Engineering topics

Rukhovets, Leonid

Publications and source records attributed to Rukhovets, Leonid.

5 records

NASA NTRS2005

A Posteriori Correction of Forecast and Observation Error Variances

Proposed method of total observation and forecast error variance correction is based on the assumption about normal distribution of "observed-minus-forecast" residuals (O-F), where O is an observed value and F is usually a short-term model forecast. This assumption can be accepted for several types of observations (except humidity) which are not grossly in error. Degree of nearness to normal distribution can be estimated by the symmetry or skewness (luck of symmetry) a(sub 3) = mu(sub 3)/sigma(sup 3) and kurtosis a(sub 4) = mu(sub 4)/sigma(sup 4) - 3 Here mu(sub i) = i-order moment, sigma is a standard deviation. It is well known that for normal distribution a(sub 3) = a(sub 4) = 0.

Rukhovets, Leonid↗

NASA NTRS2003

Jet Stream Analysis and Forecast Errors Using GADS Aircraft Observations in the DAO, ECMWF, and NCEP Models

We have utilized an extensive set of independent British Airways flight data recording wind vector and temperature observations (the Global Aircraft Data Set [GADS] archive) in three ways: (a) as an independent check of operational analyses; (b) as an analysis observing system experiment (OSE) as if the GADS observations were available in real time; and (c) as the corresponding forecast simulation experiment applicable to future operational forecasts. Using a 31 day sample (0000 UTC 20 December 2000 through 0000 UTC 20 January 2000) from Winter 2000, we conclude that over the data-dense continental U. S. analyzed jet streaks are too weak by -2% to -5%. Over nearby data-sparse regions of Canada, analyzed jet streaks are too weak by -5% to -9%. The second range provides a limit on the accuracy of current jet streak analyses over the portions of the -85% of the earth's surface that are poorly covered by non-satellite observations. The -5% to -9% range is relevant for the pre-third generation satellite (AIRS, IASI, GIFTS) era.

Cardinali, Carla↗

NASA NTRS2001

The Impact of British Airways Wind Observations on the Goddard Earth Observing System Analyses and Forecasts

British Airways flight data recorders can provide valuable meteorological information, but they are not available in real-time on the Global Telecommunication System. Information from the flight recorders was used in the Global Aircraft Data Set (GADS) experiment as independent observations to estimate errors in wind analyses produced by major operational centers. The GADS impact on the Goddard Earth Observing System Data Assimilation System (GEOS DAS) analyses was investigated using GEOS-1 DAS version. Recently, a new Data Assimilation System (fvDAS) has been developed at the Data Assimilation Office, NASA Goddard. Using fvDAS , the, GADS impact on analyses and forecasts was investigated. It was shown the GADS data intensify wind speed analyses of jet streams for some cases. Five-day forecast anomaly correlations and root mean squares were calculated for 300, 500 hPa and SLP for six different areas: Northern and Southern Hemispheres, North America, Europe, Asia, USA These scores were obtained as averages over 21 forecasts from January 1998. Comparisons with scores for control experiments without GADS showed a positive impact of the GADS data on forecasts beyond 2-3 days for all levels at the most areas.

Rukhovets, Leonid↗

NASA NTRS2000

An Adaptive Buddy Check for Observational Quality Control

An adaptive buddy check algorithm is presented that adjusts tolerances for outlier observations based on the variability of surrounding data. The algorithm derives from a statistical hypothesis test combined with maximum-likelihood covariance estimation. Its stability is shown to depend on the initial identification of outliers by a simple background check. The adaptive feature ensures that the final quality control decisions are not very sensitive to prescribed statistics of first-guess and observation errors, nor on other approximations introduced into the algorithm. The implementation of the algorithm in a global atmospheric data assimilation is described. Its performance is contrasted with that of a non-adaptive buddy check, for the surface analysis of an extreme storm that took place in Europe on 27 December 1999. The adaptive algorithm allowed the inclusion of many important observations that differed greatly from the first guess and that would have been excluded on the basis of prescribed statistics. The analysis of the storm development was much improved as a result of these additional observations.

Dee, Dick P.↗

NASA NTRS1999

Quality Control of Meteorological Observations

For the first time, a problem of the meteorological observation quality control (QC) was formulated by L.S. Gandin at the Main Geophysical Observatory in the 70's. Later in 1988 L.S. Gandin began adapting his ideas in complex quality control (CQC) to the operational environment at the National Centers for Environmental Prediction. The CQC was first applied by L.S.Gandin and his colleagues to detection and correction of errors in rawinsonde heights and temperatures using a complex of hydrostatic residuals.Later, a full complex of residuals, vertical and horizontal optimal interpolations and baseline checks were added for the checking and correction of a wide range of meteorological variables. some other of Gandin's ideas were applied and substantially developed at other meteorological centers. A new statistical QC was recently implemented in the Goddard Data Assimilation System. The central component of any quality control is a buddy check which is a test of individual suspect observations against available nearby non-suspect observations. A novel feature of this test is that the error variances which are used for QC decision are re-estimated on-line. As a result, the allowed tolerances for suspect observations can depend on local atmospheric conditions. The system is then better able to accept extreme values observed in deep cyclones, jet streams and so on. The basic statements of this adaptive buddy check are described. Some results of the on-line QC including moisture QC are presented.

Collins, William↗