首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 46 毫秒
1.
１．ＩｎｔｒｏｄｕｃｔｉｏｎＴｈｅｉｎｉｔｉａｔｉｏｎｏｆｔｈｅｃｒｏｓｅｑｕａｔｏｒｉａｌｆｌｏｗｏｆｔｈｅＳｏｍａｌｉａｃｏａｓｔｄｕｒｉｎｇＭａｙｉｎｒｅｓｐｏｎｓｅｔｏｔｈｅｈｅａｔｉｎｇｏｖｅｒｔｈｅＳｏｕｔｈＡｓｉａｎｃｏｎｔｉｎｅｎｔｍ...  相似文献   

2.
Summary A comparison of 8 regional atmospheric model systems was carried out for a three-month late summer/early autumn period in 1995 over the Baltic Sea and its catchment area. All models were configured on a common grid using similar surface and lateral boundary conditions, and ran in either data assimilation mode (short term forecasts plus data assimilation), forecast mode (short term forecasts initialised daily with analyses) or climate mode (no re-initialisation of model interior during entire simulation period). Model results presented in this paper were generally post processed as daily averaged quantities, separate for land and sea areas when relevant. Post processed output was compared against available analyses or observations of cloud cover, precipitation, vertically integrated atmospheric specific humidity, runoff, surface radiation and near surface synoptic observations. The definition of a common grid and lateral forcing resulted in a high degree of agreement among the participating model results for most cases. Models operated in climate mode generally displayed slightly larger deviations from the observations than the data assimilation or forecast mode integration, but in all cases synoptic events were well captured. Correspondence to near surface synoptic quantities was good. Significant disagreement between model results was shown in particular for cloud cover and the radiative properties, average precipitation and runoff. Problems with choosing appropriate initial soil moisture conditions from a common initial soil moisture field resulted in a wide range of evaporation and sensible heat flux values during the first few weeks of the simulations, but better agreement was shown at later times. Received September 8, 2000 Revised April 3, 2001  相似文献   

3.
Summary An intercomparison of the characteristic features of the Indian summer monsoon has been carried out for the monsoon months (June to September) of 1995 using the mean monthly analyses/forecasts from the operational centres of ECMWF, JMA, UKMO and NCMRWF. This exercise was undertaken to determine how well the large scale monsoon features over India were reproduced in the operational output in 1995 and also to assess the performance of the NCMRWF assimilation/forecast system. For this purpose, precipitation, mean sea level pressure, circulation features in the lower (850 hPa) and upper (200 hPa) troposphere, mid-tropospheric (500 hPa) temperature, and latent heat flux were examined.It is found that all the dominant features of the Indian summer monsoon are fairly well represented in the analysis and medium range forecasts of the ECMWF, JMA and UKMO. The NCMRWF output agrees well with those from other centres except for a sharp gradient in precipitation across the west coast which was not captured well in the forecasts due to the relatively coarse horizontal resolution of the model compared to that used at other operational centres. Other important features of the southwest monsoon, like the heat low over the northwestern part of the country, the lower level westerly jet and upper level easterly jet etc. are found to be reasonably well represented in the output of all operational centres. The JMA analyses and forecasts possessed greater levels of moisture compared to the NCMRWF output possibly due to the synthetic moisture information used at JMA. The evolution characteristics of the summer monsoon onset over the southern tip of India are found to be comparable in the output of JMA and NCMRWF.With 13 Figures  相似文献   

4.
To investigate the impact of various types of data on medium-range forecasts, observing system experiments are performed using an assimilation algorithm based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) reanalysis system. Data-denial experiments for radiosonde, satellite, aircraft, and sea surface observations, and selected data experiments for radiosonde and surface data, are conducted for the boreal summer of 1997 and the boreal winter of 1997/1998. The data assimilation system used in this study is remarkably dependent on radiosonde data, which provides information about the three-dimensional structure of the atmosphere. As expected, the impact of radiosonde observations on medium-range forecasts is strongly positive over the Northern Hemisphere and tropics, whereas the satellite system is most beneficial over the Southern Hemisphere. These results are also found in experiments simulating historical changes in observation systems. Over the tropics, assimilation without radiosonde observations generates unbalanced analyses resulting in unrealistic forecasts that must be corrected by the forecast model. Forecasts based on analysis from the observation data before the era of radiosonde observation are found to be less meaningful. In addition, the impacts on forecasts are closely related to the geographical distribution of observation data. The memory of observation data embedded in the analysis tends to persist throughout forecasts. However, cases exist where the effect of forecast error growth is more dominant than that of analysis error, e.g., over East Asia in summer, and where the deficiency in observations is supplemented or the imbalance in analysis is adjusted by the forecast model during the period of forecasts. Forecast error growth may be related to the synoptic correction performed by the data assimilation system. Over data-rich areas, analysis fields are corrected to a greater extent by the data assimilation system than are those over data-poor areas, which can cause the forecast model to produce more forecast errors in medium-range forecasts. It is found that even one month per season is sufficient for forecast skill verification in data impact experiments. Additionally, the use of upper-air observations is found to benefit areas that are downstream of observation data-rich areas.  相似文献   

5.
During the summer monsoon (1 June to 30 September) 2007, real-time district level rainfall forecasts in short-range time scale were generated for Indian region applying multimodel ensemble technique. The pre-assigned grid point weights on the basis of correlation coefficients (CC) between the observed values and forecast values are determined for each constituent model at the resolution of 0.5° × 0.5° utilizing two seasons datasets (1 June to 30 September, 2005 and 2006), and the multimodel ensemble forecasts (day 1 and day 2 forecasts) are generated at the same resolution on a real-time basis. The ensemble forecast fields are then used to prepare forecasts for each district taking the average value of all grid points falling in a particular district. In this paper we examined the performance skill of the multimodel ensemble-based real-time district level short-range forecast of rainfall. It has clearly emerged from the results that the multimodel ensemble technique reported in this study is superior to each ensemble member. District wise performance of the ensemble rainfall forecast reveals that the technique, in general, is capable of providing reasonably good forecast skill over most districts of the country, particularly over the districts where the monsoon systems are dominant. Though the procedure shows appreciable skill to predict occurrence or non-occurrence of rainfall at the district level, it always underestimates rainfall amount, particularly in heavy rainfall events. Possible reasons of this failure may be due to model bias and poor data assimilation procedure.  相似文献   

6.
We present the results of the impact of the 3D variational data assimilation (3DVAR) system within the Weather Research and Forecasting (WRF) model to simulate three heavy rainfall events (25–28 June 2005, 29–31 July 2004, and 7–9 August 2002) over the Indian monsoon region. For each event, two numerical experiments were performed. In the first experiment, namely the control simulation (CNTL), the low-resolution global analyses are used as the initial and boundary conditions of the model. In the second experiment (3DV-ANA), the model integration was carried out by inserting additional observations in the model’s initial conditions using the 3DVAR scheme. The 3DVAR used surface weather stations, buoy, ship, radiosonde/rawinsonde, and satellite (oceanic surface wind, cloud motion wind, and cloud top temperature) observations obtained from the India Meteorological Department (IMD). After the successful inclusion of additional observational data using the 3DVAR data assimilation technique, the resulting reanalysis was able to successfully reproduce the structure of convective organization as well as prominent synoptic features associated with the mid-tropospheric cyclones (MTC). The location and intensity of the MTC were better simulated in the 3DV-ANA as compared to the CNTL. The results demonstrate that the improved initial conditions of the mesoscale model using 3DVAR enhanced the location and amount of rainfall over the Indian monsoon region. Model verification and statistical skill were assessed with the help of available upper-air sounding data. The objective verification further highlighted the efficiency of the data assimilation system. The improvements in the 3DVAR run are uniformly better as compared to the CNTL run for all the three cases. The mesoscale 3DVAR data assimilation system is not operational in the weather forecasting centers in India and a significant finding in this study is that the assimilation of Indian conventional and non-conventional observation datasets into numerical weather forecast models can help improve the simulation accuracy of meso-convective activities over the Indian monsoon region. Results from the control experiments also highlight that weather and regional climate model simulations with coarse analysis have high uncertainty in simulating heavy rain events over the Indian monsoon region and assimilation approaches, such as the 3DVAR can help reduce this uncertainty.  相似文献   

7.
Specifying physically consistent and accurate initial conditions is one of the major challenges of numerical weather prediction (NWP) models. In this study, ground-based global positioning system (GPS) integrated water vapor (IWV) measurements available from the International Global Navigation Satellite Systems (GNSS) Service (IGS) station in Bangalore, India, are used to assess the impact of GPS data on NWP model forecasts over southern India. Two experiments are performed with and without assimilation of GPS-retrieved IWV observations during the Indian winter monsoon period (November–December, 2012) using a four-dimensional variational (4D-Var) data assimilation method. Assimilation of GPS data improved the model IWV analysis as well as the subsequent forecasts. There is a positive impact of ～10 % over Bangalore and nearby regions. The Weather Research and Forecasting (WRF) model-predicted 24-h surface temperature forecasts have also improved when compared with observations. Small but significant improvements were found in the rainfall forecasts compared to control experiments.  相似文献   

8.
Summary The air-sea interaction processes over the tropical Indian Ocean region are studied using sea surface temperature data from the Advanced Very High Resolution Radiometer sensor onboard the NOAA series of satellites. The columnar water-vapour content, low-level atmospheric humidity, precipitation, wind speed, and back radiation from the Special Sensor Microwave Imager on board the U.S. Defense Meteorological Satellite Program are all examined for two contrasting monsoon years, namely 1987 (deficit rainfall) and 1988 (excess rainfall). From these parameters the longwave radiative net flux at the sea surface and the ocean-air moisture flux are derived for further analysis of the air-sea interaction in the Arabian Sea, the Bay of Bengal, the south China Sea and the southern Indian Ocean. An analysis of ten-day and monthly mean evaporation rates over the Arabian Sea and Bay of Bengal shows that the evaporation was higher in these areas during the low rainfall year (1987) indicating little or no influence of this parameter on the ensuing monsoon activity over the Indian subcontinent. On the other hand, the evaporation in the southern Indian Ocean was higher during July and September 1988 when compared with the same months of 1987. The evaporation rate over the south Indian Ocean and the low-level cross-equatorial moisture flux seem to play a major role on the ensuing monsoon activity over India while the evaporation over the Arabian Sea is less important. Since we have only analysed one deficit/ excess monsoon cycle the results presented here are of preliminary nature. Received November 5, 1997 Revised March 20, 1998  相似文献   

9.

Variation of soil moisture during active and weak phases of summer monsoon JJAS (June, July, August, and September) is very important for sustenance of the crop and subsequent crop yield. As in situ observations of soil moisture are few or not available, researchers use data derived from remote sensing satellites or global reanalysis. This study documents the intercomparison of soil moisture from remotely sensed and reanalyses during dry spells within monsoon seasons in central India and central Myanmar. Soil moisture data from the European Space Agency (ESA)—Climate Change Initiative (CCI) has been treated as observed data and was compared against soil moisture data from the ECMWF reanalysis-Interim (ERA-I) and the climate forecast system reanalysis (CFSR) for the period of 2002–2011. The ESA soil moisture correlates rather well with observed gridded rainfall. The ESA data indicates that soil moisture increases over India from west to east and from north to south during monsoon season. The ERA-I overestimates the soil moisture over India, while the CFSR soil moisture agrees well with the remotely sensed observation (ESA). Over Myanmar, both the reanalysis overestimate soil moisture values and the ERA-I soil moisture does not show much variability from year to year. Day-to-day variations of soil moisture in central India and central Myanmar during weak monsoon conditions indicate that, because of the rainfall deficiency, the observed (ESA) and the CFSR soil moisture values are reduced up to 0.1 m3/m3 compared to climatological values of more than 0.35 m3/m3. This reduction is not seen in the ERA-I data. Therefore, soil moisture from the CFSR is closer to the ESA observed soil moisture than that from the ERA-I during weak phases of monsoon in the study region.

  相似文献   

10.
A supervised principal component regression (SPCR) technique has been employed on general circulation model (GCM) products for developing a monthly scale deterministic forecast of summer monsoon rainfall (June–July–August–September) for different homogeneous zones and India as a whole. The time series of the monthly observed rainfall as the predictand variable has been used from India Meteorological Department gridded (1°?×?1°) rainfall data. Lead 0 (forecast initialized in the same month) monthly products from GCMs are used as predictors. The sources of these GCMs are International Research Institute for Climate and Society, Columbia University, National Center for Environmental Prediction, and Japan Agency for Marine Earth Science and Technology. The performance of SPCR technique is judged against simple ensemble mean of GCMs (EM) and it is found that over almost all the zones the SPCR model gives better skill than EM in June, August, and September months of monsoon. The SPCR technique is able to capture the year to year observed rainfall variability in terms of sign as well as the magnitude. The independent forecasts of 2007 and 2008 are also analyzed for different monsoon months (Jun–Sep) in homogeneous zones and country. Here, 1982–2006 have been considered as development year or training period. Results of the study suggest that the SPCR model is able to catch the observational rainfall over India as a whole in June, August, and September in 2007 and June, July, and August in 2008.  相似文献   

11.
Summary In this study, a detailed examination on the evolution of summer monsoon onset over southern tip of the Indian peninsula, its advancement and withdrawal over the Indian sub-continent is carried out by utilizing the analysis/forecast fields of a global spectral model for Monsoon-1995. The data base used in this study is derived from the archives of global data assimilation and forecasting system of NCMRWF, India, valid for 00UTC at 1.5° latitude/longitude resolution for the summer monsoon period of 1995. By utilizing the analyses and forecast fields, and the established knowledge of the Indian monsoon, objective criteria are employed in this study for determining the onset, advancement, and withdrawal of the monsoon.It is found that all the major characteristics of Monsoon-1995 are captured well by the analysis-forecast system even though the criteria adopted in this study are more objective and different in nature as compared to the conventional procedures. The onset date of monsoon over the southern tip of the Indian peninsula as determined by the dynamical onset procedure is found to be matching well with the realized date. Further, the evolution of monsoon onset characteristics over the Arabian Sea both in the analyses and forecasts is found to be in good agreement with the earlier studies. However, the magnitudes of net tropospheric moisture build-up and tropospheric temperature increase differ with respect to analyses and corresponding forecast fields. In addition, all important characteristics of the advancement and withdrawal of monsoon over the Indian sub-continent viz. stagnation, revival etc., are brought out reasonably well by the analysis and forecast system.With 10 Figures  相似文献   

12.
Summary The study provides a concise and synthesized documentation of the current level of skill of the operational NWP model of India Meteorological Department based on daily 24 hours forecast run of the model during two normal monsoon years 2001 and 2003 making detailed inter-comparison with daily rainfall analysis from the use of high dense land rain gauge observations. The study shows that the model, in general, is able to capture three regions of climatologically heavy rainfall domains along Western Ghats, Northeast India and over east central India, over the domain of monsoon trough. However, the accuracy in prediction of location and magnitude of rainfall fluctuates considerably. The inter-comparison reveals that performance of the model rainfall forecast deteriorated in 2003 when rainfall over most parts of the region was significantly under-predicted. These features are also reflected in the error statistics. The study suggests that there is a need to maximize the data ingest in the model with a better data assimilation scheme to improve the rainfall forecast skill.  相似文献   

13.
The three-dimensional variational data assimilation (3DVAR) technique in the advanced weather research and forecast model is used to study the impact of assimilating Moderate Resolution Spectroradiometer (MODIS) retrieved temperature and humidity profiles on the dynamic and thermodynamic features for three monsoon depressions over the Bay of Bengal, India. For better understanding of the role of various physical processes in the evolution of monsoon depression, a detailed diagnostic study is performed on all the three depression cases. Numerical experiments were conducted in a system of two-way nested domains with a horizontal resolution of 36 and 12 km, respectively. The assimilation of MODIS data did improve the mean sea level pressure patterns and spatial distribution of rainfall patterns in all the three monsoon depression cases studied. Higher values of equitable threat score and lower bias values are seen consistently for the entire rainfall threshold range and for all the three depression cases with 3DVAR assimilation of MODIS temperature and humidity profiles. The current operational regional models in India do not ingest the MODIS temperature and humidity profiles and hence the present study is particularly relevant to the operational forecasting community in India in their ongoing efforts to improve weather forecasting over India.  相似文献   

14.
This study investigates the influence of Simplified Arakawa Schubert (SAS) and Relax Arakawa Schubert (RAS) cumulus parameterization schemes on coupled Climate Forecast System version.1 (CFS-1, T62L64) retrospective forecasts over Indian monsoon region from an extended range forecast perspective. The forecast data sets comprise 45 days of model integrations based on 31 different initial conditions at pentad intervals starting from 1 May to 28 September for the years 2001 to 2007. It is found that mean climatological features of Indian summer monsoon months (JJAS) are reasonably simulated by both the versions (i.e. SAS and RAS) of the model; however strong cross equatorial flow and excess stratiform rainfall are noted in RAS compared to SAS. Both the versions of the model overestimated apparent heat source and moisture sink compared to NCEP/NCAR reanalysis. The prognosis evaluation of daily forecast climatology reveals robust systematic warming (moistening) in RAS and cooling (drying) biases in SAS particularly at the middle and upper troposphere of the model respectively. Using error energy/variance and root mean square error methodology it is also established that major contribution to the model total error is coming from the systematic component of the model error. It is also found that the forecast error growth of temperature in RAS is less than that of SAS; however, the scenario is reversed for moisture errors, although the difference of moisture errors between these two forecasts is not very large compared to that of temperature errors. Broadly, it is found that both the versions of the model are underestimating (overestimating) the rainfall area and amount over the Indian land region (and neighborhood oceanic region). The rainfall forecast results at pentad interval exhibited that, SAS and RAS have good prediction skills over the Indian monsoon core zone and Arabian Sea. There is less excess rainfall particularly over oceanic region in RAS up to 30 days of forecast duration compared to SAS. It is also evident that systematic errors in the coverage area of excess rainfall over the eastern foothills of the Himalayas remains unchanged irrespective of cumulus parameterization and initial conditions. It is revealed that due to stronger moisture transport in RAS there is a robust amplification of moist static energy facilitating intense convective instability within the model and boosting the moisture supply from surface to the upper levels through convergence. Concurrently, moisture detrainment from cloud to environment at multiple levels from the spectrum of clouds in the RAS, leads to a large accumulation of moisture in the middle and upper troposphere of the model. This abundant moisture leads to large scale condensational heating through a simple cloud microphysics scheme. This intense upper level heating contributes to the warm bias and considerably increases in stratiform rainfall in RAS compared to SAS. In a nutshell, concerted and sustained support of moisture supply from the bottom as well as from the top in RAS is the crucial factor for having a warm temperature bias in RAS.  相似文献   

15.
Indian Summer Monsoon Rainfall(ISMR)exhibits a prominent inter-annual variability known as troposphere biennial oscillation.A season of deficient June to September monsoon rainfall in India is followed by warm sea surface temperature(SST)anomalies over the tropical Indian Ocean and cold SST anomalies over the western Pacific Ocean.These anomalies persist until the following monsoon,which yields normal or excessive rainfall.Monsoon rainfall in India has shown decadal variability in the form of 30 year epochs of alternately occurring frequent and infrequent drought monsoons since1841,when rainfall measurements began in India.Decadal oscillations of monsoon rainfall and the well known decadal oscillations in SSTs of the Atlantic and Pacific oceans have the same period of approximately 60 years and nearly the same temporal phase.In both of these variabilities,anomalies in monsoon heat source,such as deep convection,and middle latitude westerlies of the upper troposphere over south Asia have prominent roles.  相似文献   

16.
The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction’s (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS’s hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50°E–110°E and 10°S–35°N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon Rainfall (AISMR; only the land stations of India during JJAS), the predicted mean AISMR with March, April and May initial conditions is found to be well correlated with actual AISMR and is found to provide skillful prediction. Thus, the calibrated CFS forecast could be used as a better tool for the real time prediction of AISMR.  相似文献   

17.
Summary In this paper we address the issue of monsoon forecasts in relation to the organization of convection. Given a physical initialization procedure, within a data assimilation, it is possible to use the detailed distribution of rainfall from mesoconvective precipitating elements to define the initial state of a global model. If that is carried out using a very high resolution model then the initial state can carry within it an organization of convection within the resolvable scales. Then the impact of physical initialization on the maintenance and prediction of tropical weather such as the monsoon can be determined. Lacking such an initialization, one can expect the convectively driven energetics to be biased, and a slow degradation of the forecasts can follow. Several examples of forecasts at different resolutions are discussed here. The main findings of this study are that improved forecast results are obtained when physical initialization is invoked where the observed rain and the model resolution are comparable, i.e. the footprint of the highest resolutions rainfall estimates obtained from satellite based data sets (principally we use the SSM/I instrument over the oceans). At this resolution, we note that the model is able to carry an organization of convection in the initialization and in the forecasts through the medium-range time scale.We have compared our results of monsoon studies at a resolution T255 with those at resolution T62. The transform grid separation at the resolution T255 is approximately 50 km and at the resolution T62, it is approximately 200 km. We find that the model at the higher resolution (T255) performs better and has more realistic energy conversions for the convectively driven synoptic scale monsoon.An organization of convection, at the synoptic scales, is not seen in the forecasts at lower resolutions, T62, where the rainfall patterns are generally much broader and tend to be more zonal. Such organization appears more realistic at the resolution T255. Variances of the energy conversion, calculated in the two-dimensional spectral space, from physically initialized short range forecasts at the higher resolution are seen to be largest on the scales of the monsoon. Similar calculations for the reanalyzed fields at lower resolutions show the spectral distribution of variances to be biased towards local Hadley scale overturnings.With 12 Figures  相似文献   

18.
利用国家气象中心中尺度业务数值预报模式GRAPES-MESO v3.0,以2010年6月1～30日为例,开展地面降水率1DVAR(one-dimensional variational assimilation)同化方案在GRAPES-3DVAR(three-dimensional variational assimilation)同化系统中的应用试验研究(ASSI试验),并以未加降水资料同化的试验为对照试验(CNTL试验),以评估全国1h加密雨量资料在模式中同化应用的效果。结果表明:1)在相对湿度背景误差和降水率观测误差范围内,1DVAR同化方案能够对湿度廓线进行有意义的调整,使分析降水向观测降水靠近;ASSI试验对初始温、压、湿、风场的修正主要为正效果;2)对2010年6月17～21日江南、华南连续性降水过程进行了分析,整体而言ASSI试验对逐日及逐时降水强度的预报普遍强于CNTL试验,与实况更加接近;3)ASSI试验对2010年6月1～30日08时起报的0～24 h模式预报的小雨、中雨、大雨、暴雨、大暴雨各个降水量级TS评分及ETS评分相比CNTL试验均有较明显提高,预报偏差也更接近于1;4)ASSI试验较CNTL试验能更好地模拟雨带的分布、雨带演变特征和降水强度的变化;5)对降水所做的典型个例和统计检验分析从不同角度说明了地面降水资料1DVAR同化方案在GRAPES-3DVAR系统中的应用改善了GRAPES-MESO v3.0的降水模拟效果。  相似文献   

19.
Summary The summer monsoon rainfall over Orissa, a state of eastern India, shows characteristic intraseasonal and interannual variability, due to interaction of basic westerly flow with orography and the synoptic scale monsoon disturbances including low-pressure systems and cyclonic circulations extending upto mid-tropospheric level (LPSC). These systems normally develop over the north Bay of Bengal and move west-northwestwards along the monsoon trough. The essence of this study is to find out the main features of the intraseasonal variability of daily monsoon rainfall over Orissa in relation to synoptic systems like LPSC and its implication on the interannual variation of rainfall. For this purpose, the actual and mean daily rainfall data of 31 uniformly distributed stations, six homogeneous regions and Orissa as a whole during monsoon season (June–September) over a period of 20 years (1980–1999) are subjected to auto-correlation and power spectrum analyses. The actual and average daily scores of significant EOFs and actual daily occurrence along with daily probability of occurrence of the LPSC influencing rainfall over Orissa during the same period are also subjected to auto-correlation and power spectrum analyses. The intraseasonal variation of monsoon rainfall over Orissa and different homogeneous regions is dominated by the synoptic mode (3–9 days) of variation due to the similar mode of variation in the occurrence of LPSC influencing the rainfall. The seasonal rainfall and hence the interannual variation depends on the intraseasonal variation of rainfall modulated with the synoptic mode of variation in the occurrence of the LPSC. The occurrence of LPSC over the northwest (NW) Bay/NW and adjoining northeast (NE) Bay and its subsequent movement and persistence over Orissa and east Madhya Pradesh & Chhattisgarh in synoptic mode (3–6 days) alongwith absence of similar mode in the occurrence of the LPSC over NE Bay, Gangetic West Bengal (GWB) in the north and west central (WC) Bay to the south leads to excess rainfall over different homogeneous regions and Orissa as a whole. The reverse is the case in deficient years over Orissa and all homogeneous regions except southwest Orissa. The occurrence of the LPSC over GWB in synoptic mode (about 5 days) alongwith absence of synoptic mode in the occurrence of the LPSC over NW Bay leads to deficient rainfall year over southwest Orissa. Correspondence: U. C. Mohanty, Centre for Atmospheric Sciences, Indian Institute of Technology, Delhi Hauz Khas, New Delhi 110016, India  相似文献   

20.
吴国雄  张永生 《大气科学》1998,22(6):825-838
使用欧洲中期天气预报中心（ECMWF）的客观分析资料、ECMWF/TOGA补充数据集,美国NMC气候分析中心的向外长波辐射（OLR）资料以及国家气候中心存档的中国336个测站的降水资料,研究了1989年春天青藏高原和邻近地区的热力特征和环流特征,及其对亚洲季风区季节转换的影响。文中集中分析了表面感热和潜热通量的时空分布特征。结果表明:1989年亚洲季风的爆发由三个接续的阶段组成。第一阶段是5月上旬在孟加拉湾东岸,称为孟加拉（BOB）季风爆发阶段。第二阶段是5月20日左右开始的中国南海（SCS）季风爆发阶段。第三阶段是6月10日左右开始的印度上空的南亚季风（或称印度季风）的爆发阶段。分析表明,正是由于青藏高原的热力和机械强迫作用才使亚洲季风首先在孟加拉湾地区出现。BOB季风环流提供了有利的背景条件,使SCS季风接着爆发。最后随着亚洲热带流型的西移,印度季风爆发才发生。  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号