S. Rajamani

Construction of vertical wind profile from satellite-derived winds for objective analysis of wind field

During summer Monex-79, a variety of observing systems viz. research ships, research aircrafts, constant pressure balloons and geostationary satellite etc. were deployed, besides the regular conventional observations. The purpose of these additional systems was to make the best possible data for the studies on various aspects of monsoon circulation. The present study is aimed at the construction of vertical wind profile using cloud motion vectors obtained from GOES (I-O) satellite and to examine whether the constructed wind profiles improves the representation of the monsoon system, flow pattern etc. in the objective analysis. For this purpose, climatological normals of the wind field are considered as the initial guess and the objective analyses of the wind field are made with, first using only data from conventional observations over land areas, subsequently including the constructed winds from cloud motion vectors. These analyses are then compared with the standard analyses of wind field obtained from Quick Look Atlas by T. N. Krishnamurti et al. (1979).It is inferred that satellite estimated mean wind profiles show good agreement with the mean wind profiles of the research ships with RMS errors less than 5 mps below 500 hPa and less than 8 mps above 500 hPa. It is further inferred that the inclusion of constructed winds shows a positive impact on the objective analysis and improvement is seen to be more marked in the data-sparse region of the Arabian sea. Analyses which include the constructed winds show better agreement with the standard analysis, than the analyses obtained using only conventional winds. Thus, results of our study suggest that the wind profiles constructed using cloud motion vectors are of potential use in objective analysis to depict the major circulation features over the Indian region.

On the impact of divergent part of the wind computed from INSAT OLR data on global analysis and forecast fields

SummaryIn this paper, a procedure for the computation of the divergent part of wind from Outgoing Longwave Radiation (OLR) data is described. This divergent part is included in the global analysis scheme and its impact is studied by computing the vertical velocity, velocity potential etc., using the analysed fields with and without modifying the divergent part and also making 24 hr and 48 hr rainfall forecasts.Results show that magnitudes of vertical velocity were increased when the divergent part was modified in the wind analysis. There were also changes observed in the analysed wind field over convective regions and the changes over the oceanic regions were higher, suggesting that the impact of divergent part is more pronounced over data sparse regions. Marginal increase was observed in 24 hr and 48 hr rainfall forecast over the Indian region. The area averaged rainfall forecast at each time step in the first 6 hours of model integration was also higher in the case when the wind field contained the divergent part.To sum up, it can be stated that the inclusion of the divergent part from OLR data in the initial wind field has brought out positive impact on the wind analyses and rainfall forecast.

On some aspects of objective analysis of humidity over indian region by the optimum interpolation method

On the basis of a three year record of Radiosonde observations over Indian region, the autocorrelation function and structure function of the humidity mixing ratio (r) were computed for 850 hPa level. These are necessary for the construction of a suitable objective analysis scheme for humidity over Indian region using optimum interpolation method. The statistics were derived for the monsoon period (June through September) for 850 hPa level.In order to model the humidity correlation for Indian region, two types of curves were fitted: (i) μ(ρ)=a exp (-bρ), (ii) μ(ρ)=A exp (-Bρ2) where μ is the autocorrelation function — a function of distance ρ-between two observing stations. It was found that the best description of humidity correlation function was given by Eq. (1). The value of ‘a’ gives a quantitative impression of the observation error. Further, the mean random errors were computed from structure functions, the weighting factors for the observing stations with respect to each grid point were calculated, and objective analyses were made for the humidity mixing ratio.

Some experiments with multivariate objective analysis scheme of heights and winds using optimum interpolation

A two-dimensional, multitvariate objective analysis scheme for simultaneous analysis of geopotential height and wind fields has been developed over Indian and adjoining region for use in numerical weather prediction. The height-height correlations calculated using daily data of four July months (1976–1979), are used to derive the other autocorrelations and cross-correlations assuming geostropic relationship. A Gaussian function is used to model the autocorrelation function. Since the scheme is multivariate the regression coefficients (weights) are matrix.Near the equator, the geostrophic approximation relating mass and wind is decoupled in a way similar to Bergman (1979). The objective analyses were made over Indian and adjoining region for 850, 700, 500, 300 and 200 hPa levels for the period from 4 July to 8 July 1979, 12 GMT. The analyses obtained using multivariate optimum interpolation scheme depict the synoptic situations satisfactorily. The analyses were also compared with the FGGE analyses (from ECMWF) and also with the station observations by computing the root mean square (RMS) errors and the RMS errors are comparable with those obtained in other similar studies.

A Scheme for Objective Analysis of Wind Field Incorporating Multi—Weighting Functions in the Optimum Interpolation Method

A method of objective analysis scheme having three different weighting functions for different conditions of the wind flow has been developed for the Indian region, two of which are anisotropic and third one is isotropic. Basically Gandin’s Optimum Interpolation method is used. The “effective” distance between a grid point and observation point used for the anisotropic functions, has been applied to calculate weighting functions following Benjamin and Seaman (1985) and objective analyses were made at the 700 hPa level for three consecutive days from 6 July to 8 July 1979. The quantitative evaluation of the objectively analysed fields have been made by computing the R.M.S. erros. Analyses obtained using multi-weighting functions (anisotropic) and those obtained using ordinary circular functions (isotropic-Gandin, 1963) have been compared. Also, the centres of the monsoon depressions obtained by this method have been compared with those of subjective analyses.

Multivariate objective analysis of wind and height fields in the tropics

The commonly used objective analysis scheme (Scheme-A) for the analysis of wind and geopotential height smoothen the divergent component of the wind which is rather important in the tropics, specifically over convective regions. To overcome this deficiency, a new analysis scheme in which divergent component is included in the statisti-cal model of the wind forecast errors, has been proposed by Daley (1985). Following this scheme, a new set of correla-tion functions of forecast errors for the Indian region during monsoon season which are suitable for analysing the tropical wind are obtained. This analysis scheme (Scheme-B) as well as Scheme-A were used to make analyses for the period from 4 July to 8 July 1979 (12 GMT) at 850, 700 and 200 hPa levels over an area bounded by 1.875°N to 39.375°N and 41.250°E to 108.750°E and subsequently divergent component, velocity potential are computed for both schemes. Results from both these schemes show that in the monsoon depression region the velocity potential and divergence have increased in the later case (Scheme-B). This suggests that the divergent component has been en-hanced in Scheme-B and that the objective of this study is realized to some extent.

Use of Surface Observations to Estimate Upper Air Humidity for the Objective Analysis of Relative Humidity over Indian Region

ABSTRACTIn the present study objective analyses of relative humidity (RH) at surface and at the levels of 850, 700 and 500 hPa have been made using Gandins (1963) optimum interpolation scheme. As the horizontal resolution of the radiosonde stations is rather inadequate for upper air humidity analysis, a scheme has been developed, following Rasmussen (1982) to estimate the upper air RH from the surface observations like surface RH, present weather and cloud cover. The relative humidities at the levels 850, 700 and 500 hPa were related to the surface observations through three separate regression relations. The RH values at 850, 700 and 500 hPa levels were estimated from the surface RH, cloud coverage and present weather using the above regression relations and subsequently the objective analyses at 00 GMT for the period from 4 July to 8 July 1979, were made using these estimated data along with the observed radiosonde data. Objective analyses were also made for the same period using only the radiosonde data for comparison to study the impact of those estimated data. Root mean square errors wore computed for all the five days by interpolating RH at the observing stations from the objectively analysed field and comparing them with the actually observed RH to examine how best the analyses (with and without estimated data) fitted the observations. Lastly they were compared with satellite cloud pictures. This study shows that the estimated upper air RH values have positive impact on the analysis of upper air RH and could be used over radiosonde data sparse region and even over oceanic regions.

An efficient optimum interpolation scheme for objective analysis over Indian region

In the optimum interpolation scheme, the weights for the observations are computed by solving a set of linear equations for every grid point. As the number of observations increases particularly over data-rich regions, the matrix dimension increases and the computer time required to solve these equations to determine weights increases considerably. In order to reduce the computer time for computing the weights, Tanguay and Robert suggested schemes in which the gaussian function representing the autocorrelation function has been approximated by a second-order and also by a fourth-order Taylor series expansion. This resulted in the solution of matrices of order 4 or 9 respectively to obtain weighting functions irrespective of the number of observations used in the analysis. In the present study, the analyses of mean sea level pressure and geopotential height at 700 mbar level have been carried out for five days using the above two schemes and the regular OI scheme. The analyses are found to be similar in all the three cases suggesting that a lot of computer time could be saved without sacrificing the analysis accuracy by using the modified scheme in which the second-order approximation is utilized.