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1.
The operational prediction of climatic variables in monthly-to-seasonal scales has been issued by National Centers for Environmental Prediction (NCEP) through Climate Forecast System model (CFSv1) since 2004. After incorporating significant changes, a new version of this model (CFSv2) was released in 2011. The present study is based on the comparative evaluation of performances of CFSv2 and CFSv1 for the southwest monsoon season (June-July-August-September, JJAS) over India with May initial condition during 1982–2009. It was observed that CFSv2 has improved over CFSv1 in simulating the observed monsoon rainfall climatology and inter annual variability. The movement of the cell of Walker circulation in years of excessive and deficient rainfall is better captured in CFSv2, as well. The observed teleconnection pattern between ISMR-sea surface temperature (SST) is also better captured in CFSv2. The overall results suggest that the changes incorporated in CFSv1 through the development of CFSv2 have resulted in an improved prediction of ISMR.21  相似文献   

2.
The monsoon seasons of 2010 and 2011, with almost identical seasonal total rainfall over India from June to September, are associated with slightly different patterns of intraseasonal rainfall fluctuations. Similarly, the year 2012, with relatively less rainfall compared to 2010 and 2011, also witnessed different intraseasonal rainfall fluctuations, leading to drought-like situations over some parts of the country. The present article discusses the forecasting aspect of monsoon activity over India during these 3 years on an extended range time scale (up to 3 weeks) by using the multimodel ensemble (MME), based on operational coupled model outputs from the ECMWF monthly forecasting system and the NCEP’s Climate Forecast System (CFS). The average correlation coefficient (CC) of weekly observed all-India rainfall (AIR) and the corresponding MME forecast AIR is found to be significant, above the 98 % level up to 2 weeks (up to 18 days) with a slight positive CC for the week 3 (days 19–25) forecast. However, like the variation of observed intraseasonal rainfall fluctuations during 2010, 2011 and 2012 monsoon seasons, the MME forecast skills of weekly AIR are also found to be different from one another, with the 2012 monsoon season indicating significant CC (above 99 % level) up to week 2 (12–18 days), and also a comparatively higher CC (0.45) during the week 3 forecast (days 19–25). The average CC between observed and forecasted weekly AIR rainfall over four homogeneous regions of India is found to be the lowest over the southern peninsula of India (SPI), and northeast India (NEI) is found to be significant only for the week 1 (days 5–11) forecast. However, the CC is found to be significant over northwest India (NWI) and central India (CEI), at least above the 90 % level up to 18 days, with NWI having slightly better skill compared to the CEI. For the individual monsoon seasons of 2010, 2011 and 2012, there is some variation in CC and other skill scores over the four homogeneous regions. Thus the slight variations in the characteristics of intraseasonal monsoon rainfall over India is associated with variations in predictive skill of the coupled models and the MME-based predictions of intraseasonal monsoon fluctuations for 2–3 weeks, providing encouraging results. The MME forecast in 2010 is also able to provide useful guidance, well in advance, about an active September associated with a delayed withdrawal of the monsoon and also the heavy rainfall over north Pakistan.  相似文献   

3.
--A large part of the rainfall over India during the summer monsoon season (June-September) is contributed by synoptic scale disturbances such as monsoon depressions. To study the evolution of such disturbances in Atmospheric General Circulation Models (AGCM), the Hadley Centre AGCM (HadAM2b) has been integrated for 15 summer monsoons (1979-1993) and the output was examined for the presence of synoptic scale disturbances such as monsoon depressions, low pressure areas, land lows and land depressions over the Indian summer monsoon region. The atmospheric initial condition for each of these integrations was of 23rd May and observed Sea Surface Temperatures (SST) were described as a boundary condition.¶Although the horizontal resolution of the AGCM used in this study is only 2.5° 2 3.75° lat. long., the model is able to simulate a few monsoon disturbances. The important features of these simulated disturbances are presented. The features of the simulated disturbances are realistic. The morphologies of a well simulated monsoon depression and a simulated low pressure area are presented as examples. The frequency of the simulated monsoon depressions is less than the climatological frequency of the depressions during all four monsoon months.  相似文献   

4.
Seasonal climate prediction for the Indian summer monsoon season is critical for strategic planning of the region. The mean features of the Indian summer monsoon and its variability, produced by versions of the ‘Florida State University Coupled Ocean-Atmosphere General Circulation Model’ (FSUCGCM) hindcasts, are investigated for the period 1987 to 2002. The coupled system has full global ocean and atmospheric models with coupled assimilation. Four member models were created by choosing different combinations of parameterizations of the physical processes in the atmospheric model component. Lower level wind flow patterns and rainfall associated with the summer monsoon season are examined from this fully coupled model seasonal integrations. By comparing with observations, the mean monsoon condition simulated by this coupled model for the June, July and August periods is seen to be reasonably realistic. The overall spatial low-level wind flow patterns and the precipitation distributions over the Indian continent and adjoining oceanic regions are comparable with the respective analyses. The anomalous below normal large-scale precipitation and the associated anomalous low-level wind circulation pattern for the summer monsoon season of 2002 was predicted by the model three months in advance. For the Indian summer monsoon, the ensemble mean is able to reproduce the mean features better compared to individual member models.  相似文献   

5.
In this paper, the maintenance of Asian summer monsoon circulation is compared in the National Centres for Environmental Prediction/National Centre for Atmospheric Research (NCEP/NCAR) reanalysis and National Centre for Medium Range Weather Forecasting (NCMRWF), India operational analysis. The time mean summer monsoon circulation is bifurcated into stable mean and transient eddy components. The mean component of the summer monsoon circulation is elucidated through the study of large-scale balances of kinetic energy, heat and moisture. Although the balance requirements are fairly satisfied by both NCEP/NCAR and NCMRWF fields, a major difference is noticed. Strong monsoon circulation is evinced by NCEP/NCAR over the Oceanic regions and NCMRWF over the landmass. The various mean budgets under consideration indicated this feature invariably.  相似文献   

6.
In semi‐arid Kenya, episodes of agricultural droughts of varying severity and duration occur. The occurrence of these agricultural droughts is associated with seasonal rainfall variability and can be reflected by seasonal soil moisture deficits that significantly affect crop performance and yield. The objective of this study was to stochastically simulate the behaviour of dry and wet spells and rainfall amounts in Iiuni watershed, Kenya. The stochastic behaviour of the longest dry and wet spells (runs) and largest rainfall amounts were simulated using a Markov (order 1) model. There were eight raingauge stations within the watershed. The entire analysis was carried out using probability parameters, i.e. mean, variance, simple and conditional probabilities of dry and rain days. An analysis of variance test (ANOVA ) was used to establish significant differences in rainfall characteristics between the eight stations. An analysis of the number of rain days and rainfall amount per rain day was done on a monthly basis to establish the distribution and reliability of seasonal rainfall. The graphic comparison of simulated cumulative distribution functions (Cdfs) of the longest spells and largest rainfall amounts showed Markovian dependence or persistence. The longest dry spells could extend to 24 days in the long rainy season and 12 in the short rainy season. At 50% (median) probability level, the largest rainfall amounts were 91 mm for the long rainy season and 136 mm for the short rainy season. The short rains were more reliable for crop production than the long rains. The Markov model performed well and gave adequate simulations of the spells and rainfall amounts under semi‐arid conditions. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

7.
We examine the warm season (April-September) rainfall climatology of the northeastern US through analyses of high-resolution radar rainfall fields from the Hydro-NEXRAD system and regional climate model simulations using the weather research and forecasting (WRF) model. Analyses center on the 5-year period from 2003 to 2007 and the study area includes the New York-New Jersey metropolitan region covered by radar rainfall fields from the Fort Dix, NJ WSR-88D. The objective of this study is to develop and test tools for examining rainfall climatology, with a special focus on heavy rainfall. An additional emphasis is on rainfall climatology in regions of complex terrain, like the northeastern US, which is characterized by land-water boundaries, large heterogeneity in land use and cover, and mountainous terrain in the western portion of the region. We develop a 5-year record of warm season radar rainfall fields for the study region using the Hydro-NEXRAD system. We perform regional downscaling simulations for the 5-year study period using the WRF model. Radar rainfall fields are used to characterize the interannual, seasonal and diurnal variation of rainfall over the study region and to examine spatial heterogeneity of rainfall. Regional climate model simulations are characterized by a wet bias in the rainfall fields, with the largest bias in the high-elevation regions of the model domain. We show that model simulations capture broad features of the interannual, seasonal, and diurnal variation of rainfall. Model simulations do not capture spatial gradients in radar rainfall fields around the New York metropolitan region and land-water boundaries to the east. The model climatology of convective available potential energy (CAPE) is used to interpret the regional distribution of warm season rainfall and the seasonal and diurnal variability of rainfall. We use hydrologic and meteorological observations from July 2007 to examine the interactions of land surface processes and rainfall from a regional perspective.  相似文献   

8.
Uncertainty analysis of radar rainfall enables stakeholders and users have a clear knowledge of the possible uncertainty associated with the rainfall products. Long-term empirical modeling of the relationship between radar and gauge measurements is an efficient and practical method to describe the radar rainfall uncertainty. However, complicated variation of synoptic conditions makes the radar-rainfall uncertainty model based on historical data hard to extend in the future state. A promising solution is to integrate synoptic regimes with the empirical model and explore the impact of individual synoptic regimes on radar rainfall uncertainty. This study is an attempt to introduce season, one of the most important synoptic factor, into the radar rainfall uncertainty model and proposes a seasonal ensemble generator for radar rainfall using copula and autoregressive model. We firstly analyze the histograms of rainfall-weighted temperature, the radar-gauge relationships, and Box and Whisker plots in different seasons and conclude that the radar rainfall uncertainty has strong seasonal dependence. Then a seasonal ensemble generator is designed and implemented in a UK catchment under a temperate maritime climate, which can fully model marginal distribution, spatial dependence, temporal dependence and seasonal dependence of radar rainfall uncertainty. To test its performance, 12 typical rainfall events (4 for each season) are chosen to generate ensemble rainfall values. In each time step, 500 ensemble members are produced and the values of 5th to 95th percentiles are used to derive the uncertainty bands. Except several outliers, the uncertainty bands encompass the observed gauge rainfall quite well. The parameters of the ensemble generator vary considerably for each season, indicating the seasonal ensemble generator reflects the impact of seasons on radar rainfall uncertainty. This study is an attempt to simultaneously consider four key features of radar rainfall uncertainty and future study will investigate their impacts on the outputs of hydrological models with radar rainfall as input or initial conditions.  相似文献   

9.
Regional climate models are important tools to examine the spatial and temporal characteristics of rainfall and temperature at high resolutions. Such information has potential applications in sectors like agriculture and health. In this study, the Regional Climate Model Version 3 (RegCM3) has been integrated in the ensemble mode at 55 km resolution over India for the summer monsoon season during the years 1982–2009. Emphasis has been given on the validation of the model simulation at the regional level. In Central India, both rainfall and temperature show the best correlations with respective observed values. The model gives rise to large wet biases over Northwest and Peninsular India. RegCM3 slightly underestimates the summer monsoon precipitation over the Central and Northeast India. Nevertheless, over these regions, RegCM3 simulated rainfall is closer to the observations when compared to the other regions where rainfall is overestimated. The position of the monsoon trough simulated by the model lies to the north of its original observed position. This is similar to the usual monsoon break conditions leading to less rainfall over Central India. RegCM3 simulated surface maximum temperature shows a large negative bias over the country while the surface minimum temperature is close to the observation. Nevertheless, there is a strong correlation between the all India weighted average surface temperature simulated by RegCM3 and IMD observed values. While examining the extreme weather conditions in Central India, it is found that RegCM3 simulated frequencies of occurrence of very wet days, extremely wet days, warm days and warm nights more often as compared to those in IMD observed values. However, these are systematic biases. The model biases in the frequencies of distribution of rainfall extremes explain the wet and dry biases in different regions in the country. Overall, the inter-annual characteristics of both the rainfall and temperature extremes simulated by RegCM3 in Central India are well in phase with those found in the observed data.  相似文献   

10.
It is well established that sea surface temperature (SST) plays a significant role in the hydrologic cycle in which precipitation is the most important part. In this study, the influence of SST on Indian subdivisional monthly rainfall is investigated. Both spatial and temporal influences are investigated. The most influencing regions of sea surface are identified for different subdivisions and for different overlapping seasons in the year. The relative importance of SST, land surface temperature (LST) and ocean–land temperature contrast (OLTC) and their variation from subdivision to subdivision and from season to season are also studied. It is observed that LST does not show much similarity with rainfall series, but, in general, OLTC shows relatively higher influence in the pre‐monsoon and early monsoon periods, whereas SST plays a more important role in late‐ and post‐monsoon periods. The influence of OLTC is seen to be mostly confined to the Indian Ocean region, whereas the effect of SST indicates the climatic teleconnection between Indian regional rainfall and climate indices in Pacific and Atlantic Oceans. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

11.
Time–frequency characterization is useful in understanding the nonlinear and non-stationary signals of the hydro-climatic time series. The traditional Fourier transform, and wavelet transform approaches have certain limitations in analyzing non-linear and non-stationary hydro-climatic series. This paper presents an effective approach based on the Hilbert–Huang transform to investigate time–frequency characteristics, and the changing patterns of sub-divisional rainfall series in India, and explored the possible association of monsoon seasonal rainfall with different global climate oscillations. The proposed approach integrates the complete ensemble empirical mode decomposition with adaptive noise algorithm and normalized Hilbert transform method for analyzing the spectral characteristics of two principal seasonal rainfall series over four meteorological subdivisions namely Assam-Meghalaya, Kerala, Orissa and Telangana subdivisions in India. The Hilbert spectral analysis revealed the dynamic nature of dominant time scales for two principal seasonal rainfall time series. From the trend analysis of instantaneous amplitudes of multiscale components called intrinsic mode functions (IMFs), it is found that both intra and inter decadal modes are responsible for the changes in seasonal rainfall series of different subdivisions and significant changes are noticed in the amplitudes of inter decadal modes of two seasonal rainfalls in the four subdivisions since 1970s. Further, the study investigated the links between monsoon rainfall with the global climate oscillations such as Quasi Bienniel Oscillation (QBO), El Nino Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multidecadal Oscillation (AMO) etc. The study noticed that the multiscale components of rainfall series IMF1, IMF2, IMF3, IMF4 and IMF5 have similar periodic structure of QBO, ENSO, SN, tidal forcing and AMO respectively. As per the seasonal rainfall patterns is concerned, the results of the study indicated that for Assam-Meghalaya subdivision, there is a likelihood of extreme rare events at ~0.2 cycles per year, and both monsoon and pre-monsoon rainfall series have decreasing trends; for Kerala subdivision, extreme events can be expected during monsoon season with shorter periodicity (~2.5 years), and monsoon rainfall has statistically significant decreasing trend and post-monsoon rainfall has a statistically significant increasing trend; and for Orissa subdivision, there are chances of extremes rainfall events in monsoon season and a relatively stable rainfall pattern during post-monsoon period, but both monsoon and post-monsoon rainfall series showed an overall decreasing trend; for Telangana subdivision, there is a likelihood of extreme events during monsoon season with a periodicity of ~4 years, but both monsoon and post-monsoon rainfall series showed increasing trends. The results of correlation analysis of IMF components of monsoon rainfall and five climate indices indicated that the association is expressed well only for low frequency modes with similar evolution of trend components.  相似文献   

12.
A seasonal water budget analysis was carried out to quantify various components of the hydrological cycle using the Soil and Water Assessment Tool (SWAT) model for the Betwa River basin (43?500 km2) in central India. The model results were satisfactory in calibration and validation. The seasonal water budget analysis showed that about 90% of annual rainfall and 97% of annual runoff occurred in the monsoon season. A seasonal linear trend analysis was carried out to detect trends in the water balance components of the basin for the period 1973–2001. In the monsoon season, an increasing trend in rainfall and a decreasing trend in ET were observed; this resulted in an increasing trend in groundwater storage and surface runoff. The winter season followed almost the same pattern. A decreasing trend was observed in summer season rainfall. The study evokes the need for conservation structures in the study area to reduce monsoon runoff and conserve it for basin requirements in water-scarce seasons.

EDITOR Z.W. Kundzewicz

ASSOCIATE EDITOR F. Hattermann  相似文献   

13.
Asian summer monsoon sets in over India after the Intertropical Convergence Zone moves across the equator to the northern hemisphere over the Indian Ocean. Sea surface temperature (SST) anomalies on either side of the equator in Indian and Pacific oceans are found related to the date of monsoon onset over Kerala (India). Droughts in the June to September monsoon rainfall of India are followed by warm SST anomalies over tropical Indian Ocean and cold SST anomalies over west Pacific Ocean. These anomalies persist till the following monsoon which gives normal or excess rainfall (tropospheric biennial oscillation). Thus, we do not get in India many successive drought years as in sub-Saharan Africa, thanks to the ocean. Monsoon rainfall of India has a decadal variability in the form of 30-year epochs of frequent (infrequent) drought monsoons occurring alternately. Decadal oscillations of monsoon rainfall and the well-known decadal oscillation in SST of the Atlantic Ocean (also of the Pacific Ocean) are found to run parallel with about the same period close to 60 years and the same phase. In the active–break cycle of the Asian summer monsoon, the ocean and the atmosphere are found to interact on the time scale of 30–60 days. Net heat flux at the ocean surface, monsoon low-level jetstream (LLJ) and the seasonally persisting shallow mixed layer of the ocean north of the LLJ axis play important roles in this interaction. In an El Niño year, the LLJ extends eastwards up to the date line creating an area of shallow ocean mixed layer there, which is hypothesised to lengthen the active–break (AB) cycle typically from 1 month in a La Niña to 2 months in an El Niño year. Indian monsoon droughts are known to be associated with El Niños, and long break monsoon spells are found to be a major cause of monsoon droughts. In the global warming scenario, the observed rapid warming of the equatorial Indian ocean SST has caused the weakening of both the monsoon Hadley circulation and the monsoon LLJ which has been related to the observed rapid decreasing trend in the seasonal number of monsoon depressions.  相似文献   

14.
In this study the predictability of northeast monsoon (Oct–Nov–Dec) rainfall over peninsular India by eight general circulation model (GCM) outputs was analyzed. These GCM outputs (forecasts for the whole season issued in September) were compared with high-resolution observed gridded rainfall data obtained from the India Meteorological Department for the period 1982–2010. Rainfall, interannual variability (IAV), correlation coefficients, and index of agreement were examined for the outputs of eight GCMs and compared with observation. It was found that the models are able to reproduce rainfall and IAV to different extents. The predictive power of GCMs was also judged by determining the signal-to-noise ratio and the external error variance; it was noted that the predictive power of the models was usually very low. To examine dominant modes of interannual variability, empirical orthogonal function (EOF) analysis was also conducted. EOF analysis of the models revealed they were capable of representing the observed precipitation variability to some extent. The teleconnection between the sea surface temperature (SST) and northeast monsoon rainfall was also investigated and results suggest that during OND the SST over the equatorial Indian Ocean, the Bay of Bengal, the central Pacific Ocean (over Nino3 region), and the north and south Atlantic Ocean enhances northeast monsoon rainfall. This observed phenomenon is only predicted by the CCM3v6 model.  相似文献   

15.
An adequately tested soil and water assessment tool (SWAT) model was applied to the runoff and sediment yield of a small agricultural watershed in eastern India using generated rainfall. The capability of the model for generating rainfall was evaluated for a period of 18 years (1981–1998). The watershed and subwatershed boundaries, drainage networks, slope, soil series and texture maps were generated using a geographical information system (GIS). A supervised classification method was used for land‐use/cover classification from satellite imageries. Model simulated monthly rainfall for the period of 18 years was compared with observations. Simulated monthly rainfall, runoff and sediment yield values for the monsoon season of 8 years (1991–1998) were also compared with their observed values. In general monthly average rainfall predicted by the model was in close agreement with the observed monthly average values. Also, simulated monthly average values of surface runoff and sediment yield using generated rainfall compared well with observed values during the monsoon season of the years 1991–1998. Results of this study revealed that the SWAT model can generate monthly average rainfall satisfactorily and thereby can produce monthly average values of surface runoff and sediment yield close to the observed values. Therefore, it can be concluded that the SWAT model could be used for developing a multiple year management plan for the critical erosion prone areas of a small watershed. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

16.
In this study, sensitivity of the Indian summer monsoon simulation to the Himalayan orography representation in a regional climate model (RegCM) is examined. The prescribed height of the Himalayan orography is less in the RegCM model than the actual height of the Himalayas. Therefore, in order to understand the impact of the Himalayan orography representation on the Indian summer monsoon, the height of the Himalayan orography is increased (decreased) by 10 % from its control height in the RegCM model. Three distinct monsoon years such as deficit (1987), excess (1988) and normal rainfall years are considered for this study. The performance of the RegCM model is tested with the use of a driving force from the reanalysis data and a global model output. IMD gridded rainfall and the reanalysis-2 data are used as verification analysis to validate the model results. The RegCM model has the potential to represent mean rainfall distribution over India as well as the upper air circulation patterns and some of the semi-permanent features during the Indian summer monsoon season. The skill of RegCM is reasonable in representing the variation in circulation and precipitation pattern and intensity during two contrasting rainfall years. The simulated seasonal mean rainfall over many parts of India especially, the foothills of the Himalaya, west coast of India and over the north east India along with the whole of India are more when the orography height is increased. The low level southwesterly wind including the Somali jet stream as well as upper air circulation associated with the tropical easterly jet stream become stronger with the enhancement of the Himalayan orography. Statistical analysis suggests that the distribution and intensity of rainfall is represented better with the increased orography of RegCM by 10 % from its control height. Thus, representation of the Himalayan orography in the model is close to actual and may enhance the skill in seasonal scale simulation of the Indian summer monsoon.  相似文献   

17.
The European Centre for Medium-Range Weather Forecasts Reanalysis ERA40,National Centers for Environmental Prediction(NCEP) 20th-century reanalysis,and three station observations along an Antarctic traverse from Zhongshan to Dome-A stations are used to assess 2-m temperature simulation skill of a regional climate model.This model(HIRHAM) is from the Alfred Wegener Institute for Polar and Marine Research in Germany.Results show:(1) The simulated multiyear averaged 2-m temperature field pattern is close to that of ERA40 and NCEP;(2) the cold bias relative to ERA40 over all of Antarctic regions is 1.8℃,and that to NCEP reaches 5.1℃;(3) bias of HIRHAM relative to ERA40 has seasonal variation,with a cold bias mainly in the summer,as much as 3.4℃.There is a small inland warm bias in autumn of 0.3℃.Further analysis reveals that the reason for the cold bias of 2-m temperature is that physical conditions of the near-surface boundary layer simulated by HIRHAM are different from observations:(1) During the summer,observations show that near-surface atmospheric stability conditions have both inversions and non-inversions,which is due to the existence of both positive and negative sensible heat fluxes,but HIRHAM almost always simulates a situation of inversion and negative sensible heat flux;(2) during autumn and winter,observed near-surface stability is almost always that of inversions,consistent with HIRHAM simulations.This partially explains the small bias during autumn and winter.  相似文献   

18.
赤道MJO活动对南海夏季风爆发的影响   总被引：6，自引：0，他引：6       下载免费PDF全文
利用1979—2013年NCEP/DOE再分析资料的大气多要素日平均资料、美国NOAA日平均向外长波辐射资料和ERSST月平均海温资料,分析赤道大气季节内振荡(简称MJO)活动对南海夏季风爆发的影响及其与热带海温信号等的协同作用.结果表明,赤道MJO活动与南海夏季风爆发密切联系,MJO的湿位相(即对流活跃位相)处于西太平洋位相时,有利于南海夏季风爆发,而MJO湿位相处于印度洋位相时,则不利于南海夏季风爆发.赤道MJO活动影响南海夏季风爆发的物理过程主要是大气对热源响应的结果,当MJO湿位相处于西太平洋位相时,一方面热带西太平洋对流加强使潜热释放增加,导致处于热源西北侧的南海—西北太平洋地区对流层低层由于Rossby响应产生气旋性环流异常,气旋性环流异常则有利于西太平洋副热带高压的东退,另一方面菲律宾附近热源促进对流层高层南亚高压在中南半岛和南海北部的建立,使南海地区高层为偏东风,从而有利于南海夏季风建立;当湿位相MJO处于印度洋位相时,热带西太平洋对流减弱转为大气冷源,情况基本相反,不利于南海夏季风建立.MJO活动、孟加拉湾气旋性环流与年际尺度海温变化协同作用,共同对南海夏季风爆发迟早产生影响,近35年南海夏季风爆发时间与海温信号不一致的年份,基本上是由于季节转换期间的MJO活动特征及孟加拉湾气旋性环流是否形成而造成,因此三者综合考虑对于提高季风爆发时间预测水平具有重要意义.  相似文献   

19.
Seasonal and annual trends of changes in rainfall, rainy days, heaviest rain and relative humidity have been studied over the last century for nine different river basins in northwest and central India. The majority of river basins have shown increasing trends both in annual rainfall and relative humidity. The magnitude of increased rainfall for considered river basins varied from 2–19% of mean per 100 years. The maximum increase in rainfall is observed in the Indus (lower) followed by the Tapi river basin. Seasonal analysis shows maximum increase in rainfall in the post‐monsoon season followed by the pre‐monsoon season. There were least variations in the monsoon rainfall during the last century and winter rainfall has shown a decreasing trend. Most of the river basins have experienced decreasing trends in annual rainy days with a maximum decrease in the Mahanadi basin. The heaviest rain of the year has increased from 9–27 mm per 100 years over different river basins with a maximum of 27 mm for the Brahamani and Subaranrekha river basins. A combination of increase in heaviest rainfall and reduction in the number of rainy days suggest the possibility of increasing severity of floods. Such information is useful in the planning, development and management of water resources in the study area. Further, the majority of river basins have also experienced an increasing trend in relative humidity both on seasonal and annual scales. An increase in annual mean relative humidity for six river basins has been found in the range of 1–18% of mean per 100 years, while a decrease for three river basins from ? 1 to ? 13% of mean per 100 years was observed, providing a net increase in the study area by 2·4% of mean per 100 years. It is understood that an increase in areal extent of vegetation cover as well as rainfall over the last century has increased the moisture in the atmosphere through enhanced evapotranspiration, which in turn has increased the relative humidity. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

20.
The overall objective of this study is to improve the forecasting accuracy of the precipitation in the Singapore region by means of both rainfall forecasting and nowcasting. Numerical Weather Predication (NWP) and radar‐based rainfall nowcasting are two important sources for quantitative precipitation forecast. In this paper, an attempt to combine rainfall prediction from a high‐resolution mesoscale weather model and a radar‐based rainfall model was performed. Two rainfall forecasting methods were selected and examined: (i) the weather research and forecasting model (WRF); and (ii) a translation model (TM). The WRF model, at a high spatial resolution, was run over the domain of interest using the Global Forecast System data as initializing fields. Some heavy rainfall events were selected from data record and used to test the forecast capability of WRF and TM. Results obtained from TM and WRF were then combined together to form an ensemble rainfall forecasting model, by assigning weights of 0.7 and 0.3 weights to TM and WRF, respectively. This paper presented results from WRF and TM, and the resulting ensemble rainfall forecasting; comparisons with station data were conducted as well. It was shown that results from WRF are very useful as advisory of anticipated heavy rainfall events, whereas those from TM, which used information of rain cells already appearing on the radar screen, were more accurate for rainfall nowcasting as expected. The ensemble rainfall forecasting compares reasonably well with the station observation data. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

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