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1.
Simulation of a flood producing rainfall event of 29 July 2010 over north-west Pakistan has been carried out using the Weather Research and Forecasting (WRF) model. This extraordinary rainfall event was localized over north-west Pakistan and recorded 274 mm of rainfall at Peshawar (34.02°N, 71.58°E), within a span of 24 h on that eventful day where monthly July normal rainfall is only 46.1 mm. The WRF model was run with the triple-nested domains of 27, 9, and 3 km horizontal resolution using Kain–Fritsch cumulus parameterization scheme having YSU planetary boundary layer. The model performance was evaluated by examining the different simulated parameters. The model-derived rainfall was compared with Pakistan Meteorological Department–observed rainfall. The model suggested that this flood producing heavy rainfall event over north-west region of Pakistan might be the result of an interaction of active monsoon flow with upper air westerly trough (mid-latitude). The north-west Pakistan was the meeting point of the southeasterly flow from the Bay of Bengal following monsoon trough and southwesterly flow from the Arabian Sea which helped to transport high magnitude of moisture. The vertical profile of the humidity showed that moisture content was reached up to upper troposphere during their mature stage (monsoon system usually did not extent up to that level) like a narrow vertical column where high amounts of rainfall were recorded. The other favourable conditions were strong vertical wind shear, low-level convergence and upper level divergence, and strong vorticity field which demarked the area of heavy rainfall. The WRF model might be able to simulate the flood producing rainfall event over north-west Pakistan and associated dynamical features reasonably well, though there were some spatial and temporal biases in the simulated rainfall pattern.  相似文献   

2.
The three dimensional variational data assimilation scheme (3D-Var) is employed in the recently developed Weather Research and Forecasting (WRF) model. Assimilation experiments have been conducted to assess the impact of Indian Space Research Organisation’s (ISRO) Automatic Weather Stations (AWS) surface observations (temperature and moisture) on the short range forecast over the Indian region. In this study, two experiments, CNT (without AWS observations) and EXP (with AWS observations) were made for 24-h forecast starting daily at 0000 UTC during July 2008. The impact of assimilation of AWS surface observations were assessed in comparison to the CNT experiment. The spatial distribution of the improvement parameter for temperature, relative humidity and wind speed from one month assimilation experiments demonstrated that for 24-h forecast, AWS observations provide valuable information. Assimilation of AWS observed temperature and relative humidity improved the analysis as well as 24-h forecast. The rainfall prediction has been improved due to the assimilation of AWS data, with the largest improvement seen over the Western Ghat and eastern India.  相似文献   

3.
An abnormal warming condition with 3?C5?°C rise in temperature above its normal value was observed in the Indian state of Odisha during 12?C16 November 2009. This study aims at examining the impact of additional weather observations obtained from the automatic weather stations (AWS) installed in the recent past on the numerical simulation of such abnormal warming. AWS observations, such as temperature at 2?m (T2m), dew point temperature at 2?m (Td2m), wind vector at 10?m (speed and direction), and sea level pressure (SLP) have been assimilated into the state-of-the-art Weather Research and Forecasting (WRF) model using the three-dimensional variational data assimilation (3DVAR). Six sets of experiments have been conducted here. There is no data assimilation in the control experiment, whereas AWS and radiosonde observations have been assimilated in rest of the five experiments. The model integrations have been made for 72?h in each experiment starting from 0000 UTC November 12 to 0000 UTC November 15, 2009. Assimilation experiments have also been performed to assess the impact of individual surface parameters on the model simulations. Impact of AWS observations on model simulation has been examined with reference to the control simulation and quantified in terms of root-mean-square error and forecast skill score for temperature, sea level pressure, and relative humidity at three selected stations Bonaigarh, Brahmagiri, and Nuapada in Odisha. Results indicate improvements in the surface air temperature and SLP simulations in the timescale of 72?h at all the three stations due to additional weather data assimilation into the model. Improvements in simulation are significant up to 24?h. The assimilation of additional wind fields significantly improved the temperature simulation at all the three stations. The simulated SLP has also improved significantly due to the assimilation of surface temperature and moisture.  相似文献   

4.
Real-time predictions for the JAL severe cyclone formed in November 2010 over Bay of Bengal using a high-resolution Weather Research and Forecasting (WRF ARW) mesoscale model are presented. The predictions are evaluated with different initial conditions and assimilation of observations. The model is configured with two-way interactive nested domains and with fine resolution of 9?km for the region covering the Bay of Bengal. Simulations are performed with NCEP GFS 0.5° analysis and forecasts for initial/boundary conditions. To examine the impact of initial conditions on the forecasts, eleven real-time numerical experiments are conducted with model integration starting at 00, 06, 12, 18 UTC 4 Nov, 5?Nov and 00, 06, 12 UTC 6 Nov and all ending at 00 UTC 8 Nov. Results indicated that experiments starting prior to 18 UTC 04 Nov produced faster moving cyclones with higher intensity relative to the IMD estimates. The experiments with initial time at 18 UTC 04 Nov, 00 UTC 05 Nov and with integration length of 78?h and 72?h produced best prediction comparable with IMD estimates of the cyclone track and intensity parameters. To study the impact of observational assimilation on the model predictions FDDA, grid nudging is performed separately using (1) land-based automated weather stations (FDDAAWS), (2) MODIS temperature and humidity profiles (FDDAMODIS), and (3) ASCAT and OCEANSAT wind vectors (FDDAASCAT). These experiments reduced the pre-deepening period of the storm by 12?h and produced an early intensification. While the assimilation of AWS data has shown meagre impact on intensity, the assimilation of scatterometer winds produced an intermittent drop in intensity in the peak stage. The experiments FDDAMODIS and FDDAQSCAT produced minimum error in track and intensity estimates for a 90-h prediction of the storm.  相似文献   

5.
In the present study, diagnostic studies were undertaken using station-based rainfall data sets of selected stations of Guyana to understand the variability of rainfall. The multidecadal variation in rainfall of coastal station Georgetown and inland station Timehri has shown that the rainfall variability was less during the May–July (20–30%) of primary wet season compared to the December--January (60–70%) of second wet season. The rainfall analysis of Georgetown based on data series from 1916 to 2007 shows that El Niño/La Niña has direct relation with monthly mean rainfall of Guyana. The impact is more predominant during the second wet season December--January. A high-resolution Weather Research and Forecasting model was made operational to generate real-time forecasts up to 84 h based on 00 UTC global forecast system (GFS), NCEP initial condition. The model real-time rainfall forecast during July 2010 evaluation has shown a reasonable skill of the forecast model in predicting the heavy rainfall events and major circulation features for day-to-day operational forecast guidance. In addition to the operational experimental forecast, as part of model validation, a few sensitivity experiments are also conducted with the combination of two cloud cumulus (Kain--Fritsch (KF) and Betts–Miller–Janjic (BMJ)) and three microphysical schemes (Ferrier et al. WSM-3 simple ice scheme and Lin et al.) for heavy rainfall event occurred during 28–30 May 2010 over coastal Guyana and tropical Hurricane ‘EARL’ formed during 25 August–04 September 2010 over east Caribbean Sea. It was observed that there are major differences in the simulations of heavy rainfall event among the cumulus schemes, in spite of using the same initial and boundary conditions and model configuration. Overall, it was observed that the combination of BMJ and WSM-3 has shown qualitatively close to the observed heavy rainfall event even though the predicted amounts are less. In the case of tropical Hurricane ‘EARL’, the forecast track in all the six experiments based on 00 UTC of 28 August 2010 initial conditions for the forecast up to 84 h has shown that the combination of KF cumulus and Ferrier microphysics scheme has shown less track errors compared to other combinations. The overall average position errors for all the six experiments taken together work out to 103 km in 24, 199 km in 48, 197 km in 72 and 174 km in 84 h.  相似文献   

6.
In this study, the impact of four-dimensional data assimilation (FDDA) analysis nudging is examined on the prediction of tropical cyclones (TC) in the Bay of Bengal to determine the optimum period and timescale of nudging. Six TCs (SIDR: November 13–16, 2007; NARGIS: April 29–May 02, 2008; NISHA: November 25–28, 2008; AILA: May 23–26, 2009; LAILA: May 18–21, 2010; JAL: November 04–07, 2010) were simulated with a doubly nested Weather Research and Forecasting (WRF) model with a horizontal resolution of 9 km in the inner domain. In the control run for each cyclone, the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) analysis and forecasts at 0.5° resolution are used for initial and boundary conditions. In the FDDA experiments available surface, upper air observations obtained from NCEP Atmospheric Data Project (ADP) data sets were used for assimilation after merging with the first guess through objective analysis procedure. Analysis nudging experiments with different nudging periods (6, 12, 18, and 24 h) indicated a period of 18 or 24 h of nudging during the pre-forecast stage provides maximum impact on simulations in terms of minimum track and intensity forecasts. To determine the optimum timescale of nudging, two cyclone cases (NARGIS: April 28–May 02, 2008; NISHA: November 25–28, 2008) were simulated varying the inverse timescales as 1.0e?4 to 5.0e?4 s?1 in steps of 1.0e?4 s?1. A positive impact of assimilation is found on the simulated characteristics with a nudging coefficient of either 3.0e?4 or 4.0e?4 s?1 which corresponds to a timescale of about 1 h for nudging dynamic (u,v) and thermodynamical (t,q) fields.  相似文献   

7.
The convection and planetary boundary layer (PBL) processes play significant role in the genesis and intensification of tropical cyclones (TCs). Several convection and PBL parameterization schemes incorporate these processes in the numerical weather prediction models. Therefore, a systematic intercomparison of performance of parameterization schemes is essential to customize a model. In this context, six combinations of physical parameterization schemes (2 PBL Schemes, YSU and MYJ, and 3 convection schemes, KF, BM, and GD) of WRF-ARW model are employed to obtain the optimum combination for the prediction of TCs over North Indian Ocean. Five cyclones are studied for sensitivity experiments and the out-coming combination is tested on real-time prediction of TCs during 2008. The tracks are also compared with those provided by the operational centers like NCEP, ECMWF, UKMO, NCMRWF, and IMD. It is found that the combination of YSU PBL scheme with KF convection scheme (YKF) provides a better prediction of intensity, track, and rainfall consistently. The average RMSE of intensity (13?hPa in CSLP and 11?m?s?1 in 10-m wind), mean track, and landfall errors is found to be least with YKF combination. The equitable threat score (ETS) of YKF combination is more than 0.2 for the prediction of 24-h accumulated rainfall up to 125?mm. The vertical structural characteristics of cyclone inner core also recommend the YKF combination for Indian seas cyclones. In the real-time prediction of 2008 TCs, the 72-, 48-, and 24-h mean track errors are 172, 129, and 155?km and the mean landfall errors are 125, 73, and 66?km, respectively. Compared with the track of leading operational agencies, the WRF model is competing in 24?h (116?km error) and 72?h (166?km) but superior in 48-h (119?km) track forecast.  相似文献   

8.
Rainfall is one of the pivotal climatic variables, which influence spatio-temporal patterns of water availability. In this study, we have attempted to understand the interannual long-term trend analysis of the daily rainfall events of ≥?2.5 mm and rainfall events of extreme threshold, over the Western Ghats and coastal region of Karnataka. High spatial resolution (0.25°?×?0.25°) daily gridded rainfall data set of Indian Meteorological Department was used for this study. Thirty-eight grid points in the study area was selected to analyze the daily precipitation for 113 years (1901–2013). Grid points were divided into two zones: low land (exposed to the sea and low elevated area/coastal region) and high land (interior from the sea and high elevated area/Western Ghats). The indices were selected from the list of climate change indices recommended by ETCCDI and are based on annual rainfall total (RR), yearly 1-day maximum rainfall, consecutive wet days (≥?2.5 mm), Simple Daily Intensity Index (SDII), annual frequency of very heavy rainfall (≥?100 mm), frequency of very heavy rainfall (≥?65–100 mm), moderate rainfall (≥?2.5–65 mm), frequency of medium rainfall (≥?40–65 mm), and frequency of low rainfall (≥?20–40 mm). Mann-Kendall test was applied to the nine rainfall indices, and Theil-Sen estimator perceived the nature and the magnitude of slope in rainfall indices. The results show contrasting trends in the extreme rainfall indices in low land and high land regions. The changes in daily rainfall events in the low land region primarily indicate statistically significant positive trends in the annual total rainfall, yearly 1-day maximum rainfall, SDII, frequency of very heavy rainfall, and heavy rainfall as well as medium rainfall events. Furthermore, the overall annual rainfall strongly correlated with all the rainfall indices in both regions, especially with indices that represent heavy rainfall events which is responsible for the total increase of rainfall.  相似文献   

9.
In this work, the impact of assimilation of conventional and satellite data is studied on the prediction of two cyclonic storms in the Bay of Bengal using the three-dimensional variational data assimilation (3D-VAR) technique. The FANOOS cyclone (December 6?C10, 2005) and the very severe cyclone NARGIS (April 28?CMay 2, 2008) were simulated with a double-nested weather research and forecasting (WRF-ARW) model at a horizontal resolution of 9?km. Three numerical experiments were performed using the WRF model. The back ground error covariance matrix for 3DVAR over the Indian region was generated by running the model for a 30-day period in November 2007. In the control run (CTL), the National Centers for Environmental Prediction (NCEP) global forecast system analysis at 0.5° resolution was used for the initial and boundary conditions. In the second experiment called the VARCON, the conventional surface and upper air observations were used for assimilation. In the third experiment (VARQSCAT), the ocean surface wind vectors from quick scatterometer (QSCAT) were used for assimilation. The CTL and VARCON experiments have produced higher intensity in terms of sea level pressure, winds and vorticity fields but with higher track errors. Assimilation of conventional observations has meager positive impact on the intensity and has led to negative impact on simulated storm tracks. The QSCAT vector winds have given positive impact on the simulations of intensity and track positions of the two storms, the impact is found to be relatively higher for the moderate intense cyclone FANOOS as compared to very severe cyclone NARGIS.  相似文献   

10.
Various reanalyses have been utilized in numerous climate related researches around the globe, however, there exists considerable biasedness in these products, especially in precipitation and temperature data. The ability of these reanalysis products to simulate the precipitation and temperature patterns is observed to be satisfactory at global scale, while it differs significantly at regional scale, especially over regions of high spatio-temporal heterogeneity such as India. Therefore, it is essential to evaluate the applicability and robustness of reanalyses in climate related research. The annual and seasonal variability in spatio-temporal patterns and trends of precipitation and temperature data, with respect to the IMD gridded data over 34 yrs, are evaluated for six global reanalyses namely, NCEP/NCAR Reanalysis (NCEP R1), NCEP-DOE AMIP-2 Reanalysis (NCEP R2), Climate Forecast System Reanalysis (CFSR), ECMWF Interim Reanalysis (ERA-Interim), Modern Era Retrospective Analysis for Research and Application Land only model (MERRA-Land) and JMA 55-year Reanalysis (JRA-55). The ability of the reanalyses was tested based on several factors such as statistical and categorical indices, spells and trends, for annual and seasonal daily values. Several regional and seasonal differences were observed, particularly over high rainfall regions such as Western Ghats and northeastern India. MERRA-Land is found to give the best results for precipitation over India, which is attributed to the updated forcing data using gauge-based precipitation observations. Similarly, ERA-Interim and JRA-55 exhibit better performance for temperature than other datasets. All reanalyses failed to correctly reproduce the trends in IMD data, for both precipitation and temperature. These observations will provide a better perception on the reliability and applicability of reanalyses for climate and hydrological studies over India.  相似文献   

11.
In this paper, impact of Indian Doppler Weather Radar (DWR) data, i.e., reflectivity (Z), radial velocity (Vr) data individually and in combination has been examined for simulation of mesoscale features of a land-falling cyclone with Advance Regional Prediction System (ARPS) Model at 9-km horizontal resolution. The radial velocity and reflectivity observations from DWR station, Chennai (lat. 13.0°N and long. 80.0°E), are assimilated using the ARPS Data Assimilation System (ADAS) and cloud analysis scheme of the model. The case selected for this study is the Bay of Bengal tropical cyclone NISHA of 27–28 November 2008. The study shows that the ARPS model with the assimilation of radial wind and reflectivity observations of DWR, Chennai, could simulate mesoscale characteristics, such as number of cells, spiral rain band structure, location of the center and strengthening of the lower tropospheric winds associated with the land-falling cyclone NISHA. The evolution of 850 hPa wind field super-imposed vorticity reveals that the forecast is improved in terms of the magnitude and direction of lower tropospheric wind, time, and location of cyclone in the experiment when both radial wind and reflectivity observations are used. With the assimilation of both radial wind and reflectivity observations, model could reproduce the rainfall pattern in a more realistic way. The results of this study are found to be very promising toward improving the short-range mesoscale forecasts.  相似文献   

12.
During July 11–14, 2012, deadly floods and landslides triggered by a series of unprecedented heavy rains hit Kyushu, Japan, causing at least 32 deaths and around 400,000 evacuations. We focus on synoptic anomalies identified after inspecting rainfall patterns and documenting the conditions associated with this tragic event using data combined from the Global Rainfall Map in Near Real Time data, the NCEP/NCAR Reanalysis dataset, and the global forecast system. Rainfall maps indicated that there were many heavy rains in Kyushu in these days and this disaster was associated with the pattern of forecasts and standardized anomalies. A weather trough with positive height anomalies appeared, the center of which moved to the north of Japan over this period, which might cause wind anomalies and whereby lots of water vapor were transported to Kyushu area with up to 90 m s?1, and high values of precipitable water formed with up to 60 mm. These results suggest that a larger-scale pattern is conducive for heavy rainfall and the anomalies put the pattern in context as to the potential for an extreme rainfall event, which can provide insights and methods for predicting extreme events’ or something similar.  相似文献   

13.
We report GPS measurements of continuous observations from the multi-parametric geophysical observatory (MPGO) at Ghuttu, Garhwal Lesser Himalaya. Other than the evidence of secular motion depicting strain accumulation due to locking of the underneath seismically active detachment, measurements at Ghuttu show annual variation of ±4 mm on horizontal component. Such variations are more prominent in the north coordinate and do not directly correlate with the meteorological parameters such as variations in rainfall, water table, and atmospheric pressure measured at the MPGO observatory. These variations are also not the artefact of data processing and network. They correlate with the water load storage in the Ganga plains, with minimum in displacement coinciding with the maximum storage of water in Ganga plains immediately after the monsoon and vice versa. Such variations also appear to cause annual variation in the low-magnitude earthquake frequency in the Himalayan region, being relatively more in the winter period.  相似文献   

14.
Heavy off-season rains in the tropics pose significant natural hazards largely because they are unexpected and the popular infrastructure is ill-prepared. One such event was observed from January 9 to 11, 2002 in Senegal (14.00° N, 14.00°␣W), West Africa. This tropical country is characterized by a long dry season from November to April or May. During this period, although the rain-bearing monsoonal flow does not reach Senegal, the region can occasionally experience off-season rains. We conducted a numerical simulation of the January 9–11, 2002 heavy off-season rain using the Fifth-Generation NCAR/Pennsylvania State University Mesoscale Model (MM5) and the Weather Research and Forecasting (WRF) model. The objective was to delineate the meteorological set-up that led to the heavy rains and flooding. A secondary objective was to test the model’s performance in Senegal using relatively simpler (default) model configurations and local/regional observations. The model simulations for both MM5 and WRF agree satisfactorily with the observations, particularly as regards the wind patterns, the intensification of the rainfall, and the associated drop in temperatures. This situation provided the environment for heavy rainfall accompanied by a cold wave. The results suggest that off-the-shelf weather forecast models can be applied with relatively simple physical options and modest computational resources to simulate local impacts of severe weather episodes. In addition, these models could become part of regional hazard mitigation planning and infrastructure.  相似文献   

15.
In the present study, the Advanced Research WRF (ARW) version 3.2.1 has been used to simulate the heavy rainfall event that occurred between 7 and 9 October 2007 in the southern part of Bangladesh. Weather Research and Forecast (WRF–ARW version) modelling system with six different microphysics (MP) schemes and two different cumulus parameterization (CP) schemes in a nested configuration was chosen for simulating the event. The model domains consist of outer and inner domains having 9 and 3 km horizontal resolution, respectively with 28 vertical sigma levels. The impacts of cloud microphysical processes by means of precipitation, wind and reflectivity, kinematic and thermodynamic characteristics of the event have been studied. Sensitivity experiments have been conducted with the WRF model to test the impact of microphysical and cumulus parameterization schemes in capturing the extreme weather event. NCEP FNL data were used for the initial and boundary condition. The model ran for 72 h using initial data at 0000 UTC of 7 October 2007. The simulated rainfall shows that WSM6–KF combination gives better results for all combinations and after that Lin–KF combination. WSM3–KF has simulated, less area average rainfall out of all MP schemes that were coupled with KF scheme. The sharp peak of relative humidity up to 300 hPa has been simulated along the vertical line where maximum updraft has been found for all MPs coupled with KF and BMJ schemes. The simulated rain water and cloud water mixing ratio were maximum at the position where the vertical velocity and reflectivity has also been maximum. The production of rain water mixing ratio depends on MP schemes as well as CP schemes. Rainfall depends on rain water mixing ratio between 950 and 500 hPa. Rain water mixing ratio above 500 hPa level has no effect on surface rain.  相似文献   

16.
The paper deals with the study of the physical and dynamical characteristics of a severe thunderstorm, which had occurred on April 5, 2015, at about 2100 UTC in the southwestern Bangladesh with location around 23.3–23.7N and 89.0–89.4E within the upazilas (sub-districts) of Kumarkhali and Shailkupa under the districts of Kushtia and Jhenaidah, respectively. The thunderstorm was associated with numerous hails of large size. More than 5000 birds which used to live in the bird sanctuary at Shailkupa and 22,011 birds in Chhaglapara Bird Sanctuary of Kumarkhali died as they were hit by the hails. Large hails also damaged crops, houses and forests over the thunderstorm hit areas. The evolution of the thunderstorm is studied by the WRF model, which is initialized using the National Centers for Environmental Prediction Final reanalysis data of 0000 UTC of April 5, 2015. The simulated results provide a basis to study the physical and dynamical characteristics of the thunderstorm, which are generally not identified by the meteorological observations which are too sparse. The model has captured a micro-low over Kumarkhali and its neighborhood, which favored the occurrence of the severe thunderstorm. The model simulated rainfall is about 26 mm near the place of occurrence, which matches well with the area where the reflectivity of hydrometeor is maximum. The convective available potential energy is found to be 1600 J kg?1 at 1730 UTC near the place of occurrence of the thunderstorm; this indicates high atmospheric instability over the thunderstorm location for the formation of the thunderstorm. The vertical velocity, convergence, cloud water mixing ratio and the ice water mixing ratio and their vertical extensions are found to be satisfactory and responsible for the occurrence of large hails associated with the thunderstorm.  相似文献   

17.
Evaporation capacity is an important factor that cannot be ignored when judging whether extreme precipitation events will produce groundwater recharge. The evaporation layer’s role in groundwater recharge was evaluated using a lysimeter simulation experiment in the desert area of Dunhuang, in the western part of the Hexi Corridor in northwestern China’s Gansu Province. The annual precipitation in the study area is extremely low, averaging 38.87 mm during the 60-year study period, and daily pan evaporation amounts to 2,486 mm. Three simulated precipitation regimes (normal, 10 mm; ordinary annual maximum, 21 mm; and extreme, 31 mm) were used in the lysimeter simulation to allow monitoring of water movement and weighing to detect evaporative losses. The differences in soil-water content to a depth of 50 cm in the soil profile significantly affected rainfall infiltration during the initial stages of rainfall events. It was found that the presence of a dry 50-cm-deep sand layer was the key factor for “potential recharge” after the three rainfall events. Daily precipitation events less than 20 mm did not produce groundwater recharge because of the barrier effect created by the dry sand. Infiltration totaled 0.68 mm and penetrated to a depth below 50 cm with 31 mm of rainfall, representing potential recharge equivalent to 1.7 % of the rainfall. This suggests that only extreme precipitation events offer the possibility of recharge of groundwater in this extremely arid area.  相似文献   

18.
An accurate tropical cyclone track and intensity forecast is very important for disaster management. Specialized numerical prediction models have been recently used to provide high-resolution temporal and special forecasts. Hurricane Weather Research and Forecast (HWRF) model is one of the emerging numerical models for tropical cyclone forecasting. This study evaluates the performance of HWRF model during the post monsoon tropical cyclone Nilofar on the north Indian Ocean basin. The evaluation uses the best track data provided by the Indian Meteorological Department (IMD) and the Joint Typhoon Warning Centre (JTWC). Cyclone track, central pressure, and wind speed are covered on this evaluation. Generally, HWRF was able to predict the Nilofar track with track error less than 230 km within the first 66 h of forecast time span. HWRF predicted more intense tropical cyclone. It predicted the lowest central pressure to be 922 hPa while it reached 950 hPa according to IMD and 937 hPa according to JTWC. Wind forecast was better as it predicted maximum wind speed of 122 kt while it reached 110 and 115 kt according to IMD and JTWC, respectively.  相似文献   

19.
The cloudburst is defined as a heavy downpour at a very high rainfall rate over small spatio-temporal scale. The Indian states of Uttarakhand (30°15′N; 79°15′E) and Himachal Pradesh (32°29′N; 75°10′E) are prone to cloudburst due to its geographical setup. The large-scale monsoon flow along with elevated orography makes cloudburst phenomena frequent a well as severe over the regions. However, cloudburst and the heavy rainfall events occasionally, become difficult to distinguish. The present study attempts to identify the processes associated with cloudburst over elevated orography and compare it with one of the most debated event of 2013 which was reported as heavy rainfall but, not a cloudburst by Indian Meteorological Department (IMD). The temporal variations of rainfall and cloud-top pressure (CTP) are considered to identify the genesis of the event. The vertical developments of the system along with large-scale circulation pattern are estimated in the present study. The result of the study reveals that the mid-tropospheric dry entrainment, low-level temperature inversion and cloud height clearly distinguish the “cloudburst” and “heavy rainfall” events and confirms that the system of 2013 was indeed a heavy rainfall event and not a cloudburst.  相似文献   

20.
利用WRF3D-Var同化多普勒雷达反演风场试验研究   总被引：2，自引：0，他引：2  
杨丽丽  王莹  杨毅 《冰川冻土》2016,38(1):107-114
为了将C波段雷达风场资料更好地应用于数值预报模式中,利用两步变分法反演多普勒雷达风场资料,并处理成标准的常规探空资料,以WRF模式及其三维变分同化系统为平台,针对2013年6月19日发生在天水的一次强暴雨过程进行同化雷达反演风的试验研究.试验结果表明:同化雷达反演风场后,对降水预报的改进能维持12h,尤其同化雷达反演风场后3~9h效果非常显著;0~3h作用不是很明显;9~12h预报具有一定的正作用.另外,循环同化比同化一次效果好,但并不是同化次数越多越好.因此,同化C波段雷达反演风场后,对降水预报具有一定的正作用.  相似文献   

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