Milo Scientific LLC
Milo Scientific LLC
Leblanc T.,Jet Propulsion Laboratory |
Walsh T.D.,Jet Propulsion Laboratory |
McDermid I.S.,Jet Propulsion Laboratory |
Toon G.C.,Jet Propulsion Laboratory |
And 32 more authors.
Atmospheric Measurement Techniques | Year: 2011
The Measurements of Humidity in the Atmosphere and Validation Experiment (MOHAVE) 2009 campaign took place on 11-27 October 2009 at the JPL Table Mountain Facility in California (TMF). The main objectives of the campaign were to (1) validate the water vapor measurements of several instruments, including, three Raman lidars, two microwave radiometers, two Fourier-Transform spectrometers, and two GPS receivers (column water), (2) cover water vapor measurements from the ground to the mesopause without gaps, and (3) study upper tropospheric humidity variability at timescales varying from a few minutes to several days. A total of 58 radiosondes and 20 Frost-Point hygrometer sondes were launched. Two types of radiosondes were used during the campaign. Non negligible differences in the readings between the two radiosonde types used (Vaisala RS92 and InterMet iMet-1) made a small, but measurable impact on the derivation of water vapor mixing ratio by the Frost-Point hygrometers. As observed in previous campaigns, the RS92 humidity measurements remained within 5% of the Frost-point in the lower and mid-troposphere, but were too dry in the upper troposphere. Over 270 h of water vapor measurements from three Raman lidars (JPL and GSFC) were compared to RS92, CFH, and NOAA-FPH. The JPL lidar profiles reached 20 km when integrated all night, and 15 km when integrated for 1 h. Excellent agreement between this lidar and the frost-point hygrometers was found throughout the measurement range, with only a 3% (0.3 ppmv) mean wet bias for the lidar in the upper troposphere and lower stratosphere (UTLS). The other two lidars provided satisfactory results in the lower and mid-troposphere (2-5% wet bias over the range 3-10 km), but suffered from contamination by fluorescence (wet bias ranging from 5 to 50% between 10 km and 15 km), preventing their use as an independent measurement in the UTLS. The comparison between all available stratospheric sounders allowed to identify only the largest biases, in particular a 10% dry bias of the Water Vapor Millimeter-wave Spectrometer compared to the Aura-Microwave Limb Sounder. No other large, or at least statistically significant, biases could be observed. Total Precipitable Water (TPW) measurements from six different co-located instruments were available. Several retrieval groups provided their own TPW retrievals, resulting in the comparison of 10 different datasets. Agreement within 7% (0.7 mm) was found between all datasets. Such good agreement illustrates the maturity of these measurements and raises confidence levels for their use as an alternate or complementary source of calibration for the Raman lidars. Tropospheric and stratospheric ozone and temperature measurements were also available during the campaign. The water vapor and ozone lidar measurements, together with the advected potential vorticity results from the high-resolution transport model MIMOSA, allowed the identification and study of a deep stratospheric intrusion over TMF. These observations demonstrated the lidar strong potential for future long-term monitoring of water vapor in the UTLS. © Author(s) 2011.
Whiteman D.N.,NASA |
Cadirola M.,Ecotronics LLC |
Venable D.,Howard University |
Calhoun M.,Howard University |
And 11 more authors.
Atmospheric Measurement Techniques | Year: 2012
The MOHAVE-2009 campaign brought together diverse instrumentation for measuring atmospheric water vapor. We report on the participation of the ALVICE (Atmospheric Laboratory for Validation, Interagency Collaboration and Education) mobile laboratory in the MOHAVE-2009 campaign. In appendices we also report on the performance of the corrected Vaisala RS92 radiosonde measurements during the campaign, on a new radiosonde based calibration algorithm that reduces the influence of atmospheric variability on the derived calibration constant, and on other results of the ALVICE deployment. The MOHAVE-2009 campaign permitted the Raman lidar systems participating to discover and address measurement biases in the upper troposphere and lower stratosphere. The ALVICE lidar system was found to possess a wet bias which was attributed to fluorescence of insect material that was deposited on the telescope early in the mission. Other sources of wet biases are discussed and data from other Raman lidar systems are investigated, revealing that wet biases in upper tropospheric (UT) and lower stratospheric (LS) water vapor measurements appear to be quite common in Raman lidar systems. Lower stratospheric climatology of water vapor is investigated both as a means to check for the existence of these wet biases in Raman lidar data and as a source of correction for the bias. A correction technique is derived and applied to the ALVICE lidar water vapor profiles. Good agreement is found between corrected ALVICE lidar measurments and those of RS92, frost point hygrometer and total column water. The correction is offered as a general method to both quality control Raman water vapor lidar data and to correct those data that have signal-dependent bias. The influence of the correction is shown to be small at regions in the upper troposphere where recent work indicates detection of trends in atmospheric water vapor may be most robust. The correction shown here holds promise for permitting useful upper tropospheric water vapor profiles to be consistently measured by Raman lidar within NDACC (Network for the Detection of Atmospheric Composition Change) and elsewhere, despite the prevalence of instrumental and atmospheric effects that can contaminate the very low signal to noise measurements in the UT. © 2012 Author(s).
Stiller G.P.,Karlsruhe Institute of Technology |
Kiefer M.,Karlsruhe Institute of Technology |
Eckert E.,Karlsruhe Institute of Technology |
Von Clarmann T.,Karlsruhe Institute of Technology |
And 27 more authors.
Atmospheric Measurement Techniques | Year: 2012
MIPAS observations of temperature, water vapor, and ozone in October 2009 as derived with the scientific level-2 processor run by Karlsruhe Institute of Technology (KIT), Institute for Meteorology and Climate Research (IMK) and CSIC, Instituto de Astrofísica de Andalucía (IAA) and retrieved from version 4.67 level-1b data have been compared to co-located field campaign observations obtained during the MOHAVE-2009 campaign at the Table Mountain Facility near Pasadena, California in October 2009. The MIPAS measurements were validated regarding any potential biases of the profiles, and with respect to their precision estimates. The MOHAVE-2009 measurement campaign provided measurements of atmospheric profiles of temperature, water vapor/relative humidity, and ozone from the ground to the mesosphere by a suite of instruments including radiosondes, ozonesondes, frost point hygrometers, lidars, microwave radiometers and Fourier transform infra-red (FTIR) spectrometers. For MIPAS temperatures (version V4O-T-204), no significant bias was detected in the middle stratosphere; between 22 km and the tropopause MIPAS temperatures were found to be biased low by up to 2 K, while below the tropopause, they were found to be too high by the same amount. These findings confirm earlier comparisons of MIPAS temperatures to ECMWF data which revealed similar differences. Above 12 km up to 45 km, MIPAS water vapor (version V4O-H2O-203) is well within 10% of the data of all correlative instruments. The well-known dry bias of MIPAS water vapor above 50 km due to neglect of non-LTE effects in the current retrievals has been confirmed. Some instruments indicate that MIPAS water vapor might be biased high by 20 to 40% around 10 km (or 5 km below the tropopause), but a consistent picture from all comparisons could not be derived. MIPAS ozone (version V4O-O3-202) has a high bias of up to +0.9 ppmv around 37 km which is due to a non-identified continuum like radiance contribution. No further significant biases have been detected. Cross-comparison to co-located observations of other satellite instruments (Aura/MLS, ACE-FTS, AIRS) is provided as well. © 2012 Author(s).
Kottayil A.,Lulea University of Technology |
Buehler S.A.,Lulea University of Technology |
John V.O.,UK Met Office |
Miloshevich L.M.,Milo Scientific LLC |
And 2 more authors.
Journal of Atmospheric and Oceanic Technology | Year: 2012
A study has been carried out to assess the importance of radiosonde corrections in improving the agreement between satellite and radiosonde measurements of upper-tropospheric humidity. Infrared [High Resolution Infrared Radiation Sounder (HIRS)-12] and microwave [Advanced Microwave Sounding Unit (AMSU)-18] measurements from the NOAA-17 satellite were used for this purpose. The agreement was assessed by comparing the satellite measurements against simulated measurements using collocated radiosonde profiles of the Atmospheric Radiation Measurement (ARM) Program undertaken at tropical and midlatitude sites. The Atmospheric Radiative Transfer Simulator (ARTS) was used to simulate the satellite radiances. The comparisons have been done under clear-sky conditions, separately for daytime and nighttime soundings. Only Vaisala RS92 radiosonde sensors were used and an empirical correction (EC) was applied to the radiosonde measurements. The EC includes correction for mean calibration bias and for solar radiation error, and it removes radiosonde bias relative to three instruments of known accuracy. For the nighttime dataset, the EC significantly reduces the bias from 0.63 to -0.10 K in AMSU-18 and from 1.26 to 0.35 K in HIRS-12. The EC has an even greater impact on the daytime dataset with a bias reduction from 2.38 to 0.28 K in AMSU-18 and from 2.51 to 0.59 K in HIRS-12. The present study promises a more accurate approach in future radiosonde-based studies in the upper troposphere. © 2012 American Meteorological Society.
Hurst D.F.,University of Colorado at Boulder |
Hurst D.F.,National Oceanic and Atmospheric Administration |
Hall E.G.,University of Colorado at Boulder |
Hall E.G.,National Oceanic and Atmospheric Administration |
And 8 more authors.
Atmospheric Measurement Techniques | Year: 2011
We compare coincident, in situ, balloon-borne measurements of temperature (T) and pressure (P) by two radiosondes (Vaisala RS92, Intermet iMet-1-RSB) and similar measurements of relative humidity (RH) by RS92 sondes and frost point hygrometers. Data from a total of 28 balloon flights with at least one pair of radiosondes are analyzed in 1-km altitude bins to quantify measurement differences between the sonde sensors and how they vary with altitude. Each comparison (T, P, RH) exposes several profiles of anomalously large measurement differences. Measurement difference statistics, calculated with and without the anomalous profiles, are compared to uncertainties quoted by the radiosonde manufacturers. Excluding seven anomalous profiles, T differences between 19 pairs of RS92 and iMet sondes exceed their measurement uncertainty limits (2 σ) 31% of the time and reveal a statistically significant, altitude-independent bias of 0.5 ± 0.2 °C. Similarly, RS92-iMet P differences in 22 non-anomalous profiles exceed their uncertainty limits 23% of the time, with a disproportionate 83% of the excessive P differences at altitudes >16 km. The RS92-iMet pressure differences increase smoothly from -0.6 hPa near the surface to 0.8 hPa above 25 km. Temperature and P differences between all 14 pairs of RS92 sondes exceed manufacturer-quoted, reproducibility limits (σ) 28% and 11% of the time, respectively. About 95% of the excessive T differences are eliminated when 5 anomalous RS92-RS92 profiles are excluded. Only 5% of RH measurement differences between 14 pairs of RS92 sondes exceed the manufacturer's measurement reproducibility limit (σ). RH measurements by RS92 sondes are also compared to RH values calculated from frost point hygrometer measurements and coincident T measurements by the radiosondes. The influences of RS92-iMet Tand P differences on RH values and water vapor mixing ratios calculated from frost point hygrometer measurements are examined. © 2011 Author(s).