Votre recherche

Abstract To determine the influence of forest structures on runoff characteristics, the hydrological effects of Chinese fir plantations were studied by analysing runoff patterns at different growth and development stages (stand age classes I to V) from 1984 to 2004 at the Huitong Ecosystem Research Station, Central South University of Forestry and Technology, Hunan Province, Central South China. Results for two small experimental Chinese fir watersheds showed different peak values for surface runoff amount and coefficients at different ages, with lowest values in age classes I and V and highest values in age classes II and III. However, both underground and total runoff coefficients decreased with increasing age class. Total runoff coefficient was about twice as high in age class I (30·8%) as that in age class V (15·8%). Higher underground and total runoff coefficients were found in young forests. This was mainly attributed to soil disturbance due to human management practices such as site ploughing. Results indicate that Chinese fir plantations play a significant role in regulating water distribution in the watershed. Useful information is provided on the effects of forest management practices on hydrological processes in forest plantations. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract The present work introduces a new and useful tool to quantify the lateral boundary forcing of a regional climate model (RCM). This tool, an aging tracer, computes the time the air parcels spend inside the limited-area domain of an RCM. The aging tracers are initialized to zero when the air parcels enter the domain and grow older during their migrations through the domain with each time step in the integration of the model. This technique was employed in a 10-member ensemble of 10-yr (1980–89) simulations with the Canadian RCM on a large domain covering North America. The residency time is treated and archived as the other simulated meteorological variables, therefore allowing computation of its climate diagnostics. These diagnostics show that the domain-averaged residency time is shorter in winter than in summer as a result of the faster winter atmospheric circulation. The residency time decreases with increasing height above the surface because of the faster atmospheric circulation at high levels dominated by the jet stream. Within the domain, the residency time increases from west to east according to the transportation of the aging tracer with the westerly general atmospheric circulation. A linear relation is found between the spatial distribution of the internal variability—computed with the variance between the ensemble members—and residency time. This relation indicates that the residency time can be used as a quantitative indicator to estimate the level of control exerted by the lateral boundary conditions on the RCM simulations.

Within the framework of the European project ENSEMBLES (ensembles‐based predictions of climate changes and their impacts) we explore the systematic bias in simulated monthly mean temperature and precipitation for an ensemble of thirteen regional climate models (RCMs). The models have been forced with the European Centre for Medium Range Weather Forecasting Reanalysis (ERA40) and are compared to a new high resolution gridded observational data set. We find that each model has a distinct systematic bias relating both temperature and precipitation bias to the observed mean. By excluding the twenty‐five percent warmest and wettest months, respectively, we find that a derived second‐order fit from the remaining months can be used to estimate the values of the excluded months. We demonstrate that the common assumption of bias cancellation (invariance) in climate change projections can have significant limitations when temperatures in the warmest months exceed 4–6 °C above present day conditions.

Leaf δ 13 C is an indicator of water‐use efficiency and provides useful information on the carbon and water balance of plants over longer periods. Variation in leaf δ 13 C between or within species is determined by plant physiological characteristics and environmental factors. We hypothesized that variation in leaf δ 13 C values among dominant species reflected ecosystem patterns controlled by large‐scale environmental gradients, and that within‐species variation indicates plant adaptability to environmental conditions. To test these hypotheses, we collected leaves of dominant species from six ecosystems across a horizontal vegetation transect on the Tibetan Plateau, as well as leaves of Kobresia pygmaea (herbaceous) throughout its distribution and leaves of two coniferous tree species ( Picea crassifolia, Abies fabri ) along an elevation gradient throughout their distribution in the Qilian Mountains and Gongga Mountains, respectively. Leaf δ 13 C of dominant species in the six ecosystems differed significantly, with values for evergreen coniferous<evergreen broadleaved tree<alpine shrub<sedges∼graminoid<xeromorphs. Leaf δ 13 C values of the dominant species and of K. pygmaea were negatively correlated with annual precipitation along a water gradient, but leaf δ 13 C of A. fabri was not significantly correlated with precipitation in habitats without water‐stress. This confirms that variation of δ 13 C between or within species reflects plant responses to environmental conditions. Leaf δ 13 C of the dominant species also reflected water patterns on the Tibetan Plateau, providing evidence that precipitation plays a primary role in controlling ecosystem changes from southeast to northwest on the Tibetan Plateau.

The knowledge of tropical palaeoclimates is crucial for understanding global climate change, because it is a test bench for general circulation models that are ultimately used to predict future global warming. A longstanding issue concerning the last glacial maximum in the tropics is the discrepancy between the decrease in sea-surface temperatures reconstructed from marine proxies and the high-elevation decrease in land temperatures estimated from indicators of treeline elevation. In this study, an improved inverse vegetation modeling approach is used to quantitatively reconstruct palaeoclimate and to estimate the effects of different factors (temperature, precipitation, and atmospheric CO 2 concentration) on changes in treeline elevation based on a set of pollen data covering an altitudinal range from 100 to 3,140 m above sea level in Africa. We show that lowering of the African treeline during the last glacial maximum was primarily triggered by regional drying, especially at upper elevations, and was amplified by decreases in atmospheric CO 2 concentration and perhaps temperature. This contrasts with scenarios for the Holocene and future climates, in which the increase in treeline elevation will be dominated by temperature. Our results suggest that previous temperature changes inferred from tropical treeline shifts may have been overestimated for low-CO 2 glacial periods, because the limiting factors that control changes in treeline elevation differ between glacial and interglacial periods.

Abstract. The various precipitation types formed within winter storms (such as snow, wet snow and freezing rain) often lead to very hazardous weather conditions. These types of precipitation often occur during the passage of a warm front as a warm air mass ascends over a cold air mass. To address this issue further, we used a one-dimensional kinematic cloud model to simulate this gentle ascent (≤10 cm/s) of warm air. The initial temperature profile has an above 0°C inversion, a lower subfreezing layer, and precipitation falls from above the temperature inversion. The cloud model is coupled to a double-moment microphysics scheme that simulates the production of various types of winter precipitation. The results are compared with those from a previous study carried out in still air. Based on the temporal evolution of surface precipitation, snow reaches the surface significantly faster than in still air whereas other precipitation types including freezing rain and ice pellets have a shorter duration. Overall, even weak background vertical ascent has an important impact on the precipitation reaching the surface, the time of the elimination of the melting layer, and also the evolution of the lower subfreezing layer.