Publications (18) View all
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Article: Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis
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ABSTRACT: Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 2000–2006) from 10 forested sites within the AmeriFlux and Fluxnet-Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over-prediction of gross ecosystem photosynthesis by +160 ± 145 g C m−2 yr−1 during the spring transition period and +75 ± 130 g C m−2 yr−1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under-predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere–atmosphere feedbacks and interactions in coupled global climate models.Global Change Biology 01/2012; 18(2):566 - 584. · 6.86 Impact Factor -
Article: Reconstruction of false spring occurrences over the southeastern United States, 1901–2007: an increasing risk of spring freeze damage?
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ABSTRACT: Near-record warmth over much of the United States during March 2007 promoted early growth of crops and vegetation. A widespread arctic air outbreak followed in early April, resulting in extensive agricultural losses over much of the south-central and southeastern US. This 'false spring' event also resulted in widespread damage to newly grown tissues of native deciduous forest species, shown by previous researchers to have had measurable effects on the terrestrial carbon cycle. The current study reconstructed the historical occurrence of false springs over most of the southeastern quarter of the conterminous US (32–39°N; 75–98°W) from 1901 to 2007 using daily maximum and minimum temperature records from 176 stations in the Global Historical Climatology Network database, and enhanced vegetation index (EVI) data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. A false spring index was derived that examined the timing of the start of the growing season (SGS), or leaf emergence, relative to the timing of a potentially damaging last hard freeze (minimum temperature ≤ − 2.2 °C). SGS was modeled for the domain by combining EVI data with ground-based temperature 'degree day' calculations reflecting the rate of springtime warming. No significant area-wide, long-term SGS trend was found; however, over much of a contiguous region stretching from Mississippi eastward to the Carolinas, the timing of the last hard freeze was found to occur significantly later, this change occurring along with increased frequency of false springs. Earlier last hard freeze dates and decreased frequency of false springs were found over much of the northwestern part of the study region, including Arkansas and southern Missouri.Environmental Research Letters 05/2011; 6(2):024015. · 3.63 Impact Factor -
Article: A note on the top-down and bottom-up gradient functions over a forested site
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ABSTRACT: The dimensionless bottom-up and top-down gradient functions in the convective boundary layer (CBL) are evaluated utilizing long-term well-calibrated carbon dioxide mixing ratio and flux measurements from multiple levels of a 447-m tall tower over a forested area in northern Wisconsin, USA. The estimated bottom-up and top-down functions are qualitatively consistent with those from large-eddy simulation (LES) results and theoretical expectations. Newly fitted gradient functions are proposed based on observations for this forested site. The integrated bottom-up function over the lowest 4% of the CBL depth estimated from the tower data is about five times larger than that from LES results for a ‘with-canopy’ case, and is smaller than that from LES results for a ‘no-canopy’ case by a factor of 0.7. We discuss the uncertainty in the evaluated gradient functions due to stability, wind direction, and uncertainty in the entrainment flux and show that while all of these have a significant impact on the gradient functions, none can explain the differences between the modelled and observed functions. The effects of canopy features and atmospheric stability may need to be considered in the gradient function relations.Boundary-Layer Meteorology 07/2007; 124(2):305-314. · 1.74 Impact Factor -
Article: A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes
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ABSTRACT: Measured surface-atmosphere fluxes of energy (sensible heat, H, and latent heat, LE) and CO2 (FCO2) represent the “true” flux plus or minus potential random and systematic measurement errors. Here, we use data from seven sites in the AmeriFlux network, including five forested sites (two of which include “tall tower” instrumentation), one grassland site, and one agricultural site, to conduct a cross-site analysis of random flux error. Quantification of this uncertainty is a prerequisite to model-data synthesis (data assimilation) and for defining confidence intervals on annual sums of net ecosystem exchange or making statistically valid comparisons between measurements and model predictions.We differenced paired observations (separated by exactly 24 h, under similar environmental conditions) to infer the characteristics of the random error in measured fluxes. Random flux error more closely follows a double-exponential (Laplace), rather than a normal (Gaussian), distribution, and increase as a linear function of the magnitude of the flux for all three scalar fluxes. Across sites, variation in the random error follows consistent and robust patterns in relation to environmental variables. For example, seasonal differences in the random error for H are small, in contrast to both LE and FCO2, for which the random errors are roughly three-fold larger at the peak of the growing season compared to the dormant season. Random errors also generally scale with Rn (H and LE) and PPFD (FCO2). For FCO2 (but not H or LE), the random error decreases with increasing wind speed. Data from two sites suggest that FCO2 random error may be slightly smaller when a closed-path, rather than open-path, gas analyzer is used.Agricultural and Forest Meteorology. 01/2006; -
Article: Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations.
IEEE T. Geoscience and Remote Sensing. 01/2006; 44:1908-1925.
