共查询到20条相似文献，搜索用时 15 毫秒
1.
Agriculture in India is highly sensitive to climatic variations particularly to rainfall and temperature; therefore, any change in rainfall and temperature will influence crop yields. An understanding of the spatial and temporal distribution and changing patterns in climatic variables is important for planning and management of natural resources. Time series analysis of climate data can be a very valuable tool to investigate its variability pattern and, maybe, even to predict short- and long-term changes in the series. In this study, the sub-divisional rainfall data of India during the period 1871 to 2016 has been investigated. One of the widely used powerful nonparametric techniques namely wavelet analysis was used to decompose and de-noise the series into time–frequency component in order to study the local as well as global variation over different scales and time epochs. On the decomposed series, autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) models were applied and by means of inverse wavelet transform, the prediction of rainfall for different sub-divisions was obtained. To this end, empirical comparison was carried out toward forecast performance of the approaches namely Wavelet-ANN, Wavelet-ARIMA, and ARIMA. It is reported that Wavelet-ANN and Wavelet-ARIMA approach outperforms the usual ARIMA model for forecasting of rainfall for the data under consideration. 相似文献
2.
Peter Allerup 《Atmospheric Research》1996,42(1-4)
The aim of this paper is to present a rainfall generator which takes both spatial and temporal characteristics into account. The statistical model behind the generator is based on long-time experience with statistical analyses of empirical rainfall data and represents, therefore, a genuine theoretical point for simulating series of precipitation values. The sites of the recording gauges and the actual time (day, month, year etc.) enter a statistical model as systematic components for the prediction of expected rainfall in a two-way analysis of variance design. Beyond these systematic components, spatial correlations among the observations are still present in nature, a feature which is modelled also by the rainfall generator. 相似文献
3.
El-Niño/Southern Oscillation (ENSO) variability and its relationship with precipitation in the tropics and subtropics are analysed using the ARPEGE-OPA ocean-atmosphere coupled model. Three 150-year simulations are considered, differing by greenhouse gases (GHG) and aerosols concentrations. The first one has constant (1950 level) concentrations, and the two others follow observed values till 1999, then the SRES B2 scenario until 2099. The model is able to reproduce most present-day features characteristic of ENSO in the Pacific. It also displays ENSO as the leading mode of sea-surface temperature (SST) variability, with spatial patterns and explained variance both quite similar to the observation. A detailed analysis of its teleconnections with rainfall variability is carried out on a seasonal basis. Patterns for the last part of the twentieth century compare favourably with the observation, with the notable exception of parts of the Atlantic sector. The overall strong rainfall response arises from the strong interannual variability of simulated ENSO, and also suggests an ability to simulate atmospheric dynamics in a realistic way. In the future climate, the model does not exhibit major changes in the ENSO/rainfall teleconnections. However, on a regional basis, there is some evidence of strengthening (e.g., in parts of Southern Africa) and weakening (e.g., East Africa) in the course of the twenty-first century. In most cases, decadal swings in the correlations suggest that these alterations may partly reflect natural changes in the teleconnections with ENSO, long-term correlation trends (possibly GHG-induced) being comparatively weaker. 相似文献
4.
Iman ROUSTA Mehdi DOOSTKAMIAN Esmaeil HAGHIGHI Hamid Reza GHAFARIAN MALAMIRI Parvane YARAHMADI 《大气科学进展》2017,34(9):1069-1081
Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran's heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord Gistatistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran,have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall. 相似文献
5.
Summary The rainfall patterns and regions of the monsoonal island of Sri Lanka have been investigated. On the basis of quality-controlled monthly rainfall data from 110 gauges for the period 1931–60, three major homogeneous rainfall regions were derived based on a variety of rainfall parameters using cluster and discriminant analysis. For each of these regions, identified as the South-west Monsoon (SWM), the Northeast Monsoon (NEM) and the Inter-monsoon II (IMII) regions, multiple regression methods were used to determine the geographical factors influencing the spatial patterns of rainfall. For the NEM and IMII regions, the level of explanation as indicated by the coefficients of multiple determination were reasonable with values generally above 0.60. For the SWM region, the level of explanation was much lower at about 0.20. Examination of the residuals of the regression equations demonstrated the significance of local factors in influencing the patterns of rainfall distribution in Sri Lanka.With 6 Figures 相似文献
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7.
Selection of regional historical rainfall time series as input to urban drainage simulations at ungauged locations 总被引：1，自引：0，他引：1
P.S. Mikkelsen H. Madsen K. Arnbjerg-Nielsen D. Rosbjerg P. Harremoës 《Atmospheric Research》2005,77(1-4):4
It has become established practice during the past 20 years to use high-resolution historical rainfall time series as input to hydrological model packages for detailed simulation of urban drainage systems. However, sufficiently long rain series are rarely available from the exact catchment in question and simulations are hence often based on available rain series from other locations. Extreme rainfall properties of importance to the performance of urban storm drainage systems vary significantly even in regions with only minor physiographic differences. Part of this variation can be explained by regional variations of the mean annual rainfall and the remaining statistical residue can be interpreted as statistical uncertainty.In Denmark, more than 75 high-resolution rain gauges are installed across a total area of 43,000 m. About 40 gauges had sufficiently long records to be included in a comprehensive national investigation where newly developed statistical regionalisation procedures were used to model the regional variation of extreme rainfalls. On this basis, a spreadsheet model was made available for estimation of extreme design rainfalls and the associated uncertainty at any location in the country. Statistics were furthermore computed to classify historical rainfall time series according to the developed regional model, and this makes it possible to assess the uncertainty related with using different historical rain series for simulations at ungauged locations.This research indicates that use of historical point rainfall data at ungauged locations introduces a significant uncertainty that is largely overlooked in today's practice. The engineering recommendation is to select historical rain series based on an evaluation of the local physiographic characteristics (e.g., the mean annual rainfall) and a (pre-defined) desired safety level of the simulations. 相似文献
8.
Goutami Chattopadhyay Parthasarathi Chakraborthy Surajit Chattopadhyay 《Theoretical and Applied Climatology》2012,110(3):321-328
The present work reports studies on the spatial distribution of tropospheric ozone extending over both southern and northern hemispheres. This study is based on a univariate approach to the spatial data series obtained at regular spatial intervals. Mann?CKendall's (MK) trend analysis has been carried out to discern the trend within the spatial distribution of the tropospheric ozone, and it has been observed that in all seasons, except monsoon (JJAS), there is a linear trend within the spatial distribution. Studying both monthly and seasonal behavior through autoregressive integrated moving average (ARIMA), it has been revealed that ARIMA (0,2,2) can be used as a representative of the spatially distributed tropospheric ozone over southern and northern hemispheres. The representative model has been confirmed through the study of Willmott's index and prediction yield. 相似文献
9.
Mark W. Shephard Eva Mekis Robert J. Morris Yang Feng Xuebin Zhang Karen Kilcup 《大气与海洋》2014,52(5):398-417
Short-duration (5 minutes to 24 hours) rainfall extremes are important for a number of purposes, including engineering infrastructure design, because they represent the different meteorological scales of extreme rainfall events. Both single location and regional analyses of the changes in short-duration extreme rainfall amounts across Canada, as observed by tipping bucket rain gauges from 1965 to 2005, are presented. The single station analysis shows a general lack of a detectable trend signal, at the 5% significance level, because of the large variability and the relatively short period of record of the extreme short-duration rainfall amounts. The single station 30-minute to 24-hour durations show that, on average, 4% of the total number of stations have statistically significant increasing amounts of rainfall, whereas 1.6% of the cases have significantly decreasing amounts. However, regional spatial patterns are apparent in the single station trend results. Thus, for the same durations regional trends are presented by grouping the single station trend statistics across Canada. This regional trend analysis shows that at least two-thirds of the regions across Canada have increasing trends in extreme rainfall amounts, with up to 33% being significant (depending on location and duration). Both the southwest and the east (Newfoundland) coastal regions generally show significant increasing regional trends for 1- and 2-hour extreme rainfall durations. For the shortest durations of 5–15 minutes, the general overall regional trends in the extreme amounts are more variable, with increasing and decreasing trends occurring with similar frequency; however, there is no evidence of statistically significant decreasing regional trends in extreme rainfall amounts. The decreasing regional trends for the 5- to 15-minute duration amounts tend to be located in the St. Lawrence region of southern Quebec and in the Atlantic provinces. Additional analysis using criteria specified for traditional water management practice (e.g., Intensity-Duration-Frequency (IDF)) shows that fewer than 5.6% and 3.4% of the stations have significant increasing and decreasing trends, respectively, in extreme annual maximum single location observation amounts. This indicates that at most locations across Canada the traditional single station IDF assumption that historical extreme rainfall observations are stationary (in terms of the mean) over the period of record for an individual station is not violated. However, the trend information is still useful complementary information that can be considered for water management purposes, especially in terms of regional analysis. 相似文献
10.
V. Badescu 《Meteorology and Atmospheric Physics》2001,78(3-4):195-204
Summary
Stationarity of daily averaged surface pressure time series on Mars can be obtained (by differencing) for short time intervals
only. Large pressure variance intervals are usually associated with the dust storm season. Medium and small pressure variance
intervals can be found usually during clear sky periods. General auto-regressive integrated moving average (ARIMA) models
were developed for daily average pressure forecasting at Viking Lander sites. A procedure to find the “appropriate” model
for a given time series was developed. It is based on various degrees of differencing the original time series and a t-statistics-assisted
estimation of the significance of the fitted coefficients. A method employing the cumulative spectrum of the residuals was
used to check the models. ARIMA (3,2,3) seems to be the most “appropriate” model to forecasting the daily average surface
pressure on Mars.
Received December 16, 1999/Revised October 17, 2000 相似文献
11.
Some Unique Characteristics of Atmospheric Interannual Variability in Rainfall Time Series over India and the United Kingdom 总被引：1，自引：0，他引：1
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12.
《Atmospheric Research》2010,95(4):629-640
An important issue in pluviometric data analysis from rain gauges is the verification of their consistency. In general, this attribute is assessed using double-mass curves. This technique compares cumulative monthly rainfall from a gauge with that averaged from meteorological stations located nearby. The aim of this study was to analyze the quality of monthly rainfall data registered in Galicia (NW Spain) in a five year period (2002–2006). Initially, 159 meteorological stations were evaluated; however, 59 gauges were withdrawn because 10% of their data were missing. Double-mass analysis was performed following two procedures: a) data from each gauge were compared to those obtained in the nearby main station and b) data from each site were compared to the average from five nearby gauges, including data from neighboring regions. The second procedure proved to be more reliable. Rainfall data did not show any outlier for the study period. Determination coefficients were greater than 0.95 in all cases. A graphical analysis showed some deviations from the trend lines in certain stations. First, rainfall maps were obtained by inverse distances weighting. Furthermore, a comprehensive geostatistical analysis, centered in the characterization of the structure of rainfall spatial variability, was performed. Differences between two kriging methods, ordinary and kriging with an external drift, were confirmed, considering the later as a more appropriate technique for rainfall interpolation in the region. 相似文献
13.
14.
Natural variability of summer rainfall over China in HadCM3 总被引：1，自引：0，他引：1
Summer rainfall over China has shown decadal variability in the past half century, which has resulted in major north–south shifts in rainfall with important implications for flooding and water resource management. This study has demonstrated how multi-century climate model simulations can be used to explore interdecadal natural variability in the climate system in order to address important questions around recent changes in Chinese summer rainfall, and whether or not anthropogenic climate change is playing a role. Using a 1,000-year simulation of HadCM3 with constant pre-industrial external forcing, the dominant modes of total and interdecadal natural variability in Chinese summer rainfall have been analysed. It has been shown that these modes are comparable in magnitude and in temporal and spatial characteristics to those observed in the latter part of the twentieth century. However, despite 1,000 years of model simulation it has not been possible to demonstrate that these modes are related to similar variations in the global circulation and surface temperature forcing occurring during the latter half of the twentieth century. This may be in part due to model biases. Consequently, recent changes in the spatial distribution of Chinese summer rainfall cannot be attributed solely to natural variability, nor has it been possible to eliminate the likelihood that anthropogenic climate change has been the driving factor. It is more likely that both play a role. 相似文献
15.
Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa 总被引：1，自引：1，他引：0
It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa. 相似文献
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18.
Application of Markov models to area-average daily precipitation series and interannual variability in seasonal totals 总被引：4，自引：0，他引：4
This paper examines the success of various Markov-chain models of daily precipitation series in reproducing the characteristics of area-average rainfall in Britain. The first model considered is the standard twos-tate first-order Markov renewal process coupled to an amount model using the incomplete -probability distribution. We find that variability of seasonal totals and autocorrelation of daily amounts are both too small in this model, compared with observations. These are serious deficiencies, often overlooked, and possibly related. We proceed to consider models involving Markov chains of higher (temporal) order and many states, both of which generalizations may increase autocorrelation. A second-order two-state model is no better than the first-order, but a first-order many-state model captures a high fraction of the seasonal variability, because use of many states improves the model's representation of spells of heavy precipitation, which appear to have a considerable influence on the seasonal variance. Better still is a second-order many-state model, a type which, to our knowledge, has not previously been investigated. We suggest that the best model would have a continuum of states, rather than a discrete set. Our conclusion is that a large proportion of seasonal variability may be explained in terms of the average daily structure, but there may be a residual component caused by processes operating on longer time-scales and possibly predictable with reference to these. Reproduction of long-period (e.g. monthly or seasonal) variance and of the structure of daily autocorrelation provide crucial tests of stochastic weather generators, and we recommend that models which fail to simulate these statistics realistically be used only with great caution. 相似文献
19.
Aneesh Subramanian Markus Jochum Arthur J. Miller Richard Neale Hyodae Seo Duane Waliser Raghu Murtugudde 《Climate Dynamics》2014,42(7-8):2019-2031
The change in Madden–Julian oscillation (MJO) amplitude and variance in response to anthropogenic climate change is assessed in the 1° nominal resolution community climate system model, version 4 (CCSM4), which has a reasonable representation of the MJO characteristics both dynamically and statistically. The twentieth century CCSM4 run is compared with the warmest twenty-first century projection (representative concentration pathway 8.5, or RCP8.5). The last 20 years of each simulation are compared in their MJO characteristics, including spatial variance distributions of winds, precipitation and outgoing longwave radiation, histograms of event amplitude, phase and duration, and composite maps of phases. The RCP8.5 run exhibits increased variance in intraseasonal precipitation, larger-amplitude MJO events, stronger MJO rainfall in the central and eastern tropical Pacific, and a greater frequency of MJO occurrence for phases corresponding to enhanced rainfall in the Indian Ocean sector. These features are consistent with the concept of an increased magnitude for the hydrological cycle under greenhouse warming conditions. Conversely, the number of active MJO days decreases and fewer weak MJO events occur in the future climate state. These results motivate further study of these changes since tropical rainfall variability plays such an important role in the region’s socio-economic well being. 相似文献
20.
Daily modes of South Asian summer monsoon variability in the NCEP climate forecast system 总被引：1，自引：0，他引：1
The leading modes of daily variability of the Indian summer monsoon in the climate forecast system (CFS), a coupled general circulation model, of the National Centers for Environmental Predictions (NCEP) are examined. The space?Ctime structures of the daily modes are obtained by applying multi-channel singular spectrum analysis (MSSA) on the daily anomalies of rainfall. Relations of the daily modes to intraseasonal and interannual variability of the monsoon are investigated. The CFS has three intraseasonal oscillations with periods around 106, 57 and 30?days with a combined variance of 7%. The 106-day mode has spatial structure and propagation features similar to the northeastward propagating 45-day mode in the observations except for its longer period. The 57-day mode, despite being in the same time scale as of the observations has poor eastward propagation. The 30-day mode is northwestward propagating and is similar to its observational counterpart. The 106-day mode is specific to the model and should not be mistaken for a new scale of variability in observations. The dominant interannual signal is related to El Ni?o-Southern Oscillation (ENSO), and, unlike in the observations, has maximum variance in the eastern equatorial Indian Ocean. Although the Indian Ocean Dipole (IOD) mode was not obtained as a separate mode in the rainfall, the ENSO signal has good correlations with the dipole variability, which, therefore, indicates the dominance of ENSO in the model. The interannual variability is largely determined by the ENSO signal over the regions where it has maximum variance. The interannual variability of the intraseasonal oscillations is smaller in comparison. 相似文献