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At least 73 records · Page 4

Automatic Responses of Crop Stocks and Policies Buffer Climate Change Effects on Crop Markets and Price Volatility

Climate change has the potential to affect crop prices and price volatility. However, the economic models used in prior assessments largely do not include known, automatic, stabilizing factors. Crop storage can stabilize prices and U.S. crop policy tends to provide support that moves opposite prices. We quantify effects of circa 2050 climate forcing on the inter-annual variability of U.S. Corn Belt corn and soybean yields using statistical crop models and climate scenarios from regional and global climate models. Climate change generally reduces mean yields and increases the inter-annual variability of yields in the Midwestern U.S. Using these yield impacts and an economic model with automatic market stabilizers, we find only modest increases in price volatility. Although individual producers and states are negatively affected by the yield reductions, the aggregate effect for all corn and soybean producer returns can be positive because of price increases. Moreover, agricultural policies based on price levels or revenue variation offset some of the impacts of market variation on farm income. Our results differ from other recent results and temper concerns that increasing climate instability necessarily translates to greater uncertainty about agricultural commodity uses, including as food and biofuels, in the near future.

54 ENVIRONMENTAL SCIENCES↗

Tropospheric Ozone as a Short-lived Chemical Climate Forcer

Tropospheric ozone is the third most important greenhouse gas according to the most recent IPCC assessment. However, tropospheric ozone is highly variable in both space and time. Ozone that is located in the vicinity of the tropopause has the greatest effect on climate forcing. Nitrogen oxides (NOx) are the most important precursors for ozone In most of the troposphere. Therefore, pollution that is lofted upward in thunderstorm updrafts or NOx produced by lightning leads to efficient ozone production in the upper troposphere, where ozone is most important climatically. Global and regional model estimates of the impact of North American pollution and lightning on ozone radiative forcing will be presented. It will be shown that in the Northern Hemisphere summer, the lightning effect on ozone radiative forcing can dominate over that of pollution, and that the radiative forcing signal from North America extends well into Europe and North Africa. An algorithm for predicting lightning flash rates and estimating lightning NOx emissions is being incorporated into the NASA GEOS-5 Chemistry and Climate Model. Changes in flash rates and emissions over an ENSO cycle and in future climates will be assessed, along with the resulting changes in upper tropospheric ozone. Other research on the production of NOx per lightning flash and its distribution in the vertical based on cloud-resolving modeling and satellite observations will be presented. Distributions of NO2 and O3 over the Middle East from the OMI instrument on NASA's Aura satellite will also be shown.

Pickering, Kenneth E.↗

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1∕8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

extreme climate index↗

Climate Ocean Modeling on Parallel Computers

Ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change. However, modeling the ocean circulation at various spatial and temporal scales is a very challenging computational task.

partition↗

Modeling Mesoscale Eddies in the North Atlantic Ocean

Ocean modeling plays an important role in understanding the current climatic conditions and predicting the future climate change. Modeling the ocean at eddy-permitting and/or eddy resolving resolutions (1/3 degree or higher) has a two-fold objective. One part is to represent the ocean as realistically as possible, because mesoscale eddies have an impact on the large-scale circulation. The second objective is to learn how to represent effects of mesoscale eddies without explicitly resolving them. This is particularly important for climate models which cannot be run at eddy-resolving resolutions because of the computational constraints. At JPL, a 1/6 degree latitude by 1/6 degree longitude with 37 vertical levels Atlantic Ocean model has been developed. The model is based on the Parallel Ocean Program (POP) developed at Los Alamos National Laboratory (LANL). Using the 256-processor Cray T3D, we have conducted a 40-year integration of this Atlantic eddy-resolving ocean model. A regional analysis demonstrate that many observed features associated with the Caribbean Sea eddies can be realistically simulated by this model. Analysis of this Atlantic eddy-resolving ocean model further suggests that these Caribbean Sea eddies are connected with eddies formed outside the Caribbean Sea at the confluence of the North Brazil Current (NBC) and the North Equatorial Countercurrent. The diagram of the model simulated surface current shows that the Caribbean eddies ultimately originate in the NBC retroflection region, traveling more than a year from the North Brazil coast through the Lesser Antilles into the Caribbean Sea and eventually into the Gulf of Mexico. Additional information is contained in the original.

Chao, Yi↗

Implications of improved representations of plant respiration in a changing climate

Land-atmosphere exchanges influence atmospheric CO 2 . Emphasis has been on describing photosynthetic CO 2 uptake, but less on respiration losses. New global datasets describe upper canopy dark respiration (R d ) and temperature dependencies. This allows characterization of baseline R d , instantaneous temperature responses and longer-term thermal acclimation effects. Here we show the global implications of these parameterisations with a global gridded land model. This model aggregates R d to whole-plant respiration R p , driven with meteorological forcings spanning uncertainty across climate change models. For preindustrial estimates, new baseline R d increases R p and especially in the tropics. Compared to new baseline, revised instantaneous response decreases R p for mid-latitudes, while acclimation lowers this for the tropics with increases elsewhere. Under global warming, new R d estimates amplify modelled respiration increases, although partially lowered by acclimation. Future measurements will refine how R d aggregates to whole-plant respiration. With this being said, our analysis suggests R p could be around 30% higher than existing estimates.

59 BASIC BIOLOGICAL SCIENCES↗

Design and test of an object-oriented GIS to map plant species in the Southern Rockies

Elevational and latitudinal shifts occur in the flora of the Rocky Mountains due to long term climate change. In order to specify which species are successfully migrating with these changes, and which are not, an object-oriented, image-based geographic information system (GIS) is being created to animate evolving ecological regimes of temperature and precipitation. Research at the Earth Data Analysis Center (EDAC) is developing a landscape model that includes the spatial, spectral and temporal domains. It is designed to visualize migratory changes in the Rocky Mountain flora, and to specify future community compositions. The object-oriented database will eventually tag each of the nearly 6000 species with a unique hue, intensity, and saturation value, so their movements can be individually traced. An associated GIS includes environmental parameters that control the distribution of each species in the landscape, and satellite imagery is used to help visualize the terrain. Polygons for the GIS are delineated as landform facets that are static in ecological time. The model manages these facets as a triangular irregular net (TIN), and their analysis assesses the gradual progression of species as they migrate through the TIN. Using an appropriate climate change model, the goal will be to stop the modeling process to assess both the rate and direction of species' change and to specify the changing community composition of each landscape facet.

Morain, Stanley A.↗

Listening to the Forest: An Artificial Neural Network‐Based Model of Carbon Uptake at Harvard Forest

Abstract The terrestrial biosphere strongly modulates atmospheric CO 2 mixing ratios, whose inexorable rise propels anthropogenic climate change. Modeling and mechanistically understanding C uptake by the terrestrial biosphere are thus of broad societal concerns. Yet despite considerable progress, scaling up point observations to landscape and larger scales continues to frustrate analyses of the anthropogenically perturbed global C cycle. While that up‐scaling is our overarching motivation, here we focus on one of its elements, modeling C uptake at a given site. We devise a novel artificial neural network (ANN)‐based model of C uptake at Harvard Forest that combines locally observed and remotely sensed variables. Most of our model predictors are those used by an established ecosystem C uptake model, the Vegetation Photosynthesis and Respiration Model (VPRM), easing comparisons. To those, we add observed cumulative antecedent precipitation and soil temperature. We find that model errors are much larger in winter, indicating that better understanding and modeling of respiration will likely discernibly improve model performance. Comparing the ANN and VPRM results reveals errors attributed to unrealistic treatment of temperature in the VPRM formulation, indicating that better representation of temperature dependencies is also likely to enhance model skill. By judiciously comparing VPRM and ANN errors we thus overcome ANNs' notoriety for concealing the mechanisms underlying their predictive skills. We demonstrate their ability to identify outstanding ecosystem science knowledge gaps and particularly fruitful corresponding model development directions, improving site specific and up‐scaling flux modeling and understanding of the climate impacts of the northern forest.

Eshel, Gidon↗

Application of Ensemble Detection and Analysis to Modeling Uncertainty in Non Stationary Process

Characterization of non stationary and nonlinear processes is a challenge in many engineering and scientific disciplines. Climate change modeling and projection, retrieving information from Doppler measurements of hydrometeors, and modeling calibration architectures and algorithms in microwave radiometers are example applications that can benefit from improvements in the modeling and analysis of non stationary processes. Analyses of measured signals have traditionally been limited to a single measurement series. Ensemble Detection is a technique whereby mixing calibrated noise produces an ensemble measurement set. The collection of ensemble data sets enables new methods for analyzing random signals and offers powerful new approaches to studying and analyzing non stationary processes. Derived information contained in the dynamic stochastic moments of a process will enable many novel applications.

Racette, Paul↗

Future Global Mortality from Changes in Air Pollution Attributable to Climate Change

Ground-level ozone and fine particulate matter (PM (sub 2.5)) are associated with premature human mortality; their future concentrations depend on changes in emissions, which dominate the near-term, and on climate change. Previous global studies of the air-quality-related health effects of future climate change used single atmospheric models. However, in related studies, mortality results differ among models. Here we use an ensemble of global chemistry-climate models to show that premature mortality from changes in air pollution attributable to climate change, under the high greenhouse gas scenario RCP (Representative Concentration Pathway) 8.5, is probably positive. We estimate 3,340 (30,300 to 47,100) ozone-related deaths in 2030, relative to 2000 climate, and 43,600 (195,000 to 237,000) in 2100 (14 percent of the increase in global ozone-related mortality). For PM (sub 2.5), we estimate 55,600 (34,300 to 164,000) deaths in 2030 and 215,000 (76,100 to 595,000) in 2100 (countering by 16 percent the global decrease in PM (sub 2.5)-related mortality). Premature mortality attributable to climate change is estimated to be positive in all regions except Africa, and is greatest in India and East Asia. Most individual models yield increased mortality from climate change, but some yield decreases, suggesting caution in interpreting results from a single model. Climate change mitigation is likely to reduce air-pollution-related mortality.

Atmohspheric chemistry↗

Towards an Open (Data) Science Analytics-Hub for Reproducible Multi-Model Climate Analysis at Scale

Open Science is key to future scientific research and promotes a deep transformation in the whole scientific research process encouraging the adoption of transparent and collaborative scientific approaches aimed at knowledge sharing. Open Science is increasingly gaining attention in the current and future research agenda worldwide. To effectively address Open Science goals, besides Open Access to results and data, it is also paramount to provide tools or environments to support the whole research process, in particular the design, execution and sharing of transparent and reproducible experiments, including data provenance (or lineage) tracking. This work introduces the Climate Analytics-Hub, a new component on top of the Earth System Grid Federation (ESGF), which joins big data approaches and parallel computing paradigms to provide an Open Science environment for reproducible multi-model climate change data analytics experiments at scale. An operational implementation has been set up at the SuperComputing Centre of the Euro- Mediterranean Center on Climate Change, with the main goal of becoming a reference Open Science hub in the climate community regarding the multi-model analysis based on the Coupled Model Intercomparison Project (CMIP).

analytics-hub↗

AmeriFlux CA-ARF Attawapiskat River Fen

This is the AmeriFlux version of the carbon flux data for the site CA-ARF Attawapiskat River Fen. Site Description - Ontario Ministry of Environment and Climate Change's Environmental Monitoring and Reporting Branch has established five carbon flux monitoring towers in Ontario’s Far North as part of its Climate Change Modelling and Monitoring program. These long term monitoring stations measure carbon exchange and a suite of soil and meteorological parameters over peatland ecosystems to better understand carbon cycling in Ontario’s Far North. Information produced by these monitoring stations will assist the province in land use planning and the development of climate change adaptation strategies.

Todd, Aaron↗

AmeriFlux CA-ARB Attawapiskat River Bog

This is the AmeriFlux version of the carbon flux data for the site CA-ARB Attawapiskat River Bog. Site Description - Ontario Ministry of Environment and Climate Change's Environmental Monitoring and Reporting Branch has established five carbon flux monitoring towers in Ontario’s Far North as part of its Climate Change Modelling and Monitoring program. These long term monitoring stations measure carbon exchange and a suite of soil and meteorological parameters over peatland ecosystems to better understand carbon cycling in Ontario’s Far North. Information produced by these monitoring stations will assist the province in land use planning and the development of climate change adaptation strategies.

Todd, Aaron↗

AmeriFlux FLUXNET-1F CA-ARB Attawapiskat River Bog

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-ARB Attawapiskat River Bog. This is the FLUXNET version of the carbon flux data for the site CA-ARB Attawapiskat River Bog produced by applying the standard ONEFlux (1F) software. Site Description - Ontario Ministry of Environment and Climate Change's Environmental Monitoring and Reporting Branch has established five carbon flux monitoring towers in Ontario’s Far North as part of its Climate Change Modelling and Monitoring program. These long term monitoring stations measure carbon exchange and a suite of soil and meteorological parameters over peatland ecosystems to better understand carbon cycling in Ontario’s Far North. Information produced by these monitoring stations will assist the province in land use planning and the development of climate change adaptation strategies.

Todd, Aaron↗

AmeriFlux FLUXNET-1F CA-ARF Attawapiskat River Fen

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-ARF Attawapiskat River Fen. This is the FLUXNET version of the carbon flux data for the site CA-ARF Attawapiskat River Fen produced by applying the standard ONEFlux (1F) software. Site Description - Ontario Ministry of Environment and Climate Change's Environmental Monitoring and Reporting Branch has established five carbon flux monitoring towers in Ontario’s Far North as part of its Climate Change Modelling and Monitoring program. These long term monitoring stations measure carbon exchange and a suite of soil and meteorological parameters over peatland ecosystems to better understand carbon cycling in Ontario’s Far North. Information produced by these monitoring stations will assist the province in land use planning and the development of climate change adaptation strategies.

Todd, Aaron↗

AmeriFlux CA-PB2 Polar Bear 2 - Fen

This is the AmeriFlux version of the carbon flux data for the site CA-PB2 Polar Bear 2 - Fen. Site Description - Ontario Ministry of Environment and Climate Change's Environmental Monitoring and Reporting Branch has established five carbon flux monitoring towers in Ontario’s Far North as part of its Climate Change Modelling and Monitoring program. These long term monitoring stations measure carbon exchange and a suite of soil and meteorological parameters over peatland ecosystems to better understand carbon cycling in Ontario’s Far North. Information produced by these monitoring stations will assist the province in land use planning and the development of climate change adaptation strategies.

Humphreys, Elyn [Carleton University]↗

AmeriFlux CA-PB1 Polar Bear 1 - Peat Plateau

This is the AmeriFlux version of the carbon flux data for the site CA-PB1 Polar Bear 1 - Peat Plateau. Site Description - Ontario Ministry of Environment and Climate Change's Environmental Monitoring and Reporting Branch has established five carbon flux monitoring towers in Ontario’s Far North as part of its Climate Change Modelling and Monitoring program. These long term monitoring stations measure carbon exchange and a suite of soil and meteorological parameters over peatland ecosystems to better understand carbon cycling in Ontario’s Far North. Information produced by these monitoring stations will assist the province in land use planning and the development of climate change adaptation strategies.

Humphreys, Elyn [Carleton University]↗

AmeriFlux CA-KLP Kinoje Lake Peatland

This is the AmeriFlux version of the carbon flux data for the site CA-KLP Kinoje Lake Peatland. Site Description - Ontario Ministry of Environment and Climate Change's Environmental Monitoring and Reporting Branch has established five carbon flux monitoring towers in Ontario’s Far North as part of its Climate Change Modelling and Monitoring program. These long term monitoring stations measure carbon exchange and a suite of soil and meteorological parameters over peatland ecosystems to better understand carbon cycling in Ontario’s Far North. Information produced by these monitoring stations will assist the province in land use planning and the development of climate change adaptation strategies.

Humphreys, Elyn [Carleton University]↗