K. T. Paw U

University of California, Davis, Davis, California, United States

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Publications (81)167.5 Total impact

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    ABSTRACT: Ramp-like shapes in the turbulent scalar trace are the signature of coherent structures, and their characteristics (i.e., amplitude and duration) are resolved via a structure-function model for use in the surface renewal flux calculation. The potential for surface renewal to provide inexpensive sensible heat flux measurements has not been fully realized because this method has required calibration against eddy covariance or other more expensive flux measurement techniques. The calibration factor alpha is ideally 0.5, but a broad range of values have been reported in the surface renewal literature. Although it has been hypothesized that the sensor size, and hence sensor frequency response characteristics, influence alpha, no effort has been previously made to compensate the thermocouple signal in surface renewal measurements. We evaluate methods for compensating the frequency response of a thermocouple in the time domain and the frequency domain, and we present a novel method for compensation in the lag domain (i.e., compensating the structure function directly). We evaluated the compensation procedure as it affects the resolution of ramp characteristics at both the smallest and the second smallest scales of ramp-like turbulent shapes. The surface renewal sensible heat flux estimates from the compensated robust thermocouples (76 μm diameter wire) agree well with the estimates from the compensated fragile thermocouples (13 μm diameter). Using both the data collected for the present experiment and a meta-analysis of data in the surface renewal literature, we correct the surface renewal estimates for thermocouple frequency response characteristics to obtain alpha calibrations that converge to close to the predicted value of 0.5. We conclude that the frequency response characteristics of the thermocouple are the prevailing influence on the alpha calibrations reported in the literature.
    Agricultural and Forest Meteorology 06/2014; s 189–190:36–47. · 3.89 Impact Factor
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    ABSTRACT: Approaches on modeling urban environment have often focused on specific components of cities complexity. In some simple models, cities have been simply described as a single-layer area showing aerodynamic and thermal variations from the surroundings. Multi-layer models have been used to describe vertical interactions within a multi-layered paradigm. These allow key features of turbulent exchange of physical quantities between levels, as well as vertically differentiated source and sink terms within the urban canopy. Another improvement is to describe anthropogenic fluxes of heat, later differentiating it between sensible and latent heat. However, usually heat fluxes from buildings have not also included traffic fluxes, and human-related fluxes have generally been ignored. Many of the building energy models used were usually run on a climatological basis, neglecting the actual daily and hourly local meteorological conditions. Furthermore, many models have ignored carbon dioxide fluxes , due both to the difficult modeling of anthropogenic emissions and to the lack of an adequate soil-canopy-atmosphere exchange model. To overcome these limitations, the present work proposes an urbanized version of the UC Davis developed numerical SVAT model ACASA (Advanced Canopy-Atmosphere-Soil Algorithm). This model, initially created for vegetated canopies, has widely-tested and simulates CO2, moisture, radiation and sensible heat fluxes in natural environments. Its layered structure of soil and atmosphere permits a realistic third-order turbulent exchange of physical quantities. It can be run stand-alone (in-situ simulation on a footprint centered on a Eddy Covariance tower) or coupled interactively with the atmospheric model WRF (Weather Research and Forecasting) for regional scale simulation. The model ACASA has now been modified to include an improved, detailed urban scheme that accurately reproduces radiative and aerodynamic properties. A few basic anthropogenic fluxes (namely carbon dioxide from traffic and human respiration, and sensible heat from building heating) have been included, showing a discrete capability to reproduce observations. An additional, more complete set of urban parameterizations has been introduced, making the model able to simulate building and natural canopy in an integrated mode. No anthropogenic contributions are neglected, with the incorporation of fluxes of CO2, moisture and sensible heat from buildings, traffic and human population. Within the vertical ACASA structure, each of these source/sink contributions is assigned the proper vertical level, then the associated scalars and vector quantities are turbulently diffused between layers. The present work simulates fluxes in a complex urban environment, starting from meteorological data and footprint morphology evaluation. These serve as inputs for the ACASA model that predicts fluxes of carbon dioxide, water vapour, and sensible heat. Predictions are then validated against experimental eddy-covariance data, focusing on impact of the newly introduced anthropogenic fluxes parameterization. Model performance improvements are objectively assessed through evaluation of widely accepted statistical parameters. Results are further compared with existing scientific literature.
    31st Conference on Agricultural and Forest Meteorology/2nd Conference on Atmospheric Biogeosciences 2014 American Meteorological Society; 05/2014
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    03/2014; 15(2).
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    ABSTRACT: Ramp features in the turbulent scalar field are associated with turbulent coherent structures, which dominate energy and mass fluxes in the atmospheric surface layer. Although finer scale ramp-like shapes embedded within larger scale ramp-like shapes can readily be perceived in turbulent scalar traces, their presence has largely been overlooked in the literature. We demonstrate the signature of more than one ramp scale in structure functions of the turbulent scalar field measured from above bare ground and two types of short plant canopies, using structure-function time lags ranging in scale from isotropic to larger than the characteristic coherent structures. Spectral analysis of structure functions was used to characterize different scales of turbulent structures. By expanding structure function analysis to include two ramp scales, we characterized the intermittency, duration, and surface renewal flux contribution of the smallest (i.e., Scale One) and the dominant (i.e., Scale Two) coherent structure scales. The frequencies of the coherent structure scales increase with mean wind shear, implying that both Scale One and Scale Two are shear-driven. The embedded Scale One turbulent structure scale is ineffectual in the surface-layer energy and mass transport process. The new method reported here for obtaining surface renewal-based scalar exchange works well over bare ground and short canopies under unstable conditions, effectively eliminating the α calibration for these conditions and forming the foundation for analysis over taller and more complex surfaces.
    Boundary-Layer Meteorology 10/2012; 145(1). · 2.29 Impact Factor
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    Nature Geoscience 07/2012; 5:551-556. · 11.67 Impact Factor
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    Global Biogeochemical Cycles 04/2012; · 4.68 Impact Factor
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    ABSTRACT: Since urban population is growing fast and urban areas are recognized as the major source of CO2 emissions, more attention has being dedicated to the topic of urban sustainability and its connection with the climate. Urban flows of energy, water and carbon have an important impact on climate change and their quantification is pivotal in the city design and management. Large effort has been devoted to quantitative estimates of the urban metabolism components, and several advanced models have been developed and used at different spatial and temporal scales for this purpose. However, it is necessary to develop suitable tools and indicators to effectively support urban planning and management with the goal of achieving a more sustainable metabolism in the urban environment. In this study, the multilayer model ACASA (Advanced Canopy-Atmosphere-Soil Algorithm) was chosen to simulate the exchanges of heat, water vapour and CO2 within and above urban canopy. After several calibration and evaluation tests over natural and agricultural ecosystems, the model was recently modified for application in urban and peri-urban areas. New equations to account for the anthropogenic contribution to heat exchange and carbon production, as well as key parameterizations of leaf-facet scale interactions to separate both biogenic and anthropogenic flux sources and sinks, were added to test changes in land use or urban planning strategies. The analysis was based on the evaluation of the ACASA model performance in estimating urban metabolism components at local scale. Simulated sensible heat, latent heat, and carbon fluxes were compared with in situ Eddy Covariance measurements collected in the city centre of Florence (Italy). Statistical analysis was performed to test the model accuracy and reliability. Model sensitivity to soil types and increased population density values was conducted to investigate the potential use of ACASA for evaluating the impact of planning alternative scenarios. In this contest, an in progress application of ACASA for estimating carbon exchanges alternative scenarios is represented by its integration in a software framework composed by: (i) a Cellular Automata model to simulate the urban land-use dynamics; (ii) a transportation model, able to estimate the variation of the transportation network load; (iii) the ACASA model, and (iv) the mesoscale weather model WRF for the estimation of the relevant urban metabolism components at regional scale. The CA module is able to produce future land use maps, which represent a spatial distribution of the aggregate land-use demand consistent with the main rules governing the functioning of an urban system. Such future land use maps, together with the street network including the current traffic data, are used by the transportation module for estimating future traffic data coherent with the assumed land uses trends. All these information are then used by the coupled model WRF-ACASA for estimating future maps of CO2 fluxes in the urban area under consideration, allowing to estimate the impact of future planning strategies in reducing C emissions. The in-progress application of this system to the city of Florence is presented here.
    04/2012;
  • L. Xu, R. D. Pyles, K. T. Paw U
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    ABSTRACT: Vegetation is an important element of the climate system due to its influence on atmospheric processes through precipitation interception, moisture exchange, surface roughness, energy conversion, and momentum and gas exchanges (Monteith and Unsworth, 1990). Oversimplifying the vegetation representation can lead to the lost of vital information that can impact climate. This is especially true for regional scale studies where the influence of vegetation increases with increasing spatial resolution. This study examines the impact of vegetation canopy structure and leaf area index on surface fluxes over California. High spatial resolution satellite MODIS LAI data are used in the medium complexity WRF-NOAH and high complexity WRF-ACASA coupled models to simulate the interactions between the land surface and the atmosphere. ACASA (Advanced Canopy-Atmosphere-Soil Algorithm) is a multilayer land surface model with interactive biophysical, meteorological and full surface hydrological processes that allows micro-environmental variables such as air and canopy temperature, wind speed and humidity to vary vertically. Water vapor, energy and momentum fluxes between the atmosphere and the land surface are calculated in ACASA through third order closure turbulence equations and complex canopy physiology, such as 10 leaf classes for better light and precipitation interception. It allows counter-gradient transport that low-order turbulence closure models are unable to simulate. Therefore, the coupled model WRF-ACASA can take full advantage of high resolution MODIS LAI data to better represent the land surface layer. The model simulations with and without MODIS LAI data for both WRF-NOAH and WRF-ACASA are compared with the surface observations to study the impact of a more realistic LAI representation in the models on surface fluxes.
    AGU Fall Meeting Abstracts. 12/2011;
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    ABSTRACT: The measurement of ecosystem-scale energy and mass fluxes between the planetary surface and the atmosphere is crucial for understanding geophysical processes. Surface renewal is a flux measurement technique based on analyzing the turbulent coherent structures that interact with the surface. It is a less expensive technique because it does not require fast-response velocity measurements, but only a fast-response scalar measurement. It is therefore also a useful tool for the study of the global cycling of trace gases. Currently, surface renewal requires calibration against another flux measurement technique, such as eddy covariance, to account for the linear bias of its measurements. We present two advances in the surface renewal theory and methodology that bring the technique closer to becoming a fully independent flux measurement method. The first advance develops the theory of turbulent coherent structure transport associated with the different scales of coherent structures. A novel method was developed for identifying the scalar change rate within structures at different scales. Our results suggest that for canopies less than one meter in height, the second smallest coherent structure scale dominates the energy and mass flux process. Using the method for resolving the scalar exchange rate of the second smallest coherent structure scale, calibration is unnecessary for surface renewal measurements over short canopies. This study forms the foundation for analysis over more complex surfaces. The second advance is a sensor frequency response correction for measuring the sensible heat flux via surface renewal. Inexpensive fine-wire thermocouples are frequently used to record high frequency temperature data in the surface renewal technique. The sensible heat flux is used in conjunction with net radiation and ground heat flux measurements to determine the latent heat flux as the energy balance residual. The robust thermocouples commonly used in field experiments underestimate the sensible heat flux, yielding results that are less than 50% of the sensible heat flux measured with finer sensors. We present the methodology for correcting the thermocouple signal to avoid underestimating the heat flux at both the smallest and the second smallest coherent structure scale.
    AGU Fall Meeting Abstracts. 12/2011;
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    ABSTRACT: A crucial point in urban sustainable development is to evaluate the impact that future planning alternatives has on the main factors affecting the citizens liveableness, as the development of the urban heat island or the carbon emissions level. Recent advances in bio-physical sciences have led to new methods and models to estimate energy, water, and carbon fluxes. Also, several studies have addressed urban metabolism issues, but few have integrated the development of numerical tools and methodologies for the analysis of fluxes between a city and its environment with its validation and application in terms of future development alternatives. Over the past several years and most recently within the European Project "BRIDGE", CMCC tested the ACASA (Advanced-Canopy-Atmosphere-Soil Algorithm) land-surface model over agricultural ecosystems (grapes), wild vegetation (forests and Mediterranean maquis), and urban (Florence) or mixed urban/vegetated land (Helsinki). Preliminary results show success in adapting the model to mixed urban systems in each of the main fluxes of interest. The model was improved to adapt it for urban environment, and key parameterizations of leaf-facet scale interactions permit separate accounting of both biogenic and anthropogenic flux sources and sinks, and allow for easy scenario building for simulations designed to test changes in land use or urban planning. In this way, sustainable planning strategies are proposed based on quantitative assessments of energy, water, and carbon fluxes. In this research, three planning alternatives accounting for an increase in urbanization intensity were tested by ACASA in Helsinki (Finland) for the year 2008. Helsinki is located at a high latitude and is characterized by a rapid urbanization that requires a substantial amount of energy for heating. The model behavior for the baseline and alternatives scenarios (i.e., urban classes with low, mid, and high residential intensity) during the entire year was investigated and the model results were compared with in situ Eddy Covariance energy and mass flux measurements. Model sensitivity to land use change and increased population density values was tested individually first. Then, the impact of the three urban classes was evaluated by analyzing energy and mass fluxes produced by combining soil type classes, varying from silty-clay-loam to sand and bedrock, to increased population density values, respectively. Preliminary results are shown and statistical analysis was performed in order to evaluate the model performance for each scenario. From this first analysis, it appeared that ACASA model was able to adequately reproduce the increase in urban heat island and carbon emissions related to rapid urbanization. Also, the model could be used to simulate urban fluxes at both local and regional scale (when coupled to the mesoscale model WRF) and help local administration in planning future sustainable development strategies.
    AGU Fall Meeting Abstracts. 12/2011;
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    ABSTRACT: The number of urban metabolism studies has increased in recent years, due to the important impact that energy, water and carbon exchange over urban areas have on climate change. Urban modeling is therefore crucial in the future design and management of cities. This study presents the ACASA model coupled to the Weather Research and Forecasting (WRF-ARW) mesoscale model to simulate urban fluxes at a horizontal resolution of 200 meters for urban areas of roughly 100 km^2. As part of the European Project "BRIDGE", these regional simulations were used in combination with remotely sensed data to provide constraints on the land surface types and the exchange of carbon and energy fluxes from urban centers. Surface-atmosphere exchanges of mass and energy were simulated using the Advanced Canopy Atmosphere Soil Algorithm (ACASA). ACASA is a multi-layer high-order closure model, recently modified to work over natural, agricultural as well as urban environments. In particular, improvements were made to account for the anthropogenic contribution to heat and carbon production. For two cities four climate change and four urban planning scenarios were simulated: The climate change scenarios include a base scenario (Sc0: 2008 Commit in IPCC), a medium emission scenario (Sc1: IPCC A2), a worst case emission scenario (Sce2: IPCC A1F1) and finally a best case emission scenario (Sce3: IPCC B1). The urban planning scenarios include different development scenarios such as smart growth. The two cities are a high latitude city, Helsinki (Finland) and an historic city, Florence (Italy). Helsinki is characterized by recent, rapid urbanization that requires a substantial amount of energy for heating, while Florence is representative of cities in lower latitudes, with substantial cultural heritage and a comparatively constant architectural footprint over time. In general, simulated fluxes matched the point observations well and showed consistent improvement in the energy partitioning over urban regions. We present comparisons of observed (EC) tower flux observations from the Florence (Ximeniano) site for 1-9 April, 2008 with results from two sets of high-resolution simulations: the first using dynamically-downscaled input/boundary conditions (Model-0) and the second using fully nested WRF-ACASA (Model-1). In each simulation the model physics are the same; only the WRF domain configuration differs. Preliminary results (Figure 1) indicate a degree of parity (and a slight statistical improvement), in the performances of Model-1 vs. that of Model-0 with respect to observed. Figure 1 (below) shows air temperature values from observed and both model estimates. Additional results indicate that care must be taken to configure the WRF domain, as performance appears to be sensitive to model configuration.
    AGU Fall Meeting Abstracts. 12/2011;
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    ABSTRACT: The Advanced Canopy–Atmosphere–Soil Algorithm (ACASA) model is used to predict energy, water and carbon fluxes over a Mediterranean maquis site located in North-Western Sardinia (Italy) and the model performance is evaluated. Flux simulations are compared with Eddy Covariance field measurements collected from 2004 to 2007. The site experiences a drought season during the summer months in which the vegetation becomes water stressed. Results from the months of January, April, and July are analyzed to demonstrate the model behavior in different environmental conditions. In general, simulated and observed fluxes matched when both the thermal and moisture regime are optimal. During the July water stress period the model underestimated latent heat and carbon fluxes due to a strong stress response linked to soil properties and plant physiological characteristics. The selection of values for key parameters, e.g. maximum ideal photosynthetic capacity (RUBISCO), wilting point, soil water content, and root and leaf area ratio, is crucial to obtain close agreement between simulated and observed fluxes. The model was designed so that the most sensitive parameters are measurable quantities. Using the ACASA model to predict energy and mass fluxes between the vegetation and atmosphere appears promising in this context, and it could significantly improve our ability to estimate fluxes for use in future studies.
    Agricultural and Forest Meteorology 02/2011; 151:730-745. · 3.89 Impact Factor
  • L. Xu, R. D. Pyles, K. Paw U
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    ABSTRACT: Many GCMs have projected increase in both temperature and intensity of summer droughts over California. These changes in climate conditions will have large impacts on the state's snow water storage, water budget, and overall environmental conditions in both regional and local scale. Regional climate models in the last decade have been widely used for future climate change predictions. However, many of them lack interaction with a complex land surface scheme. In this study, we introduce a new framework with a regional atmospheric model, WRF, coupled to a high complexity microscale land surface model, ACASA. Although WRF is a state-of-art regional atmospheric model with high spatial and temporal resolutions, the land surface schemes available in WRF lack intricate biogeophysic processes and do not include carbon dioxide calculations. ACASA (Advanced Canopy-Atmosphere-Soil Algorithm) is complex multilayer land surface model with interactive canopy physiology and full surface hydrological processes that allows microenvironmental variables such as air and surface temperatures, wind speed, humidity, carbon dioxide condition to vary vertically. Carbon dioxide, sensible heat, water vapor, and momentum fluxes between the atmosphere and land surface are estimated in the ACASA model through third order turbulent equations. It includes counter-gradient transport that lower order turbulent closure models are unable to simulate. Therefore, the WRF-ACASA framework can simulate the carbon dioxide, water, and energy fluxes between the terrestrial system and the atmosphere for present and future conditions. In particular, the complex physiological processes in the WRF-ACASA model allow future climate conditions (changes in temperature and CO2 concentration) to modify plant behavior and thus the WRF-ACASA framework can simulate carbon, water, and energy fluxes more accurately. This paper aims at investigating the impact of future conditions (2050s) on the vegetation behavior in terms of CO2 and water budget using WRF-ACASA coupled model. Present day conditions from year 2001 to 2005 are used to drive a transect region over Northern California, from the coastal region to the Sierra Nevada mountains. GCM outputs from year 2051 to 2055 are used to represent the future climate conditions. Results from the present and future climate simulations are compared. WRF-ACASA shows change of future climate impacts on surface temperature, snow water equivalence, planetary boundary layer height, and evapotranspiration. It also allows future carbon dioxide flux calculations on a regional scale.
    AGU Fall Meeting Abstracts. 12/2010;
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    ABSTRACT: This research focuses on the Wind Late Successional Reserve of Southern Washington where clear-cut logging over the past 100 years has created a fragmented landscape of coniferous forests that range in age from 0 to 500 years. In this study, we integrate several datasets to examine the environmental drivers of carbon exchange in this region across time and space. These sources include: (1) network of flux towers across a disturbance choronosequence, (2) MODIS Enhanced Vegetation Index, (3) aboveground net primary production (ANPP) from forest inventories, (4) and regional precipitation and air temperature measurements from the NOAA network of weather stations and PRISM reanalysis data. Net ecosystem exchange of carbon (NEE) has been measured at the Wind River Canopy Crane AmeriFlux site since 1998. The canopy crane is located in an old-growth forest composed of late seral Douglas-fir (Pseudotsuga menziesii) and western hemlock (Tsuga heterophylla). Two flux towers were erected in early seral stands to study the effects of silviculture on net ecosystem exchange. CO2 uptake at the old-growth stand is highest in the spring before bud break when air and soil temperatures and vapor pressure deficit are relatively low, and soil moisture and light levels are favorable for photosynthesis, while maximum CO2 uptake is observed two to three months later at the early seral stands and coincide with peak leaf area index. This CO2 pattern is driven by different water conserving strategies. A reduction in carbon exchange is observed at the old-growth forest when moisture becomes limiting and canopy conductance rates drop sharply after mid-morning in the summer. In contrast, inhibition in canopy conductance rates and CO2 exchange is not observed at the early seral stands until soil moisture levels become critically low at the very end of the summer. The regional MODIS data (200 km X 200 km area) from 2000-2008 show that annual variability in the Enhanced Vegetation Index (EVI) also can be linked to precipitation and temperature anomalies at the stand level and across the region. Regional EVI anomalies are strongly negatively correlated with the annual precipitation and air temperature anomalies once the MODIS pixels are carefully examined with regards to forest age. EVI data from the tower-centered pixel also correlate well with annual NEE at the AmeriFlux site and show promise for scaling sparse flux tower observations, even over old-growth forests. Lastly, permanent plots have been continuously measured in the old-growth stand since 1947 and provide long-term data on tree demographics, recruitment, growth and mortality, and show evidence of decadal variability in response to precipitation and air temperature anomalies, as well as to disturbance (e.g., a Douglas-fir beetle kill in the 1950's). We take advantage of the overlapping measurement period 1998-2004 and compare ANPP from the forest inventories to the flux tower estimates of NEE and MODIS EVI with focus on the regional environmental drivers.
    AGU Fall Meeting Abstracts. 12/2010;
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    ABSTRACT: The number of urban metabolism studies has increased in recent years, due to the important impact that energy, water and carbon exchange over urban areas have on climate change. Urban modeling is therefore crucial in the future design and management of cities. This study presents the ACASA model coupled to the Weather Research and Forecasting (WRF-ARW) mesoscale model to simulate urban fluxes at a horizontal resolution of 200 meters for urban areas of roughly 10 by 10 km. As part of the European Project ``BRIDGE'', these regional simulations were used in combination with remotely sensed data to provide constraints on the land surface types and the exchange of carbon and energy fluxes from urban centers.Surface-atmosphere exchanges of mass and energy were simulated using the Advanced Canopy Atmosphere Soil Algorithm (ACASA). ACASA is a multi-layer high-order closure model, recently modified to work over natural, agricultural as well as urban environments. In particular, improvements were made to account for the anthropogenic contribution to heat and carbon production. In order to more accurately simulate the mass and energy exchanges across larger urban regions, ACASA was coupled with a mesoscale weather model (WRF). Here we present ACASA-WRF simulations of mass and energy fluxes over over two different urban regions: a high latitude city, Helsinki (Finland) and an historic European city, Florence (Italy). Helsinki is characterized by recent, rapid urbanization that requires a substantial amount of energy for heating, while Florence is representative of cities in lower latitudes, with substantial cultural heritage, a huge tourist flow, and an architectural footprint that remains comparatively constant in time. The in-situ ACASA model was tested over the urban environment at local point scale with very promising results when validated against urban flux measurements. This study shows the application of this methodology at a regional scale with high spatial resolution for several urban centers in Europe. In general, simulated fluxes matched the point observations well and showed consistent improvement in the energy partitioning over urban regions.
    AGU Fall Meeting Abstracts. 12/2010;
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    ABSTRACT: The aim of this study was to evaluate the performance of the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) model used to predict energy, water and carbon fluxes over a Mediterranean maquis ecosystem located in North-Western Sardinia (Italy). Vegetation at the experimental site is composed by sclerophillous shrub species experiencing a drought season during the summer months. ACASA consists of an advanced scaling model from the leaf and soil level to the canopy level. The model employs a process-based interactive set of modules that include radiative transfer within the ecosystem, ecophysiological response of the vegetation to soil and atmospheric conditions, column water, snow and ice hydrology, and sophisticated interlayer turbulent transfer physics. Parameters are added to account for soil moisture stress, which is simulated with a soil water transport model. These linked models automatically yield carbon dioxide exchange and transpiration by accounting for stomatal control of evapotranspiration. Turbulent exchange between the layers and the atmosphere is described by the ACASA higher-order closure model, which allows counter-gradient transport that simpler models are unable to describe. ACASA requires (1) plant and soil characteristics, (2) 30-minute meteorological data, and (3) initial soil water content conditions. Input data came from in situ measurements or were selected from the literature when observations were unavailable. Flux simulations were compared with Eddy Covariance field measurements collected from 2004 to 2007 (more details in the abstract Spano et al.). Results are showed for three months (January, April, and July) per each year. These months are selected since they can be assumed to be representative of the site environmental conditions during the year. January represents the typical winter time conditions of the experimental site, with little downwelling solar radiation, low air temperature values, and no water limitations. April is the most representative of the spring season showing an optimal combinations of environmental conditions. In the end, July represents the drought season (high vapor pressure deficit and water stress conditions). In general, simulated and observed fluxes matched when both the thermal and moisture regime are optimal. During the July water stress period, the model underestimated latent heat and carbon fluxes due to a strong stress response linked to soil properties and plant physiological characteristics. The selection of values for key parameters, e.g. maximum ideal photosynthetic capacity (Rubisco), wilting point, soil water content, and root and leaf area ratio, is crucial to obtain close agreement between simulated and observed fluxes. The model was designed so that the most sensitive parameters are measurable quantities. Using the ACASA model to predict energy and mass fluxes between the vegetation and atmosphere appears promising in this context, and it could significantly improve our ability to estimate fluxes for use in future studies.
    AGU Fall Meeting Abstracts. 12/2010;
  • K. Paw U, L. Xu, R. D. Pyles
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    ABSTRACT: General Circulation Models have been coupled to simplified land surface models (LSMs) for the purpose of increasing their credibility in simulating future climate regimes. Nesting to the regional level is important because many impacts are viewed from local to regional scales as opposed to global scales. Unfortunately, LSM's themselves have often been simplified, and do not adequately address within canopy interactions between turbulent exchange and ecosystem/plant physiological responses. This study describes the linked WRF-ACASA model, the coupling of the NCAR regional scale model and the UCDavis higher-order turbulence closure scheme ACASA (Advanced Canopy-Atmosphere-Soil Algorithm). This LSM includes an interactive canopy physiology and micrometeorological processes that allows variables such as air and surface temperatures, wind speed, humidity, carbon dioxide condition to vary vertically. Carbon dioxide, sensible heat, water vapor, and momentum fluxes between the atmosphere and land surface are estimated in the ACASA model through third order turbulent equations. It includes counter-gradient transport that lower order turbulent closure models are unable to simulate; previous published work has shown that this feature allows superior simulation of gradients and fluxes within plant canopies. Therefore, the WRF-ACASA framework can simulate the carbon dioxide, water, and energy fluxes between the terrestrial system and the atmosphere for present and future conditions. In particular, the complex physiological processes in the WRF-ACASA model allow future climate conditions (changes in temperature and CO2 concentration) to modify plant response and thus the WRF-ACASA framework can simulate carbon, water, and energy fluxes more accurately than previous WRF-LSM frameworks. In this paper, results from several experiments are presented. Present day conditions are used to drive a transect region over Northern California, from the coastal region to the Sierra Nevada mountains, and results from WRF-ACASA and WRF-NOAH LSM are compared to observations. WRF-ACASA shows great improvements for simulations of surface temperature, snow water equivalence, planetary boundary layer height, and evapotranspiration. WRF-ACASA yields carbon dioxide flux calculation on a regional scale, which can be linked to GCM output as drivers for downscaling from global to regional scales.
    AGU Fall Meeting Abstracts. 12/2010;
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    ABSTRACT: We modeled regional carbon dioxide (CO2) fluxes based on midday mixing ratios measured in the canopy surface layer over 6 years (2002-2007) in four AmeriFlux stations. Applying an equilibrium boundary layer approach to focus on mean CO2 balance aggregated by the atmospheric boundary layer (ABL) processes, we estimated monthly average CO2 fluxes by inverting the difference between CO2 mixing ratios in the ABL and those in the free troposphere. We used a combination of NCAR/NCEP Reanalysis and ECMWF model data to estimate mean monthly rates of vertical transport between ABL and the free troposphere. Comparison between modeled net CO2 fluxes and tower-based eddy covariance NEE measurements suggests two interesting general patterns. First, modeled regional CO2 fluxes display inter- and intra-annual variations similar to the tower NEE fluxes observed in the Rannells Prairie and Wind River Forest, whereas model discrepancies were consistently found for the Harvard Forest and Howland Forest. Second, model discrepancies show distinct temporal patterns between the two northeastern U.S. forests. At the Howland Forest site, modeled CO2 fluxes showed a lag in the onset of growing-season uptake by two months behind that of tower measurements. At the Harvard Forest, modeled CO2 fluxes agreed with the timing of growing season uptake but underestimated the magnitude of observed NEE seasonal fluctuation. This modeling inconsistency among sites can be partially attributed to the likely misrepresentation of atmospheric transport and/or CO2 gradients between ABL and the free troposphere. Remote sensing-based land cover maps indicate that spatial heterogeneity in land use and cover was very likely to explain the majority of the modeling inconsistency. We suggest that the equilibrium boundary layer budget method can serve as a routine, diagnostic tool to interpret long-term NEE observations in flux networks, providing an intermediate-level analysis to complement aircraft/MODIS-based integration efforts for estimates of continental carbon budget.
    AGU Fall Meeting Abstracts. 12/2010;
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    ABSTRACT: Vegetation albedo is a critical component of the Earth's climate system, yet efforts to evaluate and improve albedo parameterizations in climate models have lagged relative to other aspects of model development. Here, we calculated growing season albedos for deciduous and evergreen forests, crops, and grasslands based on over 40 site-years of data from the AmeriFlux network and compared them with estimates presently used in the land surface formulations of a variety of climate models. Generally, the albedo estimates used in land surface models agreed well with this data compilation. However, a variety of models using fixed seasonal estimates of albedo overestimated the growing season albedo of northerly evergreen trees. In contrast, climate models that rely on a common two-stream albedo submodel provided accurate predictions of boreal needle-leaf evergreen albedo but overestimated grassland albedos. Inverse analysis showed that parameters of the two-stream model were highly correlated. Consistent with recent observations based on remotely sensed albedo, the AmeriFlux dataset demonstrated a tight linear relationship between canopy albedo and foliage nitrogen concentration (for forest vegetation: albedo=0.01+0.071%N, r2=0.91; forests, grassland, and maize: albedo=0.02+0.067%N, r2=0.80). However, this relationship saturated at the higher nitrogen concentrations displayed by soybean foliage. We developed similar relationships between a foliar parameter used in the two-stream albedo model and foliage nitrogen concentration. These nitrogen-based relationships can serve as the basis for a new approach to land surface albedo modeling that simplifies albedo estimation while providing a link to other important ecosystem processes.
    Global Change Biology 01/2010; 16(2):696 - 710. · 8.22 Impact Factor

Publication Stats

3k Citations
167.50 Total Impact Points

Institutions

  • 1989–2014
    • University of California, Davis
      • • Department of Viticulture and Enology
      • • Department of Land, Air and Water Resources
      Davis, California, United States
  • 2000–2005
    • National Oceanic and Atmospheric Administration
      • Atmospheric Turbulence and Diffusion Division
      Boulder, Colorado, United States
    • Università degli Studi della Basilicata
      Potenza, Basilicate, Italy
  • 2003
    • Institute of Occupational Medicine and Environmental Health
      Sosnovice, Silesian Voivodeship, Poland
  • 1992
    • Argonne National Laboratory
      Lemont, Illinois, United States