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1.
Global Terrestrial Water Storage Changes and Connections to ENSO Events   总被引：1，自引：0，他引：1  
Improved data quality of extended record of the Gravity Recovery and Climate Experiment (GRACE) satellite gravity solutions enables better understanding of terrestrial water storage (TWS) variations. Connections of TWS and climate change are critical to investigate regional and global water cycles. In this study, we provide a comprehensive analysis of global connections between interannual TWS changes and El Niño Southern Oscillation (ENSO) events, using multiple sources of data, including GRACE measurements, land surface model (LSM) predictions and precipitation observations. We use cross-correlation and coherence spectrum analysis to examine global connections between interannual TWS changes and the Niño 3.4 index, and select four river basins (Amazon, Orinoco, Colorado, and Lena) for more detailed analysis. The results indicate that interannual TWS changes are strongly correlated with ENSO over much of the globe, with maximum cross-correlation coefficients up to ~0.70, well above the 95% significance level (~0.29) derived by the Monte Carlo experiments. The strongest correlations are found in tropical and subtropical regions, especially in the Amazon, Orinoco, and La Plata basins. While both GRACE and LSM TWS estimates show reasonably good correlations with ENSO and generally consistent spatial correlation patterns, notably higher correlations are found between GRACE TWS and ENSO. The existence of significant correlations in middle–high latitudes shows the large-scale impact of ENSO on the global water cycle.  相似文献   

2.
Relationships were examined between variability in tropical Atlantic sea level and major climate indices with the use of TOPEX/POSEIDON altimeter and island tide gauge data with the aim of learning more about the external influences on the variability of the tropical Atlantic ocean. Possible important connections were found between indices related to the El Niño–Southern Oscillation (ENSO) and the sea levels in all three tropical regions (north, equatorial, and south), although the existence of only one major ENSO event within the decade of available altimetry means that a more complete investigation of the ENSO-dependence of Atlantic sea level changes has to await for the compilation of longer data sets. An additional link was found with the Indian Ocean Dipole (IOD) in the equatorial region, this perhaps surprising observation is probably an artifact of the similarity between IOD and ENSO time series in the 1990s. No evidence was obtained for significant correlations between tropical Atlantic sea level and North Atlantic Oscillation or Antarctic Oscillation Index. The most intriguing relationship observed was between the Quasi-Biennial Oscillation and sea level in a band centered approximately on 10°S. A plausible explanation for the relationship is lacking, but possibilities for further research are suggested.  相似文献   

3.
In recent decades, decomposition techniques have enabled increasingly more applications for dimension reduction, as well as extraction of additional information from geophysical time series. Traditionally, the principal component analysis (PCA)/empirical orthogonal function (EOF) method and more recently the independent component analysis (ICA) have been applied to extract, statistical orthogonal (uncorrelated), and independent modes that represent the maximum variance of time series, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the autocovariance matrix and diagonalizing higher (than two) order statistical tensors from centered time series, respectively. However, the stationarity assumption in these techniques is not justified for many geophysical and climate variables even after removing cyclic components, e.g., the commonly removed dominant seasonal cycles. In this paper, we present a novel decomposition method, the complex independent component analysis (CICA), which can be applied to extract non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA, where (a) we first define a new complex dataset that contains the observed time series in its real part, and their Hilbert transformed series as its imaginary part, (b) an ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex dataset in (a), and finally, (c) the dominant independent complex modes are extracted and used to represent the dominant space and time amplitudes and associated phase propagation patterns. The performance of CICA is examined by analyzing synthetic data constructed from multiple physically meaningful modes in a simulation framework, with known truth. Next, global terrestrial water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) gravimetry mission (2003–2016), and satellite radiometric sea surface temperature (SST) data (1982–2016) over the Atlantic and Pacific Oceans are used with the aim of demonstrating signal separations of the North Atlantic Oscillation (NAO) from the Atlantic Multi-decadal Oscillation (AMO), and the El Niño Southern Oscillation (ENSO) from the Pacific Decadal Oscillation (PDO). CICA results indicate that ENSO-related patterns can be extracted from the Gravity Recovery And Climate Experiment Terrestrial Water Storage (GRACE TWS) with an accuracy of 0.5–1 cm in terms of equivalent water height (EWH). The magnitude of errors in extracting NAO or AMO from SST data using the complex EOF (CEOF) approach reaches up to ~50% of the signal itself, while it is reduced to ~16% when applying CICA. Larger errors with magnitudes of ~100% and ~30% of the signal itself are found while separating ENSO from PDO using CEOF and CICA, respectively. We thus conclude that the CICA is more effective than CEOF in separating non-stationary patterns.  相似文献   

4.
West African countries have been exposed to changes in rainfall patterns over the last decades, including a significant negative trend. This causes adverse effects on water resources of the region, for instance, reduced freshwater availability. Assessing and predicting large-scale total water storage (TWS) variations are necessary for West Africa, due to its environmental, social, and economical impacts. Hydrological models, however, may perform poorly over West Africa due to data scarcity. This study describes a new statistical, data-driven approach for predicting West African TWS changes from (past) gravity data obtained from the gravity recovery and climate experiment (GRACE), and (concurrent) rainfall data from the tropical rainfall measuring mission (TRMM) and sea surface temperature (SST) data over the Atlantic, Pacific, and Indian Oceans. The proposed method, therefore, capitalizes on the availability of remotely sensed observations for predicting monthly TWS, a quantity which is hard to observe in the field but important for measuring regional energy balance, as well as for agricultural, and water resource management. Major teleconnections within these data sets were identified using independent component analysis and linked via low-degree autoregressive models to build a predictive framework. After a learning phase of 72 months, our approach predicted TWS from rainfall and SST data alone that fitted to the observed GRACE-TWS better than that from a global hydrological model. Our results indicated a fit of 79 % and 67 % for the first-year prediction of the two dominant annual and inter-annual modes of TWS variations. This fit reduces to 62 % and 57 % for the second year of projection. The proposed approach, therefore, represents strong potential to predict the TWS over West Africa up to 2 years. It also has the potential to bridge the present GRACE data gaps of 1 month about each 162 days as well as a—hopefully—limited gap between GRACE and the GRACE follow-on mission over West Africa. The method presented could also be used to generate a near-real-time GRACE forecast over the regions that exhibit strong teleconnections.  相似文献   

5.
近年来极端气候事件的频发对全球和区域性水循环产生了重大影响,特别是2005—2017年间两次强ENSO(El Nino-Southern Oscillation)事件使得全球陆地水储量出现了较大的年际波动.GRACE(Gravity Recovery and Climate Experiment)重力卫星随着数据质量的提高、后处理方法的完善和超过十年的连续观测,捕捉陆地水储量异常的能力明显提高,这为研究2005—2017年间两次强ENSO事件对中国区域陆地水储量变化的影响提供了观测基础.本文综合利用GRACE卫星重力数据、GLDAS水文模型和实测降水资料分析了中国区域陆地水储量年际变化和与ENSO的关系.研究发现:长江流域中、下游地区和东南诸河流域与ENSO存在较高的相关性,与ENSO的相关系数最大值分别为0.55、0.78、0.70,较ENSO分别滞后约7个月、5个月和5个月.其中长江流域下游地区与ENSO的相关性最强,2010/11 La Nina和2015/16 El Nino两次强ENSO事件使得陆地水储量分别发生了约-24.1亿吨和27.9亿吨的波动.在2010/11 La Nina期间,长江流域下游地区和东南诸河流域陆地水储量异常约在2011年4—5月达到谷值,而长江流域中游地区晚1~2月达到谷值.在2015/16 El Nino期间,长江流域中、下游地区和东南诸河流域陆地水储量从2015年9月到2016年7月持续出现正异常信号.其中,2015年秋冬季(2015年9月至2016年1月)陆地水储量异常明显是受此次El Nino同期影响的结果;2016年春季(4—5月)陆地水异常是受到此次厄尔尼诺峰值的滞后影响所致;2016年7月的陆地水储量异常则与西北太平洋存在的异常反气旋环流有关.  相似文献   

6.
It is well recognized that the time series of hydrologic variables, such as rainfall and streamflow are significantly influenced by various large‐scale atmospheric circulation patterns. The influence of El Niño‐southern oscillation (ENSO) on hydrologic variables, through hydroclimatic teleconnection, is recognized throughout the world. Indian summer monsoon rainfall (ISMR) has been proved to be significantly influenced by ENSO. Recently, it was established that the relationship between ISMR and ENSO is modulated by the influence of atmospheric circulation patterns over the Indian Ocean region. The influences of Indian Ocean dipole (IOD) mode and equatorial Indian Ocean oscillation (EQUINOO) on ISMR have been established in recent research. Thus, for the Indian subcontinent, hydrologic time series are significantly influenced by ENSO along with EQUINOO. Though the influence of these large‐scale atmospheric circulations on large‐scale rainfall patterns was investigated, their influence on basin‐scale stream‐flow is yet to be investigated. In this paper, information of ENSO from the tropical Pacific Ocean and EQUINOO from the tropical Indian Ocean is used in terms of their corresponding indices for stream‐flow forecasting of the Mahanadi River in the state of Orissa, India. To model the complex non‐linear relationship between basin‐scale stream‐flow and such large‐scale atmospheric circulation information, artificial neural network (ANN) methodology has been opted for the present study. Efficient optimization of ANN architecture is obtained by using an evolutionary optimizer based on a genetic algorithm. This study proves that use of such large‐scale atmospheric circulation information potentially improves the performance of monthly basin‐scale stream‐flow prediction which, in turn, helps in better management of water resources. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

7.
An intermediate ocean-atmosphere coupled model is developed to simulate and predict the tropical interannual variability. Originating from the basic physical framework of the Zebiak-Cane(ZC) model, this tropical intermediate couple model(TICM) extends to the entire global tropics, with a surface heat flux parameterization and a surface wind bias correction added to improve model performance and inter-basin connections. The model well reproduces the variabilities in the tropical Pacific and Indian basins. The simulated El Ni?o-Southern Oscillation(ENSO) shows a period of 3–4 years and an amplitude of about 2°C, similar to those observed. The variabilities in the Indian Ocean, including the Indian Ocean basin mode(IOBM) and the Indian Ocean Dipole(IOD), are also reasonably captured with a realistic relationship to the Pacific. However, the tropical Atlantic variability in the TICM has a westward bias and is overly influenced by the tropical Pacific. A 47-year hindcast experiment using the TICM for the period of 1970–2016 indicates that ENSO is the most predictable mode in the tropics. Skillful predictions of ENSO can be made one year ahead, similar to the skill of the latest version of the ZC model, while a "spring predictability barrier" still exists as in other models. In the tropical Indian Ocean, the predictability seems much higher in the west than in the east. The correlation skill of IOD prediction reaches 0.5 at a 5-month lead, which is comparable to that of the state-of-the-art coupled general circulation models. The prediction of IOD shows a significant "winter-spring predictability barrier", implying combined influences from the tropical Pacific and the local sea-air interaction in the eastern Indian Ocean. The TICM has little predictive skill in the equatorial Atlantic for lead times longer than 3 months, which is a common problem of current climate models badly in need of further investigation.  相似文献   

8.
In this study, the nature of basin‐scale hydroclimatic association for Indian subcontinent is investigated. It is found that, the large‐scale circulation information from Indian Ocean is also equally important in addition to the El Niño‐Southern Oscillation (ENSO), owing to the geographical location of Indian subcontinent. The hydroclimatic association of the variation of monsoon inflow into the Hirakud reservoir in India is investigated using ENSO and EQUatorial INdian Ocean Oscillation (EQUINOO, the atmospheric part of Indian Ocean Dipole mode) as the large‐scale circulation information from tropical Pacific Ocean and Indian Ocean regions respectively. Individual associations of ENSO & EQUINOO indices with inflow into Hirakud reservoir are also assessed and found to be weak. However, the association of inflows into Hirakud reservoir with the composite index (CI) of ENSO and EQUINOO is quite strong. Thus, the large‐scale circulation information from Indian Ocean is also important apart form the ENSO. The potential of the combined information of ENSO and EQUINOO for predicting the inflows during monsoon is also investigated with promising results. The results of this study will be helpful to water resources managers due to fact that the nature of monsoon inflow is becoming available as an early prediction. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

9.
Abstract

This study was carried out in the framework of the Surface Water and Ocean Topography (SWOT) programme of the French National Centre of Space Studies (CNES). Based on discharge measurements and Gravity Recovery and Climate Experiment (GRACE) determination of total water storage (TWS), we have investigated the hydrological variability of the main French drainage basins (Seine, Loire, Garonne and Rhône) using a wavelet approach (continuous wavelet analyses and wavelet coherence analyses). The results of this analysis have shown a coherence ranging between 82% and 90% for TWS and discharge, thus demonstrating the potential use of TWS for characterization of the hydrological variability of French rivers. Strong coherence between the four basin discharges (between 73% and 92%) and between their associated TWS data (from 82% to 98%) suggested a common external influence on hydrological variability. To determine this influence, we investigated the relationship between hydrological variability and the North Atlantic Oscillation (NAO), considered as an index of prevailing climate in Europe. Basin discharges show strong coherence with NAO, ranging between 64% and 72% over the period 1959–2010. The coherence between NAO and TWS was 62% to 67% for 2003–2009. This is similar to the coherence between NAO and basin discharges detected for the same period. According to these results, strong influence of the NAO was clearly observed on the TWS and discharges of the major French river basins.
Editor Z.W. Kundzewicz  相似文献   

10.
Abstract

The identification of Atlantic Ocean (AO) climatic drivers may prove valuable in long lead-time forecasting of streamflow in the Adour-Garonne basin in southwestern France. Previous studies have identified the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO) as drivers of European hydrology. The current research applied the singular value decomposition (SVD) statistical method to AO sea-surface temperatures (SSTs) to identify the primary AO climatic drivers of the Adour-Garonne basin streamflow. Annual and seasonal streamflow volumes were selected as the hydrological response, while average AO SSTs were calculated for three different 6-month averages (January–June, April–September and July–December) for the year preceding streamflow. The results identified a region along the Equator as the probable driver of the basin streamflow. Additional analysis evaluated the influence of the AMO and NAO on Adour-Garonne basin streamflow.

Editor Z.W. Kundzewicz; Associate editor H. Aksoy

Citation Oubeidillah, A.A., Tootle, G. and Anderson, S.-R., 2012. Atlantic Ocean sea-surface temperatures and regional streamflow variability in the Adour-Garonne basin, France. Hydrological Sciences Journal, 57 (3), 496–506.  相似文献   

11.
The magnitude, occurrence rate and occurrence timing of floods in the Poyang Lake basin were analysed. The flood series were acquired by annual and seasonal maximum flow (AMF) sampling and peaks-over-threshold (POT) sampling. Nonstationarity and uncertainty were analysed using kernel density estimation and the bootstrap resampling methods. Using the relationships between flood indices and climate indices, i.e. El Niño/Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD) and Pacific Decadal Oscillation (PDO), the potential causes of flooding were investigated. The results indicate that (1) the magnitudes of annual and seasonal AMF- and POT-based sampled floods generally exhibit an increasing tendency; (2) the highest occurrence rates of floods identified were during the 1990s, when the flood-affected crop area, flood-damaged crop area and crop failure area reached the highest levels; and (3) ENSO and IOD are the major climate indices that significantly correlate with the magnitude and frequency of floods of the following year.

EDITOR A. Castellarin ASSOCIATE EDITOR T. Kjeldsen  相似文献   

12.
We examined rainfall anomalies associated with the El Niño–Southern Oscillation (ENSO) in northern Sarawak, Malaysia, using the oxygen isotopic composition of rainfall. Two precipitation‐sampling campaigns were conducted for isotope analysis: (a) at the Lambir Hill National Park (4.2° N, 114.0° E) from July 2004 to October 2006 and (b) at the Gunung Mulu National Park (3.9° N, 114.8° E) from January 2006 to July 2008. The records from these campaigns were merged with a previously published rainfall isotope dataset from Gunung Mulu site to create a 7‐year‐long record of the oxygen isotopic composition of Sarawak rainfall. The record exhibits clear intraseasonal variations (ISVs) with periods ranging from 10 to 70 days. The ISVs of 10‐ to 90‐day band‐pass filtered oxygen isotopic composition are linked to the synoptic‐scale precipitation anomalies over the southern South China Sea (SCS). The lead–lag correlation map of precipitation with the filtered oxygen isotope anomalies shows that an anomalous wet condition responsible for the decrease in oxygen isotopic composition appears over the SCS in association with the passage of north‐eastward propagation of the boreal summer intraseasonal oscillation (BSISO) in the summer monsoon season. The anomalous wet condition in spring is connected with eastward‐propagating Madden–Julian oscillation (MJO), whereas the sustained wet condition in winter is responsible for the occurrence of the Borneo vortex (BV) over the SCS. ENSO modulates the frequency of these synoptic conditions on a seasonal and longer time scale, showing a strong correlation between the seasonal isotopic anomalies and the Southern Oscillation index. We therefore discern, from the significant correlation between the isotope anomalies and area‐averaged Sarawak rainfall anomalies (R = ?0.65, p < 0.01), that ENSO‐related precipitation anomalies are linked to the seasonal modulation of the BSISO and MJO activity and BV genesis.  相似文献   

13.
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   

14.
In recent years, the Gravity Recovery and Climate Experiment (GRACE) has provided a new tool to study terrestrial water storage variations (TWS) at medium and large spatial scales, providing quantitative measures of TWS change. Linear trends in TWS variations in Turkey were estimated using GRACE observations for the period March 2003 to March 2009. GRACE showed a significant decrease in TWS in the southern part of the central Anatolian region up to a rate of 4 cm/year. The Global Land Data Assimilation System (GLDAS) model also captured this TWS decrease event but with underestimated trend values. The GLDAS model represents only a part of the total TWS variations, the sum of soil moisture (2 m column depth) and snow water equivalent, ignoring groundwater variations. Therefore, GLDAS model derived TWS variations were subtracted from GRACE derived TWS variations to estimate groundwater storage variations. Results revealed that decreasing trends of TWS observed by GRACE in the southern part of central Anatolia were largely explained by the decreasing trends of groundwater variations which were confirmed by the limited available well groundwater level data in the region.  相似文献   

15.
南印度洋海温偶极子型振荡及其气候影响   总被引：23，自引：2，他引：23       下载免费PDF全文
印度洋海表温度（Sea Surface Temperature，简称SST）的方差分析和相关分析表明南印度洋也存在一个海温偶极子型振荡，并定义了一个南印度洋海表温度异常偶极子指数.夏、秋季（南半球冬、春）的南印度洋偶极子指数与后期热带500hPa和100hPa高度场异常有显著而持续的相关，在冬、春达到最大，并可以持续到次年夏、秋.前期夏、秋季节的南印度洋偶极模对次年我国大陆东部夏季降水异常有显著的影响，对应偶极子正位相，次年夏季印度洋、南海（东亚）夏季风偏弱；副高加强且南撤、西伸，南亚高压偏强且位置偏东，易形成我国长江流域降水偏多，华南降水偏少；负位相年反之.后期冬季西太平洋暖池是联系南印度洋偶极子与次年我国夏季降水异常关系的一条重要途径.南印度洋偶极子表现出了明显的独立于ENSO（El Nio Southern Oscillation，简称ENSO）的特征.  相似文献   

16.
Freshwater resources in the arid Arabian Peninsula, especially transboundary aquifers shared by Saudi Arabia, Jordan, and Iraq, are of critical environmental and geopolitical significance. Monthly Gravity Recovery and Climate Experiment (GRACE) satellite‐derived gravity field solutions acquired over the expansive Saq transboundary aquifer system were analysed and spatiotemporally correlated with relevant land surface model outputs, remote sensing observations, and field data to quantify temporal variations in regional water resources and to identify the controlling factors affecting these resources. Our results show substantial GRACE‐derived terrestrial water storage (TWS) and groundwater storage (GWS) depletion rates of ?9.05 ± 0.25 mm/year (?4.84 ± 0.13 km3/year) and ?6.52 ± 0.29 mm/year (?3.49 ± 0.15 km3/year), respectively. The rapid decline is attributed to both climatic and anthropogenic factors; observed TWS depletion is partially related to a decline in regional rainfall, while GWS depletions are highly correlated with increasing groundwater extraction for irrigation and observed water level declines in regional supply wells.  相似文献   

17.
Empirical studies have shown that warm El Nino/Southern Oscillation (ENSO) episodes are associated during northern summer with, first, a southward location of the intertropical convergence zone (ITCZ) over the tropical Atlantic, and, second, a weakened convection over West Africa where the ITCZ is near its mean latitude. A modelling experiment presented here is used to help explain this apparent contradiction. In simulated ENSO conditions, the ITCZ is located southwards over the tropical Atlantic. Over West Africa the intertropical front is also displaced southwards, but more slightly; the ITCZ is located at its climatological latitude and the vertical development of convective clouds over West and Central Africa is reduced due to dynamical subsidence in the upper levels.  相似文献   

18.
The hydroclimatology of the Peruvian Amazon–Andes basin (PAB) which surface corresponding to 7% of the Amazon basin is still poorly documented. We propose here an extended and original analysis of the temporal evolution of monthly rainfall, mean temperature (Tmean), maximum temperature (Tmax) and minimum temperature (Tmin) time series over two PABs (Huallaga and Ucayali) over the last 40 years. This analysis is based on a new and more complete database that includes 77 weather stations over the 1965–2007 period, and we focus our attention on both annual and seasonal meteorological time series. A positive significant trend in mean temperature of 0.09 °C per decade is detected over the region with similar values in the Andes and rainforest when considering average data. However, a high percentage of stations with significant Tmean positive trends are located over the Andes region. Finally, changes in the mean values occurred earlier in Tmax (during the 1970s) than in Tmin (during the 1980s). In the PAB, there is neither trend nor mean change in rainfall during the 1965–2007 period. However, annual, summer and autumn rainfall in the southern Andes presents an important interannual variability that is associated with the sea surface temperature in the tropical Atlantic Ocean while there are limited relationships between rainfall and El Niño‐Southern Oscillation (ENSO) events. On the contrary, the interannual temperature variability is mainly related to ENSO events. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

19.
Pramanik  Saikat  Sil  Sourav  Mandal  Samiran  Dey  Dipanjan  Shee  Abhijit 《Ocean Dynamics》2019,69(11):1253-1271

Role of equatorial forcing on the thermocline variability in the Bay of Bengal (BoB) during positive and negative phases of the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO) was investigated using the Regional Ocean Modeling System (ROMS) simulations during 1988 to 2015. Two numerical experiments were carried out for (i) the Indian Ocean Model (IOM) with interannual open boundary conditions and (ii) the BoB Model (BoBM) with climatological boundary conditions. The first mode of Sea Surface Height Anomalies (SSHA) variability showed a west-east dipole nature in both IOM and altimetry observations around 11°N, which was absent in the BoBM. The vertical section of temperature along the same latitude showed a sharp subsurface temperature dipole with a core at ~ 100 m depth. The positive (negative) subsurface temperature anomalies were observed over the whole northeastern BoB during NIOD (PIOD) and LN (EN) composites due to stronger (weaker) second downwelling Kelvin Waves. During the negative phases of IOD and ENSO, the cyclonic eddy on the southwestern BoB strengthened due to intensified southward coastal current along the western BoB and local wind stress. The subsurface temperature dipole was at its peak during October–December (OND) with 1-month lag from IOD and was evident from the Argo observations and other reanalysis datasets as well. A new BoB dipole index (BDI) was defined as the normalized difference of 100-m temperature anomaly and found to be closely related to the frequency of cyclones and the surface chlorophyll-a concentration in the BoB.

  相似文献   

20.
Concerns about the potential effects of anthropogenic climate change have led to a closer examination of how climate varies in the long run, and how such variations may impact rainfall variations at daily to seasonal time scales. For South Florida in particular, the influences of the low-frequency climate phenomena, such as the El Nino Southern Oscillation (ENSO) and the Atlantic Multi-decadal Oscillation (AMO), have been identified with aggregate annual or seasonal rainfall variations. Since the combined effect of these variations is manifest as persistent multi-year variations in rainfall, the question of modeling these variations at the time and space scales relevant for use with the daily time step-driven hydrologic models in use by the South Florida Water Management District (SFWMD) has arisen. To address this problem, a general methodology for the hierarchical modeling of low- and high-frequency phenomenon at multiple rain gauge locations is developed and illustrated. The essential strategy is to use long-term proxies for regional climate to first develop stochastic scenarios for regional climate that include the low-frequency variations driving the regional rainfall process, and then to use these indicators to condition the concurrent simulation of daily rainfall at all rain gauges under consideration. A newly developed methodology, called Wavelet Autoregressive Modeling (WARM), is used in the first step after suitable climate proxies for regional rainfall are identified. These proxies typically have data available for a century to four centuries so that long-term quasi-periodic climate modes of interest can be identified more reliably. Correlation analyses with seasonal rainfall in the region are used to identify the specific proxies considered as candidates for subsequent conditioning of daily rainfall attributes using a Non-homogeneous hidden Markov model (NHMM). The combined strategy is illustrated for the May–June–July (MJJ) season. The details of the modeling methods and results for the MJJ season are presented in this study.  相似文献   

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