北亚热带落叶阔叶林土壤呼吸时间变化特征

利用LI-8100开路式土壤碳通量系统测定龙王山森林土壤呼吸速率,研究北亚热带落叶阔叶林土壤呼吸速率的日变化和季节性变化规律.结果表明:北亚热带落叶阔叶林土壤呼吸速率在12—14时达到最大,与土壤温度变化基本一致;森林土壤呼吸速率随土壤温度的季节性变化而变化,在夏季土壤呼吸速率较高,在冬季土壤呼吸速率较低;土壤呼吸速率与土壤温度间存在着明显的指数关系,土壤呼吸温度敏感系数Q₁₀为2.81.     

Productivity response of climax temperate forests to elevated temperature and carbon dioxide: a north american comparison between two global models

We assess the appropriateness of using regression- and process-based approaches for predicting biogeochemical responses of ecosystems to global change. We applied a regression-based model, the Osnabruck Model (OBM), and a process-based model, the Terrestrial Ecosystem Model (TEM), to the historical range of temperate forests in North America in a factorial experiment with three levels of temperature (+0 °C, +2 °C, and +5 °C) and two levels of CO₂ (350 ppmv and 700 ppmv) at a spatial resolution of 0.5° latitude by 0.5° longitude. For contemporary climate (+0 °C, 350 ppmv), OBM and TEM estimate the total net primary productivity (NPP) for temperate forests in North America to be 2.250 and 2.602 × 10¹⁵ g C ? yr^?1, respectively. Although the continental predictions for contemporary climate are similar, the responses of NPP to altered climates qualitatively differ; at +0 °C and 700 ppmv CO₂, OBM and TEM predict median increases in NPP of 12.5% and 2.5%, respectively. The response of NPP to elevated temperature agrees most between the models in northern areas of moist temperate forest, but disagrees in southern areas and in regions of dry temperate forest. In all regions, the response to CO₂ is qualitatively different between the models. These differences occur, in part, because TEM includes known feedbacks between temperature and ecosystem processes that affect N availability, photosynthesis, respiration, and soil moisture. Also, it may not be appropriate to extrapolate regression-based models for climatic conditions that are not now experienced by ecosystems. The results of this study suggest that the process-based approach is able to progress beyond the limitations of the regression-based approach for predicting biogeochemical responses to global change.     

Effects Of Grazing On Soil Respiration Of Leymus Chinensis Steppe

Soil respiration, canopy temperature, soil moisture, above and belowground biomass were observed in 2001, 2002, 2004 and 2005 at fenced and grazed typical Leymus chinensis steppes in Inner Mongolia. Based on soil respiration data obtained by the enclosed chamber method, diurnal and seasonal dynamics of soil respiration and their controlling factors were analyzed. The effects of grazing on diurnal and seasonal soil respirations were not significant. The diurnal patterns of soil respiration could be expressed as a one-humped curve and the lowest and highest values appearing from 1:00 to 3:00 and from 11:00 to 14:00, respectively. Canopy temperature had a strong influence on the diurnal variation of soil respiration. The rates of soil respiration rose to a seasonal maximum from the middle of June to the end of July and then gradually decreased. Soil moisture explained about 71.3% and 58.3% of the seasonal variation in soil respiration at fenced and grazed plots, respectively, and canopy temperature only 33.9% and 39.7%. Soil respiration rate, above and belowground biomass and soil moisture were significantly increased at the fenced plots compared to the grazed plots (P < 0.05), but the difference was not significant in canopy temperature. The mean soil respiration rates were 247.85 and 108.31 mgCO₂ m⁻² h⁻¹ during the whole experiment at fenced and grazed plots, respectively. Soil respiration rate was enhanced significantly at the fenced plots, which might attribute to the increasing soil moisture and biomass. The response of soil respiration rate to grazing varied among different sites and might be related to local soil moisture status.     

Surface energy, water and carbon cycle in China simulated by the Australian community land surface model (CABLE)

Through an Australia-China climate change bilateral project, we analyzed results of 51-year global offline simulations over China using the Australian community atmosphere biosphere land exchange (CABLE) model, focusing on integrated studies of its surface energy, water and carbon cycle at seasonal, interannual and longer time-scales. In addition to the similar features in surface climatology between the CABLE simulation and those derived from the global land-surface data assimilation system, comparison of surface fluxes at a CEOP reference site in northeast China also suggested that the seasonal cycles of surface evaporation and CO₂ flux are reasonably simulated by the model. We further assessed temporal variations of model soil moisture with the observed variations at a number of locations in China. Observations show a soil moisture recharge–discharge mechanism on a seasonal time scale in central-east China, with soil moisture being recharged during its summer wet season, retained in its winter due to low evaporation demand, and depleted during early spring when the land warms up. Such a seasonal cycle is shown at both 50- and 100-cm soil depths in observations while the model only shows a similar feature in its lower soil layers with its upper layer soil moisture varying tightly with rainfall seasonal cycle. In the analysis of the model carbon cycle, the net primary productivity (NPP) has similar spatial patterns as the ones derived from an ecosystem model with remote sensing. The simulated interannual variations of NPP by CABLE are consistent with the results derived from remote sensing-based and process-based studies over the period of 1981–2000. Nevertheless an upward trend from observations is not presented in the model results. The model shows a downward trend primarily due to the constant CO₂ concentration used in the experiment and a large increase of autotrophic respiration caused by an upward trend in surface temperature forcing data. Furthermore, we have compared river discharge data from the model experiments with observations in the Yangtze and Yellow River basins in China. In the Yangtze River basin, while the observed interannual variability is reasonably captured, the model significantly underestimates its river discharge, which is consist with its overestimation of evaporation in the region. In the Yellow River basin, the magnitudes of the river discharge is similar between modeled and observed but its variations are less skillfully captured as seen in the Yangtze River region.     

Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models

Worldwide, the majority of rapidly growing neighborhoods are found in the Global South. They often exhibit different building construction and development patterns than the Global North, and urban climate research in many such neighborhoods has to date been sparse. This study presents local-scale observations of net radiation (Q _* ) and sensible heat flux (Q _H ) from a lightweight low-rise neighborhood in the desert climate of Andacollo, Chile, and compares observations with results from a process-based urban energy-balance model (TUF3D) and a local-scale empirical model (LUMPS) for a 14-day period in autumn 2009. This is a unique neighborhood-climate combination in the urban energy-balance literature, and results show good agreement between observations and models for Q _* and Q _H . The unmeasured latent heat flux (Q _E ) is modeled with an updated version of TUF3D and two versions of LUMPS (a forward and inverse application). Both LUMPS implementations predict slightly higher Q _E than TUF3D, which may indicate a bias in LUMPS parameters towards mid-latitude, non-desert climates. Overall, the energy balance is dominated by sensible and storage heat fluxes with mean daytime Bowen ratios of 2.57 (observed Q _H /LUMPS Q _E )–3.46 (TUF3D). Storage heat flux (ΔQ _S ) is modeled with TUF3D, the empirical objective hysteresis model (OHM), and the inverse LUMPS implementation. Agreement between models is generally good; the OHM-predicted diurnal cycle deviates somewhat relative to the other two models, likely because OHM coefficients are not specified for the roof and wall construction materials found in this neighborhood. New facet-scale and local-scale OHM coefficients are developed based on modeled ΔQ _S and observed Q _* . Coefficients in the empirical models OHM and LUMPS are derived from observations in primarily non-desert climates in European/North American neighborhoods and must be updated as measurements in lightweight low-rise (and other) neighborhoods in various climates become available.     

Effect of surface layer thickness on simultaneous transport of heat and water in a bare soil and its implications for land surface schemes

Abstract

A physically‐based multi‐layer numerical model is developed to determine the coupled transport of heat and water in the soil and in the soil‐atmosphere boundary layer. Using inputs of standard weather data and initial soil conditions the model is capable of predicting the surface energy balance components as well as water content and temperature profiles in the soil. It is used to predict these variables for a bare silt loam soil under two tillage treatments, viz. culti‐packed and left loose after disc‐harrowing, and the predicted results are compared with measurements. Very good agreement between the model predictions and measured evaporation and heat fluxes and soil water and temperatures for a ten‐day period shows that the model is capable of simulating the coupled transport of soil heat and soil water and their transfer across the soil surface‐atmosphere interface adequately.

Model predictions were compared with those of CLASS (Canadian Land Surface Scheme). It is shown that CLASS, version 2.6, provides good estimates of evaporation and hence the latent heat flux density, Q_E, under wetter soil conditions, but overestimates Q_E at moderately wet soil conditions and underestimates it under dry soil conditions. Under dry to moderately wet soil conditions the calculation of evaporation from bare soil is very sensitive to the thickness of the top layer particularly as the thickness approaches 10 cm.     

Ensemble Square Root Filter Assimilation of Near-Surface Soil Moisture and Reference-Level Observations into a Coupled Land Surface-Boundary Layer Model

The potential for using the ensemble square root filter data assimilation technique to estimate soil moisture profiles, surface heat fluxes, and the state of the planetary boundary layer （PBL） is explored. An observing system simulation experiment is designed to mimic the assimilation of near-surface soil moisture observations （θo ） and in-situ measurements of 2-m temperature （To ）, 2-m specific humidity （Qo ）, and 10-m horizontal winds [Vo =（Uo , Vo ）]. The background forecasts are generated by a one-dimensional coupled land surface-boundary layer model （CLS-BLM） with soil, surface-layer and PBL parameterization schemes similar to those used in the Weather Research and Forecasting （WRF） model. Soil moisture, surface heat fluxes, and the state of the PBL evolve on different characteristic timescales, so the minimum assimilation time intervals required for skillful estimates of each target component are different. Correct estimates of the soil moisture profile are obtained effectively when a 6-h update time interval is used, while skillful estimates of surface fluxes and the PBL state require more frequent updates. The CLS-BLM requires a shorter assimilation time interval to correctly estimate the soil moisture profile than previously indicated by experiments using an off-line land surface model （LSM）. Results from assimilating different subsets of observations show that θo makes a larger contribution to soil moisture estimates, while To , θo , and Vo are more important for estimates of surface heat fluxes and the PBL state. It is therefore necessary to combine these variables to accurately estimate the states of both the land surface and the PBL. Experimentation with different prescribed observational errors shows that the assimilation system is more sensitive to increases in observational errors than to reductions in observational errors.     

土壤湿度和土壤温度模拟中的参数敏感性分析和优化

使用一种复杂洗牌算法 (SCE-UA, Shuffled Complex Evolution Algorithm) 对Noah陆面模式中的参数进行敏感性分析和优化,其中水文参数采取直接优化和优化土壤成份的形式,侧重于研究两种水文参数给出方法对土壤湿度和土壤温度模拟的敏感性。结果表明:将土壤湿度和土壤温度作为判据,模式中水文参数敏感性最高,水文参数对土壤湿度的敏感性要高于对土壤温度的敏感性。表层土壤湿度作为判据对土壤水文参数优化后,可以改善土壤湿度和土壤温度的模拟,加入深层土壤湿度同时作为判据后,优化使土壤温度的模拟变差。当土壤成份作为优化的参数,表层和深层土壤湿度作为判据,优化能够同时改善土壤湿度和土壤温度的模拟。单独使用土壤温度作为判据不能达到优化水文参数的目的。将土壤成份作为优化的参数后,土壤湿度和土壤温度的多判据优化效果最好,且减少不敏感参数的个数后对优化结果的影响总体不大。基于以上结果,将土壤成份作为优化水文参数的方法能够更好的考虑不同水文参数之间的约束关系,优化后的水文参数具有很好的一致性,优化效果较直接优化水文参数更好。     

Respiration of Recently-Fixed Plant Carbon Dominates Mid-Winter Ecosystem CO2 Production in Sub-Arctic Heath Tundra

Arctic ecosystems could provide a substantial positive feedback to global climate change if warming stimulates below-ground CO₂ release by enhancing decomposition of bulk soil organic matter reserves.Ecosystem respiration during winter is important in this context because CO₂ release from snow-covered tundra soils is a substantial component of annual net carbon (C) balance, and because global climate models predict that the most rapid rises in regional air temperature will occur in the Arctic during winter. In this manipulative field study, the relative contributions of plant and bulk soil organic matter C pools to ecosystem CO₂ production in mid-winter were investigated. We measured CO₂ efflux rates in Swedish sub-arctic heath tundra from control plots and from plots that had been clipped in the previous growing season to disrupt plant activity. Respiration derived from recently-fixed plant C (i.e., plant respiration, and respiration associated with rhizosphere exudates and decomposition of fresh litter) was the principal source of CO₂ efflux, while respiration associated with decomposition of bulk soil organic matter was low, and appeared relatively insensitive to temperature. These results suggest that warmer mid-winter temperatures in the Arctic may have a much greater impact on the cycling of recently-fixed, plant-associated C pools than on the depletion of tundra bulk soil C reserves, and consequently that there is a low potential for significant initial feedbacks from arctic ecosystems to climate change during mid-winter.     

Precipitation drives interannual variation in summer soil respiration in a Mediterranean-climate, mixed-conifer forest

Predictions of future climate change rely on models of how both environmental conditions and disturbance impact carbon cycling at various temporal and spatial scales. Few multi-year studies, however, have examined how carbon efflux is affected by the interaction of disturbance and interannual climate variation. We measured daytime soil respiration (R _s) over five summers (June–September) in a Sierra Nevada mixed-conifer forest on undisturbed plots and plots manipulated with thinning, burning and their combination. We compared mean summer R _s by year with seasonal precipitation. On undisturbed plots we found that winter precipitation (PPT_w) explained between 77–96% of interannual variability in summer R _s. In contrast, spring and summer precipitation had no significant effect on summer R _s. PPT_w is an important influence on summer R _s in the Sierra Nevada because over 80% of annual precipitation falls as snow between October and April, thus greatly influencing the soil water conditions during the following growing season. Thinning and burning disrupted the relationship between PPT_w and R_s, possibly because of significant increases in soil moisture and temperature as tree density and canopy cover decreased. Our findings suggest that R _s in some moisture-limited ecosystems may be significantly influenced by annual snowpack and that management practices which reduce tree densities and soil moisture stress may offset, at least temporarily, the effect of predicted decreases in Sierran snowpack on R _s.     

Sensitivity of an ecosystem model to hydrology and temperature

We tested the sensitivity of a dynamic ecosystem model (LPJ-GUESS) to the representation of soil moisture and soil temperature and to uncertainties in the prediction of precipitation and air temperature. We linked the ecosystem model with an advanced hydrological model (JULES) and used its soil moisture and soil temperature as input into the ecosystem model. We analysed these sensitivities along a latitudinal gradient in northern Russia. Differences in soil temperature and soil moisture had only little influence on the vegetation carbon fluxes, whereas the soil carbon fluxes were very sensitive to the JULES soil estimations. The sensitivity changed with latitude, showing stronger influence in the more northern grid cell. The sensitivity of modelled responses of both soil carbon fluxes and vegetation carbon fluxes to uncertainties in soil temperature were high, as both soil and vegetation carbon fluxes were strongly impacted. In contrast, uncertainties in the estimation of the amount of precipitation had little influence on the soil or vegetation carbon fluxes. The high sensitivity of soil respiration to soil temperature and moisture suggests that we should strive for a better understanding and representation of soil processes in ecosystem models to improve the reliability of predictions of future ecosystem changes.     

Impacts of Sea Surface Temperature on the Interannual Variability of Winter Haze Days in Guangdong Province

The impact of sea surface temperature (SST) on winter haze in Guangdong province (WHDGD) was analyzed on the interannual scale. It was pointed out that the northern Indian Ocean and the northwest Pacific SST play a leading role in the variation of WHDGD. Cold (warm) SST anomalies over the northern Indian Ocean and the Northwest Pacific stimulate the eastward propagation of cold (warm) Kelvin waves through the Gill forced response, causing Ekman convergence (divergence) in the western Pacific, inducing abnormal cyclonic (anticyclonic) circulation. It excites the positive (negative) Western Pacific teleconnection pattern (WP), which results in the temperature and the precipitation decrease (increase) in Guangdong and forms the meteorological variables conditions that are conducive (not conducive) to the formation of haze. ENSO has an asymmetric influence on WHDGD. In El Ni?o (La Ni?a) winters, there are strong (weak) coordinated variations between the northern Indian Ocean, the northwest Pacific, and the eastern Pacific, which stimulate the negative (positive) phase of WP teleconnection. In El Ni?o winters, the enhanced moisture is attributed to the joint effects of the horizontal advection from the surrounding ocean, vertical advection from the moisture convergence, and the increased atmospheric apparent moisture sink (Q2) from soil evaporation. The weakening of the atmospheric apparent heat source (Q1) in the upper layer is not conducive to the formation of inversion stratification. In contrast, in La Ni?a winters, the reduced moisture is attributed to the reduced upward water vapor transport and Q2 loss. Due to the Q1 increase in the upper layer, the temperature inversion forms and suppresses the diffusion of haze.     

Estimating net radiation at surface using artificial neural networks: a new approach

This study describes the results of artificial neural network (ANN) models to estimate net radiation (R _n), at surface. Three ANN models were developed based on meteorological data such as wind velocity and direction, surface and air temperature, relative humidity, and soil moisture and temperature. A comparison has been made between the R _n estimates provided by the neural models and two linear models (LM) that need solar incoming shortwave radiation measurements as input parameter. Both ANN and LM results were tested against in situ measured R _n. For the LM ones, the estimations showed a root mean square error (RMSE) between 34.10 and 39.48?W?m^?2 and correlation coefficient (R ²) between 0.96 and 0.97 considering both the developing and the testing phases of calculations. The estimates obtained by the ANN models showed RMSEs between 6.54 and 48.75?W?m^?2 and R ² between 0.92 and 0.98 considering both the training and the testing phases. The ANN estimates are shown to be similar or even better, in some cases, than those given by the LMs. According to the authors?? knowledge, the use of ANNs to estimate R _n has not been discussed earlier, and based on the results obtained, it represents a formidable potential tool for R _n prediction using commonly measured meteorological parameters.     

A model of the ground surface temperature for micrometeorological analysis

Micrometeorological models at various scales require ground surface temperature, which may not always be measured in sufficient spatial or temporal detail. There is thus a need for a model that can calculate the surface temperature using only widely available weather data, thermal properties of the ground, and surface properties. The vegetated/permeable surface energy balance (VP-SEB) model introduced here requires no a priori knowledge of soil temperature or moisture at any depth. It combines a two-layer characterization of the soil column following the heat conservation law with a sinusoidal function to estimate deep soil temperature, and a simplified procedure for calculating moisture content. A physically based solution is used for each of the energy balance components allowing VP-SEB to be highly portable. VP-SEB was tested using field data measuring bare loess desert soil in dry weather and following rain events. Modeled hourly surface temperature correlated well with the measured data (r ² = 0.95 for a whole year), with a root-mean-square error of 2.77 K. The model was used to generate input for a pedestrian thermal comfort study using the Index of Thermal Stress (ITS). The simulation shows that the thermal stress on a pedestrian standing in the sun on a fully paved surface, which may be over 500 W on a warm summer day, may be as much as 100 W lower on a grass surface exposed to the same meteorological conditions.     

Variability of energy fluxes in relation to the net-radiation of urban and suburban areas: a case study

This paper addresses the relation between the net-radiation (Q ^*) and the ground heat flux (Q _G), the energy stored in the soil ( $\Updelta Q_{\rm S}$ ), and the residual of the energy partition (R = Q ^* ? Q _H  ? Q _E ) of urban and suburban areas of Oklahoma City, USA. These three forms of energy were observed or estimated from observations taken during Joint Urban 2003 Campaign. The database includes net-radiation, soil temperature, ground heat flux, and turbulent fluxes. In most cases the estimates of the energy stored in the soil were obtained by assuming roughly a certain type of soil and an effective soil depth. From the residuals it seems to be possible to distinguish the urban boundary layer from the suburban boundary layer when plotted as a function of net-radiation. Hysteresis coefficients were computed for fits of net-radiation against R, $\Updelta Q_{\rm S}$ and Q _G. In particular, the hysteresis patterns show that Q ^* vs. R represents clearer urban areas or suburban areas under the influence of an urban “plume”. On the other hand, hysteresis curves obtained from $\Updelta Q_{\rm S}$ or Q _G account for better the ground composition. A possible consequence is that the land use of urban areas could be roughly inferred from curve shapes such as Q ^* vs. R, or Q ^* versus another input variable representing the storage term. The objective is to show the variability of the subsurface-related energy fluxes across an urban area using these three different quantities and also to show that $\Updelta Q_{\rm S}, \,Q_{\rm G}$ , or R (and their corresponding hysteresis curves) are likely to be quantitatively different, which have not been clearly stated in the literature.     

1998年夏季HUBEX/GAME期间热量和水汽收支(英)

By using the high-resolution GAME reanalysis data, the heat and moisture budgets during the period of HUBEX/GAME in the summer of 1998 are calculated for exploring the thermodynamic features of Meiyu over the Changjiang-Huaihe (CH) valley. During the CH Meiyu period, an intensive vertically-integrated heat source and moisture sink are predominant over the heavy rainfall area of the CH valley, accompanied by strong upward motion at 500 hPa. The heat and moisture budgets show that the main diabatic heating component is condensation latent heat released by rainfall. As residual terms, the evaporation and sensible heating are relatively small. Based on the vertical distribution of the heat source and moisture sink, the nature of the rainfall is mixed, in which the convective rainfall is dominant with a considerable percentage of continuous stratiform rainfall. There are similar time evolutions of the main physical parameters(〈Q1〉,〈Q2〉,and vertical motion ω at 500 hPa).The time variations of〈Q1〉and〈Q2〉are in phase with those of -ω500, and have their main peaks within the CH Meiyu period. This shows the influence of the heat source on the dynamic structure of the atmosphere. The wavelet analyses of those time series display similar multiple timescale characteristics. During the CH Meiyu period, both the synoptic scale(～6 days) and mesoscale (～2 days and ～12 hours) increase obviously and cause heavy rainfall as well as the appearances of the maxima of the main physical parameters. Among them, the mesoscale systems are the main factors.     

An Analytical Model for the Distribution of CO2 Sources and Sinks, Fluxes, and Mean Concentration Within the Roughness Sub-Layer

A one-dimensional analytical model that predicts foliage CO₂ uptake rates, turbulent fluxes, and mean concentration throughout the roughness sub-layer (RSL), a layer that extends from the ground surface up to 5h, where h is canopy height, is proposed. The model combines the mean continuity equation for CO₂ with first-order closure principles for turbulent fluxes and simplified physiological and radiative transfer schemes for foliage uptake. This combination results in a second-order ordinary differential equation in which soil respiration (R) and CO₂ concentration well above the RSL are imposed as lower and upper boundary conditions, respectively. An inverse version of the model was tested against datasets from two contrasting ecosystems: a tropical forest (h = 40m) and a managed irrigated rice canopy (h = 0.7m), with good agreement noted between modelled and measured mean CO₂ concentration profiles within the entire RSL. Sensitivity analysis on the model parameters revealed a plausible scaling regime between them and a dimensionless parameter defined by the ratio between external (R) and internal (stomatal conductance) characteristics controlling the CO₂ exchange process. The model can be used to infer the thickness of the RSL for CO₂ exchange, the inequality in zero-plane displacement between CO₂ and momentum, and its consequences on modelled CO₂ fluxes. A simplified version of the solution is well suited for being incorporated into large-scale climate models. Furthermore, the model framework here can be used to a priori estimate relative contributions from the soil surface and the atmosphere to canopy-air CO₂ concentration, thereby making it synergetic to stable isotopes studies.     

The climatological characteristics of photosynthetically active radiation in arid and semi-arid regions of China

Photosynthetically active radiation (Q _p ) is a key variable in models of net primary productivity and carbon cycle modelling. The relationship between broadband global solar radiation (R _s) and Q _p is investigated using 6?years of radiation data collected at 9 sites in arid and semi-arid regions of China. The dependence of Q _p /R _S on aerosol optical depth (AOD) and water vapour content are also discussed. A simple and efficient all-weather empirically derived model is developed to estimate Q _p from R _s. The annual average daily Q _p in arid and semi-arid areas is 29.9?±?11.7 and 27.3?±?10.1?mol?m^-2 d^-1, respectively. The highest value (31.9?±?11.3?mol?m^-2 d^-1) appears at Linze in the arid area. The lowest value (24.3?±?9.7?mol?m^-2 d^-1) appears at Ansai in the semi-arid area. The results show that the monthly variation of the Q _p /R _s ratio ranges from 1.69?±?0.19?mol?MJ^-1 in Aksu to 1.91?±?0.08?mol?MJ^-1 in Fukang. There is a small decreasing trend of the ratio of Q _p to R _s (PAR fraction) in arid and semi-arid regions because of the recent increase in fine aerosols. A simple and efficient empirically model suit for all-weather condition was developed to estimate Q _p from R _s. The slope a and intercept b of the regression line between estimated and measured values is close to 1 and zero, respectively. The application of the model to data collected from different locations also results in reasonable estimates of Q _p .     

Seasonal patterns of soil respiration in three types of communities along grass-desert shrub transition in Inner Mongolia,China

The seasonal dynamics of soil respiration in steppe (S. bungeana), desert shrub (A. ordosica), and shrub-perennial (A. ordosica + C. komarovii) communities were investigated during the growth season (May to October) in 2006; their environmental driving factors were also analyzed. In the three communities, soil respiration showed similar characteristics in their growth seasons, with peak respiration values in July and August owing to suitable temperature and soil moisture conditions during this period. Meanwhile, changes in soil respiration were greatly influenced by temperatures and surface soil moistures. Soil water content at a depth of 0 to 10 cm was identified as the key environmental factor affecting the variation in soil respiration in the steppe. In contrast, in desert shrub and shrub-perennial communities, the dynamics of soil respiration was significantly influenced by air temperature. Similarly, the various responses of soil respiration to environmental factors may be attributed to the different soil textures and distribution patterns of plant roots. In desert ecosystems, precipitation results in soil respiration pulses. Soil carbon dioxide (CO₂) effluxes greatly increased after rainfall rewetting in all of the ecosystems under study. However, the precipitation pulse effect differed across the ecosystem. We propose that this may be a result of a reverse effect from the soil texture.     

Satellite Monitoring of the Surface Water and Energy Budget in the Central Tibetan Plateau

The water and energy cycle in the Tibetan Plateau is an important component of Monsoon Asia and the global energy and water cycle. Using data at a CEOP （Coordinated Enhanced Observing Period）-Tibet site, this study presents a first-order evaluation on the skill of weather forecasting from GCMs and satellites in producing precipitation and radiation estimates. The satellite data, together with the satellite leaf area index, are then integrated into a land data assimilation system （LDAS-UT） to estimate the soil moisture and surface energy budget on the Plateau. The system directly assimilates the satellite microwave brightness temperature, which is strongly affected by soil moisture but not by cloud layers, into a simple biosphere model. A major feature of this system is a dual-pass assimilation technique, which can auto-calibrate model parameters in one pass and estimate the soil moisture and energy budget in the other pass. The system outputs, including soil moisture, surface temperature, surface energy partition, and the Bowen ratio, are compared with observations, land surface models, the Global Land Data Assimilation System, and four general circulation models. The results show that this satellite data-based system has a high potential for a reliable estimation of the regional surface energy budget on the Plateau.