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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Projected monthly temperature changes of the Great Lakes Basin

Highlights: • Future Tmax increases will be greater in May to October period than other months. • Sub-basins temperature change order: Superior > Huron > Michigan > Erie and Ontario. • Future Tmax and Tmin changes will be different over land areas and the Great Lakes. • Project extreme warm (Tmax ≥ 29°C ~ 32°C) and cold (Tmax ≤ -5°C ~ 0°C) day changes. • Identify some fluctuations of latitudinal temperature gradients in this region. The Great Lakes Basin is an important agricultural region for both the United States and Canada. The regional crop growths are affected by inter-annual climatic conditions and intra-seasonal variability. Consequently, monthly climate change projection data can provide more useful information for crop management than seasonal climate projections. However, very few studies undertaken for the Great Lakes Basin have focused on monthly timescales. In this study, we investigate the projected mid-century (2030–2059) monthly mean maximum temperature (Tmax) and minimum temperature changes of this region, relative to the baseline period (1980–2009). Future Tmax increases in this region are likely to be greater during the May to October period (coinciding with the region's growing season) than in other months. The order of magnitude of future Tmax and Tmin changes of the five Great Lakes sub-basins are Superior > Huron > Michigan > Erie and Ontario. Most future Tmax changes over land areas are higher than those over the lakes, whereas Tmin changes are likely to be higher over lakes than over the adjacent land areas in this region. The future number of extreme warm days (Tmax ≥ 29–32 °C) in this region will increase by between about 5 days (in the north) to 40 days (in southern parts of the basin), while the number of winter cold days (Tmax ≤ −5 °C ~ 0 °C) may decrease by between 3 days (south) and 35 days (north). This study furthermore identifies some fluctuations of latitudinal temperature gradients in the Great Lakes Basin, these areas covering the north latitude 40.5–41.5°, 43.5–44.0°, 45.5–46.5°, and 47.5–49.5°.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Precision Gas Sampling (PGS) Validation2011-2014 Final Campaign Report

In this field campaign, we used eddy covariance towers to quantify carbon, water, and energy fluxes from a pasture and a wheat field that were converted to switchgrass. The U.S. Department of Energy is investing in switchgrass as a cellulosic bioenergy crop, but there is little data available that could be used to develop or test land surface model representations of the crop. This campaign was a collaboration between Lawrence Berkeley National Laboratory and the U.S. Department of Agriculture Agricultural Research Service. Unfortunately, in 2011, Oklahoma had one of the most severe droughts on record, and the crop in one of the switchgrass fields experienced almost complete die-off. The crop was replanted, but subsequent drought conditions prevented its establishment. Then, in April 2012, a large tornado demolished the instruments at our site in Woodward, Oklahoma. These two events meant that we have some interesting data on land response to extreme weather; however, we were not able to collect continuous data for annual sums as originally intended. We did observe that, because of the drought, the net ecosystem exchange of CO 2 was much lower in 2011 than in 2010. Concomitantly, sensible heat fluxes increased and latent heat fluxes decreased. These conditions would have large consequences for land surface forcing of convection. Data from all years were submitted to the Atmospheric Radiation Measurement Climate Research Facility Data Archive, and the sites were registered in AmeriFlux.

09 BIOMASS FUELS↗
NASA NTRS1976

Solar heating and cooling technical data and systems analysis

The accomplishments of a project to study solar heating and air conditioning are outlined. Presentation materials (data packages, slides, charts, and visual aids) were developed. Bibliographies and source materials on materials and coatings, solar water heaters, systems analysis computer models, solar collectors and solar projects were developed. Detailed MIRADS computer formats for primary data parameters were developed and updated. The following data were included: climatic, architectural, topography, heating and cooling equipment, thermal loads, and economics. Data sources in each of these areas were identified as well as solar radiation data stations and instruments.

Christensen, D. L.↗
NASA NTRS2012

NASA Center for Climate Simulation (NCCS) Presentation

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

Webster, William P.↗
DOE OSTI2013

ParCAT: Parallel Climate Analysis Toolkit

Climate science is employing increasingly complex models and simulations to analyze the past and predict the future of Earth's climate. This growth in complexity is creating a widening gap between the data being produced and the ability to analyze the datasets. Parallel computing tools are necessary to analyze, compare, and interpret the simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools to efficiently use parallel computing techniques to make analysis of these datasets manageable. The toolkit provides the ability to compute spatio-temporal means, differences between runs or differences between averages of runs, and histograms of the values in a data set. ParCAT is implemented as a command-line utility written in C. This allows for easy integration in other tools and allows for use in scripts. This also makes it possible to run ParCAT on many platforms – from laptops to supercomputers. ParCAT outputs NetCDF files so it is compatible with existing utilities such as Panoply and UV-CDAT. This paper describes ParCAT and presents results from some example runs on the Titan system at ORNL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

ParCAT: Parallel Climate Analysis Toolkit

Climate science is employing increasingly complex models and simulations to analyze the past and predict the future of Earth s climate. This growth in complexity is creating a widening gap between the data being produced and the ability to analyze the datasets. Parallel computing tools are necessary to analyze, compare, and interpret the simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools to efficiently use parallel computing techniques to make analysis of these datasets manageable. The toolkit provides the ability to compute spatio-temporal means, differences between runs or differences between averages of runs, and histograms of the values in a data set. ParCAT is implemented as a command-line utility written in C. This allows for easy integration in other tools and allows for use in scripts. This also makes it possible to run ParCAT on many platforms from laptops to supercomputers. ParCAT outputs NetCDF files so it is compatible with existing utilities such as Panoply and UV-CDAT. This paper describes ParCAT and presents results from some example runs on the Titan system at ORNL.

Smith, Brian E.↗
DOE OSTI2020

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term, high-frequency measurements from ARM in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Aerosol-cloud-climate cooling overestimated by ship-track data

The effect of anthropogenic aerosol on the reflectivity of stratocumulus cloud decks through changes in cloud amount is a major uncertainty in climate projections. In frequently occurring nonprecipitating stratocumulus, cloud amount can decrease through aerosol-enhanced cloud-top mixing. The climatological relevance of this effect is debated because ship exhaust only marginally reduces stratocumulus amount. By comparing detailed numerical simulations with satellite analyses, we show that ship-track studies cannot be generalized to estimate the climatological forcing of anthropogenic aerosol. The ship track–derived sensitivity of the radiative effect of nonprecipitating stratocumulus to aerosol overestimates their cooling effect by up to 200%. Further, the offsetting warming effect of decreasing stratocumulus amount needs to be taken into account if we are to constrain the cloud-mediated radiative forcing of anthropogenic aerosol.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Computational Modeling of Atmospheric Processes at Texas Southern University

Texas Southern University (TSU) is strengthening its research program in atmospheric chemistry and physics with a climate science emphasis by leveraging partnerships with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Facility, Brookhaven National Laboratory (BNL), and the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). This RDPP-supported program focuses on secondary organic aerosols (SOAs) and reactive atmospheric species that influence cloud formation, precipitation processes, and radiative forcing. SOAs play a critical role in cloud microphysics and Earth’s energy balance, yet the chemical and physical mechanisms governing SOA–cloud interactions remain a significant source of uncertainty in predictive climate models. Through computational modeling, observational data analysis, and national laboratory collaboration, this program develops a skilled cohort of students trained in atmospheric science, environmental data analysis, and climate-relevant modeling. These research experiences build technical competencies that are transferable to careers in government laboratories, academia, and industry. By engaging students from historically underrepresented communities in high-impact climate research, TSU expands participation in the atmospheric sciences workforce while contributing meaningful scientific insights to DOE-supported ARM research activities. This partnership strengthens national capacity in climate science and supports the development of the next generation of atmospheric researchers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Data from: Nitrogen fertilization challenges the climate benefit of cellulosic biofuels

Cellulosic biofuels are intended to improve future energy and climate security. Nitrogen (N) fertilizer is commonly recommended to stimulate yields but can increase losses of the greenhouse gas nitrous oxide (N2O) and other forms of reactive N, including nitrate. We measured soil N2O emissions and nitrate leaching along a switchgrass (Panicum virgatum) high resolution N-fertilizer gradient for three years post-establishment. Results revealed an exponential increase in annual N2O emissions that each year became stronger (R 2 > 0.9, P < 0.001) and deviated further from the fixed percentage assumed for IPCC Tier 1 emission factors. Concomitantly, switchgrass yields became less responsive each year to N fertilizer. Nitrate leaching (and calculated indirect N2O emissions) also increased exponentially in response to N inputs, but neither methane (CH4) uptake nor soil organic carbon changed detectably. Overall, N fertilizer inputs at rates greater than crop need curtailed the climate benefit of ethanol production almost two-fold, from a maximum mitigation capacity of −5.71 ± 0.22 Mg CO2e ha−1 yr−1 in switchgrass fertilized at 56 kg N ha−1 to only −2.97 ± 0.18 Mg CO2e ha−1 yr−1 in switchgrass fertilized at 196 kg N ha−1. Minimizing N fertilizer use will be an important strategy for fully realizing the climate benefits of cellulosic biofuel production.

09 BIOMASS FUELS↗
NASA NTRS1982

Low-latitude cloudiness and climate feedback - Comparative estimates from satellite data

Three studies of the relative albedo to the IR components of cloud amount feedback are reviewed, and an approach to the seasonal variability in low-level cloud numbers is presented. Comparisons are made and uncertainties calculated for the predictions of cloud amounts from satellite data sets for outgoing IR flux. IR data is used directly for a linear regression analysis and seasonal and latitudinal variations are considered in terms of monthly-annual means for particular latitude zones. Investigations of NOAA-NESS satellite data revealed that cirrus clouds are transparent in the 10.5-12.5 microns range and cloud albedos decrease at wavelengths greater than 0.7 micron, which suggests a possibility of cloud-sky and clear-sky albedo comparisons at 0.5-0.7 micron. The inclusion of Rayleigh scattering and atmospheric water vapor absorption of sunlight is recommended to test the effects on observed contracts.

Cess, R. D.↗
NASA NTRS1986

Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

Terrestrial climatic effects associated with solar variability have been proposed for at least a century, but could not be assessed quantitatively owing to observational uncertainities in solar flux variations. Measurements from 1980 to 1984 by the Active Cavity Radiometer Irradiance Monitor (ACRIM), capable of resolving fluctuations above the sensible atmosphere less than 0.1% of the solar constant, permit direct albeit preliminary assessments of solar forcing effects on global temperatures during this period. The global temperature response to ACRIM-measured fluctuations was computed from 1980 to 1985 using the NYU transient climate model including thermal inertia effects of the world ocean; and compared the results with observations of recent temperature trends. Monthly mean ACRIM-driven global surface temperature fluctuations computed with the climate model are an order of magnitude smaller, of order 0.01 C. In constrast, global mean surface temperature observations indicate an approx. 0.1 C increase during this period. Solar variability is therefore likely to have been a minor factor in global climate change during this period compared with variations in atmospheric albedo, greenhouse gases and internal self-inducedoscillations. It was not possible to extend the applicability of the measured flux variations to longer periods since a possible correlation of luminosity with solar annual activity is not supported by statistical analysis. The continuous monitoring of solar flux by satellite-based instruments over timescales of 20 years or more comparable to timescales for thermal relaxation of the oceans and of the solar cycle itself is needed to resolve the question of long-term solar variation effects on climate.

Hoffert, M. I.↗
NASA NTRS2011

NASA's Earth Observing System Data and Information System - EOSDIS

This slide presentation reviews the work of NASA's Earth Observing System Data and Information System (EOSDIS), a petabyte-scale archive of environmental data that supports global climate change research. The Earth Science Data Systems provide end-to-end capabilities to deliver data and information products to users in support of understanding the Earth system. The presentation contains photographs from space of recent events, (i.e., the effects of the tsunami in Japan, and the wildfires in Australia.) It also includes details of the Data Centers that provide the data to EOSDIS and Science Investigator-led Processing Systems. Information about the Land, Atmosphere Near-real-time Capability for EOS (LANCE) and some of the uses that the system has made possible are reviewed. Also included is information about how to access the data, and evolutionary plans for the future of the system.

Ramapriyan, Hampapuram K.↗
NASA NTRS2015

Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions

The Earths land surface boundary conditions in the Goddard Earth Observing System version 5 (GEOS-5) modeling system were updated using recent high spatial and temporal resolution global data products. The updates include: (i) construction of a global 10-arcsec land-ocean lakes-ice mask; (ii) incorporation of a 10-arcsec Globcover 2009 land cover dataset; (iii) implementation of Level 12 Pfafstetter hydrologic catchments; (iv) use of hybridized SRTM global topography data; (v) construction of the HWSDv1.21-STATSGO2 merged global 30 arc second soil mineral and carbon data in conjunction with a highly-refined soil classification system; (vi) production of diffuse visible and near-infrared 8-day MODIS albedo climatologies at 30-arcsec from the period 2001-2011; and (vii) production of the GEOLAND2 and MODIS merged 8-day LAI climatology at 30-arcsec for GEOS-5. The global data sets were preprocessed and used to construct global raster data files for the software (mkCatchParam) that computes parameters on catchment-tiles for various atmospheric grids. The updates also include a few bug fixes in mkCatchParam, as well as changes (improvements in algorithms, etc.) to mkCatchParam that allow it to produce tile-space parameters efficiently for high resolution AGCM grids. The update process also includes the construction of data files describing the vegetation type fractions, soil background albedo, nitrogen deposition and mean annual 2m air temperature to be used with the future Catchment CN model and the global stream channel network to be used with the future global runoff routing model. This report provides detailed descriptions of the data production process and data file format of each updated data set.

GEOS-5↗