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The search for precipitation quality control (QC) methods has proven difficult. The high spatial and temporal variability associated with precipitation data causes high uncertainty and edge creep when regression-based approaches are applied. Precipitation frequency distributions are generally skewed rather than normally distributed. The commonly assumed normal distribution in QC methods is not a good representation of the actual distribution of precipitation and is inefficient in identifying the outliers. This paper first explores the use of a single gamma distribution, fit to all precipitation data, in a quality assurance test. A second test, the multiple intervals gamma distribution (MIGD) method, is introduced. It assumes that meteorological conditions that produce a certain range in average precipitation at surrounding stations will produce a predictable range at the target station. The MIGD bins the average of precipitation at neighboring stations; then, for the events in a specific bin, an associated gamma distribution is derived by fit to the same events at the target station. The new gamma distributions can then be used to establish the threshold for QC according to the user-selected probability of exceedance. This paper also explores a test (Q test) for precipitation, which uses a metric based on comparisons with neighboring stations. The performance of the three approaches is evaluated by assessing the fraction of “known” errors that can be identified in a seeded error dataset. The single gamma distribution and Q-test approach were found to be relatively efficient at identifying extreme precipitation values as potential outliers. However, the MIGD method outperforms the other two QC methods. This method identifies more seeded errors and results in fewer type I errors than the other methods. It will be adopted in the Applied Climatic Information System (ACIS) for precipitation quality control. [ABSTRACT FROM AUTHOR]

Atmospheric motion vectors (AMVs) are derived operationally at EUMETSAT from the AVHRR/3 instrument on the Polar System satellite MetOp-A since 2011. The launch of MetOp-B in 2012 allowed for doubling of the production of AMVs over the polar regions using both MetOp-A and MetOp-B satellite data. In addition to the single AVHRR polar wind product, in 2014 EUMETSAT developed a new global AVHRR wind product extracted from a pair of MetOp-A and MetOp-B images. This new product is extracted using the large overlap in the imagery data obtained from the tandem configuration of the two satellites on the same orbital plane but with a phase difference of about 50 min. The tandem configuration also provides the possibility to derive wind vectors over polar areas using a triplet of AVHRR images, keeping the same time period necessary to derive the single MetOp polar wind product but allowing for a temporal consistency check in the calculation of the AMV quality index. Three different AMV products are currently extracted from AVHRR imagery at EUMETSAT, using two or three images taken by one or two satellites having different coverage and time integration. This paper describes the scientific concept of the AVHRR wind extraction algorithm developed at EUMETSAT and presents the performances of the various AVHRR wind products. Intercomparisons of these different products highlight the role of the temporal gap between the images used to extract the wind and the impact of the consistency check on the calculation of the quality index. [ABSTRACT FROM AUTHOR]

EUMETSAT has been deriving atmospheric motion vectors (AMV) operationally from the EUMETSAT Polar System satellite MetOp over polar regions since 2011. The launch of MetOp-B in 2012 permitted doubling the frequency of extracting AMVs using AVHRR imagery data of both MetOp-A and -B satellites. The tandem configuration with two satellites on the same orbital plane, but with a phase difference, provided an interesting opportunity to create global AMVs from the satellites with a significant overlap in imagery data. EUMETSAT has therefore developed a new global AVHRR winds product derived from a pair of MetOp-A and MetOp-B images that has been operational since January 2015. The temporal gap between the two images used for tracking clouds is about 50 min. The global coverage of this new wind product allows for a homogeneous retrieval of wind product over the whole globe, including the polar regions. This clearly helps fill the gaps between 55° and 70° latitude north and south, where only few wind observations are currently available for assimilation into numerical weather prediction models. The new global AVHRR wind product can be directly compared with AMVs derived from geostationary satellites. This paper describes the scientific concept of wind extraction using dual MetOp satellites. It highlights the performance of the new global AVHRR wind product by comparing with collocated AMVs extracted from the EUMETSAT geostationary satellites Meteosat-7 and Meteosat-10. [ABSTRACT FROM AUTHOR]

Reliable and accurate environmental sensing is a cornerstone of modern meteorology. This paper presents a laboratory environmental simulator capable of reproducing extreme environments and performing tests and calibrations of meteorological sensor systems under controlled conditions. This facility is available to the research community as well as industry and is intended to encourage advancement in the field of sensor metrology applied to meteorology and climatology. Discussion will be made of the temperature, pressure, humidity and wind flow control, and sensing systems with reference to specific sensor test programs and future research activities. [ABSTRACT FROM AUTHOR]

This paper presents a method for tomographically reconstructing spatially varying three-dimensional atmospheric temperature profiles and wind velocity fields based on passive acoustic travel time measurements between a small unmanned aerial vehicle (UAV) and ground-based microphones. A series of simulations are presented to provide an indication of the performance of the technique. The parametric fields are modeled as the weighted sum of radial basis functions (RBFs) or Fourier series, which also allow local meteorological measurements made at the UAV and ground receivers to supplement any time delay observations. The technique has potential for practical applications such as boundary layer meteorology and theories of atmospheric turbulence and wave propagation through a turbulent atmosphere. [ABSTRACT FROM AUTHOR]

In this paper, different partitioning techniques and methods to identify wind sea and swell are investigated, addressing both 1D and 2D schemes. Current partitioning techniques depend largely on arbitrary parameterizations to assess if wave systems are significant or spurious. This makes the implementation of automated procedures difficult, if not impossible, to calibrate. To avoid this limitation, for the 2D spectrum, the use of a digital filter is proposed to help the algorithm keep the important features of the spectrum and disregard the noise. For the 1D spectrum, a mechanism oriented to neglect the most likely spurious partitions was found sufficient for detecting relevant spectral features. Regarding the identification of wind sea and swell, it was found that customarily used methods sometimes largely differ from one another. Evidently, methods using 2D spectra and wind information are the most consistent. In reference to 1D identification methods, attention is given to two widely used methods, namely, the steepness method used operationally at the National Data Buoy Center (NDBC) and the Pierson–Moskowitz (PM) spectrum peak method. It was found that the steepness method systematically overestimates swell, while the PM method is more consistent, although it tends to underestimate swell. Consistent results were obtained looking at the ratio between the energy at the spectral peak of a partition and the energy at the peak of a PM spectrum with the same peak frequency. It is found that the use of partitioning gives more consistent identification results using both 1D and 2D spectra. [ABSTRACT FROM AUTHOR]

Geostationary infrared sounding missions offer good temporal coverage; however, because of the large distance to the observed earth targets, the effect of diffraction is increased compared to sounding from a low earth orbit (LEO). Because of the wavelength dependence of diffraction, the spectral channels do not sample the same volume of air, as is generally assumed by retrieval algorithms for LEO infrared (IR) sounder data. This additional error introduced in the retrieval by diffraction-limited instruments is called pseudonoise throughout the paper. One such diffraction-limited geostationary system is the candidate Infrared Sounder (IRS) mission on the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Meteosat Third Generation (MTG) satellites with a planned need date in 2015, due to the expected lifetime of the current Meteosat Second Generation (MSG) satellites. A simplified point spread function (PSF) is applied. To represent the channels within natural conditions, measured spectra from the LEO Atmospheric Infrared Sounder (AIRS) are used as an underlying scene when integrating over the PSF. As the AIRS spatial resolution is 15 km, the basic assumption made was that the meteorological and surface features can be regarded as fractal to the extent that they can be downscaled to at least 4 km, making them useful for these investigations. The results show that the pseudonoise is highly dependent on wavelength, and highest in the window and CO2 regions (within the broader 700–1200 cm-1, or 8.3–14.3-μm, region). The worst-case pseudonoise values are approximately 1 K for these regions. A case study of the impact of the obtained pseudonoise values on temperature and water vapor retrievals shows that only with the worst-case assumptions (uncorrelated noise) is there a quantifiable impact on the results. For temperature retrievals, this ranged from 0.1 to 0.3 K in the lower and upper troposphere, respectively. [ABSTRACT FROM AUTHOR]

Ultrasonic anemometers are widely used to investigate turbulence in the surface layer. Some of their advantages are high-frequency sampling, the ability to work for long periods without a resident operator (even in adverse meteorological conditions), and their calibration related only to design parameters. In this paper an analysis of the random uncertainty associated with ultrasonic anemometer measurements is reported. The analysis is based on a statistical procedure that compares the simultaneous data taken with two identical anemometers operating in nominally identical conditions. Postprocessing of data has been carried out in different reference systems in order to evaluate how the random uncertainties change according to the postprocessing procedure used. Results show that uncertainty on wind velocity decreases with averaging time, and it can be as low as 1 cm s-1 for a typical averaging time of 30 min. The random uncertainty on average vertical wind velocity could also be as low as 1 cm s-1, and it is very sensitive to the effects of vertical misalignment. The analysis is based on six different measurement sets in which the anemometers have been deployed on a single mast or in two separate masts with and without additional detectors placed near the anemometers themselves. Results indicate that the uncertainty of all the measured parameters increases when the anemometer is used in configurations in which they are placed on separate masts. Several parameters also show an additional increase of uncertainty if other detectors are placed nearby. The relative random uncertainty on momentum and sensible heat fluxes, for typical averaging time, can be as low as 6%–7% and it could increase to a factor of 2–3 when they are placed on separate masts. Only small effects due to the influence of flow distortions caused by the presence of additional sensors have been found on fluxes and are mainly related to sensible heat flux. [ABSTRACT FROM AUTHOR]

The parameterization of physical processes in atmospheric general circulation models contributes to load imbalances among individual processors of message-passing distributed-multiprocessor systems. Load imbalances increase the overall time to completion of a model run and should be eliminated or reduced as much as possible. Presented herein is a new technique that shows promise for load balancing the parameterization of moist convection found in the Community Climate System Model's (CCSM's) Community Atmosphere Model version 3 (CAM3). At the heart of this technique is a load index that is a marker for moist convection (called a model data load index). The marker for moist convection correlates directly to the amount of processing time per model grid cell and can therefore be used to effect a load balance. Spatial locality on the model grid and temporal locality between model time steps exist that allow a decomposition from a load-balancing step to be retained for multiple time steps. The analysis in this paper shows that the load balance does not need to be applied at every time step and that the number of steps in which the previous load balance remains effective is large enough for the overhead to be cost effective. Tests performed indicate that this technique is scalable to higher-resolution models as well as to higher processor counts than those presented. Through the use of the Load Balancing and Scheduling Framework (LBSF), this technique shows promise in reducing (by ∼47%) the time of the unbalanced load of one particular subroutine in CAM3 at the T85 spectral truncation. A maximum of 3.75 s of total execution time is saved over a 2430-time-step simulation. When extrapolated to a 1000-yr simulation, this translates to a potential savings of ∼22 h in that subroutine alone. Similar methods applied to remaining subroutines can add up to a significant savings. These results are encouraging in that a fine-grained load-balancing technique using the evolving characteristics of geophysical data paves the way for load balancing a broad range of physical calculations, both in CAM3 and other scientific applications, where more general techniques are not practical. [ABSTRACT FROM AUTHOR]

Two methods for the estimation of the turbulence energy dissipation rate (TEDR) from data measured by a 2-μm coherent Doppler lidar are described in this paper. Based on data measured at the Tarbes-Lourdes-Pyrénées International Airport in summer 2003, height profiles of TEDR have been retrieved. The results of TEDR estimation both from the Doppler spectrum width and from the velocity structure function are compared. Moreover, the experiment has been treated by numerical simulation and the theoretical results have been used for verification of the described methods. [ABSTRACT FROM AUTHOR]

A field experiment to study the spectral balance of the source terms for wind-generated waves in finite water depth was carried out in Lake George, Australia. The measurements were made from a shore-connected platform at varying water depths from 1.2 m down to 20 cm. Wind conditions and the geometry of the lake were such that fetch-limited conditions with fetches ranging from approximately 10 km down to 1 km prevailed. The resulting waves were intermediate-depth wind waves with inverse wave ages in the range 1 < U10/Cp < 8. The atmospheric input, bottom friction, and whitecap dissipation were measured directly and synchronously by an integrated measurement system, described in the paper. In addition, simultaneous data defining the directional wave spectrum, atmospheric boundary layer profile, and atmospheric turbulence were available. The contribution to the spectral evolution due to nonlinear interactions of various orders is investigated by a combination of bispectral analysis of the data and numerical modeling. The relatively small scale of the lake enabled experimental conditions such as the wind field and bathymetry to be well defined. The observations were conducted over a 3-yr period, from September 1997 to August 2000, with a designated intensive measurement period [the Australian Shallow Water Experiment (AUSWEX)] carried out in August–September 1999. High data return was achieved. [ABSTRACT FROM AUTHOR]

The applicability of meteorological general circulation models (GCMs) is limited by their spatial resolution. In this paper, a method is developed for improving the resolution of GCM-generated rainfall fields, using ideas from Bayesian image analysis to improve the resolution of the binary wet--dry image. This approach incorporates both the spatial and temporal memory of the rainfall field and can be adapted to utilize any available physical information. The method is illustrated using data from a network of weather radar stations in Arkansas, and some informal diagnostic procedures are developed for assessing the adequacy of the underlying model. [ABSTRACT FROM AUTHOR]

A technique has been developed for the retrieval of three-dimensional particle velocities from Doppler data obtained with an airborne radar. The 95-GHz radar was mounted on the University of Wyoming KingAir aircraft. The retrieval technique is derived from the velocity azimuth display (VAD) analysis and is termed the airborne velocity azimuth display (AVAD). Data for this analysis are taken when the radar beam is scanned by the turning of the aircraft. As in VAD analysis, a functional form for the horizontal variation of the velocity of the scatterers must be assumed. The components of the velocity field are then determined using a least squares fit to the Doppler velocities. The AVAD technique differs from VAD analysis because of the mobility of the platform and its proximity to regions of interest, and it is due to geometric considerations dictated by the turning of the aircraft. The analysis region is only a few kilometers in diameter--considerably smaller than for a ground-based VAD analysis. This reduces the required area of cloud coverage and the importance of horizontal variations in the wind field. However, the reduced analysis area also limits the accuracy with which higher-order characteristics of the wind field, such as divergence, can be resolved. This paper presents the AVAD technique and describes the data processing required. Results from multiple AVAD analyses from flights on two days are presented and are shown to be in generally good agreement with winds measured by sensors on board the KingAir. [ABSTRACT FROM AUTHOR]

The present study is devoted to a new analysis of wind measurements from dropsonding and/or radiosonding of Doppler information from multiple Doppler radar scanning and of other wind measurements (sodar, dynamical sensors on board aircraft, and instruments at ground) aimed at retrieving three-dimensional thermodynamical and dynamical fields both in clear air and in precipitating areas of mesoscale phenomena. This analysis, well suited to assimilate data from differing platforms specified at differing spatial/temporal resolutions, is based on the analytical and variational concept of the Multiple Analytical Doppler (MANDOP) analysis and thus is an extension of it. This new analysis presents many advantages, including the same as MANDOP and others well adapted for the verification or the initialization of a mesoscale cloud model. An application to simulated and to real data extracted from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment database is presented in the paper. [ABSTRACT FROM AUTHOR]

There is a growing use of multiparameter radars for observation of the atmosphere and, in particular, for remote sensing of rain. Radar systems have the undeniable advantage of being able to monitor very large areas with a single installation in real time. On the other hand, their measurements are often only qualitative; the conversion of the radar measurables into meteorological quantities (like rain rate) is not unique, depending on the model assumed for the target. In this context, the availability of sophisticated radar simulators can prove to be extremely useful to try and discriminate the effect of the different contributions on the received echoes. In this paper a physically based software radar simulator is presented; the synthetic radar signal is generated by adding up (in amplitude and phase) all the contributions coming from each single scatterer present into a virtual meteorological environment. The characteristics of the radar system are properly taken into account, as well as the effects of propagation and wave polarization. [ABSTRACT FROM AUTHOR]

Global positioning system (GPS) signals reflected from the ocean surface can be used for various remote sensing purposes. Some possibilities include measurements of surface roughness characteristics from which the rms of wave slopes, wind speed, and direction could be determined. In this paper, reflected GPS measurements that were collected using aircraft with a delay mapping GPS receiver are used to explore the possibility of determining ocean surface wind speed and direction during flights to Hurricanes Michael and Keith in October 2000. To interpret the GPS data, a theoretical model is used to describe the correlation power of the reflected GPS signals for different time delays as a function of geometrical and sea-roughness parameters. The model employs a simple relationship between surface-slope statistics and both a wind vector and wave age or fetch. Therefore, for situations when this relationship holds there is a possibility of indirectly measuring the wind speed and the wind direction. Wind direction estimates are based on a multiple-satellite nonlinear least squares solution. The estimated wind speed using surface-reflected GPS data collected at wind speeds between 5 and 10 m s-1 shows an overall agreement of better than 2 m s-1 with data obtained from nearby buoy data and independent wind speed measurements derived from TOPEX/Poseidon, European Remote Sensing (ERS), and QuikSCAT observations. GPS wind retrievals for strong winds in the close vicinity to and inside the hurricane are significantly less accurate. Wind direction agreement with QuikSCAT measurements appears to be at the 30° level when the airplane has both a stable flight level and a stable flight direction. Discrepancies between GPS retrieved wind speeds/directions and those obtained by other means are discussed and possible explanations are proposed. [ABSTRACT FROM AUTHOR]

In this paper, a new method of dual-Doppler radar wind analysis based on a three-dimensional variational data assimilation (3DVAR) approach is proposed. In it, a cost function, including background term and radial observation term, is minimized through a limited memory, quasi-Newton conjugate-gradient algorithm with the mass continuity equation imposed as a weak constraint. In the method, the background error covariance matrix, though simple in this case, is modeled by a recursive filter. Furthermore, the square root of this matrix is used to precondition the minimization problem. The current method is applied to Doppler radar observation of a supercell storm, and the analysis results are compared to a conceptual model and previous research. It is shown that the horizontal circulations, both within and around the storms, as well as the strong updraft and the associated downdraft, are well analyzed. Because no explicit integration of the anelastic mass continuity equation is involved, error accumulation associated with such integration is avoided. As a result, the method is less sensitive to the vertical boundary uncertainties. [ABSTRACT FROM AUTHOR]

The relaxed eddy accumulation (REA) method has become a standard tool for scalar flux measurements near the surface during field experiments. With this technique, turbulent fluxes of relatively slowly reacting species are measured using the difference in the mean concentration between air samples accumulated during updrafts and downdrafts. A prototype of a relaxed eddy accumulator adapted to air-sea flux measurements aboard a research vessel was developed at the Centre National de Recherches Meteorologiques (CNRM) and was implemented on board the research vessel L'Atalante during the Programme Océan Multidisciplinaire Méso-Echelle (POMME) experiment (March-April 2001). When this technique is used on a mobile platform, a major difficulty is the real-time calculation of the true vertical wind corrected for platform motions. The different stages of this computation are described in this paper. In addition, a ground-based version of the system was tested over a maize field during the Expérience sur Sites pour Contraindre les Modèles de Pollution Atmosphérique et de Transport d'Emission (ESCOMPTE) experiment. With this simplified prototype in which the motion corrections were not needed, the effect of filtering the vertical velocity signal was evaluated and the accuracy of the gas analysis system was estimated. Water vapor, carbon dioxide (CO2), and nitrogen oxides flux over the maize field was measured by this technique. The validation of the system was carried out through comparisons between fluxes obtained by other methods (eddy covariance for CO2 and latent heat flux during ESCOMPTE, and bulk method for latent heat flux during POMME). Good correlations were observed between latent heat and CO2 fluxes measured by eddy covariance and REA techniques for the ESCOMPTE dataset. During the POMME experiment, the correlation between REA and the bulk method is reasonably good (r = 0.83) for latent heat flux. However, since the bulk method is not a direct method, this correlation is slightly lower than the comparisons during the ESCOMPTE experiment. Eventually, the scatter is of the same order of magnitude as that observed between various air-sea flux techniques (for instance, between eddy-covariance and bulk air-sea fluxes). This result leads the authors to consider that their system can be used aboard ships in the future to measure fluxes of trace species at the ocean-atmosphere interface, provided that the analyzer used is accurate enough to detect and measure the concentration difference between the two reservoirs. [ABSTRACT FROM AUTHOR]

As the U.S. Science Team's globally gridded precipitation product from the NASA--JAXA Global Precipitation Measurement (GPM) mission, the Integrated Multi-Satellite Retrievals for GPM (IMERG) estimates the surface precipitation rates at 0.18 every half hour using spaceborne sensors for various scientific and societal applications. One key component ofIMERG is the morphing algorithm, which uses motion vectors to perform quasi-Lagrangian interpolation to fill in gaps in the passive microwave precipitation field using motion vectors. Up to IMERG V05, the motion vectors were derived from the large-scale motions of infrared observations of cloud tops. This study details the changes introduced in IMERG V06 to derive motion vectors from large-scale motions of selected atmospheric variables in numerical models, which allow IMERG estimates to be extended from the 608N--608S latitude band to the entire globe. Evaluation against both instantaneous passive microwave retrievals and ground measurements demonstrates the general improvement in the precipitation field of the new approach. Most of the model variables tested exhibited similar performance, but total precipitable water vapor was chosen as the source of the motion vectors for IMERG V06 due to its competitive performance and global completeness. Continuing assessments will provide further insights into possible refinements of this revised morphing scheme in future versions of IMERG. [ABSTRACT FROM AUTHOR]

Sea level changes within wide temporal–spatial scales have great influence on oceanic and atmospheric circulations. Efforts have been made to identify long-term sea level trend and regional sea level variations on different time scales. A nonuniform sea level rise in the tropical Pacific and the strengthening of the easterly trade winds from 1993 to 2012 have been widely reported. It is well documented that sea level in the tropical Pacific is associated with the typical climate modes. However, sea level change on interannual and decadal time scales still requires more research. In this study, the Pacific sea level anomaly (SLA) was decomposed into interannual and decadal time scales via an ensemble empirical mode decomposition (EEMD) method. The temporal–spatial features of the SLA variability in the Pacific were examined and were closely associated with climate variability modes. Moreover, decadal SLA oscillations in the Pacific Ocean were identified during 1993–2016, with the phase reversals around 2000, 2004, and 2012. In the tropical Pacific, large sea level variations in the western and central basin were a result of changes in the equatorial wind stress. Moreover, coherent decadal changes could also be seen in wind stress, sea surface temperature (SST), subtropical cells (STCs), and thermocline depth. Our work provided a new way to illustrate the interannual and decadal sea level variations in the Pacific Ocean and suggested a coupled atmosphere–ocean variability on a decadal time scale in the tropical region with two cycles from 1993 to 2016. [ABSTRACT FROM AUTHOR]

In this study, the effect of assimilating Himawari-8 (HIMA-8) atmospheric motion vectors (AMVs) on forecast errors in East Asia is evaluated using observation system experiments based on the Weather Research and Forecasting Model and three-dimensional variational data assimilation system. The experimental period is from 1 August to 30 September 2015, during which both HIMA-8 and Multifunctional Transport Satellite-2 (MTSAT-2) AMVs exist. The energy-norm forecast error based on the analysis of each experiment as reference was reduced more by replacing MTSAT-2 AMVs with HIMA-8 AMVs than by adding HIMA-8 AMVs to the MTSAT-2 AMVs. When the HIMA-8 AMVs replaced or were added to MTSAT-2 AMVs, the observation impact was reduced, which implies the analysis–forecast system was improved by assimilating HIMA-8 AMVs. The root-mean-square error (RMSE) of the 500-hPa geopotential height forecasts based on the analysis of each experiment decreases more effectively when the region lacking in upper-air wind observations is reduced by assimilating both MTSAT-2 and HIMA-8 AMVs. When the upper-air radiosonde (SOUND) observations are used as reference, assimilating more HIMA-8 AMVs decreases the forecast error. Based on various measures, the assimilation of HIMA-8 AMVs has a positive effect on the reduction of forecast errors. The effects on the energy-norm forecast error and the RMSE based on SOUND observations are greater when HIMA-8 AMVs replaced MTSAT-2 AMVs. However, the effects on the RMSE of the 500-hPa geopotential height forecasts are greater when both HIMA-8 and MTSAT-2 AMVs were assimilated, which implies potential benefits of assimilating AMVs from several satellites for forecasts over East Asia depending on the choice of measurement. [ABSTRACT FROM AUTHOR]

A systematic evaluation of the performance of the World Wide Lightning Location Network (WWLLN) over the Tibetan Plateau is conducted using data from the Cloud-to-Ground Lightning Location System (CGLLS) developed by the State Grid Corporation of China for 2013-15 and lightning data from the satellite-based Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) for 2014-15. The average spatial location separation magnitudes in the midsouthern Tibetan Plateau (MSTP) region between matched WWLLN and CGLLS strokes and over the whole Tibetan Plateau between matched WWLLN and LIS flashes were 9.97 and 10.93 km, respectively. The detection efficiency (DE) of the WWLLN rose markedly with increasing stroke peak current, and the mean stroke peak currents of positive and negative cloud-to-ground (CG) lightning detected by the WWLLN in the MSTP region were 62.43 and -56.74 kA, respectively. The duration, area, and radiance of the LIS flashes that were also detected by the WWLLN were 1.27, 2.65, and 4.38 times those not detected by the WWLLN. The DE of the WWLLN in the MSTP region was 9.37% for CG lightning and 2.58% for total lightning. Over the Tibetan Plateau, the DE of the WWLLN for total lightning was 2.03%. In the MSTP region, the CG flash data made up 71.98% of all WWLLN flash data. Based on the abovementioned results, the ratio of intracloud (IC) lightning to CG lightning in the MSTP region was estimated to be 4.05. [ABSTRACT FROM AUTHOR]

The Stevens Institute of Technology Estuarine and Coastal Ocean Model (sECOM) is coupled here with the Mellor-Donelan-Oey (MDO) wave model to simulate coastal flooding due to storm tides and waves. sECOM is the three-dimensional (3D) circulation model used in the New York Harbor Observing and Prediction System (NYHOPS). The MDO wave model is a computationally cost-effective spectral wave model suitable for coupling with 3D circulation models. The coupled sECOM-MDO model takes into account wave-current interactions through wave-enhanced water surface roughness and wind stress, wave-current bottom stress, and depth-dependent wave radiation stress. The model results are compared with existing laboratory measurements and the field data collected in New York-New Jersey (NY-NJ) harbor during Hurricane Sandy. Comparisons between the model results and laboratory measurements demonstrate the capabilities of the model to accurately simulate wave characteristics, wave-induced water elevation, and undertow current. The model results for Hurricane Sandy reveal the successful performance of sECOM-MDO in situations where high waves and storm tides coexist. The results indicate that the temporal maximum wave setup in NY-NJ harbor was 0.26 m. On the other hand, the contribution of wave setup to the peak storm tide was 0.13 m, a contribution of only 3.8%. It is found that the inclusion of wave radiation stress and wave-enhanced bottom friction in the circulation model can reduce the errors in the calculated storm tides. At the Battery (New York), for example, the root-mean-square error reduced from 0.17 to 0.12 m. [ABSTRACT FROM AUTHOR]

A wind profiler network with a total of 65 profiling radar systems was operated by the China Meteorological Observation Center (MOC) of the China Meteorological Administration (CMA) until July 2015. In this study, a quality control procedure is constructed to incorporate the profiler data from the wind-profiling network into the local data assimilation and forecasting systems. The procedure applies a blacklisting check that removes stations with gross errors and an outlier check that rejects data with large deviations from the background. As opposed to the biweight method, which has been commonly implemented in outlier elimination for univariate observations, the outlier elimination method is developed based on the iterated reweighted minimum covariance determinant (IRMCD) for multivariate observations, such as wind profiler data. A quality control experiment is performed separately for subsets containing profiler data tagged with/without rain flags in parallel every 0000 and 1200 UTC from 20 June to 30 September 2015. The results show that with quality control, the frequency distributions of the differences between the observations and the model background meet the requirements of a Gaussian distribution for data assimilation. A further intensive assessment of each quality control step reveals that the stations rejected by the blacklisting contained poor data quality and that the IRMCD rejects outliers in a robust and physically reasonable manner. Detailed comparisons between the IRMCD and the biweight method are performed, and the IRMCD is demonstrated to be more efficient and more comprehensive regarding the dataset used in this study. [ABSTRACT FROM AUTHOR]

An optical flow algorithm based on polynomial expansion (OFAPE) was used to derive atmospheric motion vectors (AMVs) from geostationary satellite images. In OFAPE, there are two parameters that can affect the AMV results: the sizes of the expansion window and optimization window. They should be determined according to the temporal interval and spatial resolution of satellite images. A helpful experiment was conducted for selecting those sizes. The limitations of window sizes can cause loss of strong wind speed, and an image-pyramid scheme was used to overcome this problem. Determining the heights of AMVs for semitransparent cloud pixels (STCPs) is challenging work in AMV derivation. In this study, two-dimensional histograms (H2Ds) between infrared brightness temperatures (6.7- and 10.8- μm channels) formed from a long time series of cloud images were used to identify the STCPs and to estimate their actual temperatures/heights. The results obtained from H2Ds were contrasted with CloudSat radar reflectivity and CALIPSO cloud-feature mask data. Finally, in order to verify the algorithm adaptability, three-month AMVs (JJA 2013) were calculated and compared with the wind fields of ERA data and the NOAA/ESRL radiosonde observations in three aspects: speed, direction, and vector difference. [ABSTRACT FROM AUTHOR]

Use of an airborne platform to determine the dynamics of atmospheric motion has been ongoing for over three decades. Much of the effort has been centered on the determination of the horizontal pressure gradient force along an isobaric surface, and with wind measurements the nongeostrophic components of motion can be obtained. Recent advances using differential GPS-based altitude measurements allow accurate assessment of the geostrophic wind. Porpoise or sawtooth maneuvers are used to determine the vertical cross section of the horizontal pressure gradient force. D-values, the difference of the height of a given pressure level from that in a reference atmosphere, are used to isolate the vertical structure of the horizontal component of the pressure gradient force from the vastly larger hydrostatic pressure gradient. Comparison of measured D-value cross sections with airborne measurements of the horizontal pressure gradient is shown. Comparison of D-values with output from the WRF Model demonstrates that the airborne measurements are consistent with finescale numerical simulations. This technique provides a means of inferring the thermal wind, thereby enabling a detailed examination of the vertical structure of the forcing of mesoscale and synoptic-scale wind regimes. [ABSTRACT FROM AUTHOR]

Monitoring surface currents by coastal high-frequency radars (HFRs) is a cost-effective observational technique with good prospects for further development. An important issue in improving the efficiency of HFR systems is the optimization of radar positions on the coastline. Besides being constrained by environmental and logistic factors, such optimization has to account for prior knowledge of local circulation and the target quantities (such as transports through certain key sections) with respect to which the radar positions are to be optimized. In the proposed methodology, prior information of the regional circulation is specified by the solution of the 4D variational assimilation problem, where the available climatological data in the Bering Strait (BS) region are synthesized with dynamical constraints of a numerical model. The optimal HFR placement problem is solved by maximizing the reduction of a posteriori error in the mass, heat, and salt (MHS) transports through the target sections in the region. It is shown that the MHS transports into the Arctic and their redistribution within the Chukchi Sea are best monitored by placing HFRs at Cape Prince of Wales and on Little Diomede Island. Another equally efficient configuration involves placement of the second radar at Sinuk (western Alaska) in place of Diomede. Computations show that 1) optimization of the HFR deployment yields a significant (1.3-3 times) reduction of the transport errors compared to nonoptimal positioning of the radars and 2) error reduction provided by two HFRs is an order of magnitude better than the one obtained from three moorings permanently maintained in the region for the last 5 yr. This result shows a significant advantage of BS monitoring by HFRs compared to the more traditional technique of in situ moored observations. The obtained results are validated by an extensive set of observing system simulation experiments. [ABSTRACT FROM AUTHOR]

Passive microwave observations from the Microwave Sounding Unit (MSU) and the Advanced Microwave Sounding Unit-A (AMSU-A) have been exploited widely for numerical weather prediction (NWP), atmospheric reanalyses, and climate monitoring studies. The treatment of biases in these observations, with respect to models as well as between satellites, has been the focus of much effort in recent years. This study presents evidence that shifts, drifts, and uncertainties in pass band center frequencies are a significant contribution to these biases. Center frequencies for AMSU-A channels 6-14 and MSU channel 3 have been analyzed using NWP fields and radiative transfer models, for a series of operational satellites covering the period 1979-2012. AMSU-A channels 6 (54.40 GHz), 7 (54.94 GHz), and 8 (55.50 GHz) on several satellites exhibit significant shifts and drifts relative to nominal pass band center frequencies. No significant shifts were found for AMSU-A channels 9-14, most probably as a consequence of the active frequency locking of these channels. For MSU channel 3 (54.96 GHz) most satellites exhibit large shifts, the largest for the earliest satellites. For example, for the first MSU on the Television and Infrared Observation Satellite-N (TIROS-N), the analyzed shift is 68 MHz over the lifetime of the satellite. Taking these shifts into account in the radiative transfer modeling significantly improves the fit between model and observations, eliminates the strong seasonal cycle in the model-observation misfit, and significantly improves the bias between NWP models and observations. The study suggests that, for several channels studied, the dominant component of the model-observation bias results from these spectral errors, rather than radiometric bias due to calibration errors. [ABSTRACT FROM AUTHOR]

In this study, sensitivities of the track and intensity forecasts of Typhoon Megi (2010) to the Cooperative Institute for Meteorological Satellite Studies (CIMSS) University of Wisconsin satellite atmospheric motion vector (AMV) dataset are examined. Assimilation of the CIMSS AMV dataset using the local ensemble transform Kalman filter implemented in the Weather Research and Forecasting model shows that the AMV data can significantly improve the track forecast of Typhoon Megi, especially the sharp turn from west-northwest to north after crossing the Philippines. By broadening the western Pacific subtropical high to the west, the AMV data can help reduce the eastward bias of the track, thus steering the storm away inimical shear environment and facilitating its subsequent development. Further sensitivity experiments with separated assimilation of the low- to midlevel (800-300 hPa) and upper-level (300-100 hPa) AMV winds reveal that, despite the sparse distribution of the low-level AMV winds with most of the data points located in the periphery of Megi's main circulation, the track forecasts tend to be more sensitive to the low-level than to the upper-level wind observations. This indicates that the far-field low-level observations can improve the large-scale environmental flow that storms are to move in, giving rise to a better representation of the steering flow and subsequent intensity change. While much of the recent effort in tropical cyclone research focuses on inner-core observations to improve the intensity forecast, the results in this study show that the peripheral observations outside the storm center could contribute considerably to the intensity and track forecasts and deserve attention for better typhoon forecast skills. [ABSTRACT FROM AUTHOR]

One limiting factor in atmospheric radar observations is the inability to distinguish the often weak atmospheric signals from fluctuations of the noise. This study presents a minimum threshold of usability, SNRmin, for signal-to-noise ratios obtained from wind profiling radars. The basic form arises from theoretical considerations of radar noise; the final form includes empirical modifications based on radar observations. While SNRmin was originally developed using data from the 50-MHz profiler at Poker Flat, Alaska, it works well with data collected from a wide range of locations, frequencies, and parameter settings. It provides an objective criterion to accept or reject individual spectra, can be quickly applied to a large quantity of data, and has a false-alarm rate of approximately 0.1%. While this threshold's form depends on the methods used to calculate SNR and spectral moments, variations of the threshold could be developed for use with data processed by other methods. [ABSTRACT FROM AUTHOR]

Vertically pointed wind profiling radars can be used to obtain measurements of the underlying drop size distribution (DSD) for a rain event by means of the Doppler velocity spectrum. Precipitation parameters such as rainfall rate, radar reflectivity factor, liquid water content, mass-weighted mean drop diameter, and median volume drop diameter can then be calculated from the retrieved DSD. The DSD retrieval process is complicated by the presence of atmospheric turbulence, vertical ambient air motion, selection of fall speed relationships, and velocity thresholding. In this note, error analysis is presented to quantify the effect of each of those factors on rainfall rate. The error analysis results are then applied to two precipitation events to better interpret the rainfall-rate retrievals. It was found that a large source of error in rain rate is due to unaccounted-for vertical air motion. For example, in stratiform rain with a rainfall rate of R = 10 mm h-1, a mesoscale downdraft of 0.6 m s-1 can result in a 34% underestimation of the estimated value of R. The fall speed relationship selection and source of air density information both caused negligible errors. Errors due to velocity thresholding become more important in the presence of significant contamination near 0 m s-1, such as ground clutter. If particles having an equivalent volume diameter of 0.8 mm and smaller are rejected, rainfall rate errors from -4% to -10% are possible, although these estimates depend on DSD and rainfall rate. [ABSTRACT FROM AUTHOR]

The theory of measuring crossbeam wind, shear, and turbulence within the radar’s resolution volume V6 is described. Spaced-antenna weather radar interferometry is formulated for such measurements using phased-array weather radar. The formulation for a spaced-antenna interferometer (SAI) includes shear of the mean wind, allows turbulence to be anisotropic, and allows receiving beams to have elliptical cross sections. Auto- and cross-correlation functions are derived based on wave scattering by randomly distributed particles. Antenna separation, mean wind, shear, and turbulence all contribute to signal decorrelation. Crossbeam wind cannot be separated from shear, and thus crossbeam wind measurements are biased by shear. It is shown that SAI measures an apparent crossbeam wind (i.e., the angular shear of the radial wind component). Whereas the apparent crossbeam wind and turbulence within V6 cannot be separated using monostatic Doppler techniques, angular shear and turbulence can be separated using the SAI. [ABSTRACT FROM AUTHOR]

Raindrop size distributions are often assumed to follow a three-parameter gamma distribution. Since rain intensity retrieval from radar observations is an underdetermined problem, there is great interest in finding physical correlations between the parameters of the gamma distribution. One of the more common approaches is to measure naturally occurring drop size distributions (DSDs) using a disdrometer and to find DSD parameters by fitting a gamma distribution to these observations. Often the method of moments is used to retrieve the parameters of a gamma distribution from disdrometer observations. In this work the effect of the method of moments and data filtering on the relation between the parameters of the DSD is investigated, namely, the shape μ and the slope Λ parameters. For this study the disdrometer observations were simulated. In these simulations the gamma distribution parameters Nw, D0, and μ were randomly selected from a wide range of values that are found in rainfall. Then, using simulated disdrometer measurements, DSD parameters were estimated using the method of moments. It is shown that the statistical errors associated with data filtering of disdrometer measurements might produce a spurious relation between μ and Λ parameters. It is also shown that three independent disdrometer measurements can be used to verify the existence of such a relation. [ABSTRACT FROM AUTHOR]

A novel application of numerical weather prediction (NWP) models within an end-to-end processing system used to demonstrate advanced hyperspectral satellite technologies and instrument concepts is presented. As part of this system, sophisticated NWP models are used to generate simulated atmospheric profile datasets with fine horizontal and vertical resolution. The simulated datasets, which are treated as the “truth” atmosphere, are subsequently passed through a sophisticated forward radiative transfer model to generate simulated top-of-atmosphere (TOA) radiances across a broad spectral region. Atmospheric motion vectors and temperature and water vapor retrievals generated from the TOA radiances are then compared with the original model-simulated atmosphere to demonstrate the potential utility of future hyperspectral wind and retrieval algorithms. Representative examples of TOA radiances, atmospheric motion vectors, and temperature and water vapor retrievals are shown to illustrate the use of the simulated datasets. Case study results demonstrate that the numerical models are able to realistically simulate mesoscale cloud, temperature, and water vapor structures present in the real atmosphere. Because real hyperspectral radiance measurements with high spatial and temporal resolution are not available for large geographical domains, the simulated TOA radiance datasets are the only viable alternative that can be used to demonstrate the new hyperspectral technologies and capabilities. As such, sophisticated mesoscale models are critically important for the demonstration of the future end-to-end processing system. [ABSTRACT FROM AUTHOR]

The effective radius (re) is a crucial variable in representing the radiative properties of cloud layers in general circulation models. This parameter is proportional to the condensed water content (CWC) divided by the extinction (σ). For ice cloud layers, parameterizations for re have been developed from aircraft in situ measurements 1) indirectly, using data obtained from particle spectrometer probes and assumptions or observations about particle shape and mass to get the ice water content (IWC) and area to get σ, and recently 2) from probes that derive IWC and σ more directly, referred to as the direct approach, even though the extinction is not measured directly. This study compares [IWC/σ] derived from the two methods using datasets acquired from comparable instruments on two aircraft, one sampling clouds at midlevels and the other at upper levels during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) field program in Florida in 2002. A penetration by one of the aircraft into a cold midlatitude orographic wave cloud composed of small particles is further evaluated. The σ and IWC derived by each method are compared and evaluated in different ways for each aircraft dataset. Direct measurements of σ exceed those derived indirectly by a factor of 2–2.5. The IWC probes, relying on ice sublimation, appear to measure accurately except when the IWC is high or the particles too large to sublimate completely during the short transit time through the probe. The IWC estimated from the particle probes are accurate when direct measurements are available to provide constraints and give useful information in high IWC/large particle situations. Because of the discrepancy in σ estimates between the direct and indirect approaches, there is a factor of 2–3 difference in [IWC/σ] between them. Although there are significant uncertainties involved in its use, comparisons with several independent data sources suggest that the indirect method is the more accurate of the two approaches. However, experiments are needed to resolve the source of the discrepancy in σ. [ABSTRACT FROM AUTHOR]

Small-scale turbulence in the free atmosphere is known to be intermittent in space and time. The turbulence fraction of the atmosphere is a key parameter in order to evaluate the transport properties of small-scale motions and to interpret clear-air radar measurements as well. Mesosphere–stratosphere–troposphere (MST)/stratosphere–troposphere (ST) radars provide two independent methods for the estimation of energetic parameters of turbulence. First, the Doppler spectral width σ2 is related to the dissipation rate of kinetic energy εk. Second, the radar reflectivity, or C2n, relates to the dissipation rate of available potential energy εp. However, these two measures yield estimates that differ with respect to an important point. The Doppler width measurements, and related εk, are reflectivity-weighted averages. On the other hand, the reflectivity estimate is a volume-averaged quantity. The values of εp depend on both the turbulence intensity and the turbulent fraction within the radar sampling volume. Now, the two dissipation rates εp and εk are related quantities as shown by various measurements within stratified fluids (atmosphere, ocean, lakes, or laboratory). Therefore, by assuming a “canonical” value for the ratio of dissipation rates, an indirect method is proposed to infer the turbulent fraction from simultaneous radar measurements of reflectivity and Doppler broadening within a sampling volume. This method is checked by using very high resolution radar measurements (30 m and 51 s), obtained by the PROUST radar during a field campaign. The method is found to provide an unbiased estimation of the turbulent fraction, within a factor of 2 or less. [ABSTRACT FROM AUTHOR]

A field-deployable scanning direct-detection elastic backscatter lidar system that is eye safe at all ranges is presented. The first two-dimensional spatial images created by scanning this new 1.54-μm wavelength system, and time-lapse animations (viewable in the online version of this article) of those spatial images, are shown. The system has a useful range from approximately 500 m to several kilometers or more (depending on weather conditions) with 3-m range resolution. The time-lapse animations reveal the advection of the macroscopic structure of aerosol scattering due to atmospheric motion. The images and animations are ideal for the location of sources of pollutants and their dispersal and the elucidation of structure in the cloud-free atmosphere. Most importantly, the data presented were collected in a populated area, which would have not been possible with a non-eye-safe system. [ABSTRACT FROM AUTHOR]

The dropsonde humidity data have not been fully utilized due to lack of knowledge on performance of the dropsonde humidity sensor. This study evaluates the performance of the dropsonde humidity sensor using data collected from two field experiments, the Dynamics and Chemistry of Marine Stratocumulus Phase II: Entrainment Studies (DYCOMS-II) and the International H2O Project (IHOP)_2002. During DYCOMS-II, 63 dropsondes were dropped above marine stratocumulus clouds. It provides a unique opportunity to evaluate the performance of the dropsonde humidity sensor within clouds. Relative humidity (RH) inside clouds did not reach 100% all the time, but the maximum RH reached 100% for 28% of soundings and was within the sensor accuracy range (94%–100%). This suggests that the dropsonde humidity sensor displays no systematic dry bias near saturation. The dropsonde humidity sensor experienced large time-lag errors when it descended from a dry environment above clouds into clouds. The mean estimated time constant of the sensor is 5 s at 15°C, which is much larger than 0.5 s at 20°C given by the manufacturer. The humidity sensor still reported near-saturation RH after it exited clouds because of water on the sensor. The approximately coincident dropsonde and aircraft temperature data during DYCOMS-II show that the dropsonde underestimates temperatures inside and below clouds by averages of 0.21° and 0.93°C, respectively. Seventy-one pairs of dropsonde and radiosonde soundings during IHOP_2002 were launched within a half hour and 50 km and sampled the same air mass based on the visual examination. The comparisons show that the dropsonde and radiosonde RH data agree with each other within ±2% RH, suggesting no systematic dry bias in dropsonde humidity data. However, dropsonde-measured temperature is consistently colder than that by radiosonde by ∼0.4°C. [ABSTRACT FROM AUTHOR]

The new infrared radiometer (conveyable low-noise infrared radiometer for measurements of atmosphere and ground surface targets, or CLIMAT) is a highly sensitive field instrument designed to measure brightness temperatures or radiances in the infrared, from the ground level, or from an aircraft. It can be equipped with up to six channels in the 8--14- mm range. This instrument is characterized by its portability (total mass less than 5 kg), its self-sufficiency, and its automated operation. It can be operated either manually or automatically. The optical head of the instrument contains an objective lens and a condenser mounted according to the Köhler design, providing a uniform irradiation on the detector and a well-delimited field of view. The radiation is measured by a low-noise fast thermopile whose responsivity is slightly temperature dependent. The radiometric noise expressed as an equivalent brightness temperature is on the order of 50 mK for a 1- mm bandwidth at room temperature. The application of a thermal shock reveals no noticeable degradation of the measurements, even though the cavity of the thermopile is not stabilized in temperature. [ABSTRACT FROM AUTHOR]

Prior to the Atmospheric Radiation Measurement program's first water vapor intensive observation period (WVIOP) at the Cloud and Radiation Testbed site near Lamont, Oklahoma, an automated 24-h Raman lidar was delivered to the site. This instrument, which makes high-resolution measurements of water vapor both spatially and temporally, is capable of making these measurements with no operator interaction (other than initial start-up) for days at a time. Water vapor measurements collected during the 1996 and 1997 WVIOPs are discussed here, illustrating both the nighttime and daytime capabilities of this system. System characteristics, calibration issues, and techniques are presented. Finally, detailed intercomparisons of the lidar's data with those from a microwave radiometer, radiosondes, an instrumented tower, a chilled mirror flown on both a tethersonde and kite, and measurements from aircraft are shown and discussed, highlighting the accuracy and stability of this system for both nighttime and daytime measurements. [ABSTRACT FROM AUTHOR]

Unreliable frequency estimates at low signal-to-noise ratios, provided by a heterodyne Doppler lidar (HDL), undermines any data analysis scheme requiring high-accuracy wind fields retrievals. To meet demanding specifications, that is, high accuracy associated with high reliability on radial velocity components, a quality control (QC) procedure has to be implemented at signal processing level. The authors propose use of a recursive implementation of an adaptive filter for frequency estimate coupled with a QC that combines a statistical test on the signal energy filtered out as proposed by Rye and Hardesty and a persistency criterion (PC). The PC leads to improved performance with respect to the percentage of data finally accepted and frequency accuracy. The performance is validated using simulated signals and HDL actual data. [ABSTRACT FROM AUTHOR]

The capability of the NCAR 10.6-μm-wavelength CO[sub2] Doppler lidar to measure radial air motion is validated by examining hard-target test data, comparing measurements with those from a two-axis propeller anemometer and a 915-MHz profiling radar, and analyzing power spectra and autocovariance functions of the lidar radial velocities in a daytime convective boundary layer. Results demonstrate that the lidar is capable of measuring radial velocity to less than 0.5 m s[sup-1] precision from 20 laser pulse averages under high signal-to-noise ratio conditions. Hard-target test data and comparisons with other sensors show that the lidar data can be biased by as much as &+mn;2 m s[sup-1] when operating in the coherent oscillator mode and that correlated errors are negligible. Correlation coefficients are as large as 0.96 for 90-min comparisons of horizontal velocities averaged for 1 min from the lidar and anemometer, and 0.87 for 2.5-h comparisons between vertical velocities averaged for 30 s from the lidar and profiler. Comparisons of the lidar and profiler vertical velocities are particularly encouraging for the profiler since these results show that 915-MHz profilers are capable of making good vertical velocity measurements in strong convective boundary layers. The authors conclude that despite the commonplace systematic bias in lidar radial velocity, ground-based operation of the NCAR CO[sub2] Doppler lidar can provide valuable velocity data for meso- and microscale meteorological studies. The lidar can also provide filtered velocity statistics that may be useful for boundary layer turbulence research. [ABSTRACT FROM AUTHOR]

A system has been developed for use on a light aircraft for the measurement of the turbulent wind vector components that does not rely on the use of either an inertial navigation system (INS) or Doppler radar. The system described here uses a five-hole probe to measure the wind vector relative to the aircraft. A GPS system, a vertical gyroscope for aircraft pitch and roll angles, a gyrocompass system, and a strap-down three-axis accelerometer system are used to obtain aircraft motion. Flight tests and results of an intercomparison with the United Kingdom Meteorological Office C-130 are presented. Under conditions of straight and level flight, the estimated rms errors are 0.3 m s[sup-1] for the vertical wind component and 2 m s[sup-1] for the horizontal components. [ABSTRACT FROM AUTHOR]