Impact of horizontal model resolution and ... - Wiley Online Library

Meteorol. Appl. 11, 115–127 (2004)

DOI:10.1017/S1350482704001227

Impact of horizontal model resolution and orography on the simulation of a western disturbance and its associated precipitation A. P. Dimri Research and Development Center – Snow and Avalanche Study Establishment, Him Parisar, Sector 37A, Chandigarh, India − 160036 Email: [email protected]

A nonhydrostatic version of Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5) is used to study the effects of the horizontal model resolution and orography while simulating an active western disturbance (WD) that affected northwest India from 21 to 25 January 1999. Two numerical experiments are conducted with six combinations of two factors: horizontal model resolution and topography. National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysed data are used for the initial and boundary conditions. Simulation results indicate that the distribution and the rate of simulated precipitation due to a WD over northwest India is highly sensitive to the horizontal model resolution and topography. The model with finer resolution (30 km) is better able to estimate effects of mesoscale forcing on precipitation over the selected domain. The amount of precipitation simulated over the coarse domain is much less than the observed precipitation owing to the model’s unrealistic representation of orographic effects and mesoscale forcing. Simulated terrain, vertical velocity, wind and streamline at different horizontal model resolutions are presented. The detailed structure and distribution of wind speed are simulated in the finer domain. Simulated vertical velocity and precipitation are less in the second experiment when a flat topography is used across the domain, which indicates that topography plays a significant role in modulating the WD. Sensitivity of the horizontal model resolution for precipitation is assessed and it is found that the finer domain of the model simulation gives better results.

1. Introduction High resolution limited area models have been successfully used for both the simulation and the prediction of regional and local mesoscale weather events (Anthes et al. 1989). The success of such models depends upon the initial state and lateral boundary conditions of the model domain. Horizontal model resolution is an integral and essential issue when simulating weather systems at regional and global scales. Giorgi & Marinucci (1996) studied the sensitivity of simulated precipitation to model resolution and its implication for climate studies and found that precipitation amounts do vary with model resolution. Wind fields for the same region change when horizontal grid dimension is changed (Kallos & Kassomenos 1994). Krishnamurty’s (1990) global forecasts using a high resolution spectral model show substantial improvements in the prediction results. Horizontal model resolution affects precipitation predictions in various ways. First, local effects, or surface forcing, such as that caused by topography, valley effects, snowlines, etc., could be missing in the model owing to its coarse horizontal resolution. Furthermore, at coarse resolutions it is

not possible to represent subgrid processes in the model. Indeed, almost all physical parameterisations in the model are sensitive to its horizontal resolution. Thus the model resolution plays an important role in the prediction of various meteorological fields associated with weather and also regulates the mesoscale forcing. In this study, the impact of horizontal model resolution and orography on the simulation of a western disturbance (WD) and associated weather fields is examined. WDs are low pressure systems observed in the mid-latitude westerlies over the subtropical region of Asia and the Middle East. They are observed to move from west to east in all seasons, but are most prominent during the winter months of December to March. WDs are important weather systems of synoptic scale over northwest India. During the winter season, WDs cause fog, rain, snow, cold waves and avalanches in the snow-covered hill/mountainous regions. In winter over northern India, high pressure at ground level is generally observed and the associated weather is usually clear and dry. This situation changes with the passage of a trough in the middle- and upper-air westerlies, which causes

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A. P. Dimri cloudy conditions and light to moderate precipitation. Associated with the cloud and precipitation belts, warm and moist easterly−southeasterly winds are also noticed in the lower troposphere. Hence, in brief, the term WD can be taken to refer to a low pressure/trough, either at the surface or in the upper air in the region of westerly wind regimes (north of 20◦ N), accompanied by clouds and rain. However, in the absence of cloud and rain, a low having the above characteristics is simply referred to as a ‘low pressure region’. Further, when a low is represented by two or more closed isobars at 2 hPa intervals on the sea level chart, it is referred to as a ‘western depression’. Associated with the WDs, the occurrence of another low pressure system to the south, say over Rajasthan, Gujarat or Madhya Pradesh, is customarily described as an ‘induced low’. Earlier studies (for example, Pisharoti & Desai 1956; Kalsi 1980; Kalsi & Haldar 1992) have mentioned that interaction between the tropics and the mid-latitude systems is associated with extensive sheets of mid- and high-level clouds and maxima in the subtropical jet. Kalsi & Haldar (1992) suggest that mobile cloud systems are related to short waves in the subtropical jet and facilitate the interaction between the tropics and midlatitude systems by amplifying the long wave troughs leading to a large influence of mid-latitude westerlies over the subtropics and lower latitudes. Thus, WD is an interesting mid-latitude weather system that is modulated by tropical air masses and the presence of the Himalayas. The object of the present study is to simulate a weather situation associated with an active WD that occurred over northwest India in the period 21− 25 January 1999, by using a high resolution limited area atmospheric model. A nonhydrostatic version of PSU/NCAR mesoscale model MM5 is employed to integrate this WD. Here, WD is simulated with 30 km, 60 km and 90 km horizontal model resolution with topography and flat topography. The aim is to present simulated results of the WD that show the effect of horizontal model resolution and topography on prediction. A brief description of the model is given in Section 2, followed by numerical experiments and dataset description in Section 3. Section 4 briefly presents the synoptic situation for the case considered here. Results and discussion of the simulation and the actual weather situation are presented in Section 5. Section 6 shows the sensitivity of simulated precipitation to the horizontal model resolution and topographic variations.

2. Model description The mesoscale model used in this study is a nonhydrostatic limited area model, known as the MM5

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modelling system, which was developed at PSU/NCAR (Grell et al. 1994; Dhudhia et al. 1998). Dudhia (1993) used this model for validation tests and for simulation of an Atlantic cyclone and cold front. The MM5 uses a terrain-following sigma coordinate in the vertical. In the nonhydrostatic version of the model, a reference state pressure instead of pressure is used to define the sigma coordinate. A constant reference state and a perturbation form are defined as p(x, y, z, t) = p0 (z) + p (x, y, z, t) T(x, y, z, t) = T0 (z) + T (x, y, z, t) where p and T are pressure and temperature respectively, and subscript 0 and prime represent the reference state and perturbation respectively. The temperature profile for the reference state is an idealised hydrostatic equilibrium. It is specified by the following equation; T0 = Ts 0 + Aloge

p0 p00

(1)

where, p00 is sea level pressure taken to be at 1000 hPa, Ts 0 is the reference temperature at p00 taken to be 280 K, and A is a measure of the lapse rate taken to be 50 K, representing the temperature difference between p00 and p00 /e = 367.88 hPa. The vertical coordinate is then defined as σ=

p − pt ps − pt

(2)

where, ps and pt are surface pressure and pressure at the top of the model (50 hPa in the present study) for the reference state. The reference state surface pressure, which depends only on the terrain height, can be derived from (1) using the hydrostatic relation, p0 2 p0 RTs 0 RA ln ln − Z=− 2g p00 g p00

(3)

This equation is quadratic in p0 and can be solved while Z, the terrain height, is known. The reference pressure of the model sigma levels is then calculated as p = ( ps − pt )σ + pt In the nonhydrostatic model perturbation, pressure p is a prognostic quantity. The primitive hydrostatic/nonhydrostatic model equations in the terrain-following sigma coordinate system are written in flux form and are solved on an Arakawa B grid using the finite difference method. The finite difference method approximately conserves mass, momentum and total energy. The time integration scheme used in the model is the leapfrog

Impact of horizontal model resolution and orography Table 1. MM5 configuration used in this study.

Model Dynamics Main prognostic variables Map projection Central point of domain No. of horizontal grid points

Horizontal grid distance Number of vertical levels Horizontal grid scheme Time integration scheme Lateral boundary conditions Radiation Scheme Planetary boundary layer parameterisation schemes Cumulus parameterisation schemes Microphysics Soil model

time integration scheme with a time-splitting technique. In this technique, time interval 2t from (n − 1)t to (n + 1)t is divided into a number of smaller time steps and slowly varying terms are integrated in time with longer time steps, while terms responsible for fast-moving waves are integrated with shorter time steps. A second-order centred difference scheme is used for spatial finite differencing. A fourth-order diffusion for damping the subgrid advective processes that are modified to second order near the boundaries are applied in the model. A brief description of the model configuration used in this study is given in Table 1.

3. Numerical experiments and data used Numerical experiments for producing 96-hour forecasts were conducted. The Hong−Pan Scheme as implemented in NCEP Medium Range Forecast (MRF) model (Hong & Pan 1996) and the Betts−Miller scheme (Betts & Miller 1986, 1993) are used for parameterisation of planetary boundary layer processes and convection respectively. These two schemes were selected following the study by Azadi et al. (2001), which showed that the combination of the two schemes for boundary layer and convective parameterisation is better than that for other possible combinations. Numerical simulation of an active WD that affected the northwestern part of India from 21 to 25 January 1999 was examined. This case was selected because it produced widespread precipitation over northwest India including the western Himalayas. The domain

Fifth-generation PSU/NCAR Mesoscale Model (MM5) version 2.12 Nonhydrostatic with 3-d coriolis force U, v, w, T, p and q Lambert conformal mapping 33◦ N, 65◦ E 170,95 grid points (x, y respectively) 135,99 grid points (x, y respectively) 90,65 grid points (x, y respectively) 30 km, 60 km, 90 km 23 half sigma levels Arakawa B grid Time-splitting Nudging toward the NCEP/NCAR reanalysis Cloud radiation scheme with radiation frequency of 30 min Hong–Pan as implemented in the NCEP MRF model. It includes vertical diffusion in the stable atmosphere and moist vertical diffusion in clouds Betts–Miller Explicit scheme of Reisner (mixed phase) Multi layer soil model

selected for the study is shown in Figure 1. Here, simulations are made using different horizontal model resolutions and differences in the simulated topography can be clearly distinguished. The model simulation at 30-km resolution achieved a more intricate topography compared with the 60-km and 90-km horizontal model resolutions. The numerical experiments are thus carried out using (1) an assumed flat topography and (2) normal topography, at 30, 60 and 90 km horizontal model resolutions. The model with a 90-km horizontal resolution (coarse domain = CD) covers an area of 8100 km × 5850 km (90 × 65 grid points); that with a 60-km horizontal resolution (medium domain = MD 8100 km × 5940 km (135 × 99 grid points), and that with a 30km horizontal resolution (fine domain = FD) covers 5100 km × 2850 km (170 × 95 grid points). Initial conditions for the model are extracted from NCEP/NCAR reanalysis datasets and interpolated into the model domain. The usual procedure is to use the reanalysis datasets as the first guess in the objective analysis process to enhance them, because interpolation by itself cannot reproduce small-scale features that have already been smoothed out in the large-scale reanalysis. As suggested by Sashegyi et al. (1994), when insufficient data are available on the scale required by the numerical model, the model can be used to provide the time continuity between the observation times and to generate the spatial variability on the scales resolved by the model. Hence, in this study, 12-hour nudging is applied before starting model integration. During the nudging period, small-scale features are generated by the model physics and are

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Figure 1. Topography with different horizontal model resolution and with flat topography.

consistent with the large-scale datasets used as initial conditions. The boundary layer variables are excluded from nudging towards the observation. The topography is obtained from United State Geological Survey (USGS). These three horizontal resolution numerical experiments are conducted with different topographies. In the first experiment the 5 min (9 km) global topography is incorporated for the FD and 10 min (18 km) global topography is incorporated for the MD and CD. In the second experiment, the topography is assumed to be flat and a constant value of 1 metre is applied over the entire domain. The model is integrated with 96 hour in both experiments. Simulated streamlines and isotach, vertical velocity at 500 hPa and precipitation at 24-hour and 48-hour model forecasts, which correspond to 00UTC on 22 January 1999 and 00UTC 23 January 1999 respectively, are obtained for analysis.

4. Synoptic situations On 21 January 1999 a trough at 500 hPa was observed extending from Afghanistan to northwest India. This trough was associated with a low pressure at the surface over northwest India. On 22 January 1999 the low at sea level remained stationary. The associated upper air circulation could be seen up to 700 hPa, and the trough extended up to 300 hPa. The trough tilted westward with height. Precipitation amounts, varying between

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2 cm/day and 6 cm/day, were recorded at a number of places in northwest India. On 23 January 1999, at 0000 UTC, the pressure trough remained at the same location, but the pressure gradient steepened considerably over the region. The associated upper air cyclonic circulation also strengthened and could be seen extending up to 500 hPa and the trough aloft up to 200 hPa. The upper air cyclonic circulation and the associated trough tilted westward with height. On this day, precipitation amounts varying between 2 cm day−1 and 6 cm day−1 were recorded at a number of places in northwest India. On 24 January 1999 a low pressure area was located over Rajasthan and the steep pressure gradient to the north of it could still be observed over northwest Indian states. The associated cyclonic circulation extended up to 500 hPa and the trough aloft up to 200 hPa. The trough was located close to 70◦ E. On this particular day the daily precipitation varied between 2 cm to 9 cm at many places over northwest India. On 25 January 1999 the low pressure area over Rajasthan weakened considerably and moved east-northeastwards. The associated upper air trough was noticed between 700 hPa and 200 hPa. The precipitation amounts varying between 2 cm day−1 to 4 cm day−1 were recorded at a few places in northwest India. On 26 January 1999 the trough became very feeble. The observed 24-hourly precipitation amounts as recorded by the India Meteorological Department (IMD) at 0300 UTC from 22 to 25 January 1999 over northwest India are shown in Figure 9a−d. Synoptic weather information associated with the WD at 500 hPa is depicted in Figure 2.

Impact of horizontal model resolution and orography

Figure 2. Synoptic situations prevailing at 500 hPa, 21–25 January 1999.

5. Results and discussion To investigate the effects of horizontal model resolution and topography, simulated results from these experiments are considered for detailed analysis.

5.1. Experiment 1 In this experiment, actual topography is used for model integration for 96-hour forecasts with different horizontal model resolution and the results are discussed below.

to the height of 6000 m. It can be seen that the peaks over the northwest Himalayan region are higher in the FD than in the CD. Similarly, the valleys in the FD and the MD are seen more clearly than in the CD, where they appear to be absent. Though topography in the finer domain shows features of the Himalayan region better than that in the coarser domain, the FD does not represent the real mountain peaks and hence does not fully capture the actual gradient of the topography. In addition, simulation of the intricate orientation of the Himalayan ranges also depends on the computational limit of the machines.

5.1.1. Topography

5.1.2. Circulation features

The topography for the area (45◦ −90◦ E and 20◦ −42◦ N) for the FD, the MD and the CD are presented in Figure 1 respectively. Figure 1a is representative for the topography when replaced by a constant value of 1 metre over the entire domain as a flat surface. Differences in orographic structure among the three domains are apparent due to the horizontal resolution effect. The ridge paralleling to the northwest to southeast are the Himalayan ranges, which extend up

Model-simulated streamlines at 500 hPa at 24 hours (Figure 3d−f) show a well-defined trough over the northwest region. On comparing these simulations in the three domains with the actual, as shown in Figure 2a, it can be seen that the low pressure systems are stronger in the FD than in the CD. At 48 hours (Figure 4d−f) streamlines in the model simulation show the development of a low pressure centre in the region, where the trough existed the previous day. The location

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Figure 3. Streamline, isotach and wind (m sec−1 ) at 500 hPa after 24-hour forecast valid at 0000UTC on 22 January 1999 over flat and normal topography with different resolution.

of the simulated low pressure system is close to the observed one over northwest India (Figure 2b). The simulated low pressure centre in the FD is stronger and is followed by a feeble low pressure centre, which is not simulated at all by the MD and the CD. General flow patterns of the simulated winds at 500 hPa at 24 hours (Figure 3d−f) and 48 hours (Figure 4d−f) are comparable in the three domains. However, the finer the model resolution, the more prominent are the wind structures. The wind patterns for the MD and the FD show a more consistent cyclonic circulation than that in the CD. Strong maximum wind speed and the detailed structure of the wind distribution around the low pressure system are more pronounced in the FD. A maximum wind speed of 52 cm sec−1 is observed in the FD compared with only 45 cm sec−1 in the CD. Simulated vertical velocities at 500 hPa at 24 hours are shown in Figure 5d−f. The orographic lifting effect of the Himalayas is apparent in the vertical velocity fields in all the domains and it becomes stronger as

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the domain resolution becomes finer. Rising motions along the Himalayas are clearly seen. Similarly, sinking motions in various pockets indicate valleys in the region. However, the vertical velocities simulated in the three domains are quite different, and the stronger vertical velocity is better simulated in the finer domain. The maximum upward motion along the Himalayas at 24 hours for the CD (Figure 5f), the MD (Figure 5e) and the FD (Figure 5d) are about 16, 18 and 24 cm sec−1 , respectively. It shows that the simulated vertical velocity is very sensitive to model resolution. Similar trends in vertical velocities are found in the 48-hour simulations (Figure 6d−f).

5.1.3. Precipitation Observed accumulated 24-hour precipitation amounts, ending at 0300UTC, from 22 to 25 January 1999, are shown in Figure 9a−d. The corresponding simulated precipitation (from model integration, 0−24 h) for the FD, MD and CD over the same area is shown in


Figure 4. Streamline, isotach and wind (m sec−1 ) at 500 hPa after 48-hour forecast valid at 0000UTC on 23 January 1999 over flat and normal topography with different resolution.

Figure 7d−f. The simulated distribution of precipitation during this period remains widespread. The precipitation rate and the distribution pattern follow the existing orography in the region, but deviate somewhat from the actual quantity of precipitation. The centre of maximum precipitation also deviates from the observed centre. Obviously, the orographic lifting effect of the Himalayas could not be represented by the coarse resolution (x = 90 km) of the CD. Similarly, the MD (x = 60 km) does not simulate the actual observation well, though definite improvements in simulated precipitation quantity and location are observed. The precipitation rate and distribution are best simulated with the FD (x = 30 km). Here, the location of the maximum simulated precipitation is relatively close to that of the actual observation. The precipitation over the northwest Himalayas is better simulated, and the simulated precipitation rates are higher than those in the MD and the CD, which is closer to the actual. The predicted precipitation in the region agrees well with the observations, with a maximum value of about 6 cm/ day.

Observed accumulated 24-hour precipitation in cm/day for 23 January 1999 ending at 0300 UTC is shown in Figure 9b, and the corresponding simulated precipitation rate (from 24 to 48 hours) is shown in Figure 8d−f. The observed precipitation remains homogeneously distributed over the region with a maximum of 6 cm/day. The distribution of simulated precipitation in the CD is illustrated in Figure 8f. The figure shows that the precipitation is only 3 cm/day in the CD simulation, much less than the observed. The precipitation simulated in the MD case is better, though it shows the slight eastward shift of maxima from the actual, with maximum precipitation of 4 cm/day. In addition, the precipitation is more homogeneously distributed. The precipitation simulated in the FD case is shown in Figure 8d. The distribution pattern of simulated precipitation in the FD is similar to that in the MD, but with a higher maximum precipitation rate over the region. The predicted precipitation is much closer to the observed values. The maximum simulated precipitation rate of 6 cm/day is close to the observed value.

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Figure 5. Vertical velocity (cm sec−1 ) at 500 hPa after 24-hour forecast valid at 0000UTC on 22 January 1999 over flat and normal topography with different resolution.

5.2. Experiment 2 In this experiment, flat topography is applied within the fine, medium and coarse domains. Comparisons are made with the three domains of Experiment 1 to show the effect of horizontal model resolution with orographic change.

5.2.1. Circulation features Simulated streamlines at 500 hPa at 24 hours and 48 hours are studied. Simulated results at 24 hours show that a trough is located over the area (Figure 3a−c). In the 48-hour simulation (Figure 4a−c), this trough has become more intense. But comparison with the actual

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topography (Figure 4d−f) shows that the strength of this trough is overestimated in the flat terrain simulation. This suggests that the topography modulated the existing weather system. The general pattern of the wind speed at different horizontal model resolutions at 500 hPa at 24 hours (Figure 3a−c) and 48 hours (Figure 4a−c) also shows a similar reaction to the absence of topography. The existing trough on the first day gets deeper but fails to match the actual situation, although cyclonic circulation in the finer domain is more consistent with observation than the coarse domain. Similarly, the pattern of vertical velocity only poorly resembles the actual situation, being generally more


Figure 6. Vertical velocity (cm sec−1 ) at 500 hPa after 48-hour forecast valid at 0000UTC on 23 January 1999 over flat and normal topography with different resolution.

stable except in some patches where rising motions are prevalent (Figure 5a−c) and (Figure 6a−c).

differs too. This indicates that topography does affect the WD and shows that higher resolution of topography in the model produces better prediction of precipitation (Jarrand et al. 1988).

5.2.2. Precipitation With flat topography an almost homogeneous distribution of precipitation is observed. Simulated precipitation for day 1 and day 2 are given in Figure 7a−c and Figure 8a−c, respectively. As with experiment 1, the model with finer domains shows more detailed structure. Differences between Experiment 1 and Experiment 2 in the simulated precipitation rate and its distribution pattern over the FD, the MD and the CD exist due to differences in topography. The amount of precipitation over these domains is much less than for those in Experiment 1, and the precipitation distribution

6. Sensitivity studies of area-averaged precipitation Precipitation sensitivity is studied by considering the difference in precipitation rates across the three domains and the two experiments. Area-averaged precipitation (65◦ E to 80◦ E and 30◦ N to 40◦ N) for 24 hours during the entire 96-hour model integration is examined. The area-averaged maximum and area time-averaged values of simulated precipitation are given in Table 2. It is found that more precipitation is simulated as

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Figure 7. Precipitation (cm) after 24-hour forecast valid at 0000UTC on 22 January 1999 over flat and normal topography.

Table 2. Precipitation (cm/day) sensitivity analysis (30◦ –40◦ N and 65◦ –80◦ E) with the FD, the MD and the CD, and the reanalysed NCEP dataset and actual IMD/SASE observations. CD

Day 1 Day 2 Day 3 Day 4

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MD

FD

With terrain

Flat terrain

With terrain

Flat terrain

With terrain

Flat terrain

Max

Av

Max

Av

Max

Av

Max

Max

Max

Av

Max

Av

IMD/SASE Max

3.168 1.830 1.355 2.922

0.353 0.433 0.537 0.460

0.137 0.233 0.015 0.000

0.210 0.123 0.032 0.000

3.618 3.727 3.667 2.764

0.319 0.440 0.642 0.468

0.150 0.227 0.000 0.000

0.681 0.214 0.007 0.011

0.257 0.133 0.035 0.032

2.0 1.0 2.0 1.0

0.472 0.203 0.309 0.155

6.0 6.0 8.0 4.0

Av

Av

0.181 5.373 0.363 0.123 6.707 0.358 0.000 10.598 0.570 0.000 5.718 0.490

NCEP


Figure 8. Precipitation (cm) after 48-hour forecast valid at 0000UTC on 23 January 1999 over flat and normal topography.

the domain becomes finer and as the topography resolution becomes higher. Further, area-averaged maxima and area time-averaged precipitation rates get larger as the domain becomes finer. Secondly, less precipitation was simulated with flat topography than with normal topography as the gradient becomes smaller. This shows that model resolution and the topography gradient play a very important role in the prediction of precipitation in a western disturbance. As the estimation of precipitation mainly depends upon horizontal moisture convergence and vertical velocity, and since horizontal convergence and vertical velocity are stronger in finer domains, more precipitation is simulated in finer domains. Further, as topography is better presented in finer domains, location and structure of orography barriers allows the generation

of more realistic location-specific precipitation. Because orographic gradients are larger in finer domains, better precipitation results can be simulated. However, it is very difficult to say whether it is the effect of model resolution or of topography that plays the major part as both are closely related to each other. But the ratios of the FD mean and the CD mean in these experiments − 1.028 and 1.220, respectively − suggest that the effect of topography plays the more important role. Further, in comparing these precipitation rates with the NCEP/NCAR reanalysis datasets, it is found that precipitation rates simulated at fine resolution are much closer to these and also to the observations of the IMD and the Snow and Avalanche Study Establishment (SASE), Manali.

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Figure 9. Precipitation (cm): (a–d) observed; (e–h) simulated, for 30 km model resolution.

7. Summary and conclusions Simulation of an active WD is carried out with three types of horizontal model resolutions with actual topography (Experiment 1) and flat topography (Experiment 2). A MM5 model is used to study the impact of horizontal model resolution and topography on the simulation of a WD and associated precipitation. Model simulations with finer horizontal model resolution bring out more features than does the coarser resolution. It is seen that the precipitation rate and its distribution are very sensitive to the horizontal model resolution and topography. Larger precipitation rates are simulated better in the finer

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domain. Larger amounts of precipitation and more intense precipitation distributions are observed in the finer horizontal model resolution. Vertical velocity, 500 hPa wind speed and their general flow pattern are also sensitive to the model resolution. Orographic lifting effects due to mountain are simulated in finer domains and it is observed that the gradient of the topography plays a crucial role in modifying the weather system. This study indicates that with the same physics, but with finer resolution, orographic and mesoscale features can be better simulated. Topography plays a more crucial role in the sensitivity of the precipitation rate than the horizontal model resolution.


Acknowledgements The author acknowledges NCEP/NCAR for the use of its reanalysis datasets in the present study. The author thanks the IMD for providing datasets and synoptic information.

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