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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The discrepancy between stratospheric ozone profiles from balloon soundings and from other techniques: A possible explanation

Regular balloon ozone soundings with electrochemical sondes have been performed at Uccle since 1969. More than 450 ozone soundings between 1985 and 1989 were used to calculate the altitudes Zs from the VIZ radiosonde data and the altitudes Zr deduced from the tracking of the balloon train with a primary wind-finding radar. The values of Zs at fixed times appeared to be systematically too low as compared to Zr. The differences Zr-Zs increase with altitude; at 30 km the annual mean values of Zr-Zs (plus or minus standard deviation) vary between 590 plus or minus 910 m and 1410 plus or minus 1160 m, according to the pressure calibration of different manufacturing series of radiosondes. From these results it is found that around the 30 km level the ozone concentrations calculated from soundings with VIZ sondes are too low by 7.5 to 14 percent, depending upon the manufacturing series of radiosondes. At least part of the discrepancy which has often been found between ozone profiles from balloon soundings and from other techniques such as rocket observations or Umkehr measurements may be explained by this effect. An altitude correction would have important consequences as to the climatology of ozone in the middle stratosphere as adopted at the moment. About half of the day-to-day variability of ozone observed from soundings with VIZ radiosondes above the 30 km level, is induced by the variability of Zr-Zs. The agreement between altitudes calculated from radar data and Vaisala radiosondes is much better; from 34 comparative soundings a mean difference (plus or minus standard deviation) of about -300 plus/minus 180 m was found at 30 km.

Demuer, Dirk↗
NASA NTRS1987

Improved VAS regression soundings of mesoscale temperature structure observed during the 1982 atmospheric variability experiment

An Atmospheric Variability Experiment (AVE) was conducted over the central U.S. in the spring of 1982, collecting radiosonde date to verify mesoscale soundings from the VISSR Atmospheric Sounder (VAS) on the GOES satellite. Previously published VAS/AVE comparisons for the 6 March 1982 case found that the satellite retrievals scarcely detected a low level temperature inversion or a mid-tropospheric cold pool over a special mesoscale radiosonde verification network in north central Texas. The previously published regression and physical retrieval algorithms did not fully utilize VAS' sensitivity to important subsynoptic thermal features. Therefore, the 6 March 1982 case was reprocessed adding two enhancements to the VAS regression retrieval algorithm: (1) the regression matrix was determined using AVE profile data obtained in the region at asynoptic times, and (2) more optimistic signal-to-noise statistical conditioning factors were applied to the VAS temperature sounding channels. The new VAS soundings resolve more of the low level temperature inversion and mid-level cold pool. Most of the improvements stems from the utilization of asynoptic radiosonde observations at NWS sites. This case suggests that VAS regression soundings may require a ground-based asynoptic profiler network to bridge the gap between the synoptic radiosonde network and the high resolution geosynchronous satellite observations during the day.

Chesters, Dennis↗
NASA NTRS1986

Operational remote sounder (TOVS) retrieved temperature comparability with conventional in situ instruments

Monthly layer-mean TOVS retrieved temperatures for NOAA-6 and NOAA-7 from the tropics to the midlatitudes for 1980-1983 are compared to monthly layer-mean radiosonde temperature data. The amplitude of the January/July mean temperatures and the amplitude of the annual temperature cycle in the 100-70 and the 700-500 hPa layers are analyzed. It is observed that in the 100-70 hPa layer the TOVS data underestimate the annual cycle by about 3-4 K and the NOAA-6 data are closer to the radiosonde temperatures than the NOAA-7; in the 700-500 hPa layer the NOAA-6 is within + or - 1 K of the radiosonde measurements and the NOAA-7 data are within 0.5-1 K of the radiosonde data.

Schmidlin, Francis J.↗
NASA NTRS1988

Satellite/radiosonde comparison

Collocated measurements of radiosonde and TIROS Operational Vertical Sounder (TOVS) data are compared to determine whether significant latitudinal, seasonal, or instrumental biases exist. Long-wave structure determined by each system is being examined for correlation. Because U.S. radiosonde data are archived uncorrected, an effort to correct the measurements is being considered. These corrections will be applied to 7 years of measurements. New comparisons will then be made using corrected radiosonde and TOVS data. A regression method is used to retrieve temperatures, and radiosonde zonal means are used to update the regression coefficients. Preliminary results of auto-correlation analysis indicate that detection of long-wave structure in each set of data is slightly different with some levels and locations experiencing different wave periods or amplitudes. Scatter diagrams and linear regression for each layer show bias in the mean temperatures. Winter-time measurements show poorer correlations due to noisy measurements.

Schmidlin, F. J.↗
NASA NTRS1991

An assessment of VAS-derived retrievals and parameters used in thunderstorm forecasting

VAS satellite retrievals and derived parameters used in forecasting severe local storms were evaluated against corresponding radiosonde values. VAS products were also compared with the first-guess input to the retrieval algorithm. The evaluation methodology was to pair each radiosonde observation with the closest VAS retrieval within 50 km during a four-month period in 1986. VAS temperatures agreed closely with radiosonde values; dewpoints showed less agreement. Sounding differences were poorly correlated with the number of pixels from which the retrievals were prepared. VAS discrepancies usually were not well correlated with first-guess errors. Horizontal gradients of VAS products were stronger than those from radiosondes. VAS precipitable water agreed better with ground truth than did dewpoints at individual levels, but VAS thicknesses were not much improved. Results for severe storms forecasting parameters indicated that discrepancies increased with the amount of manipulation required during computation. The lifted index showed the best agreement; positive bouyant energy showed poor comparisons.

Fuelberg, Henry E.↗
NASA NTRS1999

Stratospheric Temperature Changes: Observations and Model Simulations

This paper reviews observations of stratospheric temperatures that have been made over a period of several decades. Those observed temperatures have been used to assess variations and trends in stratospheric temperatures. A wide range of observation datasets have been used, comprising measurements by radiosonde (1940s to the present), satellite (1979 - present), lidar (1979 - present) and rocketsonde (periods varying with location, but most terminating by about the mid-1990s). In addition, trends have also been assessed from meteorological analyses, based on radiosonde and/or satellite data, and products based on assimilating observations into a general circulation model. Radiosonde and satellite data indicate a cooling trend of the annual-mean lower stratosphere since about 1980. Over the period 1979-1994, the trend is 0.6K/decade. For the period prior to 1980, the radiosonde data exhibit a substantially weaker long-term cooling trend. In the northern hemisphere, the cooling trend is about 0.75K/decade in the lower stratosphere, with a reduction in the cooling in mid-stratosphere (near 35 km), and increased cooling in the upper stratosphere (approximately 2 K per decade at 50 km). Model simulations indicate that the depletion of lower stratospheric ozone is the dominant factor in the observed lower stratospheric cooling. In the middle and upper stratosphere both the well-mixed greenhouse gases (such as CO) and ozone changes contribute in an important manner to the cooling.

Ramaswamy, V.↗
NASA NTRS1999

Characterization of Climate Change and Variability with GPS

We compared zonal mean specific humidity derived from the 21 June-4 July 1995 Global Positioning System (GPS)/MET occultation observations with that derived from the European Center for Medium-Range Weather Forecasts (ECMWF) global analyses. The GPS/MET results indicate a drier troposphere, especially near the subtropical tradewind inversion. A small, moist bias in the GPS/MET upper northern-hemisphere troposphere compared to ECMWF may be due to a small radiosonde temperature bias. A diagram shows the difference (g/kg) between the GPS/MET zonal mean specific humidity and that for June-August derived from 1963-1973 radiosondes. Although the observing period is short, GPS and ECMWF results both indicate a significantly wetter boundary layer at most latitudes consistent with decadal trends observed in radiosonde data. GPS/MET results exhibit higher tropical convective available potential energy (CAPE), suggesting a more vigorous tropical Hadley circulation. Drier, free troposphere air in the descending branches of the Hadley circulation is due in part to a moist radiosonde bias but may also reflect some negative moisture feedback. Using 1992-1997 ground GPS observations and recent advancements in GPS technology, we removed an apparent altimetric drift (-1.2 +/- 0.4 mm/yr) due to columnar water vapor from the Topography (Ocean) Experiment (TOPEX) microwave radiometer, which brought the TOPEX mean sea level change estimates into better agreement with historical tide gauge records, suggesting global mean sea level is rising at a rate of 1.5-2.0 mm/yr. We can also discern a statistically significant increase of 0.2 +/- 0.1 kg/square m/yr in mean columnar water vapor over the ocean from 1992-1997. Optimal fingerprinting can be used for the detection and attribution of tropospheric warming due to an anthropogenic greenhouse. Optimal fingerprinting distinguishes between different types of signals according to their spatial and temporal patterns, while minimizing the influence of natural climate variability. S. Leroy concludes that the signal-to-noise ratio of global warming detection increases by unity approximately every 10 years if a single oceanic region is chosen. Less time for detection is likely when many global regions are considered simultaneously. GPS occultation constellations allow the possibility of detecting small changes in upper air temperature with inconsequential calibration errors, making occultation an ideal data type for global warming detection studies. Our initial study of a 22-GHz satellite-satellite occultation system predicts upper troposphere moisture sensitivities of 3-5 ppmv and 1-2 percent in the middle and lower troposphere. Additional information contained in original.

Kursinski, R.↗
NASA NTRS2003

The Use of Sage Water Vapor Data for Investigating Climate Change Issues

SAGE water vapor data has proven valuable for addressing several of the important issues in climate change research. It has been used to investigate how the upper troposphere water vapor responds to warming and convection, a key question in understanding the water vapor feedback to anthropogenic global warming. In the case of summer versus winter differences, SAGE results showed that the upper tropospheric relative humidity remained approximately constant; this result was in general agreement with how a GCM handled the seasonal difference, and gave credence to the argument that the GCM was not overestimating the water vapor feedback associated with convection. In addition, the convection-water vapor relationship was investigated further using SAGE water vapor and ISCCP cloud data. The results showed that upper tropospheric drying did appear to occur simultaneously with deep convective events in the tropics, only to be replaced by moistening a few hours later, associated (most likely) with the reevaporation of moisture from anvil clouds. The total effect was, again, a moistening of the upper troposphere associated with convection. Calculation of the actual trends in upper tropospheric moisture is a potential goal for SAGE data usage; trends calculated with radiosonde data, or instruments calibrated with radiosonde data have the problem of the effect of changing radiosonde instruments. SAGE data have in effect been used to compare different radiosondes through comparisons, and could continue to do so. SAGE 3 should also help clarify the absolute accuracy of SAGE retrievals in the troposphere. and its consequences. Model results show that water vapor increases can help explain the observations of stratospheric cooling, along with increasing C02 and ozone reduction. SAGE has been shown to provide trends similar to those of some other satellite and in situ retrievals, with increasing water vapor over time. However, SAGE is impacted by aerosol contamination which must be removed from the data; approaches used in the past will be reviewed. The SAGE water vapor errors, if taken literally, would make it hard to justify using SAGE data for such trends, and the error bars must be investigated. Stratospheric water vapor increases, like tropospheric increases, would lead to noticeable warming at the surface, and their changes must be quantified.

Rind, D.↗
NASA NTRS2009

Water Vapor Measurements by Howard University Raman Lidar during the WAVES 2006 Campaign

Retrieval of water vapor mixing ratio using the Howard University Raman Lidar is presented with emphasis on three aspects: i) performance of the lidar against collocated radiosondes and Raman lidar, ii) investigation of the atmospheric state variables when poor agreement between lidar and radiosondes values occurred and iii) a comparison with satellite-based measurements. The measurements were acquired during the Water Vapor Validation Experiment Sondes/Satellites 2006 field campaign. Ensemble averaging of water vapor mixing ratio data from ten night-time comparisons with Vaisala RS92 radiosondes shows on average an agreement within 10 % up to approx. 8 km. A similar analysis of lidar-to-lidar data of over 700 profiles revealed an agreement to within 20 % over the first 7 km (10 % below 4 km). A grid analysis, defined in the temperature - relative humidity space, was developed to characterize the lidar - radiosonde agreement and quantitatively localizes regions of strong and weak correlations as a function of altitude, temperature or relative humidity. Three main regions of weak correlation emerge: i) regions of low relative humidity and low temperature, ii) moderate relative humidity at low temperatures and iii) low relative humidity at moderate temperatures. Comparison of Atmospheric InfraRed Sounder and Tropospheric Emission Sounder satellites retrievals of moisture with that of Howard University Raman Lidar showed a general agreement in the trend but the formers miss a lot of the details in atmospheric structure due to their low resolution. A relative difference of about 20 % is usually found between lidar and satellites measurements.

Adam, M.↗
NASA NTRS2012

Comments on: Accuracy of Raman Lidar Water Vapor Calibration and its Applicability to Long-Term Measurements

In a recent publication, LeBlanc and McDermid proposed a hybrid calibration technique for Raman water vapor lidar involving a tungsten lamp and radiosondes. Measurements made with the lidar telescope viewing the calibration lamp were used to stabilize the lidar calibration determined by comparison with radiosonde. The technique provided a significantly more stable calibration constant than radiosondes used alone. The technique involves the use of a calibration lamp in a fixed position in front of the lidar receiver aperture. We examine this configuration and find that such a configuration likely does not properly sample the full lidar system optical efficiency. While the technique is a useful addition to the use of radiosondes alone for lidar calibration, it is important to understand the scenarios under which it will not provide an accurate quantification of system optical efficiency changes. We offer examples of these scenarios.

Whiteman, David N.↗
NASA NTRS2012

Evaluation of the Relative Contribution of Observing Systems in Reanalyses: Aircraft Temperature Bias and Analysis Innovations

Reanalyses have become important sources of data in weather and climate research. While observations are the most crucial component of the systems, few research projects consider carefully the multitudes of assimilated observations and their impact on the results. This is partly due to the diversity of observations and their individual complexity, but also due to the unfriendly nature of the data formats. Here, we discuss the NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) and a companion dataset, the Gridded Innovations and Observations (GIO). GIO is simply a post-processing of the assimilated observations and their innovations (forecast error and analysis error) to a common spatio-temporal grid, following that of the MERRA analysis fields. This data includes in situ, retrieved and radiance observations that are assimilated and used in the reanalysis. While all these disparate observations and statistics are in a uniform easily accessible format, there are some limitations. Similar observations are binned to the grid, so that multiple observations are combined in the gridding process. The data is then implicitly thinned. Some details in the meta data may also be lost (e.g. aircraft or station ID). Nonetheless, the gridded observations should provide easy access to all the observations input to the reanalysis. To provide an example of the GIO data, a case study evaluating observing systems over the United States and statistics is presented, and demonstrates the evaluation of the observations and the data assimilation. The GIO data is used to collocate 200mb Radiosonde and Aircraft temperature measurements from 1979-2009. A known warm bias of the aircraft measurements is apparent compared to the radiosonde data. However, when larger quantities of aircraft data are available, they dominate the analysis and the radiosonde data become biased against the forecast. When AMSU radiances become available the radiosonde and aircraft analysis and forecast error take on an annual cycle. While this supports results of previous work that recommend bias corrections for the aircraft measurements, the interactions with AMSU radiances will also require further investigation. This also provides an example for reanalysis users in examining the available observations and their impact on the analysis. GIO data is presently available alongside the MERRA reanalysis.

Bosilovich, Michael G.↗
NASA NTRS1971

Determination of stratospheric temperature and height gradients from nimbus 3 radiation data

To improve the specification of stratospheric horizontal temperature and geopotential height fields from satellite radiation data, needed for high flying aircraft, a technique was derived to estimate data between satellite tracks using interpolated IRIS 15-micron data from Nimbus III. The interpolation is based on the observed gradients of the MRIR 15-micron radiances between subsatellite tracks. The technique was verified with radiosonde data taken within 6 hours of the satellite data. The sample varied from 1126 pairs at low levels to 383 pairs at 10 mb using northern hemisphere data for June 15 to July 20, 1969. The data were separated into five latitude bands. The Rms temperature differences were generally from 2 to 5 C for all levels above 300 mb. From 500 to 300 mb RMS differences vary from 4 to 9C except at high latitudes which show values near 3C. The RMS differences between radiosonde heights and those calculated hydrostatically from the surface were from 30 to 280 meters increasing from the surface to 10 mb. Integration starting at 100 mb reduced the RMS difference in the stratosphere to 20 to 120 meters from 70 to 10 mb. From a comparison with actual operational maps at 50 and 10 mb, it appears the techniques developed produce analyses in general agreement with those from radiosonde data. In addition, they are able to indicate details over areas of sparse data not shown by conventional techniques.

Nicholas, G. W.↗
NASA NTRS1976

Mesoscale temperature and moisture fields from satellite infrared soundings

The combined use of radiosonde and satellite infrared soundings can provide mesoscale temperature and moisture fields at the time of satellite coverage. Radiance data from the vertical temperature profile radiometer on NOAA polar-orbiting satellites can be used along with a radiosonde sounding as an initial guess in an iterative retrieval algorithm. The mesoscale temperature and moisture fields at local 9 - 10 a.m., which are produced by retrieving temperature profiles at each scan spot for the BTPR (every 70 km), can be used for analysis or as a forecasting tool for subsequent weather events during the day. The advantage of better horizontal resolution of satellite soundings can be coupled with the radiosonde temperature and moisture profile both as a best initial guess profile and as a means of eliminating problems due to the limited vertical resolution of satellite soundings.

Hillger, D. W.↗
NASA NTRS1976

Investigations with satellite data temperature retrievals

A method is presented for using satellite measurements to interpolate vertical temperature soundings between radiosonde stations. The method finds a set of coefficients, which when multiplied by corresponding measured radiance quantities, yield zero temperature error at a radiosonde station. This derived set of coefficients is then applied to satellite radiance measurements at places between radiosonde stations. The computations show, for example, that the average absolute error in the layer 1000-800 mbs is only 0.3K when the corresponding 'minimum-information' method error was 2.9K. The method may be most applicable to measurements from geostationary satellites, but should also be applicable to measurements from polar orbiting satellites under certain conditions.

Fritz, S.↗
NASA NTRS1976

Recovery of atmospheric parameters from the Apollo/Soyuz-ATS-F radio occultation data

As part of the Apollo-Soyuz Test Project, Apollo was tracked in the satellite-to-satellite tracking mode by ATS-F. The tracking data obtained at occultation of Apollo by the earth has been used in this study to compute atmospheric parameters like pressure and temperature. The results of the numerical inversion have been compared with data from a radiosonde station near the occultation site. Near the surface of the earth, the refractivity computed from occultation data agreed with the radiosonde-derived values to within 3%. A pressure profile deduced from the refractivity profile by using a simplified model of the atmosphere showed good agreement with radiosonde measurements.

Rangaswamy, S.↗
NASA NTRS1977

Temperature retrievals from satellite radiance measurements - An empirical method

This paper presents a method for using satellite measurements to interpolate vertical temperature soundings between radiosonde stations. The calculations presented show that especially in the 1000-800 mb layer, where linear methods of temperature retrieval usually contain large errors, the proposed method reduces the errors substantially. The method finds a set of coefficients, which when multiplied by corresponding measured radiance quantities, yield zero temperature error at a radiosonde station. This derived set of coefficients is then applied to satellite radiance measurements at places between the radiosonde stations. The computations show, for example, that the average absolute error in the layer 1000-800 mb is only 0.3 K when the corresponding 'minimum-information' method error was 2.9 K. The method may be most applicable to measurements from geostationary satellites, but should also be applicable to measurements from polar orbiting satellites under certain conditions.

Fritz, S.↗
NASA NTRS1978

Microwave radiometer measurement of water vapor path delay: Data reduction techniques

Data reduction techniques are developed to compensate for water vapor path delay, a limiting error source in geodetic measurements made with very long baseline interferometry and in radio ranging to spacecraft. It is shown that water vapor path delay is proportional to a linear combination of saturation-corrected sky brightness temperatures, measured on and off the water vapor line. The effects of emission from liquid water droplets in clouds as well as most of the oxygen emission are removed by the off-line channel. Sky brightness temperatures are saturation-corrected or 'linearized' using estimates of effective sky temperatures made from surface temperature. Tipping curves are used to remove instrumental error. Coefficients are found by two methods: from a regression analysis of measured brightness temperatures versus radiosonde measured delay, and from a regression analysis of theoretical brightness temperatures versus radiosonde measured delay. In each case the coefficients are adjusted for differing climatic conditions by measurements of surface temperature, pressure, and relative humidity. Regression solutions are constrained to remove liquid water contributions and to give the correct slope for radiometer versus radiosonde path delay.

Claflin, E. S.↗
NASA NTRS1983

Balloon-borne pressure sensor performance evaluation utilizing tracking radars

The pressure sensors on balloon-borne sondes relate the sonde measurements to height above the Earth's surface through the hypsometric equation. It is crucial that sondes used to explore the vertical structure of the atmosphere do not contribute significant height errors to their measurements of atmospheric constituent concentrations and properties. A series of radiosonde flights was conducted. In most cases, each flight consisted of two sondes attached to a single balloon and each flight was tracked by a highly accurate C-band radar. For the first 19 radiosonde flights, the standard aneroid cell baroswitch assembly used was the pressure sensor. The last 26 radiosondes were equipped with a premium grade aneroid cell baroswitch assembly sensor and with a hypsometer. It is shown that both aneroid cell baroswitch sensors become increasingly inaccurate with altitude. The hypsometer radar differences are not strongly dependent upon altitude and it is found that the standard deviation of the differences at 35 km is 0.179 km.

Norcross, G. A.↗