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1.
Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features of very heavy rainfall (24 hours rainfall ≥125 mm) over Orissa during summer monsoon season (June–September) by analysing 20 years (1980–1999) daily rainfall data of different stations in Orissa. The principal objective of this study is to find out the role of synoptic scale monsoon disturbances in spatial and temporal variability of very heavy rainfall over Orissa. Most of the very heavy rainfall events occur in July and August. The region, extending from central part of coastal Orissa in the southeast towards Sambalpur district in the northwest, experiences higher frequency and higher intensity of very heavy rainfall with less interannual variability. It is due to the fact that most of the causative synoptic disturbances like low pressure systems (LPS) develop over northwest (NW) Bay of Bengal with minimum interannual variation and the monsoon trough extends in west-northwesterly direction from the centre of the system. The very heavy rainfall occurs more frequently with less interannual variability on the western side of Eastern Ghat during all the months and the season except September. It occurs more frequently with less interannual variability on the eastern side of Eastern Ghat during September. The NW Bay followed by Gangetic West Bengal/Orissa is the most favourable region of LPS to cause very heavy rainfall over different parts of Orissa except eastern side of Eastern Ghat. The NW Bay and west central (WC) Bay are equally favourable regions of LPS to cause very heavy rainfall over eastern side of Eastern Ghat. The frequency of very heavy rainfall does not show any significant trend in recent years over Orissa except some places in north-east Orissa which exhibit significant rising trend in all the monsoon months and the season as a whole.  相似文献   

2.
In boreal summer (June–September), most of the Indian land and its surroundings experience rainrates exceeding 6 mm day\(^{-1}\) with considerable spatial variability. Over southern Bay of Bengal (BoB) along the east coast of the Indian peninsula (henceforth referred to as the Bay of Bengal cold pool or BoB-CP), the rain intensity is significantly lower (<2 mm day\(^{-1}\)) than its surroundings. This low rainfall occurs despite the fact that the sea surface temperature in this region is well above the threshold for convection and the mean vorticity of the boundary layer is cyclonic with a magnitude comparable to that over the central Indian monsoon trough where the rainrate is about 10 mm day\(^{-1}\). It is also noteworthy that the seasonal cycle of convection over the BoB-CP shows a primary peak in November and a secondary peak in May. This is in contrast to the peak in June–July over most of the oceanic locations surrounding the BoB-CP. In this study, we investigate the role of the Western Ghat (WG) mountains in an Atmospheric General Circulation Model (AGCM) to understand this paradox. Decade-long simulations of the AGCM were carried out with varying (from 0 to 2 times the present) heights of the WG. We find that the lee waves generated by the strong westerlies in the lower troposphere in the presence of the WG mountains cause descent over the BoB-CP. Thus, an increase in the height of the WG strengthens the lee waves and reduces rainfall over the BoB-CP. More interestingly in the absence of WG mountains, the BoB-CP shows a rainfall maxima in the boreal summer similar to that over its surrounding oceans. The WG also impacts the climate over the middle and high latitude regions by modifying the upper tropospheric circulation. The results of this study underline the importance of narrow mountains like the WG in the tropics in determining the global climate and possibly calls for a better representation of such mountains in climate models.  相似文献   

3.
The summer monsoon rainfall over Orissa occurs mostly due to low pressure systems (LPS) developing over the Bay of Bengal and moving along the monsoon trough. A study is hence undertaken to find out characteristic features of the relationship between LPS over different regions and rain-fall over Orissa during the summer monsoon season (June-September). For this purpose, rainfall and rainy days over 31 selected stations in Orissa and LPS days over Orissa and adjoining land and sea regions during different monsoon months and the season as a whole over a period of 20 years (1980-1999) are analysed. The principal objective of this study is to find out the role of LPS on spatial and temporal variability of summer monsoon rainfall over Orissa. The rainfall has been significantly less than normal over most parts of Orissa except the eastern side of Eastern Ghats during July and hence during the season as a whole due to a significantly less number of LPS days over northwest Bay in July over the period of 1980-1999. The seasonal rainfall shows higher interannual variation (increase in coefficient of variation by about 5%) during 1980-1999 than that during 1901-1990 over most parts of Orissa except northeast Orissa. Most parts of Orissa, especially the region extending from central part of coastal Orissa to western Orissa (central zone) and western side of the Eastern Ghats get more seasonal monsoon rainfall with the development and persistence of LPS over northwest Bay and their subsequent movement and persistence over Orissa. The north Orissa adjoining central zone also gets more seasonal rainfall with development and persistence of LPS over northwest Bay. While the seasonal rainfall over the western side of the Eastern Ghats is adversely affected due to increase in LPS days over west central Bay, Jharkhand and Bangladesh, that over the eastern side of the Eastern Ghats is adversely affected due to increase in LPS days over all the regions to the north of Orissa. There are significant decreasing trends in rainfall and number of rainy days over some parts of southwest Orissa during June and decreasing trends in rainy days over some parts of north interior Orissa and central part of coastal Orissa during July over the period of 1980-1999  相似文献   

4.
The impact of Southern Oscillation on thecyclogenesis over the Bay of Bengal duringthe summer monsoon has been investigated.The analysis of correlation coefficients(CCs) between the frequency of monsoondepressions and the Southern OscillationIndex (SOI) reveals that more depressionsform during July and August of El Niñoyears. Due to this, the seasonal frequencyof monsoon depressions remains little higherduring El Niño epochs even though thecorrelations for June and September are notsignificant. The CCs for July and August aresignificant at the 99% level.The El Niño-Southern Oscillation (ENSO)is known to affect Indian MonsoonRainfall (IMR) adversely. The enhancedcyclogenesis over the Bay of Bengal duringJuly and August is an impact of ENSO whichneeds to be examined closely. Increasedcyclogenesis over the Bay of Bengal may bereducing the deficiency in IMR duringEl Niño years by producing more rainfallover the eastern parts of India duringJuly and August. Thus there is a considerablespatial variation in the impact of ENSOon the monsoon rainfall over India and El Niñoneed not necessarily imply a monsoonfailure everywhere in India.The area of formation of monsoon depressionsshifts eastward during El Niño years.Warmer sea surface temperature (SST) anomaliesprevail over northwest and adjoiningwestcentral Bay of Bengal during premonsoon andmonsoon seasons of El Niño years.May minus March SOI can provide useful predictionsof monsoon depression frequencyduring July and August.  相似文献   

5.
Meteorological drought during the southwest monsoon season and for the northeast monsoon season over five meteorological subdivisions of India for the period 1901–2015 has been examined using district and all India standardized precipitation index (SPI). Whenever all India southwest monsoon rainfall was less than ?10% or below normal, for those years all India SPI was found as ?1 or less. Composite analysis of SPI for the below normal years, viz., less than ?15% and ?20% of normal rainfall years indicate that during those years more than 30% of country’s area was under drought condition, whenever all India southwest monsoon rainfall was –15% or less than normal. Trend analysis of monthly SPI for the monsoon months identified the districts experiencing significant increase in drought occurrences. Significant positive correlation has been found with the meteorological drought over most of the districts of central, northern and peninsular India, while negative correlation was seen over the districts of eastern India with NINO 3.4 SST. For the first time, meteorological drought analysis over districts and its association with equatorial pacific SST and probability analysis has been done for the northeast monsoon over the affected regions of south peninsular India. Temporal correlation of all India southwest monsoon SPI and south peninsular India northeast monsoon SPI has been done with the global SST to identify the teleconnection of drought in India with global parameters.  相似文献   

6.
The Indian northeast monsoon is inherently chaotic in nature as the rainfall realised in the peninsular India depends substantially on the formation and movement of low-pressure systems in central and southwest Bay of Bengal and on the convective activity which is mainly due to the moist north-easterlies from Bay of Bengal. The objective of this study is to analyse the performance of the PSU-NCAR Mesoscale Model Version 5 (MM5), for northeast monsoon 2008 that includes tropical cyclones – Rashmi, Khai-Muk and Nisha and convective events over Sriharikota region, the rocket launch centre. The impact of objective analysis system using radiosonde observations, surface observations and Kalpana-1 satellite derived Atmospheric Motion Wind Vectors (AMV) is also studied. The performance of the model is analysed by comparing the predicted parameters like mean sea level pressure (MSLP), intensity, track and rainfall with the observations. The results show that the model simulations could capture MSLP and intensity of all the cyclones reasonably well. The dependence of the movement of the system on the environmental flow is clearly observed in all the three cases. The vector displacement error and percentage of improvement is calculated to study the impact of objective data analysis on the movement and intensity of the cyclone.  相似文献   

7.
A two-dimensional, nonlinear, vertically integrated model was used to simulate depth-mean wind-driven circulation in the upper Ekman layers of the Bay of Bengal and Andaman Sea. The model resolution was one third of a degree in the latitude and longitude directions. Monthly mean wind stress components used to drive the model were obtained from the climatic monthly mean wind data compiled by Hastenrath and Lamb. A steady-state solution was obtained after numerical integration of the model for 15 days. The sensitivity of the model to two types of open boundary conditions, namely, a radiation type and clamped type, was tested. A comparison of simulated results for January with available ship drift data showed that the application of the latter along the open boundary could reproduce all the observed features near the boundary and the interior of the model domain. The model was integrated for 365 days to study the circulation during the southwest and northeast monsoon seasons. The model was successful in simulating the broad features of circulation including gyres and eddies observed during both the seasons, the development of north equatorial current during the northeast monsoon period and eastward moving monsoon drift current up to 90°E during the southwest monsoon season. During the latter season, two anticyclonic gyres were observed in the central and the southern parts of the Bay. A cyclonic type of circulation was prevalent in the central and western parts of the Bay of Bengal during the northeast monsoon months of November and December. The simulated western boundary current along the east coast of India, flows northward and southward during the southwest and northeast monsoon seasons respectively. It is presumed that this western boundary current, simulated during both the seasons, is locally wind-driven.  相似文献   

8.
Statistical bias correction methods for numerical weather prediction (NWP) forecasts of maximum and minimum temperatures over India in the medium-range time scale (up to 5 days) are proposed in this study. The objective of bias correction is to minimize the systematic error of the next forecast using bias from past errors. The need for bias corrections arises from the many sources of systematic errors in NWP modeling systems. NWP models have shortcomings in the physical parameterization of weather events and have the inability to handle sub-grid phenomena successfully. The statistical algorithms used for minimizing the bias of the next forecast are running-mean (RM) bias correction, best easy systematic estimator, simple linear regression and the nearest neighborhood (NN) weighted mean, as they are suitable for small samples. Bias correction is done for four global NWP model maximum and minimum temperature forecasts. The magnitude of the bias at a grid point depends upon geographical location and season. Validation of the bias correction methodology is carried out using daily observed and bias-corrected model maximum and minimum temperature forecast over India during July–September 2011. The bias-corrected NWP model forecast generally outperforms direct model output (DMO). The spatial distribution of mean absolute error and root-mean squared error for bias-corrected forecast over India indicate that both the RM and NN methods produce the best skill among other bias correction methods. The inter-comparison reveals that statistical bias correction methods improve the DMO forecast in terms of accuracy in forecast and have the potential for operational applications.  相似文献   

9.
Seasonal forecasting of tropical cyclogenesis over the North Indian Ocean   总被引：1，自引：0，他引：1  
Over the North Indian Ocean (NIO) and particularly over the Bay of Bengal (BoB), the post-monsoon season from October to December (OND) are known to produce tropical cyclones, which cause damage to life and property over India and many neighbouring countries. The variability of frequency of cyclonic disturbances (CDs) during OND season is found to be associated with variability of previous large-scale features during monsoon season from June to September, which is used to develop seasonal forecast model of CDs frequency over the BoB and NIO based on principal component regression (PCR). Six dynamical/thermodynamical parameters during previous June–August, viz., (i) sea surface temperature (SST) over the equatorial central Pacific, (ii) sea level pressure (SLP) over the southeastern equatorial Indian Ocean, (iii) meridional wind over the eastern equatorial Indian Ocean at 850 hPa, (iv) strength of upper level easterly, (v) strength of monsoon westerly over North Indian Ocean at 850 hPa, and (vi) SST over the northwest Pacific having significant and stable relationship with CDs over BoB in subsequent OND season are used in PCR model for a training period of 40 years (1971–2010) and the latest four years (2011–2014) are used for validation. The PCR model indicates highly significant correlation coefficient of 0.77 (0.76) between forecast and observed frequency of CD over the BoB (NIO) for the whole period of 44 years and is associated with the root mean square error and mean absolute error ≤ 1 CD. With respect to the category forecast of CD frequency over BoB and NIO, the Hit score is found to be about 63% and the Relative Operating Curves (ROC) for above and below normal forecast is found to be having much better forecast skill than the climatology. The PCR model performs very well, particularly for the above and below normal CD year over the BoB and the NIO, during the test period from 2011 to 2014.  相似文献   

10.
Objective analysis of daily rainfall at the resolution of 1° grid for the Indian monsoon region has been carried out merging dense land rainfall observations and INSAT derived precipitation estimates. This daily analysis, being based on high dense rain gauge observations was found to be very realistic and able to reproduce detailed features of Indian summer monsoon. The inter-comparison with the observations suggests that the new analysis could distinctly capture characteristic features of the summer monsoon such as north-south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough/low, over the east central parts of the country, over north-east India, along the foothills of Himalayas and over the north Bay of Bengal. When this product was used to assess the quality of other available standard climate products (CMAP and ECMWF reanalysis) at the gird resolution of 2.5°, it was found that the orographic heavy rainfall along Western Ghats of India was poorly identified by them. However, the GPCC analysis (gauge only) at the resolution of 1° grid closely discerns the new analysis. This suggests that there is a need for a higher resolution analysis with adequate rain gauge observations to retain important aspects of the summer monsoon over India. The case studies illustrated show that the daily analysis is able to capture large-scale as well as mesoscale features of monsoon precipitation systems. This study with data of two seasons (2001 and 2003) has shown sufficiently promising results for operational application, particularly for the validation of NWP models.  相似文献   

11.
In this study, an attempt has been made to examine the relationship between summer monsoon rainfall (June–September) and the total number of depressions, cyclones and severe cyclones (TNDC) over Bay of Bengal during the post-monsoon (October–December) season. The seasonal rainfall of the subdivisions (located in south India) (referred as rainfall index – RI), is positively and significantly correlated (r=0.59; significant at >99% level) with the TNDC during the period, 1984–2013. By using the first differences (current season minus previous season), the correlations are enhanced and a remarkably high correlation of 0.87 is observed between TNDC and RI for the recent period, 1993–2013. The average seasonal genesis potential parameter (GPP) showed a very high correlation of 0.84 with the TNDC. A very high correlation of 0.83 is observed between GPP and RI for the period, 1993–2013. The relative vorticity and mid-tropospheric relative humidity are found to be the dominant terms in GPP. The GPP was 3.5 times higher in above (below) normal RI in which TNDC was 4 (2). It is inferred that RI is playing a key role in TNDC by modulating the environmental conditions (low level vorticity and relative humidity) over Bay of Bengal during post-monsoon season which could be seen from the very high correlation of 0.87 (which explains 76% variability in TNDC). For the first time, we show that RI is a precursor for the TNDC over Bay of Bengal during post-monsoon season. Strong westerlies after the SW monsoon season transport moisture over the subdivisions towards Bay of Bengal due to cyclonic circulation. This circulation favours upward motion and hence transport moisture vertically to mid-troposphere which causes convective instability and this in turn favour more number of TNDC, under above-normal RI year.  相似文献   

12.
Unprecedented precipitation along with heavy falls occurred over many parts of India from 28th February to 2nd March 2015. Many of the stations of northwest and central India received an all time high 24 hr cumulative precipitation of March during this period. Even the national capital, New Delhi, broke all the previous historical 24 hr rainfall records of the last 100 years to the rainfall record in March 2015. Due to this event, huge loss to agricultural and horticultural crops occurred in several parts of India. In the present study, an attempt is made to understand the various meteorological features associated with this unprecedented precipitation event over India. It occurred due to the presence of an intense western disturbance (WD) over Afghanistan and neighbouring areas in the form of north–south oriented deep trough in westerlies in middle and upper tropospheric levels with its southern end deep in the Arabian Sea, which pumped huge moisture feed over Indian region. Also, there was a jet stream with core wind speed up to 160 knots that generated high positive divergence at upper tropospheric level over Indian region; along with this there was high magnitude of negative vertical velocity and velocity convergence were there at middle tropospheric level. It caused intense upward motion and forced lower levels air to rise and strengthen the lower levels cyclonic circulations (CCs)/Lows. Moreover, the induced CCs/Lows at lower tropospheric levels associated with WD were more towards south of its normal position. Additionally, there was wind confluence over central parts of India due to westerlies in association with WD and easterlies from anticyclone over north Bay of Bengal. Thus, intense WD along with wind confluence between westerlies and easterlies caused unprecedented precipitation over India during the 1st week of March 2015.  相似文献   

13.
MODIS (Moderate Resolution Imaging Spectroradiometer) level-3 aerosol data, NCEP (National Centers for Environmental Prediction) reanalysis winds and QuikSCAT ocean surface winds were made use of to examine the role of atmospheric circulation in governing aerosol variations over the Bay of Bengal (BoB) during the first phase of the ICARB (Integrated Campaign for Aerosols, gases and Radiation Budget) campaign (March 18–April 12, 2006). An inter-comparison between MODIS level-3 aerosol optical depth (AOD) data and ship-borne MICROTOPS measurements showed good agreement with correlation 0.92 (p < 0.0001) and a mean MODIS underestimation by 0.01. During the study period, the AOD over BoB showed high values in the northern/north western regions, which reduced towards the central and southern BoB. The wind patterns in lower atmospheric layers (> 850 hPa) indicated that direct transport of aerosols from central India was inhibited by the presence of a high pressure and a divergence over BoB in the lower altitudes. On the other hand, in the upper atmospheric levels, winds from central and northern India stretched south eastwards and converged over BoB with a negative vorticity indicative of a downdraft. These wind patterns pointed to the possibility of aerosol transport from central India to BoB by upper level winds. This mechanism was further confirmed by the significant correlations that AOD variations over BoB showed with aerosol flux convergence and flux vorticity at upper atmospheric levels (600–500 hPa). AOD in central and southern BoB away from continental influences displayed an exponential dependence on the QuikSCAT measured ocean surface wind speed. This study shows that particles transported from central and northern India by upper atmospheric circulations as well as the marine aerosols generated by ocean surface winds contributed to the AOD over the BoB during the first phase of ICARB.  相似文献   

14.
The change in the type of vegetation fraction can induce major changes in the local effects such as local evaporation, surface radiation, etc., that in turn induces changes in the model simulated outputs. The present study deals with the effects of vegetation in climate modeling over the Indian region using the MM5 mesoscale model. The main objective of the present study is to investigate the impact of vegetation dataset derived from SPOT satellite by ISRO (Indian Space Research Organization) versus that of USGS (United States Geological Survey) vegetation dataset on the simulation of the Indian summer monsoon. The present study has been conducted for five monsoon seasons (1998–2002), giving emphasis over the two contrasting southwest monsoon seasons of 1998 (normal) and 2002 (deficient). The study reveals mixed results on the impact of vegetation datasets generated by ISRO and USGS on the simulations of the monsoon. Results indicate that the ISRO data has a positive impact on the simulations of the monsoon over northeastern India and along the western coast. The MM5-USGS has greater tendency of overestimation of rainfall. It has higher standard deviation indicating that it induces a dispersive effect on the rainfall simulation. Among the five years of study, it is seen that the RMSE of July and JJAS (June–July–August–September) for All India Rainfall is mostly lower for MM5-ISRO. Also, the bias of July and JJAS rainfall is mostly closer to unity for MM5-ISRO. The wind fields at 850 hPa and 200 hPa are also better simulated by MM5 using ISRO vegetation. The synoptic features like Somali jet and Tibetan anticyclone are simulated closer to the verification analysis by ISRO vegetation. The 2 m air temperature is also better simulated by ISRO vegetation over the northeastern India, showing greater spatial variability over the region. However, the JJAS total rainfall over north India and Deccan coast is better simulated using the USGS vegetation. Sensible heat flux over north-west India is also better simulated by MM5-USGS.  相似文献   

15.
Hydrographic data collected on board ORV Sagar Kanya in the southern Bay of Bengal during the BOBMEX-Pilot programme (October–November 1998) have been used to describe the thermohaline structure and circulation in the upper 200 m water column of the study region. The presence of seasonal Inter-Tropical Convergence Zone (ITCZ) over the study area, typically characterized with enhanced cloudiness and flanked by the respective east/northeast winds on its northern part and west/southwest winds on its southern part, has led to net surface heat loss of about 55 W/m2. The sea surface dynamic topography relative to 500 db shows that the upper layer circulation is characterised by a cyclonic gyre encompassing the study area. The eastward flowing Indian Monsoon Current (IMC) between 5‡N and 7‡N in the south and its northward branching along 87‡E up to 13‡N appear to feed the cyclonic gyre. The Vessel-Mounted Acoustic Doppler Current Profiler (VM-ADCP) measured currents confirm the presence of the cyclonic gyre in the southern Bay of Bengal during the withdrawing phase of the southwest monsoon from the northern/central parts of the Bay of Bengal.  相似文献   

16.
The coastal regions of India are profoundly affected by tropical cyclones during both pre- and post-monsoon seasons with enormous loss of life and property leading to natural disasters. The endeavour of the present study is to forecast the intensity of the tropical cyclones that prevail over Arabian Sea and Bay of Bengal of North Indian Ocean (NIO). A multilayer perceptron (MLP) model is developed for the purpose and compared the forecast through MLP model with other neural network and statistical models to assess the forecast skill and performances of MLP model. The central pressure, maximum sustained surface wind speed, pressure drop, total ozone column and sea surface temperature are taken to form the input matrix of the models. The target output is the intensity of the tropical cyclones as per the T??number. The result of the study reveals that the forecast error with MLP model is minimum (4.70?%) whereas the forecast error with radial basis function network (RBFN) is observed to be 14.62?%. The prediction with statistical multiple linear regression and ordinary linear regression are observed to be 9.15 and 9.8?%, respectively. The models provide the forecast beyond 72?h taking care of the change in intensity at every 3-h interval. The performance of MLP model is tested for severe and very severe cyclonic storms like Mala (2006), Sidr (2007), Nargis (2008), Aila (2009), Laila (2010) and Phet (2010). The forecast errors with MLP model for the said cyclones are also observed to be considerably less. Thus, MLP model in forecasting the intensity of tropical cyclones over NIOs may thus be considered to be an alternative of the conventional operational forecast models.  相似文献   

17.
S. Curtis 《Atmósfera》2013,26(2):243-259
The seasonal (March to October) and interannual variability of the cumulative distribution function (CDF) of precipitation is examined for Meso-America, the eastern Pacific and western Atlantic, commonly referred to as the intra-Americas sea (IAS). Large-area precipitation CDFs were constructed over land and temperature pools greater than 28.5° C and between 26.5° and 28.5° C. The cooler waters tend to have their precipitation distributions shifted to lower values as compared to land and the western hemisphere warm pool (WHWP). The land and the WHWP have similar precipitation distributions from March to May. From June to October the land histogram of precipitation is narrower (less light and heavy rainfall) relative to the WHWP histogram. The highest probability of finding heavy to extreme precipitation over the WHWP is in June. From 1997 to 2008, in the summer months, the El Niño/Southern Oscillation (ENSO) is related to the CDFs of precipitation over land, where during El Niño there is a shift toward lower daily rain totals. There is not a strong relationship between ENSO and the CDFs of precipitation over the ocean pools. Finally, a large WHWP in May-June-July is related to the CDF of precipitation over the WHWP in October, namely a shift towards higher daily rain totals and more extreme events. The size of the July WHWP explains 75% of the variability in the frequency of rainfall greater than 50 mm within the WHWP in October, and the root mean square error between the observed points and the linear models is about 0.005. However, the reason for this apparent predictability is not simply due to a warm seasonal anomaly leading to local thermodynamic effects. The concurrent correlation between the size of the WHWP in October and the CDF of precipitation therein is small, indicating a lack of a contemporaneous response. Here it is shown through atmospheric-oceanic reanalysis that rainfall extremes in October are dependent upon the development of the Atlantic portion of the WHWP in May-June-July. Large WHWPs in these months are consistent with an early onset of the Atlantic warm pool and atmospheric instability over Central America leading to extreme precipitation events in the fall.  相似文献   

18.
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   

19.
We document the flow features, which are associated with the important synoptic systems that affected the Bay of Bengal (BoB) and its neighbourhood and controlled the convective activity there during BOBMEX. The monsoon during July and August, 1999 was subdued. It was slightly more active in the initial phase of BOBMEX that commenced on 15th July 1999 and continued up to first week of August 1999 but weakened during the second half of August. The convection was accordingly affected, reducing the rainfall over India. There were several active and weak spells of convection over the Bay of Bengal that manifested in five low pressure systems, of which two became depressions.  相似文献   

20.
In 2013, Indian summer monsoon witnessed a very heavy rainfall event (>30 cm/day) over Uttarakhand in north India, claiming more than 5000 lives and property damage worth approximately 40 billion USD. This event was associated with the interaction of two synoptic systems, i.e., intensified subtropical westerly trough over north India and north-westward moving monsoon depression formed over the Bay of Bengal. The event had occurred over highly variable terrain and land surface characteristics. Although global models predicted the large scale event, they failed to predict realistic location, timing, amount, intensity and distribution of rainfall over the region. The goal of this study is to assess the impact of land state conditions in simulating this severe event using a high resolution mesoscale model. The land conditions such as multi-layer soil moisture and soil temperature fields were generated from High Resolution Land Data Assimilation (HRLDAS) modelling system. Two experiments were conducted namely, (1) CNTL (Control, without land data assimilation) and (2) LDAS, with land data assimilation (i.e., with HRLDAS-based soil moisture and temperature fields) using Weather Research and Forecasting (WRF) modelling system. Initial soil moisture correlation and root mean square error for LDAS is 0.73 and 0.05, whereas for CNTL it is 0.63 and 0.053 respectively, with a stronger heat low in LDAS. The differences in wind and moisture transport in LDAS favoured increased moisture transport from Arabian Sea through a convectively unstable region embedded within two low pressure centers over Arabian Sea and Bay of Bengal. The improvement in rainfall is significantly correlated to the persistent generation of potential vorticity (PV) in LDAS. Further, PV tendency analysis confirmed that the increased generation of PV is due to the enhanced horizontal PV advection component rather than the diabatic heating terms due to modified flow fields. These results suggest that, two different synoptic systems merged by the strong interaction of moving PV columns resulted in the strengthening and further amplification of the system over the region in LDAS. This study highlights the importance of better representation of the land surface fields for improved prediction of localized anomalous weather event over India.  相似文献   

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