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31.
Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5 总被引:1,自引:0,他引:1
The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model
errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which
CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems
to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the
sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian
satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations
were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each
of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different
CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, Kain-Fritsch
and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, root-mean-squares error (RMSE),
and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating
the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute
BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It
was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde
observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four
CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in
the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation.
Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper
levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption
in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation
is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is
more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller
scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study
is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the
CPSs for different synoptic situations. 相似文献
32.
-- This work extends the results that Apparao et al. (1997a) obtained for a vertical resistive sheet to the case of inclined resistive sheet models for different electrode arrays. It is found that the depth of investigation (DI) remains the same as that for the vertical target. Using this DI, modified pseudo-depth sections have been constructed over sheet models at different inclinations. It is noted that, for the Wenner array, the maximum anomaly contours fall directly over the target cross section. For dipole-dipole and three-electrode arrays, these contours fall on the up-dip side of the dipping target, with the maximum anomaly contour matching the depth level of the top of the target. It is also observed that the target cross section is at a distance of about 0.33L (L/3) from the maximum anomaly value/contour position for the three-electrode array and 0.25L (L/4) for the dipole-dipole system. These features are identifiable in the individual profiles and may help field geophysicists in the recognition and location of dipping target bodies. 相似文献
33.
The Simulation of Ground Motions Using Envelope Summations 总被引:2,自引:0,他引:2
—?The technique of Midorikawa (1993) has been modified to obtain a resultant envelope function at the observation point by placing the rupture causing an earthquake in a layered earth model. The method and its dependency on various modelling parameters are studied in detail. The complete study shows that the generated resultant envelope follows important strong motion characteristics such as directivity and attenuation effects. The simulated resultant envelope is further used for generating synthetic accelerograms by multiplying filtered white noise with the envelope of accelerogram at a particular observation point. Filters through which white noise passes include the effects of geometrical spreading, anelastic attenuation and near-site attenuation at high frequencies.¶Uttarkashi earthquake is among few Indian earthquakes for which strong motion data are available at thirteen different stations. Using the technique presented in this work, envelope function as well as complete acceleration time history during Uttarkashi earthquake has been simulated at these observation points. Comparison of peak acceleration, duration and acceleration response spectra confirms the utility and efficacy of the approach. 相似文献
34.
The brightness temperatures of the Microwave sensor MSMR (Multichannel Scanning Microwave Radiometer) launched in May 1999
onboard Indian Oceansat-1 IRS-P4 are used to develop a direct retrieval method for latent heat flux by multivariate regression
technique. The MSMR measures the microwave radiances at 8 channels at frequencies of 6.6, 10.7, 18 and 21 GHz at both vertical
and horizontal polarizations. It is found that the surface LHF (Latent Heat Flux) is sensitive to all the channels. The coefficients
were derived using the National Centre for Environmental Prediction (NCEP) reanalysis data of three months: July, September,
November of 1999. The NCEP daily analyzed latent heat fluxes and brightness temperatures observed by MSMR were used to derive
the coefficients. Validity of the derived coefficients was checked within situ observations over the Indian Ocean and with NCEP analyzed LHF for global points. The LHF derived directly from the MSMR brightness
temperature (Tb) yielded an accuracy of 35 watt/m2. LHF was also computed by applying bulk formula using the geophysical parameters extracted from MSMR. In this case the errors
were higher apparently due to the errors involved in derivation of the geophysical parameters. 相似文献
35.
M. M. Wani V. K. Choubey Himanshu Joshi 《Journal of the Indian Society of Remote Sensing》1996,24(1):25-32
Indian Remote Sensing satellite (IRS)-1B, Linear Imaging Self Scanner (LISS)-II spectral digital data was analysed to determine the feasibility of quantifying the concentration of suspended solids in the surface water of inland water body, Dal lake, in Srinagar, India. The water samples collected in concurrent with IRS-1B overpass, were analysed to determine the concentration of suspended solids. The results indicate that a positive functional relationship exist between the concentration of suspended solids and the visible wave length bands 1 and 3 and near infrared band 4. It has been observed that as the concentration of suspended solids increase, the spectral response also increases. It is concluded that IRS LISS-H data can be effectively used to quantify suspended sediment concentration in the Dal lake surface water. 相似文献
36.
The sedimentation rates and diffusive sediment mixing coefficients at several Lake Ontario locations have been derived from measurements of unsupported210Pb profiles in sediment cores. The values of mixing coefficients obtained in the present study are significantly lower than those obtained previously through an analysis of porosity profiles. The present estimates, however, are consistent with the rather well-preserved pollutant profiles at some of these locations. It is observed that the more realistic value of the mixing coefficient, obtained by inclusion of the sedimentation rate parameter, follows the sign opposite to that for the constant obtained by regression analysis of the porosity data. Further work is required to delineate this apparent relationship between two important physical characteristics of deposited sediments.Analysis of available suspended sediment data shows that Niagara River supplies about 1.8 million tonnes of sediment annually to Lake Ontario. This value is significantly lower than that (4.6 mt/yr) used previously in constructing sediment and pollutant budgets for Lake Ontario. From the presently derived sedimentation rate and suspended solid discharge estimates, an average value of 441 km2 (range 220-938 km2) is obtained for the minimum area of Lake Ontario over which the Niagara River-supplied fine sediment is deposited. 相似文献
37.
38.
Remotely sensed estimation of forest canopy density: A comparison of the performance of four methods
Chudamani Joshi Jan De Leeuw Andrew K. Skidmore Iris C. van Duren Henk van Oosten 《International Journal of Applied Earth Observation and Geoinformation》2006
In recent years, a number of alternative methods have been proposed to predict forest canopy density from remotely sensed data. To date, however, it remains difficult to decide which method to use, since their relative performance has never been evaluated. In this study the performance of: (1) an artificial neural network, (2) a multiple linear regression, (3) the forest canopy density mapper and (4) a maximum likelihood classification method was compared for prediction of forest canopy density using a Landsat ETM+ image. Comparison of confusion matrices revealed that the regression model performed significantly worse than the three other methods. These results were based on a z-test for comparison of weighted kappa statistics, which is an appropriate statistic for analysis of ranked categories. About 89% of the variance of the observed canopy density was explained by the artificial neural networks, which outperformed the other three methods in this respect. Moreover, the artificial neural networks gave an unbiased prediction, while other methods systematically under or over predicted forest canopy density. The choice of biased method could have a high impact on canopy density inventories. 相似文献
39.
40.
Significant Wave Height (SWH) measurement data from the AltiKa Radar Altimeter (RA) for the first 13 cycles of satellite coverage are compared with the SWH from Wave Rider Buoys (WRB) located at nine stations along the Indian coast to assess the performance of the altimeter over the coastal region. AltiKa SWH observations within a 30-minute interval and 50 km distance from WRBs are found to be over estimated by 6%, the Root Mean Square Error (RMSE) is 0.36 m, the Scatter Index (SI) is 26%, and the correlation coefficient (r) is 0.91. Relaxing the distance criteria by 50 km leads to increase in RMSE and deterioration of r to 0.89. There is a marked difference in the statistics on the comparison pairs pooled separately for the buoys near west and east coasts, with the latter showing RMSE error 26% more than the former. The method of Cressman weights adopted to correct for the errors arising out of the temporal and spatial differences in altimeter and buoy data comparison pairs resulted in reduction of RMSE by 5% and 25%, respectively, for the 30-minute and 50 km criteria and 4% and 56% for the 30-minute and 100 km criteria. 相似文献