David N. Whiteman

Bio: David N. Whiteman is an academic researcher from Goddard Space Flight Center. The author has contributed to research in topics: Lidar & Water vapor. The author has an hindex of 35, co-authored 94 publications receiving 4117 citations.

Raman lidar system for the measurement of water vapor and aerosols in the Earth’s atmosphere

Abstract: A nighttime operating Raman lidar system that is designed for the measurement of high vertical and temporal resolution profiles of the water vapor mixing ratio and the aerosol backscattering ratio is described. The theory of the measurements is presented. Particular attention is given to operational problems that have been solved during the development of the system. Data are presented from Sept. 1987 and described in their meteorological context.

Absolute accuracy of water vapor measurements from six operational radiosonde types launched during AWEX-G and implications for AIRS validation

Abstract: [1] A detailed assessment of radiosonde water vapor measurement accuracy throughout the tropospheric column is needed for assessing the impact of observational error on applications that use the radiosonde data as input, such as forecast modeling, radiative transfer calculations, remote sensor retrieval validation, climate trend studies, and development of climatologies and cloud and radiation parameterizations. Six operational radiosonde types were flown together in various combinations with a reference-quality hygrometer during the Atmospheric Infrared Sounder (AIRS) Water Vapor Experiment-Ground (AWEX-G), while simultaneous measurements were acquired from Raman lidar and microwave radiometers. This study determines the mean accuracy and variability of the radiosonde water vapor measurements relative to simultaneous measurements from the University of Colorado (CU) Cryogenic Frostpoint Hygrometer (CFH), a reference-quality standard of known absolute accuracy. The accuracy and performance characteristics of the following radiosonde types are evaluated: Vaisala RS80-H, RS90, and RS92; Sippican Mark IIa; Modem GL98; and the Meteolabor Snow White hygrometer. A validated correction for sensor time lag error is found to improve the accuracy and reduce the variability of upper tropospheric water vapor measurements from the Vaisala radiosondes. The AWEX data set is also used to derive and validate a new empirical correction that improves the mean calibration accuracy of Vaisala measurements by an amount that depends on the temperature, relative humidity, and sensor type. Fully corrected Vaisala radiosonde measurements are found to be suitably accurate for AIRS validation throughout the troposphere, whereas the other radiosonde types are suitably accurate under only a subset of tropospheric conditions. Although this study focuses on the accuracy of nighttime radiosonde measurements, comparison of Vaisala RS90 measurements to water vapor retrievals from a microwave radiometer reveals a 6–8% dry bias in daytime RS90 measurements that is caused by solar heating of the sensor. An AWEX-like data set of daytime measurements is highly desirable to complete the accuracy assessment, ideally from a tropical location where the full range of tropospheric temperatures can be sampled.

Accuracy assessment and correction of Vaisala RS92 radiosonde water vapor measurements

Abstract: Relative humidity (RH) measurements from Vaisala RS92 radiosondes are widely used in both research and operational applications, although the measurement accuracy is not well characterized as a function of its known dependences on height, RH, and time of day (or solar altitude angle). This study characterizes RS92 mean bias error as a function of its dependences by comparing simultaneous measurements from RS92 radiosondes and from three reference instruments of known accuracy. The cryogenic frostpoint hygrometer (CFH) gives the RS92 accuracy above the 700 mb level; the ARM microwave radiometer gives the RS92 accuracy in the lower troposphere; and the ARM SurTHref system gives the RS92 accuracy at the surface using 6 RH probes with NIST-traceable calibrations. These RS92 assessments are combined using the principle of Consensus Referencing to yield a detailed estimate of RS92 accuracy from the surface to the lowermost stratosphere. An empirical bias correction is derived to remove the mean bias error, yielding corrected RS92 measurements whose mean accuracy is estimated to be +/-3% of the measured RH value for nighttime soundings and +/-4% for daytime soundings, plus an RH offset uncertainty of +/-0.5%RH that is significant for dry conditions. The accuracy of individual RS92 soundings is further characterized by the 1-sigma "production variability," estimated to be +/-1.5% of the measured RH value. The daytime bias correction should not be applied to cloudy daytime soundings, because clouds affect the solar radiation error in a complicated and uncharacterized way.

Inversion with regularization for the retrieval of tropospheric aerosol parameters from multiwavelength lidar sounding

Abstract: We present an inversion algorithm for the retrieval of particle size distribution parameters, i.e., mean (effective) radius, number, surface area, and volume concentration, and complex refractive index from multiwavelength lidar data. In contrast to the classical Tikhonov method, which accepts only that solution for which the discrepancy reaches its global minimum, in our algorithm we perform the averaging of solutions in the vicinity of this minimum. This averaging stabilizes the underlying ill-posed inverse problem, particularly with respect to the retrieval of number concentration. Results show that, for typical tropospheric particles and 10% error in the optical data, the mean radius could be retrieved to better than 20% from a lidar on the basis of a Nd:YAG laser, which provides a combination of backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm. The accuracy is improved if the lidar is also equipped with a hydrogen Raman shifter. In this case two additional backscatter coefficients at 416 and 683 nm are available. The combination of two extinction coefficients and five backscatter coefficients then allows one to retrieve not only averaged aerosol parameters but also the size distribution function. There was acceptable agreement between physical particle properties obtained from the evaluation of multiwavelength lidar data taken during the Lindenberg Aerosol Characterization Experiment in 1998 (LACE 98) and in situ data, which were taken aboard aircraft.

Examination of the traditional Raman lidar technique. I. Evaluating the temperature-dependent lidar equations.

Abstract: The essential information required for the analysis of Raman lidar water vapor and aerosol data acquired by use of a single laser wavelength is compiled here and in a companion paper [Appl. Opt. 42, 2593 (2003)]. Various details concerning the evaluation of the lidar equations when Raman scattering is measured are covered. These details include the influence of the temperature dependence of both pure rotational and vibrational-rotational Raman scattering on the lidar profile. The full temperature dependence of the Rayleigh-Mie and Raman lidar equations are evaluated by use of a new form of the lidar equation where all the temperature dependence is carried in a single term. The results indicate that, for the range of temperatures encountered in the troposphere, the magnitude of the temperature-dependent effect can reach 10% or more for narrowband Raman water-vapor measurements. Also, the calculation of atmospheric transmission, including the effects of depolarization, is examined carefully. Various formulations of Rayleigh cross-section determination commonly used in the lidar field are compared and reveal differences of as much as 5% among the formulations. The influence of multiple scattering on the measurement of aerosol extinction with the Raman lidar technique is considered, as are several photon pulse pileup-correction techniques.

Climate Change 2007: Impacts, Adaptation and Vulnerability.

Abstract: Impatti, adattamento e vulnerabilita Le cause e le responsabilita dei cambiamenti climatici sono state trattate sul numero di ottobre della rivista Cda. Approfondiamo l’argomento presentando il documento: “Cambiamenti climatici 2007: impatti, adattamento e vulnerabilita” votato ad aprile 2007 dal secondo gruppo di lavoro del Comitato Intergovernativo sui Cambiamenti Climatici (Intergovernmental Panel on Climate Change). Si tratta del secondo di tre documenti che compongono il quarto rapporto sui cambiamenti climatici.

AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems

Abstract: The Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the Humidity Sounder for Brazil (HSB) form an integrated cross-track scanning temperature and humidity sounding system on the Aqua satellite of the Earth Observing System (EOS). AIRS is an infrared spectrometer/radiometer that covers the 3.7-15.4-/spl mu/m spectral range with 2378 spectral channels. AMSU is a 15-channel microwave radiometer operating between 23 and 89 GHz. HSB is a four-channel microwave radiometer that makes measurements between 150 and 190 GHz. In addition to supporting the National Aeronautics and Space Administration's interest in process study and climate research, AIRS is the first hyperspectral infrared radiometer designed to support the operational requirements for medium-range weather forecasting of the National Ocean and Atmospheric Administration's National Centers for Environmental Prediction (NCEP) and other numerical weather forecasting centers. AIRS, together with the AMSU and HSB microwave radiometers, will achieve global retrieval accuracy of better than 1 K in the lower troposphere under clear and partly cloudy conditions. This paper presents an overview of the science objectives, AIRS/AMSU/HSB data products, retrieval algorithms, and the ground-data processing concepts. The EOS Aqua was launched on May 4, 2002 from Vandenberg AFB, CA, into a 705-km-high, sun-synchronous orbit. Based on the excellent radiometric and spectral performance demonstrated by AIRS during prelaunch testing, which has by now been verified during on-orbit testing, we expect the assimilation of AIRS data into the numerical weather forecast to result in significant forecast range and reliability improvements.

Aerosol light absorption and its measurement: A review

Abstract: Light absorption by aerosols contributes to solar radiative forcing through absorption of solar radiation and heating of the absorbing aerosol layer. Besides the direct radiative effect, the heating can evaporate clouds and change the atmospheric dynamics. Aerosol light absorption in the atmosphere is dominated by black carbon (BC) with additional, significant contributions from the still poorly understood brown carbon and from mineral dust. Sources of these absorbing aerosols include biomass burning and other combustion processes and dust entrainment. For particles much smaller than the wavelength of incident light, absorption is proportional to the particle volume and mass. Absorption can be calculated with Mie theory for spherical particles and with more complicated numerical methods for other particle shapes. The quantitative measurement of aerosol light absorption is still a challenge. Simple, commonly used filter measurements are prone to measurement artifacts due to particle concentration and modification of particle and filter morphology upon particle deposition, optical interaction of deposited particles and filter medium, and poor angular integration of light scattered by deposited particles. In situ methods measure particle absorption with the particles in their natural suspended state and therefore are not prone to effects related to particle deposition and concentration on filters. Photoacoustic and refractive index-based measurements rely on the heating of particles during light absorption, which, for power-modulated light sources, causes an acoustic signal and modulation of the refractive index in the air surrounding the particles that can be quantified with a microphone and an interferometer, respectively. These methods may suffer from some interference due to light-induced particle evaporation. Laser-induced incandescence also monitors particle heating upon absorption, but heats absorbing particles to much higher temperatures to quantify BC mass from the thermal radiation emitted by the heated particles. Extinction-minus-scattering techniques have limited sensitivity for measuring aerosol light absorption unless the very long absorption paths of cavity ring-down techniques are used. Systematic errors can be dominated by truncation errors in the scattering measurement for large particles or by subtraction errors for high single scattering albedo particles. Remote sensing techniques are essential for global monitoring of aerosol light absorption. While local column-integrated measurements of aerosol light absorption with sun and sky radiometers are routinely done, global satellite measurements are so far largely limited to determining a semi-quantitative UV absorption index.

Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements

Abstract: The Aerosol Robotic Network (AERONET) has provided highly accurate, ground-truth measurements of the aerosol optical depth (AOD) using Cimel Electronique Sun–sky radiometers for more than 25 years In Version 2 (V2) of the AERONET database, the near-real-time AOD was semiautomatically quality controlled utilizing mainly cloud-screening methodology, while additional AOD data contaminated by clouds or affected by instrument anomalies were removed manually before attaining quality-assured status (Level 20) The large growth in the number of AERONET sites over the past 25 years resulted in significant burden to the manual quality control of millions of measurements in a consistent manner The AERONET Version 3 (V3) algorithm provides fully automatic cloud screening and instrument anomaly quality controls All of these new algorithm updates apply to near-real-time data as well as post-field-deployment processed data, and AERONET reprocessed the database in 2018 A full algorithm redevelopment provided the opportunity to improve data inputs and corrections such as unique filter-specific temperature characterizations for all visible and near-infrared wavelengths, updated gaseous and water vapor absorption coefficients, and ancillary data sets The Level 20 AOD quality-assured data set is now available within a month after post-field calibration, reducing the lag time from up to several months Near-real-time estimated uncertainty is determined using data qualified as V3 Level 20 AOD and considering the difference between the AOD computed with the pre-field calibration and AOD computed with pre-field and post-field calibration This assessment provides a near-real-time uncertainty estimate for which average differences of AOD suggest a +002 bias and one sigma uncertainty of 002, spectrally, but the bias and uncertainty can be significantly larger for specific instrument deployments Long-term monthly averages analyzed for the entire V3 and V2 databases produced average differences (V3–V2) of + 0002 with a ± 002 SD (standard deviation), yet monthly averages calculated using time-matched observations in both databases were analyzed to compute an average difference of −0002 with a ±0004 SD The high statistical agreement in multiyear monthly averaged AOD validates the advanced automatic data quality control algorithms and suggests that migrating research to the V3 database will corroborate most V2 research conclusions and likely lead to more accurate results in some cases