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Hoffman, Forrest M

Publications and source records attributed to Hoffman, Forrest M.

10 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Characterization and classification of vegetation canopy structure and distribution within the Great Smoky Mountains National Park using LiDAR

Vegetation canopy structure is a critically important habit characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape pro- vided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify and analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and to characterize and map the vegetation canopy structures for 139,859 hectares (540 sq. miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.

Clustering↗
DOE OSTI2015

Evaluations of CMIP5 simulations over cropland

Cropland is one of major sources of carbon lost to the atmosphere and directly contributes to the emissions of greenhouse gases. There is, however, large potential for cropland to reduce its carbon flux to the atmosphere and sequester soil carbon through conservative agriculture management including no-tillage, perennial and/or deep root crops, irrigation, and organic fertilization etc. But these estimations on carbon emissions and sequestrations over cropland under future climate changes and variability remain largest uncertain among all other terrestrial biomes. Global climate and earth system models are an effective tool to study the cropland responses and feedbacks to present and future climate, yet most models in the latest couple model intercomparsion project phase 5 (CMIP5), generally treat cropland similarly as grassland with tuned parameters and do not account for realistic crop phenology, physiology, and management. In this study, we will evaluate the limitations and deficiencies of the CMIP5 models without process-based crop growth models over cropland by comparing their simulations against FLUXNET observations at eight cropland sites. The results show that: (1) the observed and simulated annual cycles generally are not consistent in either phase or amplitude; (2) the MPI and IPSL model families have better skills in the annual cycles of gross primary product (GPP), net ecosystem production (NEP), and terrestrial ecosystem respiration (TER) than other models at the corn/soybean and cereal sites respectively; (3) none of the CMIP5 models successfully simulate the observed two-peak pattern in the annual cycles of sensible heat fluxes at the corn/soybean sites; (4) the simulated GPPs and NEPs of the CESM1, BCC model families and NorESM1-M are much smaller than the observations for entire year; (5) model members from same model family normally simulate similar annual cycles both in phase and magnitude, but the model members from the CESM1 model family with different atmospheric models have different annual cycles; (6) the biases both in phases and magnitudes of annual cycles for the biogeochemical variables (GPP, NEP and TER) are generally larger than those biogeophysical variables (sensible and latent heat fluxes). Because of the above limitations and deficiencies of CMIP5 simulations over cropland, it is essential to incorporate process-based crop growth models into ESMs to improve the model physics and performance over cropland.

AGRICULTURE↗
DOE OSTI2014

Causes and Implications of Persistent Atmospheric Carbon Dioxide Biases in Earth System Models

The strength of feedbacks between a changing climate and future CO2 concentrations are uncertain and difficult to predict using Earth System Models (ESMs). We analyzed emission-driven simulations--in which atmospheric CO2 levels were computed prognostically--for historical (1850-2005) and future periods (RCP 8.5 for 2006-2100) produced by 15 ESMs for the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). Comparison of ESM prognostic atmospheric CO2 over the historical period with observations indicated that ESMs, on average, had a small positive bias in predictions of contemporary atmospheric CO2. Weak ocean carbon uptake in many ESMs contributed to this bias, based on comparisons with observations of ocean and atmospheric anthropogenic carbon inventories. We found a significant linear relationship between contemporary atmospheric CO2 biases and future CO2 levels for the multi-model ensemble. We used this relationship to create a contemporary CO2 tuned model (CCTM) estimate of the atmospheric CO2 trajectory for the 21st century. The CCTM yielded CO2 estimates of 600 {plus minus} 14 ppm at 2060 and 947 {plus minus} 35 ppm at 2100, which were 21 ppm and 32 ppm below the multi-model mean during these two time periods. Using this emergent constraint approach, the likely ranges of future atmospheric CO2, CO2-induced radiative forcing, and CO2-induced temperature increases for the RCP 8.5 scenario were considerably narrowed compared to estimates from the full ESM ensemble. Our analysis provided evidence that much of the model-to-model variation in projected CO2 during the 21st century was tied to biases that existed during the observational era, and that model differences in the representation of concentration-carbon feedbacks and other slowly changing carbon cycle processes appear to be the primary driver of this variability. By improving models to more closely match the long-term time series of CO2 from Mauna Loa, our analysis suggests uncertainties in future climate projections can be reduced.

Hoffman, Forrest M↗
DOE OSTI2013

Representativeness-Based Sampling Network Design for the State of Alaska

Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. A quantitative methodology for stratifying sampling domains, informing site selection, and determining the representativeness of measurement sites and networks is described here.

Hoffman, Forrest M↗
DOE OSTI2013

Global latitudinal-asymmetric vegetation growth trends and their driving mechanisms: 1982-2009

Using a recent Leaf Area Index (LAI) dataset and the Community Land Model version 4 (CLM4), we investigate percent changes and controlling factors of global vegetation growth for the period 1982 to 2009. Over that 28-year period, both the remote-sensing estimate and model simulation show a significant increasing trend in annual vegetation growth. Latitudinal asymmetry appeared in both products, with small increases in the Southern Hemisphere (SH) and larger increases at high latitudes in the Northern Hemisphere (NH). The south-to-north asymmetric land surface warming was assessed to be the principal driver of this latitudinal asymmetry of LAI trend. Heterogeneous precipitation functioned to decrease this latitudinal LAI gradient, and considerably regulated the local LAI change. CO2 fertilization during the last three decades, was simulated to be the dominant cause for the enhanced vegetation growth. Our study, though limited by observational and modeling uncertainties, adds further insight into vegetation growth trends and environmental correlations. These validation exercises also provide new quantitative and objective metrics for evaluation of land ecosystem process models at multiple spatio-temporal scales.

Mao, Jiafu↗
DOE OSTI2012

North American Carbon Project (NACP) Regional Interim Synthesis: Terrestrial Biospheric Model Intercomparison

Understanding of carbon exchange between terrestrial ecosystems and the atmosphere can be improved through direct observations and experiments, as well as through modeling activities. Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding to much larger terrestrial regions. Although models vary in their specific goals and approaches, their central role within carbon cycle science is to provide a better understanding of the mechanisms currently controlling carbon exchange. Recently, the North American Carbon Program (NACP) organized several interim-synthesis activities to evaluate and inter-compare models and observations at local to continental scales for the years 2000 to 2005. Here, we compare the results from the TBMs collected as part of the regional and continental interim-synthesis (RCIS) activities. The primary objective of this work is to synthesize and compare the 19 participating TBMs to assess current understanding of the terrestrial carbon cycle in North America.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Photoperiodic Regulation of the Seasonal Pattern of Photosynthetic Capacity and the Implications for Carbon Cycling

Although temperature is an important driver of seasonal changes in photosynthetic physiology, photoperiod also regulates leaf activity. Climate change will extend growing seasons if temperature cues predominate, but photoperiod-controlled species will show limited responsiveness to warming. We show that photoperiod explains more seasonal variation in photosynthetic activity across 23 tree species than temperature. Although leaves remain green, photosynthetic capacity peaks just after summer solstice and declines with decreasing photoperiod, before air temperatures peak. In support of these findings, saplings grown at constant temperature but exposed to an extended photoperiod maintained high photosynthetic capacity, but photosynthetic activity declined in saplings experiencing a naturally shortening photoperiod; leaves remained equally green in both treatments. Incorporating a photoperiodic correction of photosynthetic physiology into a global-scale terrestrial carbon-cycle model significantly improves predictions of seasonal atmospheric CO{sub 2} cycling, demonstrating the benefit of such a function in coupled climate system models. Accounting for photoperiod-induced seasonality in photosynthetic parameters reduces modeled global gross primary production 2.5% ({approx}4 PgC y{sup -1}), resulting in a >3% ({approx}2 PgC y{sup -1}) decrease of net primary production. Such a correction is also needed in models estimating current carbon uptake based on remotely sensed greenness. Photoperiod-associated declines in photosynthetic capacity could limit autumn carbon gain in forests, even if warming delays leaf senescence.

54 ENVIRONMENTAL SCIENCES↗