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87
Effects of temperature and precipitation variability on snowpack trends in the western United States
- J. Climate
, 1175
"... Recent studies have shown substantial declines in snow water equivalent (SWE) over much of the western United States in the last half century, as well as trends toward earlier spring snowmelt and peak spring streamflows. These trends are influenced both by interannual and decadal-scale climate varia ..."
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Cited by 71 (5 self)
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Recent studies have shown substantial declines in snow water equivalent (SWE) over much of the western United States in the last half century, as well as trends toward earlier spring snowmelt and peak spring streamflows. These trends are influenced both by interannual and decadal-scale climate variability, and also by temperature trends at longer time scales that are generally consistent with observations of global warming over the twentieth century. In this study, the linear trends in 1 April SWE over the western United States are examined, as simulated by the Variable Infiltration Capacity hydrologic model implemented at 1/8 ° latitude–longitude spatial resolution, and driven by a carefully quality controlled gridded daily pre-cipitation and temperature dataset for the period 1915–2003. The long simulations of snowpack are used as surrogates for observations and are the basis for an analysis of regional trends in snowpack over the western United States and southern British Columbia, Canada. By isolating the trends due to temperature and precipitation in separate simulations, the influence of temperature and precipitation variability on the overall trends in SWE is evaluated. Downward trends in 1 April SWE over the western United States from 1916 to 2003 and 1947 to 2003, and for a time series constructed using two warm Pacific decadal oscillation (PDO) epochs concatenated together, are shown to be primarily due to widespread warming. These tem-
Simulating the response of natural ecosystems and their fire regimes to climatic variability in Alaska
, 2005
"... Abstract: The dynamic global vegetation model MC1 was used to examine climate, fire, and ecosystems interactions in Alaska under historical (1922–1996) and future (1997–2100) climate conditions. Projections show that by the end of the 21st century, 75%–90 % of the area simulated as tundra in 1922 is ..."
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Cited by 27 (3 self)
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Abstract: The dynamic global vegetation model MC1 was used to examine climate, fire, and ecosystems interactions in Alaska under historical (1922–1996) and future (1997–2100) climate conditions. Projections show that by the end of the 21st century, 75%–90 % of the area simulated as tundra in 1922 is replaced by boreal and temperate forest. From 1922 to 1996, simulation results show a loss of about 9 g C·m–2·year–1 from fire emissions and 360 000 ha burned each year. During the same period 61 % of the C gained (1.7 Pg C) is lost to fires (1 Pg C). Under future climate change scenarios, fire emissions increase to 11–12 g C·m–2·year–1 and the area burned increases to 411 000 – 481 000 ha·year–1. The carbon gain between 2025 and 2099 is projected at 0.5 Pg C under the warmer CGCM1 climate change scenario and 3.2 Pg C under HADCM2SUL. The loss to fires under CGCM1 is thus greater than the carbon gained in those 75 years, while under HADCM2SUL it represents only about 40 % of the carbon gained. Despite increases in fire losses, the model simulates an increase in carbon gains during the 21st century until its last decade, when, under both climate change scenarios, Alaska becomes a net carbon source. Résumé: Le modèle de végétation dynamique adapté à l’échelle globale MC1 a été utilisé pour étudier les interactions entre le climat, les feux et les écosystèmes sous des conditions climatiques passées (1922–1996) et futures (1997–2100) en Alaska. Les projections montrent que 75 % à 90 % de la superficie de la toundra simulée en 1922 sera remplacée par une forêt boréale ou tempérée vers la fin du 21e siècle. Selon les résultats de la simulation, de 1922 à 1996, les feux
Combining LiDAR estimates of aboveground biomass and Landsat estimates of stand age for spatially extensive validation of modelled forest productivity. Remote Sensing of Environment.
, 2005
"... Abstract Extensive estimates of forest productivity are required to understand the relationships between shifting land use, changing climate and carbon storage and fluxes. Aboveground net primary production of wood (NPP Aw ) is a major component of total NPP and of net ecosystem production (NEP). R ..."
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Cited by 16 (2 self)
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Abstract Extensive estimates of forest productivity are required to understand the relationships between shifting land use, changing climate and carbon storage and fluxes. Aboveground net primary production of wood (NPP Aw ) is a major component of total NPP and of net ecosystem production (NEP). Remote sensing of NPP and NPP Aw is generally based on light use efficiency or process-based biogeochemistry models. However, validating these large area flux estimates remains a major challenge. In this study we develop an independent approach to estimating NPP Aw , based on stand age and biomass, that could be implemented over a large area and used in validation efforts. Stand age is first mapped by iterative unsupervised classification of a multi-temporal sequence of images from a passive optical sensor (e.g. Landsat TM). Stand age is then cross-tabulated with estimates of stand height and aboveground biomass from lidar remote sensing. NPP Aw is then calculated as the average increment in lidar-estimated biomass over the time period determined using change detection. In western Oregon, productivity estimates made using this method compared well with forest inventory estimates and were significantly different than estimates from a spatially distributed biogeochemistry model. The generality of the relationship between lidar-based canopy characteristics and stand biomass means that this approach could potentially be widely applicable to landscapes with stand replacing disturbance regimes, notably in regions where forest inventories are not routinely maintained. D
Twentieth-century trends in runoff, evapotranspiration, and soil moisture in the Western United States
- J. Climate
, 2007
"... A physically based hydrology model is used to produce time series for the period 1916–2003 of evapo-transpiration (ET), runoff, and soil moisture (SM) over the western United States from which long-term trends are evaluated. The results show that trends in ET in spring and summer are determined prim ..."
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Cited by 15 (1 self)
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A physically based hydrology model is used to produce time series for the period 1916–2003 of evapo-transpiration (ET), runoff, and soil moisture (SM) over the western United States from which long-term trends are evaluated. The results show that trends in ET in spring and summer are determined primarily by trends in precipitation and snowmelt that determine water availability. From April to June, ET trends are mostly positive due primarily to earlier snowmelt and earlier emergence of snow-free ground, and second-arily to increasing trends in spring precipitation. From July to September trends in ET are more strongly influenced by precipitation trends, with the exception of areas (most notably California) that receive little summer precipitation and have experienced large changes in snowmelt timing. Trends in the seasonal timing of ET are modest, but during the period 1947–2003 when temperature trends are large, they reflect a shift of ET from midsummer to early summer and late spring. As in other studies, it is found that runoff is occurring earlier in spring, a trend that is related primarily to increasing temperature, and is most apparent during 1947–2003. Trends in the annual runoff ratio, a variable critical to western water management, are determined primarily by trends in cool season precipitation, rather than changes in the timing of runoff or ET. It was found that the signature of temperature-related trends in runoff and SM is strongly keyed to
DAYCENT National-scale simulations of nitrous oxide emissions from cropped soils in the United States
- Journal of Environmental Quality
, 2006
"... Until recently, Intergovernmental Panel on Climate Change (IPCC) emission factor methodology, based on simple empirical rela-tionships, has been used to estimate carbon (C) and nitrogen (N) fluxes for regional and national inventories. However, the 2005 USEPA greenhouse gas inventory includes estima ..."
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Cited by 13 (0 self)
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Until recently, Intergovernmental Panel on Climate Change (IPCC) emission factor methodology, based on simple empirical rela-tionships, has been used to estimate carbon (C) and nitrogen (N) fluxes for regional and national inventories. However, the 2005 USEPA greenhouse gas inventory includes estimates of N2O emis-sions from cultivated soils derived from simulations using DAYCENT, a process-based biogeochemical model. DAYCENT simulated major U.S. crops at county-level resolution and IPCC emission factor methodology was used to estimate emissions for the approximately 14 % of cropped land not simulated by DAYCENT. The methodology used to combine DAYCENT simulations and IPCC methodology to estimate direct and indirect N2O emissions is described in detail. Nitrous oxide emissions from simulations of presettlement native vegetation were subtracted from cropped soil N2O to isolate an-thropogenic emissions. Meteorological data required to drive DAY-CENTwere acquired from DAYMET, an algorithm that uses weather station data and accounts for topography to predict daily temperature and precipitation at 1-km2 resolution. Soils data were acquired from the State Soil Geographic Database (STATSGO). Weather data and dominant soil texture class that lie closest to the geographical center of the largest cluster of cropped land in each county were used to drive DAYCENT. Land management information was implemented at the agricultural–economic region level, as defined by the Agricultural Sector Model. Maps of model-simulated county-level crop yields were compared with yields estimated by the USDA for quality control. Combining results from DAYCENT simulations of major crops and IPCC methodology for remaining cropland yielded estimates of ap-proximately 109 and approximately 70 Tg CO2 equivalents for direct and indirect, respectively, mean annual anthropogenic N2O emissions for 1990–2003. AGRICULTURAL SOILS are responsible for the majorityof anthropogenic nitrous oxide (N2O) emissions (Mosier and Kroeze, 2000). Nitrous oxide is an im-portant greenhouse gas (GHG) because it has approx-imately 300 times the global warming potential of CO2 on a mass basis (IPCC, 2001), and it also influences
E.: Monitoring forest carbon sequestration with remote sensing and carbon cycle modelling, Environ
- Management
"... ABSTRACT / Sources and sinks of carbon associated with forests depend strongly on the management regime and spa-tial patterns in potential productivity. Satellite remote sensing can provide spatially explicit information on land cover, stand-age class, and harvesting. Carbon-cycle process models cou ..."
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Cited by 12 (1 self)
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ABSTRACT / Sources and sinks of carbon associated with forests depend strongly on the management regime and spa-tial patterns in potential productivity. Satellite remote sensing can provide spatially explicit information on land cover, stand-age class, and harvesting. Carbon-cycle process models cou-pled to regional climate databases can provide information on potential rates of production and related rates of decomposi-tion. The integration of remote sensing and modeling thus produces spatially explicit information on carbon storage and flux. This integrated approach was employed to compare car-bon flux for the period 1992–1997 over two 165-km2 areas in western Oregon. The Coast Range study area was predomi-nately private land managed for timber production, whereas the West Cascades study area was predominantly public land that was less productive but experienced little harvesting in
Improving estimation of hourly daily and monthly solar radiation by importing global data sets.
- Agric. Forest Meteorol.,
, 2006
"... Abstract Surface solar radiation is an important parameter in hydrological models and crop yield models. This study developed a model to estimate solar radiation from sunshine duration. The model is more accurate and more general than traditional Å ngström-Prescott models. It can explicitly account ..."
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Cited by 10 (3 self)
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Abstract Surface solar radiation is an important parameter in hydrological models and crop yield models. This study developed a model to estimate solar radiation from sunshine duration. The model is more accurate and more general than traditional Å ngström-Prescott models. It can explicitly account for radiative extinction processes in the atmosphere. Moreover, global data sets that describe the spatial and temporal distribution of ozone thickness and Å ngström turbidity were introduced in the model to enhance its universal reliability and applicability. The model was calibrated in lowland and humid sites and validated at a number of sites in various climate and elevation regions. The new model shows overall better performances than three Å ngström-Prescott models. Because this model follows the simple form of the Å ngström-Prescott model, and its inputs (sunshine duration, air temperature, and relative humidity) are accessible from routine surface meteorological observations, it can be easily applied to hydrological and agricultural studies. The source code and the auxiliary data of the model are available from the authors upon request. #
PHYSIOLOGY IN FOREST MODELS: HISTORY AND THE FUTURE
, 2003
"... Empirical models are standard tools in forest management. They provide quantitative information for management and planning that is accurate within the limits of sampling and measurement accuracy, but they are generally site-specific and cannot simulate the results of changing conditions. Mechanisti ..."
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Cited by 10 (0 self)
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Empirical models are standard tools in forest management. They provide quantitative information for management and planning that is accurate within the limits of sampling and measurement accuracy, but they are generally site-specific and cannot simulate the results of changing conditions. Mechanistic, or process-based models, based on the physiological processes that govern tree growth can, in principle, provide estimates of the potential productivity of sites for which no mensuration data exist, calculate realized growth and evaluate the effects of actions such as fertilisation or thinning, or the impact of pests and diseases on productivity. It should also be possible to use these models to evaluate the probable effects of climate change on forest growth. However, most process-based models contain too many poorly known parameters and their projections are not as reliable in practice as those of empirical models. In addition they have not, up to now, produced outputs of interest to those concerned with forest management. The reasons for this state of affairs are considered and a brief historical survey of some of the physiological research that, over the last 30 years, has produced the knowledge and information needed to produce useful, practical process-based forest models, is presented. The survey deals with light interception, photosynthesis, stomatal
Modeling snow accumulation and ablation processes in forested environments
- Water Resources Research
, 2009
"... Abstract. The effects of forest canopies on snow accumulation and ab-lation processes can be very important for the hydrology of mid- and north-latitude basins. A mass and energy balance model for snow accumulation and ablation processes in forested environments was developed utilizing exten-sive me ..."
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Cited by 7 (1 self)
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Abstract. The effects of forest canopies on snow accumulation and ab-lation processes can be very important for the hydrology of mid- and north-latitude basins. A mass and energy balance model for snow accumulation and ablation processes in forested environments was developed utilizing exten-sive measurements of snow interception and release in a maritime climate mountainous site in Oregon. The model, which was calibrated against one year of weighing lysimeter data and tested at the same site against measure-ments from the next year was able to reproduce the SWE evolution through-out both winters beneath the canopy as well as the nearby clearing, with cor-relations ranging from 0.87 to 0.99. Additionally, the model was evaluated using measurements from the BOREAS field campaign in Canada, without any calibration to test the model robustness in a boreal climate given the effects of micro-meteorology on snow interception. Simulated SWE was rel-atively close to the observations for the forested sites, while simulated snow depth was underestimated during the accumulation period at the forested sites but simulated fairly accurately during ablation.
Assessment of some global solar radiation parameterizations.
- Journal of Atmospheric and Terrestrial Physics
, 2002
"... Abstract In spite of their practicability, most classical models are not versatile but rather restrictive in their application. Consequently, their applicability for a particular location depends largely on validation against actual measurements. Global solar radiation parameterizations have been e ..."
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Cited by 6 (0 self)
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Abstract In spite of their practicability, most classical models are not versatile but rather restrictive in their application. Consequently, their applicability for a particular location depends largely on validation against actual measurements. Global solar radiation parameterizations have been evaluated in this study for a lowland and a mountain site. Tested models were broadly categorised as cloud-based (Kasten) and sunshine-based ( Angstr om-Prescott, Garg and Garg, Sivkov). Data sets utilised for the evaluation extended from 1991 to 1994. Adjustable parameters in the models were determined. Observed monthly mean values of solar radiation G and those estimated using Kasten model agreed within 2.5% for the lowland site and 13% for the mountain site. Root mean square errors of estimated hourly values of G using Kasten model appreciated signiÿcantly with fractional cloud cover N (particularly for N ¿ 4 octals). For the study sites as well as other locations examined here, Angstr om-Prescott coe cients did not show a distinctive trend with respect to season, geographical co-ordinate or altitude. Monthly mean values of G estimated using Angstr om-Prescott model agreed with observation within 2.5% for the lowland site and 3.4% for the mountain site. The e ect of air mass, latitude and water vapour terms on the Angstr om-Prescott relation has also been investigated. In general, Angstr om-Prescott as well as Garg and Garg models yielded the least RMSE (¡ 0:047) for the study sites and are thus recommended for estimating G for an arbitrary location.
