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At least 91 records · Page 5

SHADOZ (Southern Hemisphere Additional Ozonesondes): A Tropical Ozonesonde-Radiosonde Network for the Atmospheric Community

A lack of sounding data has limited the accuracy of ozone satellite retrievals in the tropics and our understanding of chemical-dynamical interactions in a region strongly influenced by natural variability and anthropogenic activity. In 1998, NASA s Goddard Space Flight Center, NOAA's Climate Monitoring and Diagnostics Laboratory (CMDL) and a team of international sponsors established the SHADOZ (Southern Hemisphere ADditional OZonesondes) project to address the gap in tropical ozone soundings. SHADOZ augments launches at selected sites and provides a public archive of ozonesonde and radiosonde data from twelve tropical and subtropical stations at http://croc.gsfc.nasa.gov/shadoz. Instrumentation, data and a summary of the first scientific findings from SHADOZ are presented.

Thompson, Anne M.↗

Effect of Ducting on Radio Occultation Measurements: An Assessment Based on High-Resolution Radiosonde Soundings

Recent studies have shown that the presence of elevated ducts in the lower atmosphere has an adverse effect on the inversion of GPS radio occultation data. The problem arises because the microwave refractivity within and below an elevated duct is no longer uniquely determined by the bending angle profile. Applying Abel inversion without a priori knowledge of the duct will introduce a negative bias in the retrieved refractivity profile within and below the duct. In this work, high vertical resolution radiosonde data are used to give a quantitative assessment of the characteristics and effects of ducts, including their frequency of occurrences, heights, and thicknesses at different latitudes and seasons. The negative bias from the Abel-retrieved refractivity profiles resulting from these ducts is also computed. The results give a strong indication that ducting in the lower troposphere is a frequent phenomenon over the tropics and midlatitudes. The ducts are shown to be predominantly caused by sharp changes in the vertical structure of water vapor. The majority of the ducts are found to be below 2 km, with a median duct layer thickness of about 100 m. The negative refractivity bias is shown to be largest below 2 km, with a median value of about 0.5-1% in the tropics and 0.2-0.5% in midlatitudes. The bias is about a factor of 2-3 smaller between 2 to 3 km and is negligible above 4 km.

signals↗

Integrating Wind Profiling Radars and Radiosonde Observations with Model Point Data to Develop a Decision Support Tool to Assess Upper-Level Winds for Space Launch

On the day-of-launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds for their launch customers to include NASA's Launch Services Program and NASA's Ground Systems Development and Operations Program. They currently do not have the capability to display and overlay profiles of upper-level observations and numerical weather prediction model forecasts. The LWOs requested the Applied Meteorology Unit (AMU) develop a tool in the form of a graphical user interface (GUI) that will allow them to plot upper-level wind speed and direction observations from the Kennedy Space Center (KSC) 50 MHz tropospheric wind profiling radar, KSC Shuttle Landing Facility 915 MHz boundary layer wind profiling radar and Cape Canaveral Air Force Station (CCAFS) Automated Meteorological Processing System (AMPS) radiosondes, and then overlay forecast wind profiles from the model point data including the North American Mesoscale (NAM) model, Rapid Refresh (RAP) model and Global Forecast System (GFS) model to assess the performance of these models. The AMU developed an Excel-based tool that provides an objective method for the LWOs to compare the model-forecast upper-level winds to the KSC wind profiling radars and CCAFS AMPS observations to assess the model potential to accurately forecast changes in the upperlevel profile through the launch count. The AMU wrote Excel Visual Basic for Applications (VBA) scripts to automatically retrieve model point data for CCAFS (XMR) from the Iowa State University Archive Data Server (http://mtarchive.qeol.iastate.edu) and the 50 MHz, 915 MHz and AMPS observations from the NASA/KSC Spaceport Weather Data Archive web site (http://trmm.ksc.nasa.gov). The AMU then developed code in Excel VBA to automatically ingest and format the observations and model point data in Excel to ready the data for generating Excel charts for the LWO's. The resulting charts allow the LWOs to independently initialize the three models 0-hour forecasts against the observations to determine which is the best performing model and then overlay the model forecasts on time-matched observations during the launch countdown to further assess the model performance and forecasts. This paper will demonstrate integration of observed and predicted atmospheric conditions into a decision support tool and demonstrate how the GUI is implemented in operations.

Bauman, William H., III↗

Standard Operating Procedure (SOP) for Flight Testing a Radiosonde and 3D Sonic Anemometer Configuration on a Multi-rotor Uninhabited Aerial System (UAS)

The purpose of this Standard Operating Procedure (SOP) is to establish a uniform procedure for initialization of a radiosonde, a 3D sonic anemometer, and collection of sounding data with correct sensor integration via a multi-rotor uninhabited aerial system (UAS) within the Langley Research Center’s (LaRC) Uninhabited Aerial System Operations Office (UASOO).

Tyler L. Willhite↗

Induction powered biological radiosonde

An induction powered implanted monitor for epidurally measuring intracranial pressure and telemetering the pressure information to a remote readout is disclosed. The monitor utilizes an inductance-capacitance (L-C) oscillator in which the C comprises a variable capacitance transducer, one electrode of which is a small stiff pressure responsive diaphragm. The oscillator is isolated from a transmitting tank circuit by a buffer circuit and all electric components in the implanted unit except an input and an output coil are shielded by a metal housing.

Fryer, T. B.↗

A portable real-time data processing system for standard meteorological radiosondes

The UMET-1 is a microprocessor-based portable system for automatic real-time processing of flight data transmitted from the standard RAWINSONDE upper atmosphere meteorological balloonsonde. The first 'target system' is described which was designed to receive data from a mobile tracking and telemetry receiving station (TRADAT), as the balloonsonde ascends to apogee. After balloon-burst, the UMET-1 produces user-ready hardcopy.

Staffanson, F. L.↗

Coordinated study of the behavior of the middle atmosphere in winter: Monthly mean comparisons of satellite and radiosonde data and derived quantities

A series of workshops were conducted for intercomparison of middle atmosphere data from a variety of sounding systems. The purposes were several: intercomparison of temperature data from various sources: characterization of any observed differences with an attempt to understand those differences, and to provide guidance to users of the data as to the validity of derived quantitites.

Grose, W. L.↗

Relationships between 6.7 micrometer imagery and radiosonde-derived parameters

The relationships between water vapor images and various thermodynamic and kinematic patterns derived from ground-based data obtained on March 6-7, 1982 are investigated. The synoptic-scale characteristics of the observed image streaks are studied. Water vapor budgets were calculated from sonde data. Variations in black body temperatures are analyzed using water vapor budgets. The data reveal that the observed warm image streaks are caused by subsidence and horizontal flux divergence of vapor.

Stewart, Michael R.↗

The Influence of Radiosonde 'Age' on TRMM Field Campaign Soundings Humidity Correction

Hundreds of Vaisala sondes with a RS80-H Humicap thin-film capacitor humidity sensor were launched during the Tropical Rainfall Measuring Mission (TRMM) field campaigns in Large Scale Biosphere-Atmosphere held in Brazil (LBA) and in Kwajalein experiment (KWAJEX) held in the Republic of Marshall Islands. Using Six humidity error correction algorithms by Wang et al., these sondes were corrected for significant dry bias in the RS80-H data. It is further shown that sonde surface temperature error must be corrected for a better representation of the relative humidity. This error becomes prominent due to sensor arm-heating in the first 50-s data.

Roy, Biswadev↗

Integrating Wind Profiling Radars and Radiosonde Observations with Model Point Data to Develop a Decision Support Tool to Assess Upper-Level Winds for Space Launch

On the day of launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds for their launch customers. During launch operations, the payload/launch team sometimes asks the LWOs if they expect the upper-level winds to change during the countdown. The LWOs used numerical weather prediction model point forecasts to provide the information, but did not have the capability to quickly retrieve or adequately display the upper-level observations and compare them directly in the same display to the model point forecasts to help them determine which model performed the best. The LWOs requested the Applied Meteorology Unit (AMU) develop a graphical user interface (GUI) that will plot upper-level wind speed and direction observations from the Cape Canaveral Air Force Station (CCAFS) Automated Meteorological Profiling System (AMPS) rawinsondes with point forecast wind profiles from the National Centers for Environmental Prediction (NCEP) North American Mesoscale (NAM), Rapid Refresh (RAP) and Global Forecast System (GFS) models to assess the performance of these models. The AMU suggested adding observations from the NASA 50 MHz wind profiler and one of the US Air Force 915 MHz wind profilers, both located near the Kennedy Space Center (KSC) Shuttle Landing Facility, to supplement the AMPS observations with more frequent upper-level profiles. Figure 1 shows a map of KSC/CCAFS with the locations of the observation sites and the model point forecasts.

Bauman, William H., III↗