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At least 217 records · Page 12

Interannual Variations of Shallow Firn Temperature at Greenland Summit

Firn-temperature profiles are calculated in a thermal model using continuous surface temperatures derived from Automatic Weather Station (AWS) data and passive microwave data in the Greenland Summit region during the period 1987-1999. The results show that significant interannual variations of mean summer (June to August) and annual temperatures occur in the top 15 m, in addition to the normal seasonal cycle of firn temperature. At 5 m depth, the seasonal cycle is damped to 13% of the surface seasonal amplitude, but even at 15 m about 1% or 0.6 C of the seasonal cycle persists. Both summer and mean annual temperatures decrease from 1987 to 1992, followed by a general increasing trend. Interannual variability is 5 C at the surface, but only is only dampened to 3.2 C at 10 m depth and 0.7 C at 15 m depth. Dampening of the interannual variability with depth is slower than dampening of the seasonal cycle, because of the longer time constant of the interannual variation. The warmer spring and summer temperatures experienced in the top 5 m, due to both the seasonal cycle and interannual variations, affect the rate of firn densification, which is non-linearly dependent on temperature. During the 12 year period 1987-1999, the mean annual surface temperature is -29.2 C, and the mean annual 15 m temperature is -30. 1 C, which is more than 1 C warmer than a 15-m borehole temperature representing the period of about 1959 and warmer than the best-fit temperature history by Alley and Koci back to 1500 A.D..

Jun, Li↗

Capturing the Value: Earth Applications of Space Human Factors Research

This paper details how the Space Human Factors/Life Sciences program at Ames Research Center (ARC) has provided, and continues to provide, a variety of Earth-based benefits. These benefits will be considered under five categories: aeronautics, space-like environments, general applications, human/automation interaction, and methodology. The human factors work at ARC includes a range of activities whose products serve the aerospace community. Some areas of research focus specifically on aeronautical requirements; others are driven by space needs. However, the symbiosis between these two domains allows a sharing of resources, and the insights and experimental results gathered in one domain can often be applied in the other. Aeronautics is an industry whose survival is generally viewed as critical to American competitiveness, and where benefits can result in a very high payoff. The ability to apply space-initiated research to aeronautical requirements represents one example of bringing space benefits down to Earth. The second-order value of space human factors research goes well beyond the aerospace community. Spaceflight shares with a number of other activities certain environmental characteristics that drive human factors engineering design and procedural specification. Spaceflight is an isolated activity, conducted under severely confined conditions, with a high level of risk, and where provisions are restricted and opportunities for outside help are limited. A number of Earth-based activities including submarines and other naval vessels, oil rigs, remote weather stations, and scientific and polar expeditions, share many of these characteristics. These activities serve as testbeds for space-related research and, in turn, space-related research provides beneficial insight to the conduct of these activities.

Connors, Mary M.↗

Ground-Based Lidar Measurements of Aerosols During ACE-2: Instrument Description, Results, and Comparisons with Other Ground-Based and Airborne Measurements

A micro-pulse lidar system (MPL) was used to measure the vertical and horizontal distribution of aerosols during the Aerosol Characterization Experiment 2 (ACE-2) in June and July of 1997. The MPL measurements were made at the Izana observatory (IZO), a weather station located on a mountain ridge (28 deg 18 min N, 16 deg 30 min W, 2367 m asl) near the center of the island of Tenerife, Canary Islands. The MPL was used to acquire aerosol backscatter, extinction, and optical depth profiles for normal background periods and periods influenced by Saharan dust from North Africa. System tests and calibration procedures are discussed, and an analysis of aerosol optical profiles acquired during ACE-2 is presented. MPL data taken during normal IZO conditions (no dust) showed that upslope aerosols appeared during the day and dissipated at night and that the layers were mostly confined to altitudes a few hundred meters above IZO. MPL data taken during a Saharan dust episode on 17 July showed that peak aerosol extinction values were an order of magnitude greater than molecular scattering over IZO, and that the dust layers extended to 5 km asl. The value of the dust backscatter-extinction ratio was determined to be 0.027 +/- 0.007 sr(exp -1). Comparisons of the MPL data with data from other collocated instruments showed good agreement during the dust episode.

Welton, Ellsworth J.↗

Earth Observation Services Weather Imaging

Microprocessor-based systems for processing satellite data offer mariners real-time images of weather systems, day and night, of large areas or allow them to zoom in on a few square miles. Systems West markets these commercial image processing systems, which have significantly decreased the cost of satellite weather stations. The company was assisted by the EOCAP program, which provides government co-funding to encourage private investment in, and to broaden the use of, NASA-developed technology for analyzing information about Earth and ocean resources.

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Global Surface Solar Energy Anomalies Including El Nino and La Nina Years

This paper synthesizes past events in an attempt to define the general magnitude, duration, and location of large surface solar anomalies over the globe. Surface solar energy values are mostly a function of solar zenith angle, cloud conditions, column atmospheric water vapor, aerosols, and surface albedo. For this study, solar and meteorological parameters for the 10-yr period July 1983 through June 1993 are used. These data were generated as part of the Release 3 Surface meteorology and Solar Energy (SSE) activity under the NASA Earth Science Enterprise (ESE) effort. Release 3 SSE uses upgraded input data and methods relative to previous releases. Cloud conditions are based on recent NASA Version-D International Satellite Cloud Climatology Project (ISCCP) global satellite radiation and cloud data. Meteorological inputs are from Version-I Goddard Earth Observing System (GEOS) reanalysis data that uses both weather station and satellite information. Aerosol transmission for different regions and seasons are for an 'average' year based on historic solar energy data from over 1000 ground sites courtesy of Natural Resources Canada (NRCan). These data are input to a new Langley Parameterized Shortwave Algorithm (LPSA) that calculates surface albedo and surface solar energy. That algorithm is an upgraded version of the 'Staylor' algorithm. Calculations are performed for a 280X280 km equal-area grid system over the globe based on 3-hourly input data. A bi-linear interpolation process is used to estimate data output values on a 1 X 1 degree grid system over the globe. Maximum anomalies are examined relative to El Nino and La Nina events in the tropical Pacific Ocean. Maximum year-to-year anomalies over the globe are provided for a 10-year period. The data may assist in the design of systems with increased reliability. It may also allow for better planning for emergency assistance during some atypical events.

Whitlock, C. H.↗

Global Autocorrelation Scales of the Partial Pressure of Oceanic CO2

A global database of approximately 1.7 million observations of the partial pressure of carbon dioxide in surface ocean waters (pCO2) collected between 1970 and 2003 is used to estimate its spatial autocorrelation structure. The patterns of the lag distance where the autocorrelation exceeds 0.8 is similar to patterns in the spatial distribution of the first baroclinic Rossby radius of deformation indicating that ocean circulation processes play a significant role in determining the spatial variability of pCO2. For example, the global maximum of the distance at which autocorrelations exceed 0.8 averages about 140 km in the equatorial Pacific. Also, the lag distance at which the autocorrelation exceed 0.8 is greater in the vicinity of the Gulf Stream than it is near the Kuroshio, approximately 50 km near the Gulf Stream as opposed to 20 km near the Kuroshio. Separate calculations for times when the sun is north and south of the equator revealed no obvious seasonal dependence of the spatial autocorrelation scales. The pCO2 measurements at Ocean Weather Station (OWS) 'P', in the eastern subarctic Pacific (50 N, 145 W) is the only fixed location where an uninterrupted time series of sufficient length exists to calculate a meaningful temporal autocorrelation function for lags greater than a few days. The estimated temporal autocorrelation function at OWS 'P', is highly variable. A spectral analysis of the longest four pCO2 time series indicates a high level of variability occurring over periods from the atmospheric synoptic to the maximum length of the time series, in this case 42 days. It is likely that a relative peak in variability with a period of 3-6 days is related to atmospheric synoptic period variability and ocean mixing events due to wind stirring. However, the short length of available time series makes identifying temporal relationships between pCO2 and atmospheric or ocean processes problematic.

Li, Zhen↗

Dynamic Domains in Data Production Planning

This paper discusses a planner-based approach to automating data production tasks, such as producing fire forecasts from satellite imagery and weather station data. Since the set of available data products is large, dynamic and mostly unknown, planning techniques developed for closed worlds are unsuitable. We discuss a number of techniques we have developed to cope with data production domains, including a novel constraint propagation algorithm based on planning graphs and a constraint-based approach to interleaved planning, sensing and execution.

Golden, Keith↗

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

AVHRR (ADVANCED VERY HIGH RESOLUTION RADIOMETER)↗

(abstract) Monitoring Seasonal Change in Taiga Forests Using ERS-1 SAR Data

Sensitivity of radar backscatter to the dielectric and geometric character of forested regions suggests significant changes in backscatter are expected with season due to freezing temperatures, snow, wind, leaf fall, and drought. The first European Remote Sensing Satellite, ERS-1, offers a unique opportunity to monitor a complete seasonal cycle for the Alaskan taiga forest ecosystem with synthetic aperture radar. During the 3-day repeat Commissioning Phase of ERS-1, from August 1991to December 1991, ERS-1 SAR data were collected in the region of Manley Hot Springs, Alaska, along the Tanana River, west of Fairbanks. In parallel with the SAR data collection, meteorological data from three weather stations positioned in three forest stands were collected continuously along with in situ measurements of the dielectric and moisture properties of the canopy and of ground cover which were collected during each overflight. The in situ data were collected in floodplain forest stands dominated by balsam poplar, white spruce, and black spruce. These results from the Commissioning Phase as well as preliminary results from the 35-day Repeat Phase will be presented.

characteristics geometric characteristics moisture↗

Poultry Industry Energy Research

The poultry industry, a multi-billion dollar business in the United States, uses great amounts of energy in such operations as broiler growing, feed manufacturing, poultry processing and packing. Higher costs and limited supply of fuels common to the industry are predicted, so poultry producers are seeking ways to reduce energy expenditure. NASA is providing assistance to Delmarva Poultry Industry, Inc., an association of some 4,000 growers and suppliers in one of the nation's largest poultry production areas. Delmarva is the East Coast peninsula that includes Delaware and parts of Maryland and Virginia. The upper right photo shows a weather station in the Delmarva area (wind indicator on the pole, other instruments in the elevated box). The station is located at the University of Maryland's Broiler Sub-station, Salisbury; Maryland, where the university conducts research on poultry production and processing. The sub-station is investigating ways of conserving energy in broiler production and also exploring the potential of solar collectors as an alternative energy source. For these studies, it is essential that researchers have continuous data on temperature, pressure, wind speed and direction, solar intensity and cloud cover. Equipment to acquire such data was loaned and installed by NASA's Wallops Flight Center, Wallops Island, Virginia.

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A Web 2.0 and OGC Standards Enabled Sensor Web Architecture for Global Earth Observing System of Systems

This paper will describe the progress of a 3 year research award from the NASA Earth Science Technology Office (ESTO) that began October 1, 2006, in response to a NASA Announcement of Research Opportunity on the topic of sensor webs. The key goal of this research is to prototype an interoperable sensor architecture that will enable interoperability between a heterogeneous set of space-based, Unmanned Aerial System (UAS)-based and ground based sensors. Among the key capabilities being pursued is the ability to automatically discover and task the sensors via the Internet and to automatically discover and assemble the necessary science processing algorithms into workflows in order to transform the sensor data into valuable science products. Our first set of sensor web demonstrations will prototype science products useful in managing wildfires and will use such assets as the Earth Observing 1 spacecraft, managed out of NASA/GSFC, a UASbased instrument, managed out of Ames and some automated ground weather stations, managed by the Forest Service. Also, we are collaborating with some of the other ESTO awardees to expand this demonstration and create synergy between our research efforts. Finally, we are making use of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) suite of standards and some Web 2.0 capabilities to Beverage emerging technologies and standards. This research will demonstrate and validate a path for rapid, low cost sensor integration, which is not tied to a particular system, and thus be able to absorb new assets in an easily evolvable, coordinated manner. This in turn will help to facilitate the United States contribution to the Global Earth Observation System of Systems (GEOSS), as agreed by the U.S. and 60 other countries at the third Earth Observation Summit held in February of 2005.

Mandl, Daniel↗

Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

Hall, Dorothy K.↗

More Frequent Cloud Free Sky and Less Surface Solar Radiation in China from 1955-2000

In this study, we used newly available data frorn extended weather stations and time period to reveal that much of China has experienced significant decreases in cloud cover over the last half of the Twentieth century. This conclusion is supported by analysis of the more reliably observed frequency of cloud-free sky and overcast sky. We estimated that the total cloud cover and low cloud cover in China have decreased 0.88% and 0.33% per decade, respectively, and cloud-free days have increased 0.60% and overcast days decreased 0.78% per decade from 1954-2001. Meanwhile, both solar radiation and pan evaporation have decreased in China, with'solar radiation decreasing 3.1 w/square m and pan evaporation decreasing 39 mm per decade. Combining these results with findings of previous studies, we speculated that increased air pollution may have produced a fog-like haze that reflected/absorbed radiation from the sun and resulted in less solar radiation reaching the surface, despite concurrent increasing trends in cloud-free sky over China.

Qian, Yun↗

Finland Validation of the New Blended Snow Product

As part of an ongoing effort to validate satellite remote sensing snow products for the recentlydeveloped U.S. Air Force Weather Agency (AFWA) - NASA blended snow product, Satellite and in-situ data for snow extent and snow water equivalent (SWE) are evaluated in Finland for the 2006-2007 snow season Finnish Meteorological Institute (FMI) daily weather station data and Finnish Environment Institute (SYKE) bi-monthly snow course data are used as ground truth. Initial comparison results display positive agreement between the AFWA NASA Snow Algorithm (ANSA) snow extent and SWE maps and in situ data, with discrepancies in accordance with known AMSR-E and MODIS snow mapping limitations. Future ANSA product improvement plans include additional validation and inclusion of fractional snow cover in the ANSA data product. Furthermore, the AMSR-E 19 GHz (horizontal channel) with the difference between ascending and descending satellite passes (Diurnal Amplitude Variations, DAV) will be used to detect the onset of melt, and QuikSCAT scatterometer data (14 GHz) will be used to map areas of actively melting snow.

Kim, E. J.↗

NASA-Modified Precipitation Products to Improve EPA Nonpoint Source Water Quality Modeling for the Chesapeake Bay

The Environmental Protection Agency (EPA) has estimated that over 20,000 water bodies within the United States do not meet water quality standards. Ninety percent of the impairments are typically caused by nonpoint sources. One of the regulations in the Clean Water Act of 1972 requires States to monitor the Total Maximum Daily Load (TMDL), or the amount of pollution that can be carried by a water body before it is determined to be "polluted", for any watershed in the U.S.. In response to this mandate, the EPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a Decision Support Tool (DST) for assessing pollution and to guide the decision making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program -- Fortran (HSPF), computes daily stream flow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA modified/NOAA precipitation data. Using these data within HSPF, stream flow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better stream flow statistics and, ultimately, in improved water quality assessment.

Nigro, Joseph↗

Investigation of Long-Term Impacts of Urbanization when Considering Global Warming for a Coastal Tropical Region

The overachieving goal of this project is to gain a better understanding of the climate impacts caused by the combined effects of land cover and land use (LCLU) changes and increasing global concentrations of green house gases (GHG) in tropical coastal areas, regions where global, regional and local climate phenomena converge, taking as the test case the densely populated northeast region of the Caribbean island of Puerto Rico. The research uses an integrated approach of high-resolution remote sensing information linked to a high resolution Regional Atmospheric Modeling System (RAMS), which was employed to perform ensembles of climate simulations (combining 2-LCLU and 2-GHG concentration scenarios). Reconstructed agricultural maps are used to define past LCLU, and combined with reconstructed sea surface temperatures (SST) for the same period form the PAST climate scenario (1951-1956); while the PRESENT scenario (2000-2004) was additionally supported by high resolution remote sensing data (10-m-res). The climate reconstruction approach is validated with available observed climate data from surface weather stations for both periods of time simulated. The selection of the past and present climate scenarios considers large-scale biases (i.e. ENSO/NAO) as reflected in the region of interest. Direct and cross comparison of the results is allowing quantifying single, combined, and competitive effects. Results indicate that global GHG have dominant effects on minimum temperatures (following regional tendencies), while urban sprawl dominates maximum temperatures. To further investigate impacts of land use the Bowen Ratio and the thermal response number (TRN) are analyzed. The Bowen ratio indicates that forestation of past agricultural high areas have an overwhelmingly mitigation effect on increasing temperatures observed in different LCLU scenarios, but when abandoned agricultural lands are located in plains, the resulting shrub/grass lands produce higher surface temperatures. The TRN (J/m^2/degC) is a surface property defined as the ratio of the surface net radiation to the rate of change in surface temperature, expresses how those fluxes are reacting to radiant energy inputs. Natural vegetated surfaces have a greater TRN than urban and barren surfaces because the net radiation processed by them is mostly used for latent heat and thermal storage heat rather than sensible heat (heating the air). Significant changes in TRN were observed in the metropolitan area of San Juan for the two analyzed periods reflecting a reduction of this variable in the present from the past consistent with increasing in thermal mass, or intense urbanization.

Gonalez, Jorge E.↗

A Climate-Data Record (CDR) of the "Clear Sky" Surface Temperature of the Greenland Ice Sheet

To quantify the ice-surface temperature (IST) we are developing a climate-data record (CDR) of monthly IST of the Greenland ice sheet, from 1982 to the present using Advanced Very High Resolution Radiometer (AVHRR) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data at 5-km resolution. "Clear-sky" surface temperature increases have been measured from the early 1980s to the early 2000s in the Arctic using AVHRR data, showing increases ranging from 0.57-0.02 (Wang and Key, 2005) to 0.72 0.10 deg C per decade (Comiso, 2006). Arctic warming has implications for ice-sheet mass balance because much of the periphery of the ice sheet is near 0 deg C in the melt season and is thus vulnerable to more extensive melting (Hanna et al., 2008). The algorithm used for this work has a long history of measuring IST in the Arctic with AVHRR (Key and Haefliger, 1992). The data are currently available from 1981 to 2004 in the AVHRR Polar Pathfinder (APP) dataset (Fowler et al., 2000). J. Key1NOAA modified the AVHRR algorithm for use with MODIS (Hall et al., 2004). The MODIS algorithm is now being processed over Greenland. Issues being addressed in the production of the CDR are: time-series bias caused by cloud cover, and cross-calibration between AVHRR and MODIS instruments. Because of uncertainties, time series of satellite ISTs do not necessarily correspond with actual surface temperatures. The CDR will be validated by comparing results with in-situ (see Koenig and Hall, in press) and automatic-weather station data (e.g., Shuman et al., 2001).

Hall, Dorothy K.↗

Atmospheric Airborne Pressure Measurements Using the Oxygen A Band for the ASCENDS Mission

We report on airborne atmospheric pressure measurements using new fiber-based laser technology and the oxygen A-band at 765 nm. Remote measurements of atmospheric temperature and pressure are required for a number of NASA Earth science missions and specifically for the Active Sensing of CO2 Emissions Over Nights, Days, and Seasons (ASCENDS) mission. Accurate measurements of tropospheric CO2 on a global scale are very important in order to better understand its sources and sinks and to improve predictions on any future climate change. The ultimate goal of a CO2 remote sensing mission, such as ASCENDS, is to derive the CO2 concentration in the atmosphere in terms of mole fraction in unit of parts-per-million (ppmv) with regard to dry air. Therefore, both CO2 and the dry air number of molecules in the atmosphere are needed in deriving this quantity. O2 is a stable molecule and uniformly mixed in the atmosphere. Measuring the O2 absorption in the atmosphere can thus be used to infer the dry air number of molecules and then used to calculate CO2 concentration. With the knowledge of atmospheric water vapor, we can then estimate the total surface pressure needed for CO2 retrievals. Our work, funded by the ESTO IIP program, uses fiber optic technology and non-linear optics to generate 765 nm laser radiation coincident with the Oxygen A-band. Our pulsed, time gated technique uses several on- and off-line wavelengths tuned to the O2 absorption line. The choice of wavelengths allows us to measure the pressure by using two adjacent O2 absorptions in the Oxygen A-band. Our retrieval algorithm fits the O2 lineshapes and derives the pressure. Our measurements compare favorably with a local weather monitor mounted outside our laboratory and a local weather station.

Riris, Haris↗