A comparative study of the performance of various vertical discretization schemes

Summary Most finite-difference numerical weather prediction models employ vertical discretizations that are staggered, and are low-order (usually second-order) approximations for the important terms such as the derivation of the geopotential from the hydrostatic equation, and the calculation of the vertically integrated divergence. In a sigma-coordinate model the latter is used for computing both the surface pressure change and the vertical velocity. All of the above-mentioned variables can diminish the accuracy of the forecast if they are not calculated accurately, and can have an impact on related quantities such as precipitation.In this study various discretization schemes in the vertical are compared both in theory and in practice. Four different vertical grids are tested: one unstaggered and three staggered (including the widely-used Lorenz grid). The comparison is carried out by assessing the accuracy of the grids using vertical numerics that range from second-order up to sixth-order.The theoretical part of the study examines how faithfully each vertical grid reproduces the vertical modes of the governing equations linearized with a basic state atmosphere. The performance of the grids is evaluated for 2nd, 4th and 6th-order numerical schemes based on Lagrange polynomials, and for a 6th-ordercompact scheme.Our interpretation of the results of the theoretical study is as follows. The most important result is that the order of accuracy employed in the numerics seems to be more significant than the choice of vertical grid. There are differences between the grids at second-order, but these differences effectively vanish as the order of accuracy increases. The sixth-order schemes all produce very accurate results with the grids performing equally well, and with the compact scheme significantly outperforming the Lagrange scheme. A second major result is that for the number of levels typically used in current operational forecast models, second-order schemes (which are used almost universally) all appear to be relatively poor, for other than the lowest modes.The theoretical claims were confirmed in practice using a large number (100) of forecasts with the Australian Bureau of Meteorology Research Centre's operational model. By comparing test model forecasts using the four grids and the different orders of numerics with very high resolution control model forecasts, the results of the theoretical study seem to be corroborated.With 8 Figures     

Principal oscillation pattern analysis of the tropical 30- to 60-day oscillation

In Part I (Storch and Xu 1990) the principal oscillation pattern (POP) analysis of 200 mb equatorial velocity potential leads to the definition of a bivariate (POP-) index of the tropical 30- to 60-day oscillation. Using the POP prediction scheme this index is predictable for a few days in advance. In Part 11, the prediction of the equatorial velocity potential field, made by the POP method and made by two GCMs, is investigated. The POP index forecast can incorporate skillful forecasts of the equatorial velocity potential () field. Its ensemble correlation skill score passes the 0.50 level at 7 days, whereas persistence passes after 3 days. If there is a strong 30- to 60-day oscillation signal in the initial state, useful forecasts of more than 20 days are sometimes possible; if the initial signal is weak, the POP forecast fails. Also, the forecast skill of two GCMs is considered. The NCAR T31 GCM appears to be quite skillful in predicting the equatorial -field, and in particular the 30- to 60-day oscillation. Its skill, however, is less than that of the POP scheme. The CNRM T42 GCM seems not to be able to predict the regular development associated with the tropical 30- to 60-day oscillation. The power of the POP index in explaining the equatorial x-field is a measure of the strength and dominance of the 30- to 60-day oscillation. This measure at day 0 is an a priori indicator of the NCAR T31 GCM's skill in predicting the equatorial velocity potential field.The National Center for Atmospheric Research is sponsored by the National Science Foundation     

Outgoing long-wave radiation over the Tropical Pacific and Atlantic Ocean and Indian summer monsoon rainfall

Summary In this paper, the interannual variability of satellite derived outgoing longwave radiation (OLR) is examined in relation to the Indian summer monsoon rainfall (June to September total rainfall; ISMR). Monthly grid point OLR field over the domain i.e. the tropical Pacific and Atlantic region (30°N to 30°S, 110°E to 10°W) and the ISMR for the period 1974–2001 are used for the study. A strong and significant north–south dipole structure in the correlation pattern is found between the ISMR and the OLR field over the domain during January. This dipole is located over the west Pacific region with highly significant negative (positive) correlations over the South China Sea and surrounding region (around north-east Australia). The dipole weakens and moves northwestward during February and disappears in March. During the month of May, the OLR over the central Atlantic Ocean shows a significant positive relationship with the ISMR. These relationships are found to be consistent and robust during the period of analysis and can be used in the prediction of the ISMR.A multiple regression equation is developed, using the above results, for prediction of the ISMR and the empirical relationships are verified using an independent data set. The results are encouraging for the prediction of the ISMR. The composite annual cycle of the OLR, over the west Pacific regions during extreme ISMR is found to be useful in the prediction of extreme summer monsoon rainfall conditions over the Indian subcontinent.     

Principal oscillation pattern analysis of the 30- to 60-day oscillation in the tropical troposphere

The Principal Oscillation Pattern technique is used to derive an index of the 30- to 60-day oscillation in the tropical troposphere. In the 200-mb equatorial velocity potential field, one dominant pair of POPS is found. Its properties compare very well with the properties of the oscillation identified in previous studies. In particular, a good correlation between the time evolution of the POP coefficients and area-averaged outgoing long-wave radiation (ORL) is found. The POPS are derived from a 2-year subinterval of the whole 5-year data set. This leaves independent data for subsequent verification. The patterns and their characteristic numbers are almost unchanged if the whole data set is analysed. Also, the analysis is insensitive to changes of the analysis area: if the analysis is limited to 90°-longitude equatorial sectors, the signal is also identified and its patterns are consistent with the patterns derived from the full data set. Interestingly, the signal is best defined in the eastern hemisphere. The POPS may be used to derive associated correlation patterns of other quantities in winter and summer separately. The path of the oscillation has a marked annual cycle: in northern winter it migrates from the Indian Ocean across northern Australia into the region of the South Pacific Convergence Zone (SPCZ) and in northern summer it moves from the Indian Ocean across South Asia along the intertropical Convergence Zone (ITCZ) to South America. The POP coefficient may be seen as a bivariate index of the state (phase and strength) of the 30- to 60-day oscillation. Since the POP technique incorporates a prediction equation for the phase of the POP coefficients, the POP model allows for the prediction of the complex amplitude of the oscillation. In a sequence of forecast experiments, of which about two-thirds used independent data, the POP forecasts were found to be useful in about half of all cases for lead times of several days. The correlation and RMS skills were calculated for the POP forecast and for persistence. The POP forecast appears to be considerably better with respect to both measures. The correlation skill scores 60% after 7 days. The POP forecast is most skillful in northern winter and if strong signals are present with minima of velocity potential in the eastern hemisphere.     

Reactions of alkoxy radicals under atmospheric conditions: The relative importance of decomposition versus reaction with O2

The reactions of alkoxy radicals determine to a large extent the products formed during the atmospheric degradations of emitted organic compounds. Experimental data concerning the decompositions, 1,5-H shift isomerizations and reactions with O₂ of several classes of alkoxy radicals are inconsistent with literature estimations of their absolute or relative rate constants. An alternative, although empirical, method for assessing the relative importance under atmospheric conditions of the reactions of alkoxy radicals with O₂ versus decomposition was derived. This estimation method utilizes the differences in the heats of reaction, (H)=(H_{decomposition}–H_{O 2 reaction}), between these two reactions pathways. For (H)[22–0.5(H_{O 2 reaction})], alkoxy radical decomposition dominates over the reaction with O₂ at room temperature and atmospheric pressure of air, while for (H)[25-0.5(H_{O 2 reaction})], the O₂ reaction dominates over decomposition (where the units of H are in kcal mol^–1). The utility and shortcomings of this approach are discussed. It is concluded that further studies concerning the reactions of alkoxy radicals are needed.     

Effect of land management on ecosystem carbon fluxes at a subalpine grassland site in the Swiss Alps

Summary The influence of agricultural management on the CO₂ budget of a typical subalpine grassland was investigated at the Swiss CARBOMONT site at Rigi-Seebodenalp (1025m a.s.l.) in Central Switzerland. Eddy covariance flux measurements obtained during the first growing season from the mid of spring until the first snow fall (17 Mai to 25 September 2002) are reported. With respect to the 10-year average 1992–2001, we found that this growing season had started 10 days earlier than normal, but was close to average temperature with above-normal precipitation (100–255% depending on month). Using a footprint model we found that a simple approach using wind direction sectors was adequate to classify our CO₂ fluxes as being controlled by either meadow or pasture. Two significantly different light response curves could be determined: one for periods with external interventions (grass cutting, cattle grazing) and the other for periods without external interventions. Other than this, meadow and pasture were similar, with a net carbon gain of –128±17g Cm^–2 on the undisturbed meadow, and a net carbon loss of 79±17g Cm^–2 on the managed meadow, and 270±24g Cm^–2 on the pasture during 131 days of the growing season, respectively. The grass cut in June reduced the gross CO₂ uptake of the meadow by 50±2% until regrowth of the vegetation. Cattle grazing reduced gross uptake over the whole vegetation period (37±2%), but left respiration at a similar level as observed in the meadow.     

Surface downward flux computed by using geophysical parameters derived from HIRS 2/MSU soundings

Summary The global field of outgoing longwave radiation (OLR) and surface downward flux (SDF) are computed for January and July 1979 (FGGE year). The computation was done by using geophysical parameters retrieved from space in conjunction which a radiation code. The geophysical parameters (such as temperature and humidity profiles, surface/land temperature, and cloud information) are retrieved from analysis of HIRS 2/MSU using the Goddard Laboratory for Atmospheres (GLA) physical retrieval system. The radiation code is a modified version of the Wu-Kaplan radiation code used in the GLA 4th order GCM. Other fluxes (such as clear OLR and clear SDF, and Earth emission) flux divergences (upward flux divergence and net upward flux divergence), flux differences and longwave radiative forcing (clear OLR — cloudy OLR, cloudy SDF — clear SDF, and atmospheric cloud forcing) which have physical meaning but can not be measured directly from space have also been computed and presented.

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Zusammenfassung Die globalen Felder der emitierten langwelligen Strahlung (OLR) und des nach unten gerichteten Flusses (SDF) werden für Januar und Juli des FGGE-Jahres 1979 berechnet. Die Berechnungen wurden mit Hilfe von geophysikalischen Parametern aus Satellitendaten und einem Strahlungsmodell ausgeführt. Die geophysikalischen Parameter (wie Temperatur-und Feuchtprofile, Oberflächen- bzw. Landtemperatur sowie Bewölkung) werden durch Analysen der HIRS 2/MSU-Daten mit Hilfe des GLA-Physical Retrieval System gewonnen. Das Strahlungsmodell ist ein modifiziertes Modell nach Wu-Kaplan, wie es im Modell der allgemeinen Zirkulation des GLA verwendet wird. Andere Flüsse (wie OLR und SDF bei klarem Himmel, sowie die Emission der Erde), Flußdivergenzen (nach oben gerichtete Fluß- und Nettoflußdivergenz), Flußdifferenzen und langwelliger Strahlungsantrieb (OLR bei klarem und bewölktem Himmel, SDF bei klarem und bewölktem Himmel und der Antrieb durch die Bewölkung), die alle physikalische Bedeutung haben, aber nicht direkt aus dem All gemessen werden können, wurden ebenfalls berechnet und werden hier vorgestellt.

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With 13 Figures     

Feature-based predictability of 500 hpa height in the Australia-New Zealand region

Summary Feature-based predictability stratifies forecast model errors on the basis of individual weather systems. We examine only one level and chose very simple categories: high, cut-off low, trough and block. European Centre for Medium-range Weather Forecasts data are used. We emphasize systems found near Australia and New Zealand during winter 1987. Calculations for the preceding summer and fall and for other midlatitude regions of the southern hemisphere yield similar results.The approach herein is fully automated and simple to implement. Features are identified in the verification field. Then an error calculation is made on moving grids that are each centered upon and contain one system.The total error is the root mean square difference (RMS) between forecast and verification. The structural error is the RMS difference when the forecast and verification small grids are independently centered upon the corresponding feature in each field. The difference between the structural and total errors, called the locational error, is typically a quarter of the total. Even when normalized by presistence, highs are forecast better than troughs; cut-off lows and troughs have similar errors. The distance between the forecast and observed positions is typically 3° longitude west and 0.5° latitude north of where features should be at 72 hours. The model has a systematic bias of too small amplitude of vorticity. No relation is found between skill and jet stream splitting.With 4 Figures     

General circulation model experiments with surface albedo changes

In 1975, Charney proposed a biogeophysical feedback mechanism to partly explain the droughts that occur in desert border areas. He showed that a perturbation of albedo (due to a natural or anthropogenic decrease of vegetation) can be unstable and lead to a variation of precipitation in the region where albedo is changed.Several numerical experiments have been achieved with general circulation models to study the sensitivity of climate to surface albedo. We compare the GLAS and LMD model results for the Sahel. For all models, rainfall decreases when albedo increases and net radiative heating of soil decreases. We show the variations of circulation simulated by the LMD model that we obtain when albedo is increased. These changes are compared to the weakening of Easterly Jet at 200 mb observed during dry years.     

Reduction of forecast error for global numerical weather prediction by The Florida State University (FSU) Superensemble

Summary The skill of the FSU Superensemble technique as applied to global numerical weather prediction is evaluated extensively in this paper. The global mass and motion fields for year 2000 and precipitation over the domain 55S to 55N for year 2001, as predicted by the Superensemble, the ensemble member models, and the mean of the ensemble members, are evaluated by standard statistical measures of skill to determine the performance of the Superensemble in relation to the other models. The member models are global forecast models from 5 of the worlds operational forecast centers in addition to the FSU global spectral model. For precipitation 5 additional versions of the FSU global model are utilized in the ensemble, as defined by different initial conditions provided by various physical initialization algorithms. Statistical parameters calculated for the mass and motion fields include root mean square (RMS) error, systematic error (or bias), and anomaly correlation. These are applied to the mean sea level pressure, 500hPa heights, and the wind fields at 850hPa and 200hPa. Statistical parameters that were calculated for precipitation include RMS error, correlation, equitable threat score (ETS), and a special definition of bias appropriate for the precipitation field. For the mass and motion fields the performance of the Superensemble was considered for the annual global case, as well as for each hemisphere (north and south) and for each of the four seasons. For precipitation only the annual case was considered over the domain cited above.For the mass and motion fields the RMS calculations showed the Superensemble to be superior (to have the smallest total forecast error) in all comparisons to the ensemble member models, and to be superior to the ensemble mean in the vast majority of comparisons. Performance in comparison to the other models was generally better in the Southern Hemisphere than in the Northern Hemisphere, and better in the transition seasons of fall and spring than in the extreme seasons of winter and summer. The Superensemble had the best success with mean sea level pressure, followed in order by 500hPa geopotential heights, 850hPa winds, and 200hPa winds.In the calculations of 500hPa geopotential height anomaly correlation the Superensemble had higher scores in all comparisons to the ensemble member models, as well as higher scores in the majority of comparisons to the ensemble mean. As with the RMS error results, the Superensemble performed better in the Southern Hemisphere than in the Northern Hemisphere, and better in fall than in summer, in comparison to the other models. The superior anomaly correlation scores of the Superensemble attest to the ability of the model to forecast daily perturbations from the climatological means, perturbations that are associated with transient synoptic scale features, given the horizontal resolution in the forecast models.In terms of systematic error reduction the Superensemble produces its most impressive results. Annual global mean sea-level pressure systematic errors for day 5 forecasts are generally in the range of ±1hPa (compared to errors as high as 8hPa in other models), and day 2 forecasts of 500hPa geopotential height produced systematic errors generally in the range of ±10 meters (compared to errors as high as 60 meters in other models). The Superensemble was able to reduce systematic errors in forecasts of a variety of important features in the global mass and motion fields: surface equatorial trough, wave amplitude in geopotential heights at 500hPa, trade winds and Somali Jet at 850hPa, mid-latitude westerlies, subtropical jet, and Tropical Easterly Jet (TEJ) at 200hPa.In terms of forecasting precipitation the Superensemble outperforms all ensemble member models and the ensemble mean in terms of RMS error, correlation coefficient, equitable threat score, and bias. The superior correlation scores indicate that the Superensemble is more reliable than the other models in predicting perturbations in the area distribution of precipitation, perturbations that are essentially associated with migrant synoptic scale disturbances, considering the horizontal resolution of the forecast models.The Superensemble is a valuable tool for significantly improving upon the global model forecasts of the worlds operational forecast centers. These forecasts are used daily as important guidance in making weather forecasts in all regions of the world. This paper will demonstrate that the Superensemble improves upon the ensemble member model forecasts: (1) in a statistical sense considering broad areas of the globe, (2) in a synoptic climatology sense through focus on the improved forecasts of climatological features seen in the global mass and motion fields, (3) in a synoptic sense through use of anomaly correlation and correlation coefficient where improvement is demonstrated in the forecasts of perturbations from mean fields which are essentially associated with transient synoptic scale disturbances.     

Sensitivity of hurricane intensity forecasts to physical initialization

Summary Intensity forecasts of a hurricane are shown to be quite sensitive to the initial meso-convective scale precipitation distributions. These are included within the data assimilation using a physical initialization that was developed at Florida State University. We show a case study of a hurricane forecast where the inclusion of the observed precipitation did provide reasonable intensity forecasts. Further experimentation with the inclusion or exclusion of individual meso-convective rainfall elements, around and over the storm, shows that the intensity forecasts were quite sensitive to these initial rainfall distributions. The exclusion of initial rain in the inner rain area of a hurricane leads to a much reduced intensity forecast, whereas that impact is less if the rainfall of an outer rain band was initially excluded.Intensity forecasts of hurricanes may be sensitive to a number of factors such as sea surface temperature anomalies, presence or absence of concentric eye walls, potential vorticity interactions in the upper troposphere and other environmental factors.This paper is a sequel to a recent study, Krishnamurti et al., 1997, on the prediction of hurricane OPAL of 1995 that was a category III storm over the Gulf of Mexico. In that study we showed successful forecasts of the storm intensity from the inclusion of observed rainfall distributions within physical initialization. In that paper we examined the issues of diabatic potential vorticity and the angular momentum in order to diagnose the storm intensity. All of the terms of the complete Ertel potential vorticity equation were evaluated and it was concluded that the diabatic contributions to the potential vorticity were quite important for the diagnosis of the storm's intensity. The present paper addresses some sensitivity issues related to the individual mesoconvective precipitating elements.With 4 Figures     

Near-field dispersion from instantaneous sources in the surface layer

This paper considers the near-field dispersion of an ensemble of tracer particles released instantaneously from an elevated source into an adiabatic surface layer. By modelling the Lagrangian vertical velocity as a Markov process which obeys the Langevin equation, we show analytically that the mean vertical drift velocity w(t) is w()=bu _*(1–e ^–(1+)), where is time since release (nondimensionalized with the Lagrangian time scale at the source), b Batchelor's constant, and u _*, the friction velocity. Hence, the mean height and mean depth of the ensemble are calculated. Although the derivation is formally valid only when 1, the predictions for w, mean height and mean depth are consistent in the downstream limit ( 1) with surface-layer Lagrangian similarity theory and with the diffusion equation. By comparing the analytical predictions with numerical, randomflight solutions of the Langevin equation, the analytical predictions are shown to be good approximations at all times, both near-field and far-field.     

On the impact on forecast accuracy of the step-mountain (eta) vs. sigma coordinate

Summary Impact on forecast accuracy of the choice of the step-mountain (eta) vs. the traditional sigma coordinate is examined by using a model which can be run as either an eta or sigma system model via a simple switch in its code. This is done by (a) synoptic examination of the differences in a set of three forecasts, and (b) comparison of precipitation skill scores in a set of nine consecutive forecasts; each of these sets of forecasts was performed using one and then the other of the two systems. Both efforts indicate that greater accuracy is achnieved in the step-mountain coordinate forecasts. The three forecasts examined from the synoptic point of view are also compared against forecasts of another sigma system model. The two sigma models are found to have errors of an almost identical pattern (two cases) or to have errors which seemed to have the same basic cause.With 13 Figures     

Prediction of tropical systems over Indian region using mesoscale model

Summary The Advanced Regional Prediction System (ARPS) model developed at Center for Analysis and Prediction of Storms at Oklahoma State University, USA is used for simulation of monsoon depression and tropical cyclone over Indian region. The radiosonde data are included in the initial analyses and subsequently; the simulations are performed with 50km and 25km grid resolutions. Two sets of forecast experiments produced by two types of analyses (with radiosonde and without radiosonde data) are compared. It is found that predicted mean sea-level pressure of the depression becomes closer to mean sea level pressure reported in Indian Daily Weather Reports when initialized with analyses containing radiosonde data. The precipitation forecast also is improved when initialized with the analyses containing radiosonde data. The simulation of tropical cyclone with 25km grid resolution is able to simulate some subsynoptic scale features of the system.     

Simulation of daily energy budget and mean soil temperatures at an arid site

Summary Soil temperature is often inadequately based upon relatively few measurements at widely dispersed locations. Within arid regions, such as the desert southwestern United States, soils, microclimates, and thus soil temperature may be markedly heterogeneous. Because extensive measurement of soil temperature is often not feasible, models are needed that simulate soil temperature based on readily available soil survey and above-ground weather information. This paper describes a simple energy-budget based model for simulating daily mean temperatures within a bare arid land soil. The model requires basic information on soil physical properties, and daily weather data including air temperature, windspeed, rainfall, and solar radiation to calculate daily surface energy budget components and surface temperature. One of two alternative numerical methods is then used to calculated subsurface temperatures. Tests of the model using 1987 daily temperature data from an arid site at Yuma, Arizona resulted in root mean square deviations within 1.4°C between daily modeled and measured temperatures at both 0.05 and 0.10 m depths. Sensitivity analysis showed modeled temperatures at 0.05 m depth to be most sensitive to parameters affecting the surface energy balance such as air temperature and solar radiation. Modeled temperatures at 1.0m depth were relatively more sensitive to initial temperature conditions and to parameters affecting distribution of energy within the profile such as thermal conductivity.With 3 Figures     

Equilibrium evaporation beneath a growing convective boundary layer

Expressions for the equilibrium surface Bowen ratio ( _s ) and equilibrium evaporation are derived for a growing convective boundary layer (CBL) in terms of the Bowen ratio at the top of the mixed layer _i and the entrainment parameter A _R . If A_R is put equal to zero, the solution for _s becomes-that previously obtained for the zero entrainment or closed box model. The Priestley-Taylor parameter is also calculated and plotted in terms ofA _R and _i . Realistic combinations of the atmospheric parameters give values of in the range 1.1 to 1.4.     

On the annual and monthly mean diurnal variations of diffuse solar radiation at a meteorological station in west Africa

Summary In addition to global solar radiationE ^g , the hourly diffuse componentE ^d incident on a horizontal surface has been measured from February 1993 to January 1995 at a meteorological station in tropical West Africa. The measured diffuse solar irradiance data was corrected for shadow band effects. The monthly mean diurnal variations of diffuse solar irradiance obtained for identical months in the two years have been compared and found to be generally consistent. The corresponding monthly mean hourly values ofE ^d for identical months in 1993 and 1994 agreed to within 9% while yielding correlation coefficients greater than 0.960. In addition, the monthly mean daily totals ofE ^d for identical months were found to agree mostly to within 6% and showed virtually the same annual variations in both years. The monthly mean daily total values of diffuse solar radiation for most months in the two years ranged between 7.94 MJm^–2d^–1 and 10.50 MJm^–2d^–1. The monthly mean of daily hourly maximum values ofE ^d obtained for identical months in the two years have been discussed in relation to the dominant atmospheric conditions during these months. The results been presented here have been compared with those of some investigators within and outside the Africa region.With 8 Figures     

The use of bootstrap confidence intervals for the correlation coefficient in climatology

Summary The importance of defining confidence intervals for sample statistics that are used to estimate characteristics of the parent population(s) is emphasised. Not all sample statistics are unbiased estimators or have normally distributed sampling distributions and so it is not always easy to reflect the reliability of the estimator. In such cases, Efron's bias corrected percentile method, which uses bootstrap samples to estimate the bias and makes no assumptions about the distribution of the sample statistic can be used to define confidence limits for the population parameter. The method is explained and the procedure for calculating the confidence limits is outlined.As an example, bootstrap confidence limits calculated for the maximum correlation between the Southern Oscillation Index and rainfall at South African stations over the period 1935–1983 suggest that the sample correlation is an unreliable measure of the true association. One possible reason for this is that the association is thought to have broken down during the 1940s. However, the reliability of the estimator does not seem to improve when confidence limits are calculated for the 30-year period 1954–1983. It is possible that the width of the confidence interval is an indication of more than one distinct statistical population.     

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

Summary In 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.With 12 Figures     

Orographic effects on a conditionally unstable flow over an idealized three-dimensional mesoscale mountain

Summary Idealized numerical simulations using the Weather and Research Forecast (WRF) model indicate that three flow regimes, based on the moist Froude number, can be identified for a conditionally unstable, rotational, horizontally homogeneous, uniformly stratified flow over an idealized, three-dimensional, mesoscale mountain stretched spanwise to the impinging flow: (I) a quasi-stationary upslope convective system and an upstream-propagating convective system, (II) a quasi-stationary upslope convective system, and (III) a stationary upslope convective system and a quasi-stationary downstream convective system. Several major differences from a similar type of flow with no rotation over a two-dimensional mountain range are found. One important finding is that relatively strong mean flow produces a quasi-stationary mesoscale convective system (MCS) and maximum rainfall on the windward slope (upslope rain), instead of on the mountain peak or over the lee side.We found that the Coriolis force helps produce heavy upslope rainfall by making transition from flow-around the eastern part of the upslope to flow-over the western part of the upslope (transits to a higher flow regime) by deflecting the incident southerly flow to become east–southeasterly barrier winds. We found that the addition of the western flank of the arc-shaped mountain helps slow down the barrier wind from east and causes the maximum rainfall to move east of the windward slope. A lower-Froude number flow tends to produce a rainfall maximum near the concave region.Several other important facts can also be found in this study. The ratio of the maximum grid scale rainfall to the sub-grid scale rainfall increases when the moist Froude number increases. When the CAPE decreases, it is found that the upstream moist flow tends to shift to a higher Froude-number regime. Therefore, the Froude number cannot solely be used to define a moist flow regime when different CAPEs are considered. In another word, other parameters, such as CAPE, might play an important role in determining moist flow regimes.