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At least 307 records · Page 17

Landscape and geomorphic survey of Zhamanshin area, Northern Kazakhstan: Preliminary report on 1992 field trip data

The June 1992 geographical expedition to Zhamanshin crater area made a landscape and geomorphic survey of this impact structure. Observational points in the area of 300 sq km give new data on the geographical processes in the impact crater. The data obtained could be applied to search for unknown impact structures anywhere through the traces of such features in landscapes.

Burba, G. G., Jr.↗

Detecting surface roughness effects on the atmospheric boundary layer via AIRSAR data: A field experiment in Death Valley, California

The part of the troposphere influenced by the surface of the earth is termed the atmospheric boundary layer. Flow within this layer is influenced by the roughness of the surface; rougher surfaces induce more turbulence than smoother surfaces and, hence, higher atmospheric transfer rates across the surface. Roughness elements also shield erodible particles, thus decreasing the transport of windblown particles. Therefore, the aerodynamic roughness length (z(sub 0)) is an important parameter in aeolian and atmospheric boundary layer processes as it describes the aerodynamic properties of the underlying surface. z(sub 0) is assumed to be independent of wind velocity or height, and dependent only on the surface topography. It is determined using in situ measurements of the wind speed distribution as a function of height. For dry, unvegetated soils the intensity of the radar backscatter (sigma(sup 0)) is affected primarily by surface roughness at a scale comparable with the radar wavelength. Thus, both wind and radar respond to surface roughness variations on a scale of a few meters or less. Greeley showed the existence of a correlation between z(sub 0) and sigma(sup 0). This correlation was based on measurements over lava flows, alluvial fans, and playas in the southwest deserts of the United States. It is shown that the two parameters behave similarly also when there are small changes over a relatively homogeneous surface.

Blumberg, Dan G.↗

[MODIS Investigation]

The objectives of the last six months were: Continue analysis of Hawaii Ocean Time-series (HOT) bio-optical mooring data, Recover instrumentation from JGOFS cruises in the Southern Ocean and analyze data Maintain documentation of MOCEAN algorithms and software for use by MOCEAN and GLI teams Continue chemostat experiments on the relationship of fluorescence quantum yield to environmental factors. Continue to develop and expand browser-based information system for in situ bio-optical data Work Analysis of Field Data from Hawaii We are continuing to analyze bio-optical data collected at the Hawaii Ocean Time Series mooring. The HOT bio-optical mooring was recovered in May 1998. After retrieving the data, the sensor package was serviced and redeployed. We now have over 18 months of data. These are being analyzed as part of a larger study of mesoscale processes at this JGOFS time series site. We have had some failures in the data logger which have affected the fluorescence channels. These are being repaired. We also had an instrument housing failure, and minor modifications have been made to avoid subsequent problems. In addition, Ricardo Letelier is funded as part of the SeaWiFS calibrator/validation effort (through a subcontract from the University of Hawaii, Dr. John Porter), and he is collecting bio-optical and fluorescence data as part of the HOT activity.

Abbott, Mark R.↗

Modeling Aerosol Nucleation

The goal of this work has been to understand how nitric acid condenses on cirrus ice cloud particles by analyzing data obtained during the SAGE III Ozone Loss and Validation Experiment (SOLVE) research mission based out of Kiruna, Sweden. Ms. Gamblin simultaneously analyzed gas phase nitric acid data along with particulate NO, data, particulate, vapor and gas-phase water data from several different instruments, particle size data, which included surface area and volume measurements, ozone concentration data as well as temperature, pressure and GPS coordinates of the sampled air parcel. All parameters where held constant with only one allowed to vary in order to determine what controls the extent to which nitric acid will condensation on ice. In addition, this data was compared to theoretical values of nitric acid condensation on ice based upon recent laboratory data. Comparison of these two data sets shows the field data does not agree with what is expected in the laboratory at comparable temperatures and nitric acid pressures. The most significant difference is that surface coverages in the atmosphere were found to be elevated relative to surface coverages measured in the laboratory. The results of this study were accepted for publication by Geophysical Research Letters.

Toon, Owen B.↗

The CEOP Inter-Monsoon Studies (CIMS)

Prediction of climate relies on models, and better model prediction depends on good model physics. Improving model physics requires the maximal utilization of climate data of the past, present and future. CEOP provides the first example of a comprehensive, integrated global and regional data set, consisting of globally gridded data, reference site in-situ observations, model location time series (MOLTS), and integrated satellite data for a two-year period covering two complete annual cycles of 2003-2004. The monsoon regions are the most important socio-economically in terms of devastation by floods and droughts, and potential impacts from climate change md fluctuatinns nf the hydrologic cyc!e. Scientifically, it is most challenging, because of complex interactions of atmosphere, land and oceans, local vs. remote forcings in contributing to climate variability and change in the region. Given that many common features, and physical teleconnection exist among different monsoon regions, an international research focus on monsoon must be coordinated and sustained. Current models of the monsoon are grossly inadequate for regional predictions. For improvement, models must be confronted with relevant observations, and model physic developers must be made to be aware of the wealth of information from existing climate data, field measurements, and satellite data that can be used to improve models. Model transferability studles must be conducted. CIMS is a major initiative under CEOP to engage the modeling and the observational communities to join in a coordinated effort to study the monsoons. The objectives of CIMS are (a) To provide a better understanding of fundamental physical processes (diurnal cycle, annual cycle, and intraseasonal oscillations) in monsoon regions around the world and (b) To demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. In this talk, I will present the basic concepts of CIMS and the key scientific problems facing monsoon climates and provide examples of common monsoon features, and possible monsoon induced teleconnections linking different parts of the world.

Lau, William K. M.↗

The Prediction of Long-Term Coating Performance from Short-Term Electrochemical Data: Comparison of Electrochemical Data to Field Exposure Results for Coatings on Steel - Part 2

The pace of coatings development is limited by the time required to assess their corrosion protection properties. This study takes a step f orward from Part I in that it correlates the corrosion performance of organic coatings assessed by a series of short-term electrochemical measurement with 18-month beachside exposure results of duplicate pan els. A series of 19 coating systems on A36 steel substrates were test ed in a completely blind study using the damage tolerance test (DTT). In the DTT, a through-film pinhole defect is created, and the electro chemical characteristics of the defect are then monitored over the ne xt 4 to 7 days while immersed in 0.SM NaCl. The open circuit potentia l, anodic potentiostatic polarization tests and electrochemical imped ance spectroscopy were used to study the corrosion behavior of the co ating systems. The beachside exposure tests were conducted at the Ken nedy Space Center according to ASTM D610-01. It was found that for 79 % of the coatings systems examined, the 18 month beachside exposure r esults could be predicted by two independent laboratory tests obtained within 7 days.

Contu, F.↗

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

A code for predicting supersonic jet broadband shock-associated noise was assessed using a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify deficiencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the measured data, a sensitivity analysis of the model parameters with emphasis on the definition of the convection velocity parameter, and a least-squares fit of the predicted to the measured shock-associated noise component spectra, resulted in a new definition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Dahl, Milo D.↗

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

A code for predicting supersonic jet broadband shock-associated noise was assessed us- ing a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify de ciencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the mea- sured data, a sensitivity analysis of the model parameters with emphasis on the de nition of the convection velocity parameter, and a least-squares t of the predicted to the mea- sured shock-associated noise component spectra, resulted in a new de nition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Dahl, Milo D.↗

A New Tropical Cyclone Dynamic Initialization Technique Using High Temporal and Spatial Density Atmospheric Motion Vectors and Airborne Field Campaign Data

Background: Initialization of tropical cyclones in numerical weather prediction (NWP) systems is a great challenge: Mass-wind field balance; Secondary circulation and heating; Asymmetries. There can be large adjustments in structure and intensity in the first 24 hours if the initial vortex is not in balance: Spurious gravity waves; Spin-up (model and physics). Existing mesoscale NWP model TC (Tropical Cyclone) initialization strategies: Bogus vortex, cold start from global analyses; 3DVAR or 4DVAR, possibly with synthetic observations; EnKF (Ensemble Kalman Filter); Dynamic initialization. Dynamic initialization allows vortex to have improved balance and physics spin-up at the initial time (e.g., Hendricks et al. 2013, 2011; Nguyen and Chen 2011; Fiorino and Warner 1981; Hoke and Anthes 1976). Himawari-8 geostationary satellite has capability of continuous imagery (10-minutes) over the full disk: New GOES-R satellites will have same capability. This will allow for unprecedented observations of tropical cyclones. However, current data assimila1on systems are not capable of ingesting such high temporal observations (Atmospheric Mo1on Vectors - AMVs). Hourly AMVs are produced, and thinned to 100-kilometer spacing in the horizontal. An entirely new data assimilation concept is required to utilize these observations.

remote sensing↗

Mapping Forest Disturbance Intensity in North and South Carolina Using Annual Landsat Observations and Field Inventory Data

Disturbance and regrowth are vital processes in determining the roles of forest ecosystem in the carbon and biogeochemical cycles. Using time series observations, the vegetation change tracker (VCT) algorithm was designed to map the location, timing, and spectral magnitudes of forest disturbance events. While these spectral disturbance magnitudes are indicative of physical changes in tree cover or biomass, their quantitative relationships have yet to be established. This study focuses on estimating disturbance intensity as measured by percent basal area removal using spectral indices from the VCT algorithm over North and South Carolina. Repeat measurements on Forest Service Forest Inventory Analysis (FIA) ground plots, which provide changes in basal area between multiple dates at precise locations, are used for training and validation of the model. The overall R2 between predicted disturbance intensity and reference data is 0.66, and cross-validation prediction uncertainty is 14% in North Carolina. Possible causes of this uncertainty could be site heterogeneity and the temporal offset between ground measurements and satellite observations. Results show the area of stand clearing disturbances remains relatively stable around 1143 km2 yr−1 in North and South Carolina throughout the period of observations (1985–2015). The average amount of forest area affected by partial disturbance is much higher at 3287 km2 yr−1. The area of partial disturbances has strong inter-annual variability with a high value of 6000 km2 in 2007 and a low value of 1919 km2 in 2013.

Xin Tao↗

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

evapotranspiration↗