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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Assimilation of a Coordinated Fleet of Uncrewed Aircraft System Observations in Complex Terrain: Observing System Experiments

Uncrewed aircraft system (UAS) observations from the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting (WRF) Model. The impact of assimilating targeted UAS observations in addition to surface observations was compared to that obtained when assimilating surface observations alone using observing system experiments (OSEs) for a terrain-driven flow case and a convection initiation (CI) case observed within Colorado’s San Luis Valley (SLV). The assimilation of UAS observations in addition to surface observations results in a clear increase in skill for both flow regimes over that obtained when assimilating surface observations alone. For the terrain-driven flow case, the UAS observations improved the representation of thermal stratification across the northern SLV, which produced stronger upvalley flow over the eastern half of the SLV that better matched the observations. For the CI case, the UAS observations improved the representation of the pre-convective environment by reducing dry biases across the SLV and over the surrounding terrain. This led to earlier CI and more organized convection over the foothills that spilled outflows into the SLV, ultimately helping to increase low-level convergence and CI there. In addition, the importance of UAS capturing an outflow that originated over the Sangre de Cristo Mountains and triggered CI is discussed. These outflows and subsequent CI were not well captured in the simulation that assimilated surface observations alone. We report that observations obtained with a fleet of UAS are shown to notably improve high-resolution analyses and short-term predictions of two very different mesogamma-scale weather events.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Assessing the Impact of Light/Shallow Precipitation Retrievals from Satellite-Based Observations Using Surface Radar and Micro Rain Radar Observations

The accurate representation of precipitation across the Earth’s surface is crucial to furthering our knowledge and understanding of the Earth System and its component processes. Precipitation poses a number of challenges, particularly due to the variability of precipitation over time and space and whether it falls as snow or rain. While conventional measures of precipitation are reasonably good at the location of their measurement, their distribution across the Earth’s surface is uneven with some regions having no surface measurements. Spaceborne sensors have the capability of providing regular observations across the Earth’s surface that can provide estimates of precipitation. However, the estimation of precipitation from satellite observations is not necessarily straightforward. Visible and/or infrared techniques rely upon imprecise cloud-top to surface precipitation relationships, while the sensitivity of passive microwave techniques to different precipitation types is not consistent. Active microwave (radar) observations provide the most direct satellite measurements of precipitation but cannot provide estimates close to the surface and are generally not sufficiently sensitive to resolve light precipitation. This is particularly problematic at mid to high latitudes, where light and/or shallow precipitation dominates. This paper compares measurements made by ground-based weather radars, Micro Rain Radars and the spaceborne Dual-frequency Precipitation Radar to study both light precipitation intensity and shallow precipitation occurrence and to assess their impact on satellites retrievals of precipitation at the mid to high latitudes.

light precipitation↗
NASA NTRS1993

Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature

The global fields of normal monthly soil moisture and land surface evapotranspiration are derived with a simple water budget model that has precipitation and potential evapotranspiration as inputs. The precipitation is observed and the potential evapotranspiration is derived from the observed surface air temperature with the empirical regression equation of Thornthwaite (1954). It is shown that at locations where the net surface radiation flux has been measured, the potential evapotranspiration given by the Thornthwaite equation is in good agreement with those obtained with the radiation-based formulations of Priestley and Taylor (1972), Penman (1948), and Budyko (1956-1974), and this provides the justification for the use of the Thornthwaite equation. After deriving the global fields of soil moisture and evapotranspiration, the assumption is made that the potential evapotranspiration given by the Thornthwaite equation and by the Priestley-Taylor equation will everywhere be about the same; the inverse of the Priestley-Taylor equation is used to obtain the normal monthly global fields of net surface radiation flux minus ground heat storage. This and the derived evapotranspiration are then used in the equation for energy conservation at the surface of the earth to obtain the global fields of normal monthly sensible heat flux from the land surface to the atmosphere.

Mintz, Y.↗
DOE OSTI2021

Mocking the u-plane integral

Abstract The u -plane integral is the contribution of the Coulomb branch to correlation functions of $${\mathcal {N}}=2$$ N = 2 gauge theory on a compact four-manifold. We consider the u -plane integral for correlators of point and surface observables of topologically twisted theories with gauge group $$\mathrm{SU}(2)$$ SU ( 2 ) , for an arbitrary four-manifold with $$(b_1,b_2^+)=(0,1)$$ ( b 1 , b 2 + ) = ( 0 , 1 ) . The u -plane contribution equals the full correlator in the absence of Seiberg–Witten contributions at strong coupling, and coincides with the mathematically defined Donaldson invariants in such cases. We demonstrate that the u -plane correlators are efficiently determined using mock modular forms for point observables, and Appell–Lerch sums for surface observables. We use these results to discuss the asymptotic behavior of correlators as function of the number of observables. Our findings suggest that the vev of exponentiated point and surface observables is an entire function of the fugacities.

Mathematics↗
NASA NTRS1981

Spaceborne radar observation of the earth surface

Seasat SAR images are being analyzed to determine the potential of spaceborne radars for earth resources and ocean surface observation. Examples are presented for a variety of applications in structural mapping, lithological classification, soil moisture detection, polar ice motion monitoring and ocean features observation. These examples are briefly discussed with emphasis on the future research needed to further the capability of radar sensors, by themselves or in combination with other sensors. A brief discussion is then given on the spaceborne sensors which are required and planned to meet these needs.

Elachi, C.↗
NASA NTRS1997

Surface-Based Observations of Contrail Occurrence Over the US, Apr. 1993 to Apr. 1994

Surface observers stationed at 19 U.S. Air Force Bases and Army Air Stations recorded the daytime occurrence of contrails and cloud fraction on an hourly basis for the period April 1993 through April 1994. Each observation uses one of four main categories to report contrails as unobserved, non-persistent, persistent, and indeterminate. Additional classification includes the co-occurrence of cirrus with each report. The data cover much of the continental U.S. including locations near major commercial air routes. The mean annual frequency of occurrence in unobstructed viewing conditions is 13 percent for these sites. Contrail occurrence varied substantially with location and season. Most contrails occurred during the winter months and least during the summer with a pronounced minimum during July. Although nocturnal observations are not available, it appears that the contrails have a diurnal variation that peaks during mid morning over most areas. Contrails were most often observed in areas near major commercial air corridors and least often over areas far removed from the heaviest air traffic. A significant correlation exists between mean contrail frequency and aircraft fuel usage above 7 km suggesting predictive potential for assessing future contrail effects on climate.

Minnis, Patrick↗
NASA NTRS1987

Temporal observations of surface soil moisture using a passive microwave sensor

A series of 10 aircraft flights was conducted over agricultural fields to evaluate relationships between observed surface soil moisture and soil moisture predicted using passive microwave sensor observations. An a priori approach was used to predict values of surface soil moisture for three types of fields: tilled corn, no-till corn with soybean stubble, and idle fields with corn stubble. Acceptable predictions were obtained for the tilled corn fields, while poor results were obtained for the others. The source of error is suspected to be the density and orientation of the surface stubble layer; however, further research is needed to verify this explanation. Temporal comparisons between observed, microwave predicted, and soil water-simulated moisture values showed similar patterns for tilled well-drained fields. Divergences between the observed and simulated measurements were apparent on poorly drained fields. This result may be of value in locating and mapping hydrologic contributing areas.

Jackson, T. J.↗
NASA NTRS2001

Atmospheric attenuation calibrations of surface weather observations

A correlation between near-IR atmospheric attenuation measurements made by the Atmospheric Visibility Monitor (AVM) at the Table Mountain Facility and airport surface weather observations at Edwards Air Force Base has been performed. High correlations (over 0.93) exist between the simultaneous Edwards observed sky cover and the average AVM measured attenuations over the course of the 10 months analyzed. The statistical relationship between the data-sets allows the determination of coarse attenuation statistics from the surface observations, suggesting that such statistics may be extrapolated from any surface weather observation site, Furthermore, a superior technique for converting AVM images to attenuation values by way of MODTRAN predictions has been demonstrated.

laser propogation↗
DOE OSTI2021

Boundary Layer Climatology at ARM Southern Great Plains

Operational since 1992, the Atmospheric Radiation Measurement (ARM) southern great plains (SGP) site at Oklahoma, USA has become a reference research site for meteorological studies. Due to an open data policy the ARM data are used by researchers all over the world. In this report, we review the long-term climatology of the atmospheric boundary layer, SGP instrumentations, the site and some site-specific atmospheric conditions which potentially effect wind turbines within the region. As the atmospheric boundary layer is bounded and influenced by the surface, observations of surface radiation components and heat fluxes are crucial in understanding land-atmosphere interactions. The entrainment of air, updrafts, downdrafts and boundary layer height characteristics is needed for understanding the structure and growth of the atmospheric boundary layer. Therefore, measurements from both surface in-situ and remote sensing observations at SGP provide an overall climatology and their interactions from surface up to the boundary layer. Measurements from a 60 m meteorological tower, surface flux stations, disdrometers, soil temperature and moisture flux plates, coherent Doppler lidar, Raman lidar, radiosondes, and satellite data at SGP central facility were analyzed. All the measurements were generally within a few square kilometers of each other at the central facility. This report focuses on data from January 2010 to June 2020 at SGP central facility. The various sections describe the ARM SGP site and surrounding wind turbines; in-situ and remote sensing instrumentation used in the report; provides mathematical equations to analyze fluxes, turbulence and other boundary layer parameters; a climatological analysis of surface winds, fluxes and thermodynamic parameters for several years; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; an analysis of the boundary layer winds and direction from a Doppler lidar; multi-year turbulence estimates through the boundary layer from a Doppler lidar; atmospheric boundary layer water vapor and relative humidity profiles from Raman lidar; cloud base height and boundary layer height from multiple sensors and satellite data; and finally site specific atmospheric conditions, such as nocturnal low-level jets. Diurnal, seasonal and yearly variations of surface, sub-surface and boundary layer quantities, such as wind speed, direction, temperature, atmospheric stability, soil temperature, and various atmospheric fluxes at SGP showed distinct trends useful for focused modeling studies. The applicability of surface similarity theory on ARM SGP data is also evaluated, which showed northerly flows are aligned with MO theory estimates compared to southerly flows. Boundary layer winds and direction profiles for several years from a Doppler lidar shows a consistent presence of a nocturnal low-level jet and predominant southerly wind directions through the boundary layer at SGP. The inter-annual variability at SGP is low (<3.5%), with a mean annual wind speed of approximately 7 m s -1 at 100 m above ground level. Boundary layer turbulence and moisture transport from Doppler and Raman lidars are evaluated, which provides evidence of increased water vapor mass flux into the great plains during nocturnal low-level jets. The moisture flux from nocturnal low-level jets is observed to be maximum during summer periods. A novel machine learning algorithm is implemented to accurately estimate the planetary boundary layer height, providing further insights into growth and destruction of the convective boundary layer height during various seasons and land-atmosphere conditions. The high frequency of low-level clouds during winter, spring and fall seasons is validated using the multi-sensor array and satellite estimates of cloud top height. Satellite vegetative fraction data provides insight into seasonal surface roughness and vegetation variability around SGP site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Boundary Layer Climatology at ARM Southern Great Plains

Operational since 1992, the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, USA, has become a reference research site for meteorological studies. Because of an open data policy the ARM data are used by researchers all over the world. In this report, we review the long-term climatology of the atmospheric boundary layer, the SGP instrumentation, the site and some site-specific atmospheric conditions, which potentially affect wind turbines in the region. Because the atmospheric boundary layer is bounded and influenced by the land surface, observations of surface radiation components and heat fluxes are crucial to understanding land–atmosphere interactions. The entrainment of air, updrafts, downdrafts, and boundary layer height characteristics is needed for understanding the structure and growth of the atmospheric boundary layer. Therefore, measurements from both ground surface in situ and remote-sensing observations at the SGP site provide an overall climatology and their interactions from ground surface up to the boundary layer. Measurements from a 60 m meteorological tower, surface flux stations, disdrometers, soil temperature and moisture flux plates, coherent Doppler lidar, Raman lidar, radiosondes, and satellite data at the SGP central facility were analyzed. All the measurements were generally made within a few square kilometers of each other at the central facility. This report focuses on data from January 2010 to June 2020 at the SGP central facility. The various sections describe the ARM SGP site and surrounding wind turbines; in situ and remotesensing instrumentation used in the report; mathematical equations to analyze fluxes, turbulence, and other boundary layer parameters; a climatological analysis of surface winds, fluxes and thermodynamic parameters for several years; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory (MOST); an analysis of the boundary layer winds and direction from a Doppler lidar; multi-year turbulence estimates through the boundary layer from a Doppler lidar; atmospheric boundary layer water vapor and relative humidity profiles from Raman lidar; cloud base height and boundary layer height from multiple sensors and satellite data; and finally site-specific atmospheric conditions, such as nocturnal low-level jets.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Geomagnetopause surface fluctuations observed by Voyager 1

The paper discusses the geomagnetopause surface fluctuations observed by Voyager 1. Normals to the magnetopause were determined for the crossings of Voyager 1 by minimum variance analysis of the internal magnetic field; the oscillating nature of the ecliptic plane component of these normals indicates that the multiple crossings were due to a wavelike surface disturbance moving tailward along the magnetopause. The estimated amplitude of these waves was small compared to their wavelengths; this conclusion is independent of any bulk normal motion of the magnetopause.

Lepping, R. P.↗
DOE OSTI2023

Calibrating radar wind profiler reflectivity factor using surface disdrometer observations

Abstract. This study uses surface disdrometer reflectivity factor estimates to calibrate the vertical and off-vertical pointing radar beams produced by an ultra high frequency (UHF) band radar wind profiler (RWP) deployed at the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) Central Facility in northern Oklahoma from April 2011 through July 2019. The methodology consists of five steps. First, the recorded Doppler velocity power spectra are adjusted to account for Nyquist velocity aliasing and coherent integration filtering effects. Second, the spectrum moments are calculated. The third step increases the signal-to-noise ratio (SNR) due to inflated noise power estimates during convective rain events that cause SNR to be biased low. The fourth step determines the RWP calibration constant for one radar beam (called the “reference” beam) by comparing uncalibrated RWP reflectivity factors at 500 m above the ground to 1 min resolution surface disdrometer reflectivity factors. The last step uses the calibrated reference beam reflectivity factor to calibrate the other radar beams during precipitation. There are two key findings. The RWP sensitivity decreased by approximately 3 to 4 dB yr−1 as the hardware aged. This drift was slow enough that the reference calibration constant can be estimated over 3-month intervals using episodic rain events. The calibrated moments are available on the DOE ARM data archive, and the Python processing code is available on public repositories.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

An OSSE on Mesoscale Model Assimilation of Simulated HIRAD-Observed Hurricane Surface Winds

The hazards of landfalling hurricanes are well known, but progress on improving the intensity forecasts of these deadly storms at landfall has been slow. Many cite a lack of high-resolution data sets taken inside the core of a hurricane, and the lack of reliable measurements in extreme conditions near the surface of hurricanes, as possible reasons why even the most state-of-the-art forecasting models cannot seem to forecast intensity changes better. The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for observing hurricanes, and is operated and researched by NASA Marshall Space Flight Center in partnership with the NOAA Atlantic Oceanographic and Meteorological Laboratory/Hurricane Research Division, the University of Central Florida, the University of Michigan, and the University of Alabama in Huntsville. This instrument?s purpose is to study the wind field of a hurricane, specifically observing surface wind speeds and rain rates, in what has traditionally been the most difficult areas for other instruments to study; the high wind and heavy rain regions. Dr. T. N. Krishnamurti has studied various data assimilation techniques for hurricane and monsoon rain rates, and this study builds off of results obtained from utilizing his style of physical initializations of rainfall observations, but obtaining reliable observations in heavy rain regions has always presented trouble to our research of high-resolution rainfall forecasting. Reliable data from these regions at such a high resolution and wide swath as HIRAD provides is potentially very valuable to mesoscale forecasting of hurricane intensity. This study shows how the data assimilation technique of Ensemble Kalman Filtering (EnKF) in the Weather Research and Forecasting (WRF) model can be used to incorporate wind, and later rain rate, data into a mesoscale model forecast of hurricane intensity. The study makes use of an Observing System Simulation Experiment (OSSE) with a simulated HIRAD dataset sampled during a hurricane and uses EnKF to forecast the track and intensity prediction of the hurricane. Comparisons to truth and error metrics are used to assess the model?s forecast performance.

Albers, Cerese↗