are derived as well as shadow patterns. Continuous images of the effects of buildings and of buildings plus vegetationon sky view factor (Ψ) are derived. A general reduction of Ψ is found, indicating the importance of including vegetation when deriving Ψ in urban areas. The contribution of vegetation to the shadowing at ground level is higher during summer than in autumn. Using these 3D data the influence on urban climate and mean radiant temperature (T mrt ) is calculated with SOLWEIG. The results from these simulations highlight that vegetation can be most effective at reducing heat stress within dense urban environments in summer. The daytime average T mrt is found to be lowest in the densest urban environments due to shadowing; foremost from buildings but also from trees. It is clearly shown that this method could be used to quantify the influence of vegetation on T mrt within the urban environment. The results presented in this paper highlight a number of possible climate sensitive planning practices for urban areas at the local scale (i.e. 102- 5 × 103 m).

The influence of vegetation and building morphology on shadow patterns and mean radiant temperatures in urban areas: model development and evaluation

The solar and longwave environmental irradiance geometry (SOLWEIG) model simulates spatial variations of 3-D radiation fluxes and mean radiant temperature (T mrt) as well as shadow patterns in complex urban settings. In this paper, a new vegetation scheme is included in SOLWEIG and evaluated. The new shadow casting algorithm for complex vegetation structures makes it possible to obtain continuous images of shadow patterns and sky view factors taking both buildings and vegetation into account. For the calculation of 3-D radiation fluxes and T mrt, SOLWEIG only requires a limited number of inputs, such as global shortwave radiation, air temperature, relative humidity, geographical information (latitude, longitude and elevation) and urban geometry represented by high-resolution ground and building digital elevation models (DEM). Trees and bushes are represented by separate DEMs. The model is evaluated using 5 days of integral radiation measurements at two sites within a square surrounded by low-rise buildings and vegetation in Göteborg, Sweden (57°N). There is good agreement between modelled and observed values of T mrt, with an overall correspondence of R 2 = 0.91 (p < 0.01, RMSE = 3.1 K). A small overestimation of T mrt is found at locations shadowed by vegetation. Given this good performance a number of suggestions for future development are identified for applications which include for human comfort, building design, planning and evaluation of instrument exposure.

A comprehensive benchmarking system for evaluating global vegetation models

We present a benchmark system for global vegetation models. This system provides a quantitative evaluation of multiple simulated vegetation properties, including primary production; seasonal net ecosystem production; vegetation cover; composition and height; fire regime; and runoff. The benchmarks are derived from remotely sensed gridded datasets and site-based observations. The datasets allow comparisons of annual average conditions and seasonal and inter-annual variability, and they allow the impact of spatial and temporal biases in means and variability to be assessed separately. Specifically designed metrics quantify model performance for each process, and are compared to scores based on the temporal or spatial mean value of the observations and a "random" model produced by bootstrap resampling of the observations. The benchmark system is applied to three models: a simple light-use efficiency and water-balance model (the Simple Diagnostic Biosphere Model: SDBM), the Lund-Potsdam-Jena (LPJ) and Land Processes and eXchanges (LPX) dynamic global vegetation models (DGVMs). In general, the SDBM performs better than either of the DGVMs. It reproduces independent measurements of net primary production (NPP) but underestimates the amplitude of the observed CO2 seasonal cycle. The two DGVMs show little difference for most benchmarks (including the inter-annual variability in the growth rate and seasonal cycle of atmospheric CO2), but LPX represents burnt fraction demonstrably more accurately. Benchmarking also identified several weaknesses common to both DGVMs. The benchmarking system provides a quantitative approach for evaluating how adequately processes are represented in a model, identifying errors and biases, tracking improvements in performance through model development, and discriminating among models. Adoption of such a system would do much to improve confidence in terrestrial model predictions of climate change impacts and feedbacks.

The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model

A process-based fire regime model (SPITFIRE) has been developed, coupled with ecosystem dynamics in the LPJ Dynamic Global Vegetation Model, and used to explore fire regimes and the current impact of fire on the terrestrial carbon cycle and associated emissions of trace atmospheric constituents. The model estimates an average release of 2.24 Pg C yr−1 as CO2 from biomass burning during the 1980s and 1990s. Comparison with observed active fire counts shows that the model reproduces where fire occurs and can mimic broad geographic patterns in the peak fire season, although the predicted peak is 1–2 months late in some regions. Modelled fire season length is generally overestimated by about one month, but shows a realistic pattern of differences among biomes. Comparisons with remotely sensed burnt-area products indicate that the model reproduces broad geographic patterns of annual fractional burnt area over most regions, including the boreal forest, although interannual variability in the boreal zone is underestimated.

Global patterns of vegetation response to millennial-scale variability and rapid climate change during the last glacial period

Ninety-four sites worldwide have sufficient resolution and dating to document the impact of millennial-scale climate variability on vegetation and fire regimes during the last glacial period. Although Dansgaard–Oeschger (D–O) cycles all show a basically similar gross structure, they vary in the magnitude and the length of the warm and cool intervals. We illustrate the geographic patterns in the climate-induced changes in vegetation by comparing D–O 6, D–O 8 and D–O 19. There is a strong response to both D–O warming events and subsequent cooling, most marked in the northern extratropics. Pollen records from marine cores from the northern extratropics confirm that there is no lag between the change in climate and the vegetation response, within the limits of the dating resolution (50–100 years). However, the magnitude of the change in vegetation is regionally specific and is not a simple function of either the magnitude or the duration of the change in climate as registered in Greenland ice cores. Fire regimes also show an initial immediate response to climate changes, but during cooling intervals there is a slow recovery of biomass burning after the initial reduction, suggesting a secondary control through the recovery of vegetation productivity. In the extratropics, vegetation changes are largely determined by winter temperatures while in the tropics they are largely determined by changes in plant-available water. Tropical vegetation records show changes corresponding to Heinrich Stadials but the response to D–O warming events is less marked than in the northern extratropics. There are very few high-resolution records from the Southern Hemisphere extratropics, but these records also show both a vegetation and fire response to millennial-scale climate variability. It is not yet possible to determine unequivocally whether terrestrial records reflect the asynchroneity apparent in the ice-core records.