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.

Synergistic feedbacks between ocean and vegetation on mid- and high-latitude climates during the mid-Holocene

Simulations with the IPSL atmosphere–ocean model asynchronously coupled with the BIOME1 vegetation model show the impact of ocean and vegetation feedbacks, and their synergy, on mid- and high-latitude (>40°N) climate in response to orbitally-induced changes in mid-Holocene insolation. The atmospheric response to orbital forcing produces a +1.2 °C warming over the continents in summer and a cooling during the rest of the year. Ocean feedback reinforces the cooling in spring but counteracts the autumn and winter cooling. Vegetation feedback produces warming in all seasons, with largest changes (+1 °C) in spring. Synergy between ocean and vegetation feedbacks leads to further warming, which can be as large as the independent impact of these feedbacks. The combination of these effects causes the high northern latitudes to be warmer throughout the year in the ocean–atmosphere-vegetation simulation. Simulated vegetation changes resulting from this year-round warming are consistent with observed mid-Holocene vegetation patterns. Feedbacks also impact on precipitation. The atmospheric response to orbital-forcing reduces precipitation throughout the year; the most marked changes occur in the mid-latitudes in summer. Ocean feedback reduces aridity during autumn, winter and spring, but does not affect summer precipitation. Vegetation feedback increases spring precipitation but amplifies summer drying. Synergy between the feedbacks increases precipitation in autumn, winter and spring, and reduces precipitation in summer. The combined changes amplify the seasonal contrast in precipitation in the ocean–atmosphere-vegetation simulation. Enhanced summer drought produces an unrealistically large expansion of temperate grasslands, particularly in mid-latitude Eurasia.

Climate and CO2 controls on global vegetation distribution at the last glacial maximum: analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations.

The global vegetation response to climate and atmospheric CO2 changes between the last glacial maximum and recent times is examined using an equilibrium vegetation model (BIOME4), driven by output from 17 climate simulations from the Palaeoclimate Modelling Intercomparison Project. Features common to all of the simulations include expansion of treeless vegetation in high northern latitudes; southward displacement and fragmentation of boreal and temperate forests; and expansion of drought-tolerant biomes in the tropics. These features are broadly consistent with pollen-based reconstructions of vegetation distribution at the last glacial maximum. Glacial vegetation in high latitudes reflects cold and dry conditions due to the low CO2 concentration and the presence of large continental ice sheets. The extent of drought-tolerant vegetation in tropical and subtropical latitudes reflects a generally drier low-latitude climate. Comparisons of the observations with BIOME4 simulations, with and without consideration of the direct physiological effect of CO2 concentration on C3 photosynthesis, suggest an important additional role of low CO2 concentration in restricting the extent of forests, especially in the tropics. Global forest cover was overestimated by all models when climate change alone was used to drive BIOME4, and estimated more accurately when physiological effects of CO2 concentration were included. This result suggests that both CO2 effects and climate effects were important in determining glacial-interglacial changes in vegetation. More realistic simulations of glacial vegetation and climate will need to take into account the feedback effects of these structural and physiological changes on the climate.

Impact of vegetation and preferential source areas on global dust aerosol: results from a model study

[1] We present a model of the dust cycle that successfully predicts dust emissions as determined by land surface properties, monthly vegetation and snow cover, and 6-hourly surface wind speeds for the years 1982–1993. The model takes account of the role of dry lake beds as preferential source areas for dust emission. The occurrence of these preferential sources is determined by a water routing and storage model. The dust source scheme also explicitly takes into account the role of vegetation type as well as monthly vegetation cover. Dust transport is computed using assimilated winds for the years 1987–1990. Deposition of dust occurs through dry and wet deposition, where subcloud scavenging is calculated using assimilated precipitation fields. Comparison of simulated patterns of atmospheric dust loading with the Total Ozone Mapping Spectrometer satellite absorbing aerosol index shows that the model produces realistic results from daily to interannual timescales. The magnitude of dust deposition agrees well with sediment flux data from marine sites. Emission of submicron dust from preferential source areas are required for the computation of a realistic dust optical thickness. Sensitivity studies show that Asian dust source strengths are particularly sensitive to the seasonality of vegetation cover.

Modern pollen samples from alpine vegetation on the Tibetan Plateau.

1  A set of 316 modern surface pollen samples, sampling all the alpine vegetation types that occur on the Tibetan Plateau, has been compiled and analysed. Between 82 and 92% of the pollen present in these samples is derived from only 28 major taxa. These 28 taxa include examples of both tree (AP) and herb (NAP) pollen types. 2  Most of the modern surface pollen samples accurately reflect the composition of the modern vegetation in the sampling region. However, airborne dust-trap pollen samples do not provide a reliable assessment of the modern vegetation. Dust-trap samples contain much higher percentages of tree pollen than non-dust-trap samples, and many of the taxa present are exotic. In the extremely windy environments of the Tibetan Plateau, contamination of dust-trap samples by long-distance transport of exotic pollen is a serious problem. 3  The most characteristic vegetation types present on the Tibetan Plateau are alpine meadows, steppe and desert. Non-arboreal pollen (NAP) therefore dominates the pollen samples in most regions. Percentages of arboreal pollen (AP) are high in samples from the southern and eastern Tibetan Plateau, where alpine forests are an important component of the vegetation. The relative importance of forest and non-forest vegetation across the Plateau clearly follows climatic gradients: forests occur on the southern and eastern margins of the Plateau, supported by the penetration of moisture-bearing airmasses associated with the Indian and Pacific summer monsoons; open, treeless vegetation is dominant in the interior and northern margins of the Plateau, far from these moisture sources. 4  The different types of non-forest vegetation are characterized by different modern pollen assemblages. Thus, alpine deserts are characterized by high percentages of Chenopodiaceae and Artemisia, with Ephedra and Nitraria. Alpine meadows are characterized by high percentages of Cyperaceae and Artemisia, with Ranunculaceae and Polygonaceae. Alpine steppe is characterized by high abundances of Artemisia, with Compositae, Cruciferae and Chenopodiaceae. Although Artemisia is a common component of all non-forest vegetation types on the Tibetan Plateau, the presence of other taxa makes it possible to discriminate between the different vegetation types. 5  The good agreement between modern vegetation and modern surface pollen samples across the Tibetan Plateau provides a measure of the reliability of using pollen data to reconstruct past vegetation patterns in non-forested areas.