Research using high (and higher) resolution radiosonde data
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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.
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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.
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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.
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.
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.
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.
Launch directors need to know upper-level wind forecasts. We developed an Excel-based GUI to display upper-level winds: (1) Rawinsonde at CCAFS, (2) Wind profilers at KSC, (3) Model point data at CCAFS.
No abstract available
The meteorological sensor calibration facility is designed to test and assess radiosonde measurement quality through actual flights in the atmosphere. United States radiosonde temperature measurements are deficient in that they require correction for errors introduced by long- and short-wave radiation. The effect of not applying corrections results in a large bias between day time and night time measurements. This day/night bias has serious implications for users of radiosonde data, of which NASA is one. The derivation of corrections for the U.S. radiosonde is quite important. Determination of corrections depends on solving the heat transfer equation of the thermistor using laboratory measurements of the emissivity and absorptivity of the thermistor coating. The U.S. radiosonde observations from the World Meteorological Organization International Radiosonde Intercomparison were used as the data base to test whether the day/night height bias can be removed. Twenty-five noon time and 26 night time observations were used. Corrected temperatures were used to calculate new geopotentials. Day/night bias in the geopotentials decreased significantly when corrections were introduced. Some testing of thermal lag attendant with the standard carbon hygristor took place. Two radiosondes with small bead thermistors imbedded in the hygristor were flown. Detailed analysis was not accomplished; however, cursory examination of the data showed that the hygristor is at a higher temperature than the external thermistor indicates.
Two correlation studies of Total Ozone Mapping Spectrometer (TOMS) data with tropopause height from radiosondes performed over Europe showed a correlation coefficient of 0.94 and 0.96. As a result, the rms error in the prediction of tropopause height from total ozone was found to be 20 mb. Correlation between tropopause height and TOMS data was the highest of all the other correlations with variables directly derived from radiosondes or simulated thermal radiances over the location of radiosondes. Comparing the two dimensional fields of TOMS, tropopause height from radiosondes and tropopause height field from TIROS-N retrievals, we can say that the first field is much closer to the true field from radiosondes than the third. The correlation coefficient for a ten-day study between TOMS data and tropopause height from radiosondes is between 0.85 and 0.9 for 30-70N. Tropopause analysis provided by GLA model also shows a very high correlation with TOMS data.
A method has been devised to ensure stable, long-term calibration of Raman lidar measurements that are used to determine the altitude-dependent mixing ratio of water vapor in the upper troposphere and lower stratosphere. Because the lidar measurements yield a quantity proportional to the mixing ratio, rather than the mixing ratio itself, calibration is necessary to obtain the factor of proportionality. The present method involves the use of calibration data from two sources: (1) absolute calibration data from in situ radiosonde measurements made during occasional campaigns and (2) partial calibration data obtained by use, on a regular schedule, of a lamp that emits in a known spectrum determined in laboratory calibration measurements. In this method, data from the first radiosonde campaign are used to calculate a campaign-averaged absolute lidar calibration factor (t(sub 1)) and the corresponding campaign-averaged ration (L(sub 1)) between lamp irradiances at the water-vapor and nitrogen wavelengths. Depending on the scenario considered, this ratio can be assumed to be either constant over a long time (L=L(sub 1)) or drifting slowly with time. The absolutely calibrated water-vapor mixing ratio (q) obtained from the ith routine off-campaign lidar measurement is given by q(sub 1)=P(sub 1)/t(sub 1)=LP(sub 1)/P(sup prime)(sub 1) where P(sub 1) is water-vapor/nitrogen measurement signal ration, t(sub 1) is the unknown and unneeded overall efficiency ratio of the lidar receiver during the ith routine off-campaign measurement run, and P(sup prime)(sub 1) is the water-vapor/nitrogen signal ratio obtained during the lamp run associated with the ith routine off-campaign measurement run. If L is assumed constant, then the lidar calibration is routinely obtained without the need for new radiosonde data. In this case, one uses L=L(sub 1) = P(sup prime)(sub 1)/t(sub 1), where P(sub 1)(sup prime) is the water-vapor/nitrogen signal ratio obtained during the lamp run associated with the first radiosonde campaign. If L is assumed to drift slowly, then it is necessary to postpone calculation of a(sub 1) until after a second radiosonde campaign. In this case, one obtains a new value, L(sub 2), from the second radiosonde campaign, and for the ith routine off-campaign measurement run, one uses an intermediate value of L obtained by simple linear time interpolation between L(sub 1) and L(sub 2).
During the period of May 11 and 12, 1974, NASA conducted its second Atmospheric Variability Experiment (AVE II) over the eastern United States. In this time interval, two Nimbus 5 orbits crossed the AVE II area, providing a series of ITPR soundings as well as THIR data. Horizontal temperature mapping of the AVE II cloud field is examined using two grid print map scales. Implied cloud top heights are compared with maximum radar-echo top reports. In addition, shelter temperatures in areas of clear sky are compared with the surface temperatures as determined from 11.5 micrometer radiometer data of the THIR experiment. The ITPR sounding accuracy is evaluated using interpolated radiosonde temperatures at times nearly coincident with the ITPR soundings. It was found that mean differences between the two data sets were as small as 1.3 C near 500 mb and as large as 2.9 C near the tropopause. The differences between ITPR and radiosonde temperatures at constant pressure levels were sufficient to induce significant differences in the horizontal temperature gradient. Cross sections of geostrophic wind along the orbital tracks were developed using a thermal wind buildup based on the ITPR temperature data and the radiosonde temperature data. Differences between the radiosonde and ITPR geostrophic winds could be explained on the basis of differences in the ITPR and radiosonde temperature gradients.
Various combinations of temperature and moisture data from the VISSR Atmospheric Sounder (VAS), conventional radiosonde data, and National Meteorological Center (NMC) global analysis, were used in a successive-correction type of objective-analysis procedure to produce analyses for 1200 GMT. The NMC global analyses served as the first-guess field for all of the objective analysis procedures. The first-guess field was enhanced by radiosonde data alone, VAS data alone, both radiosonde and VAS data, or by neither data source. In addition, two objective analyses were used in a dynamic initialization: one included only radiosonde data and the other used both radiosonde and VAS data. The dependence of 12 hour forecast skill on data type and the methods by which the data were used in the analysis/initialization were then investigated. This was done by comparison of forecast and observed fields, of sea-level pressure, temperature, wind, moisture, and accumulated precipitation. The use of VAS data in the initial conditions had a slight positive impact upon forecast temperature and moisture but a negative impact upon forecast wind. This was true for both the static and dynamic initialization experiments. Precipitation forecasts from all of the model simulations were nearly the same.