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1.
The interannual variability in the formation of mini warm pool (MWP, SST ≥ 30.5°C) and its impact on the formation of onset vortex (OV) over the east-central Arabian Sea (ECAS) are addressed by analyzing the NCEP OIV 2-weekly SST data and NCEP–NCAR reanalysis 850 hPa wind fields from May to June (prior to the onset of monsoon) over the north Indian Ocean for a period of 12 years from 1992 to 2003. Strong interannual variability in the formation and intensification of MWP was observed. Further, the 850 hPa wind fields showed that OV developed into an intense system only during 1994, 1998 and 2001. It formed in the region north of the MWP and on the northern flank of the low-level jet axis, which approached the southern tip of India just prior to the onset of monsoon, similar to the vortex of MONEX-79. The area-averaged zonal kinetic energy (ZKE) over the ECAS (8–15°N, 65–75°E) as well as over the western Arabian Sea (WAS, 5°S–20°N, 50–70°E) showed a minimum value of 5–15 m2 s?2 prior to monsoon onset over Kerala (MOK), whereas a maximum value of 280 m2 s?2 (40–70 m2 s?2) was observed over the ECAS (WAS) during and after MOK. The study further examined the plausible reasons for the occurrence of MWP and OV.  相似文献   

2.
本文探究了不同海表温度(SST)模态对6—8月和12月—次年2月全球陆地降水的趋势以及年代际变化的相对贡献。首先对热带地区陆地降水和SST进行SVD分析,得到影响陆地降水的趋势和年代际变化主要的海洋模态为:海洋中的全球变暖(Global Warming,GW)、大西洋多年代际振荡(Atlantic Multidecadal Oscillation,AMO)和太平洋多年代际振荡(Interdecadal Pacific Oscillation,IPO)。其次利用多元线性回归模型进一步定量评估了全球变暖、AMO和IPO对不同地区陆地降水的相对贡献大小。结果表明,全球变暖对陆地降水变化的贡献在冬夏季都是最大的,AMO在6—8月的贡献次之。IPO在12月—次年2月的贡献次之。不同纬度带,三者的贡献不同。GW的贡献在6—8月期间对10°N以北地区较大,南半球受GW的贡献相对较小,GW在12月—次年2月对40°N以北降水贡献异常显著;AMO主要在6—8月对10°~40°S和50°~60°S纬度带上的降水变化的贡献比较大;而IPO主要在12月—次年2月对北半球中纬度降水变化的贡献比较大。GW对许多地区降水变化的方差贡献都是最大的,例如6—8月期间,对北美洲东北部和亚洲降水变化贡献最大,12月—次年2月期间,对欧洲降水变化贡献最大。AMO对6—8月降水变化的方差贡献最大的区域为非洲萨赫勒、西伯利亚和南美洲。12月—次年2月期间,IPO对美国西南部的降水变化贡献最大,此外,北美洲东北部、南美洲西北部、非洲南部、澳大利亚东部、南亚季风区和我国北部的降水在12月—次年2月期间同样受IPO影响显著。进一步利用信息流的方法,探究了GW、AMO和IPO与陆地降水变化之间的因果关系,验证了上述结论。  相似文献   

3.
 This study examines time evolution and statistical relationships involving the two leading ocean-atmosphere coupled modes of variability in the tropical Atlantic and some climate anomalies over the tropical 120 °W–60 °W region using selected historical files (75-y near global SSTs and precipitation over land), more recent observed data (30-y SST and pseudo wind stress in the tropical Atlantic) and reanalyses from the US National Centers for Environmental Prediction (NCEP/NCAR) reanalysis System on the period 1968–1997: surface air temperature, sea level pressure, moist static energy content at 850 hPa, precipitable water and precipitation. The first coupled mode detected through singular value decomposition of the SST and pseudo wind-stress data over the tropical Atlantic (30 °N–20 °S) expresses a modulation in the thermal transequatorial gradient of SST anomalies conducted by one month leading wind-stress anomalies mainly in the tropical north Atlantic during northern winter and fall. It features a slight dipole structure in the meridional plane. Its time variability is dominated by a quasi-decadal signal well observed in the last 20–30 ys and, when projected over longer-term SST data, in the 1920s and 1930s but with shorter periods. The second coupled mode is more confined to the south-equatorial tropical Atlantic in the northern summer and explains considerably less wind-stress/SST cross-covariance. Its time series features an interannual variability dominated by shorter frequencies with increased variance in the 1960s and 1970s before 1977. Correlations between these modes and the ENSO-like Nino3 index lead to decreasing amplitude of thermal anomalies in the tropical Atlantic during warm episodes in the Pacific. This could explain the nonstationarity of meridional anomaly gradients on seasonal and interannual time scales. Overall the relationships between the oceanic component of the coupled modes and the climate anomaly patterns denote thermodynamical processes at the ocean/atmosphere interface that create anomaly gradients in the meridional plane in a way which tends to alter the north–south movement of the seasonal cycle. This appears to be consistent with the intrinsic non-dipole character of the tropical Atlantic surface variability at the interannual time step and over the recent period, but produces abnormal amplitude and/or delayed excursions of the intertropical convergence zone (ITCZ). Connections with continental rainfall are approached through three (NCEP/NCAR and observed) rainfall indexes over the Nordeste region in Brazil, and the Guinea and Sahel zones in West Africa. These indices appear to be significantly linked to the SST component of the coupled modes only when the two Atlantic modes+the ENSO-like Nino3 index are taken into account in the regressions. This suggests that thermal forcing of continental rainfall is particularly sensitive to the linear combinations of some basic SST patterns, in particular to those that create meridional thermal gradients. The first mode in the Atlantic is associated with transequatorial pressure, moist static energy and precipitable water anomaly patterns which can explain abnormal location of the ITCZ particularly in northern winter, and hence rainfall variations in Nordeste. The second mode is more associated with in-phase variations of the same variables near the southern edge of the ITCZ, particularly in the Gulf of Guinea during the northern spring and winter. It is primarily linked to the amplitude and annual phase of the ITCZ excursions and thus to rainfall variations in Guinea. Connections with Sahel rainfall are less clear due to the difficulty for the model to correctly capture interannual variability over that region but the second Atlantic mode and the ENSO-like Pacific variability are clearly involved in the Sahel climate interannual fluctuations: anomalous dry (wet) situations tend to occur when warmer (cooler) waters are present in the eastern Pacific and the gulf of Guinea in northern summer which contribute to create a northward (southward) transequatorial anomaly gradient in sea level pressure over West Africa. Received: 14 April 1998 / Accepted: 24 December 1998  相似文献   

4.
The sea surface temperature (SST) or sea level pressure (SLP) has usually been used to measure the strength of El Niño–Southern Oscillation (ENSO) events. In this study, two new indices, based on the upper-ocean heat content (HC), are proposed to quantify the two “flavours” of El Niño (i.e., the Cold Tongue El Niño (CTE) and Warm Pool El Niño (WPE)). Compared with traditional SST or SLP indices, the new HC-based indices can distinguish CTE and WPE events much better and also represent the two leading modes of the interannual variability of the atmosphere–ocean coupled system in the tropical Indo-Pacific region. The two leading modes are obtained by performing multivariate Empirical Orthogonal Function analysis on two oceanic variables (SST and HC) over the tropical Pacific (30°S–30°N, 120°E–80°W) and six atmospheric variables (outgoing longwave radiation, SLP, streamfunction, and velocity potential at 850?hPa and 200?hPa) over the tropical Indo-Pacific region (30°S–30°N, 60°E–80°W) for the period 1980–2010. Because the two new HC-based indices are capable of better depicting coherent variations between the ocean and atmosphere, they can provide a supplementary tool for ENSO monitoring of and climate research into the two flavours of El Niño.  相似文献   

5.
根据热带西太平洋(130°-160°E,10°-20°N)上空对流的年际变化,对表面温度、向外长波幅射、850 hPa纬向风进行了合成分析。合成分析结果表明,热带西太平洋上空的弱(强)对流对应着前冬和春季厄尔尼诺(拉尼娜)型的海温异常。与以前的研究结果进行了比较,说明上述海温异常的时空分布也与热带西太平洋和南海季风的爆发早晚相关联。合成分析结果还表明,热带西太平洋上空的弱(强)对流对应着从热带西太平洋向西伸展到盂加拉湾的东风(西风)异常。数值模拟也得到类似的结果。此外,在对流弱(强)的夏季,热带西太平洋上空的对流和南海低层纬向风均表现出弱(强)的季节演变特征。  相似文献   

6.
The present study examines the relationship between two types of El Niño–Southern Oscillation (ENSO), the central Pacific (CP) ENSO and the eastern Pacific (EP) ENSO, and the sea surface temperature (SST) variability over the South Pacific (SP) (20° S–60° S, 145° E–70° W) using NOAA OI SST for the period 1982–2006. The SP SST variability associated with the two types of ENSO varies with season. These two types of ENSO can excite different atmospheric patterns associated with the Pacific–South American mode, through which they influence the SP SST variability. Both the surface turbulent air–sea heat fluxes and the heat advection by Ekman currents (i.e., Ekman heat fluxes) have an important impact on the SST variability. An analysis of the surface mixed layer heat budget indicates that the heat fluxes (the sum of turbulent heat fluxes and Ekman heat fluxes) can effectively explain much of the SST variability related to the two types of ENSO.  相似文献   

7.
Mathew Roxy 《Climate Dynamics》2014,43(5-6):1159-1169
Over the tropical oceans, higher sea surface temperatures (SST, above 26 °C) in summer are generally accompanied by increased precipitation. However, it has been argued for the last three decades that, any monotonic increase in precipitation with respect to SST is limited to an upper threshold of 28–29.5 °C, and beyond this, the relationship fails. Based on this assessment it has often been presumed that, since the mean SSTs over the Asian monsoon basins (Indian Ocean and north-west Pacific) are mostly above the threshold, SST does not play an active role on the summer monsoon variability. It also implies that increasing SSTs due to a changing climate need not result in increasing monsoon precipitation. The current study shows that the response of precipitation to SST has a time lag, that too with a spatial variability over the monsoon basins. Taking this lag into account, the results here show that enhanced convection occurs even up to the SST maxima of 31 °C averaged over these basins, challenging any claim of an upper threshold for the SST-convection variability. The study provides us with a novel method to quantify the SST-precipitation relationship. The rate of increase is similar across the basins, with precipitation increasing at ~2 mm day?1 for an increase of 1 °C in SST. This means that even the high SSTs over the monsoon basins do play an active role on the monsoon variability, challenging previous assumptions. Since the response of precipitation to SST variability is visible in a few days, it would also imply that including realistic ocean–atmosphere coupling is crucial even for short term monsoon weather forecasts. Though recent studies suggest a weakening of the monsoon circulation over the last few decades, results here suggest an increased precipitation over the tropical monsoon regions, in a global warming environment with increased SSTs. Thus the signature of SST is found to be significant for the Asian summer monsoon, in a quantifiable manner, seamlessly through all the timescales—from short-term intraseasonal to long-term climate scales.  相似文献   

8.
In order to improve seasonal-to-interannual precipitation forecasts and their application by decision makers, there is a clear need to understand when, where, and to what extent seasonal precipitation anomalies are driven by potentially predictable surface–atmosphere interactions versus to chaotic interannual atmospheric dynamics. Using a simple Monte Carlo approach, interannual variability and linear trends in the SST-forced signal and potential predictability of boreal winter precipitation anomalies is examined in an ensemble of twentieth century AGCM simulations. Signal and potential predictability are shown to be non-stationary over more than 80% of the globe, while chaotic noise is shown to be stationary over most of the globe. Correlation analysis with respect to magnitudes of the four leading modes of global SST variability suggests that interannual variability and trends in signal and potential predictability over 35% of the globe is associated with ENSO-related SST variability; signal and potential predictability are not significantly associated with SST modes characterized by a global SST trend, North Atlantic SST variability, and North Pacific SST variability, respectively. Results suggest that mechanisms other than SST variability contribute to the non-stationarity of signal and noise characteristics of hydroclimatic variability over mid- and high-latitude regions.  相似文献   

9.
Coupled ocean atmosphere general circulation models (GCM) are typically coupled once every 24 h, excluding the diurnal cycle from the upper ocean. Previous studies attempting to examine the role of the diurnal cycle of the upper ocean and particularly of diurnal SST variability have used models unable to resolve the processes of interest. In part 1 of this study a high vertical resolution ocean GCM configuration with modified physics was developed that could resolve the diurnal cycle in the upper ocean. In this study it is coupled every 3 h to atmospheric GCM to examine the sensitivity of the mean climate simulation and aspects of its variability to the inclusion of diurnal ocean-atmosphere coupling. The inclusion of the diurnal cycle leads to a tropics wide increase in mean sea surface temperature (SST), with the strongest signal being across the equatorial Pacific where the warming increases from 0.2°C in the central and western Pacific to over 0.3°C in the eastern equatorial Pacific. Much of this warming is shown to be a direct consequence of the rectification of daily mean SST by the diurnal variability of SST. The warming of the equatorial Pacific leads to a redistribution of precipitation from the Inter tropical convergence zone (ITCZ) toward the equator. In the western Pacific there is an increase in precipitation between Papa new guinea and 170°E of up to 1.2 mm/day, improving the simulation compared to climatology. Pacific sub tropical cells are increased in strength by about 10%, in line with results of part 1 of this study, due to the modification of the exchange of momentum between the equatorially divergent Ekman currents and the geostropic convergence at depth, effectively increasing the dynamical response of the tropical Pacific to zonal wind stresses. During the spring relaxation of the Pacific trade winds, a large diurnal cycle of SST increases the seasonal warming of the equatorial Pacific. When the trade winds then re-intensify, the increase in the dynamical response of the ocean leads to a stronger equatorial upwelling. These two processes both lead to stronger seasonal basin scale feedbacks in the coupled system, increasing the strength of the seasonal cycle of the tropical Pacific sector by around 10%. This means that the diurnal cycle in the upper ocean plays a part in the coupled feedbacks between ocean and atmosphere that maintain the basic state and the timing of the seasonal cycle of SST and trade winds in the tropical Pacific. The Madden–Julian Oscillation (MJO) is examined by use of a large scale MJO index, lag correlations and composites of events. The inclusion of the diurnal cycle leads to a reduction in overall MJO activity. Precipitation composites show that the MJO is stronger and more coherent when the diurnal cycle of coupling is resolved, with the propagation and different phases being far more distinct both locally and to larger lead times across the tropical Indo-Pacific. Part one of this study showed that that diurnal variability of SST is modulated by the MJO and therefore increases the intraseasonal SST response to the different phases of the MJO. Precipitation-based composites of SST variability confirm this increase in the coupled simulations. It is argued that including this has increased the thermodynamical coupling of the ocean and atmosphere on the timescale of the MJO (20–100 days), accounting for the improvement in the MJO strength and coherency seen in composites of precipitation and SST. These results show that the diurnal cycle of ocean–atmosphere interaction has profound impact on a range of up-scale variability in the tropical climate and as such, it is an important feature of the modelled climate system which is currently either neglected or poorly resolved in state of the art coupled models.  相似文献   

10.
Long-term variability of sea surface temperature (SST) in the Taiwan Strait was studied from the U.K. Met Office Hadley Centre climatological data set HadISST1. In 1957–2011, three epochs were identified. The first epoch of cooling SST lasted through 1976. The regime shift of 1976–1977 led to an extremely rapid warming of 2.1 °C in 22 years. Another regime shift occurred in 1998–1999, resulting in a 1.0 °C cooling by 2011. The cross-frontal gradient between the China Coastal Current and offshore Taiwan Strait waters has abruptly decreased in 1992 and remained low through 2011. The long-term warming of SST increased towards the East China Sea, where the SST warming in 1957–2011 was about three times that in the South China Sea. The long-term warming was strongly enhanced in winter, with the maximum warming of 3.8 °C in February. The wintertime amplification of long-term warming has resulted in a decrease of the north–south SST range from 5 to 4 °C and a decrease in the amplitude of seasonal cycle of SST from 11 to 8 °C.  相似文献   

11.
The boreal summer intraseasonal oscillation (BSISO) of the Asian summer monsoon (ASM) is one of the most prominent sources of short-term climate variability in the global monsoon system. Compared with the related Madden-Julian Oscillation (MJO) it is more complex in nature, with prominent northward propagation and variability extending much further from the equator. In order to facilitate detection, monitoring and prediction of the BSISO we suggest two real-time indices: BSISO1 and BSISO2, based on multivariate empirical orthogonal function (MV-EOF) analysis of daily anomalies of outgoing longwave radiation (OLR) and zonal wind at 850 hPa (U850) in the region 10°S–40°N, 40°–160°E, for the extended boreal summer (May–October) season over the 30-year period 1981–2010. BSISO1 is defined by the first two principal components (PCs) of the MV-EOF analysis, which together represent the canonical northward propagating variability that often occurs in conjunction with the eastward MJO with quasi-oscillating periods of 30–60 days. BSISO2 is defined by the third and fourth PCs, which together mainly capture the northward/northwestward propagating variability with periods of 10–30 days during primarily the pre-monsoon and monsoon-onset season. The BSISO1 circulation cells are more Rossby wave like with a northwest to southeast slope, whereas the circulation associated with BSISO2 is more elongated and front-like with a southwest to northeast slope. BSISO2 is shown to modulate the timing of the onset of Indian and South China Sea monsoons. Together, the two BSISO indices are capable of describing a large fraction of the total intraseasonal variability in the ASM region, and better represent the northward and northwestward propagation than the real-time multivariate MJO (RMM) index of Wheeler and Hendon.  相似文献   

12.
Inter-annual variability in the onset of monsoon over Kerala (MOK), India, is investigated using daily temperature; mean sea level pressure; winds at 850, 500 and 200 hPa pressure levels; outgoing longwave radiation (OLR); sea surface temperature (SST) and vertically integrated moisture content anomaly with 32 years (1981–2013) observation. The MOK is classified as early, delayed, or normal by considering the mean monsoon onset date over Kerala to be the 1st of June with a standard deviation of 8 days. The objective of the study is to identify the synoptic setup during MOK and comparison with climatology to estimate the predictability of the onset type (early, normal, or delayed) with 5, 10, and 15 days lead time. The study reveals that an enhanced convection observed over the Bay of Bengal during early MOK is found to shift over the Arabian Sea during delayed MOK. An intense high-pressure zone observed over the western south Indian Ocean during early MOK shifts to the east during delayed MOK. Higher tropospheric temperature (TT) over the western Equatorial Ocean during early MOK and lower TT over the Indian subcontinent intensify the land–ocean thermal contrast that leads to early MOK. The sea surface temperature (SST) over the Arabian Sea is observed to be warmer during delayed than early MOK. During early MOK, the source of 850 hPa southwesterly wind shifts to the west equatorial zone while a COL region has been found during delayed MOK at that level. The study further reveals that the wind speed anomaly at the 200-hPa pressure level coincides inversely with the anomaly of tropospheric temperature.  相似文献   

13.
We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.  相似文献   

14.
This is the second of the two-part paper series on the analysis and evaluation of the Fifth phase of Coupled Model Intercomparison Project (CMIP5) simulation of contemporary climate as well as IPCC, AR5 Representative Concentrations Pathways (RCP), 4.5 and 8.5 scenarios projections of the Greater Horn of Africa (GHA) Climate. In the first part (Otieno and Anyah in Clim Dyn, 2012) we focused on the historical simulations, whereas this second part primarily focuses on future projections based on the two scenarios. Six Earth System Models (ESMs) from CMIP5 archive have been used to characterize projected changes in seasonal and annual mean precipitation, temperature and the hydrological cycle by the middle of twenty-first century over the GHA region, based on IPCC, 5th Assessment Report (AR5) RCP4.5 and RCP8.5 scenarios. Nearly all the models outputs analyzed reproduce the correct mean annual cycle of precipitation, with some biases among the models in capturing the correct peak of precipitation cycle, more so, March–April–May (MAM) seasonal rainfall over the equatorial GHA region. However, there is significant variation among models in projected precipitation anomalies, with some models projecting an average increase as others project a decrease in precipitation during different seasons. The ensemble mean of the ESMs indicates that the GHA region has been experiencing a steady increase in both precipitation and temperature beginning in the early 1980s and 1970s respectively in both RCP4.5 and RCP8.5 scenarios. Going by the ensemble means, temperatures are projected to steadily increase uniformly in all the seasons at a rate of 0.3/0.5 °C/decade under RCP4.5/8.5 scenarios over northern GHA region leading to an approximate temperature increase of 2/3 °C by the middle of the century. On the other hand, temperatures will likely increase at a rate of 0.3/0.4 °C/decade under RCP4.5/8.5 scenarios in both equatorial and southern GHA region leading to an approximate temperature increase of 2/2.5 °C by the middle of twenty-first century. Nonetheless, projected precipitation increase varied across seasons and sub-regions. With the exception of the equatorial region, that is projected to experience precipitation increase during DJF season, most sub-regions are projected to experience precipitation increase within their peak seasons, with the highest rate of increase experienced during DJF and OND seasons over southern and equatorial GHA regions respectively. Notably, as precipitation increases, the deficit (E < P) between evaporation (E) and precipitation (P) increased over the years, with a negatively skewed distribution. This generally implies that there is a high likelihood of an increased deficit in local moisture supply. This remarkable change in the general hydrological cycle (i.e. deficit in local moisture) is projected to be also coincident with intensified westerly anomaly influx from the Congo basin into the region. However, better understanding of the detailed changes in hydrological cycle will require comprehensive water budget analyses that require daily or sub-daily variables, and was not a specific focus of the present study.  相似文献   

15.
Scott Curtis 《Climate Dynamics》2012,38(11-12):2209-2225
Seasonal (three-month average) climate forecasts have advanced due in large part to improved modeling of the ENSO phenomenon. Long-range monthly forecasts are more problematic because of internal atmospheric variability. Further, it is often assumed that monthly precipitation anomalies are representative of the overall seasonal anomaly. This is not always the case as, according to the Global Precipitation Climatology Project Version 2.1 data set, up to 20% of areas demonstrating some significant teleconnection to ENSO show El Ni?o minus La Ni?a differences of one sign in the middle month and the opposite sign in the adjacent months. Most interestingly, this maximum percentage occurs in December–January–February (DJF), a time when the ENSO boundary forcing is strongest. These oscillatory DJF seasons also cluster in space—with significant positive–negative-positive differences in the western South Tropical Indian Ocean (STIO) and negative–positive–negative differences in the far eastern STIO. Representative gauges confirm that these precipitation patterns have been associated with ENSO events since 1951, and pentad precipitation data confirm that they are confined to DJF and evolve at the monthly scale. The abrupt end of the Indian Ocean Dipole mode in January, an increase in the importance of local SST anomalies in February, and an ENSO-induced mid-latitude Rossby wave during austral summer combine to generate the cross-basin precipitation gradient around 15°S.  相似文献   

16.
The relative impacts of Indian and Pacific Ocean processes on Tanzanian rainfall was evaluated using composite and correlation analyses. It was found that the seasonal responses of rainfall to positive Indian Ocean Dipole (pIOD) and El Niño events are substantial from September–October–November (SON) to December–January–February (DJF), whereas the Indian Ocean Dipole (IOD) exerts more control than El Niño–Southern Oscillation (ENSO) in both seasons. The associated relationship with the sea surface temperature (SST) and large-scale atmospheric circulations revealed distinct features. For the pure pIOD years, there is above-normal rainfall over the entire country. A strong rainfall condition is evident over the Lake Victoria basin and coastal and northeastern highland parts of the country during SON, while areas of the central and southern highlands exhibit substantial rains during DJF. For the pure El-Niño events, Tanzania has suffered from insignificant, weak, and non-coherent rainfall conditions during SON. However, a contrasting insignificant rainfall signature is found between the northern and southern parts of the country during the subsequent DJF season. For the co-occurrence of pIOD and El Niño, significant, excessive rainfall conditions are restricted to over the northern coast and northeastern areas of the country during SON, consistent with the rainfall pattern for pIOD. A weak, positive rainfall condition is observed over the entire country in the following season of DJF. Generally, in terms of Tanzanian rainfall, the IOD/ENSO variability and the associated impacts can be explained by the anomalous SST and circulation anomalies.  相似文献   

17.
The seasonal variation of lightning flash activity over the Indian subcontinent (0°N–35°N and 60°E–100°E) is studied using the quality checked monthly lightning flash data obtained from lightning imaging sensor on board the Tropical Rainfall Measuring Mission satellite. This paper presents results of spatio-temporal variability of lightning activity over the Indian subcontinent. The study of seasonal total lightning flashes indicates that the lightning flash density values are in qualitative agreement with the convective activity observed over this region. Maximum seasonal total flash counts are observed during the monsoon season. The propagation of the inter-tropical convergence zone over this region is also confirmed. Synoptic conditions responsible for variation of lightning activity are also investigated with the help of an observed dataset. The mean monthly flash counts show a peak in the month of May, which is the month of maximum temperatures over this region. Maximum flash density (40.2 km?2 season?1) is observed during the pre-monsoon season at 25.2°N/91.6°E and the annual maximum flash density of 28.2 km?2 year?1 is observed at 33.2°N/74.6°E. The study of the inter-annual variability of flash counts exhibits bimodal nature with the first maximum in April/May and second maximum in August/September.  相似文献   

18.
 The predictability of atmospheric responses to global sea surface temperature (SST) anomalies is evaluated using ensemble simulations of two general circulation models (GCMs): the GENESIS version 1.5 (GEN) and the ECMWF cycle 36 (ECM). The integrations incorporate observed SST variations but start from different initial land and atmospheric states. Five GEN 1980–1992 and six ECM 1980–1988 realizations are compared with observations to distinguish predictable SST forced climate signals from internal variability. To facilitate the study, correlation analysis and significance evaluation techniques are developed on the basis of time series permutations. It is found that the annual mean global area with realistic signals is variable dependent and ranges from 3 to 20% in GEN and 6 to 28% in ECM. More than 95% of these signal areas occur between 35 °S–35 °N. Due to the existence of model biases, robust responses, which are independent of initial condition, are identified over broader areas. Both GCMs demonstrate that the sensitivity to initial conditions decreases and the predictability of SST forced responses increases, in order, from 850 hPa zonal wind, outgoing longwave radiation, 200 hPa zonal wind, sea-level pressure to 500 hPa height. The predictable signals are concentrated in the tropical and subtropical Pacific Ocean and are identified with typical El Ni?o/ Southern Oscillation phenomena that occur in response to SST and diabatic heating anomalies over the equatorial central Pacific. ECM is less sensitive to initial conditions and better predicts SST forced climate changes. This results from (1) a more realistic basic climatology, especially of the upper-level wind circulation, that produces more realistic interactions between the mean flow, stationary waves and tropical forcing; (2) a more vigorous hydrologic cycle that amplifies the tropical forcing signals, which can exceed internal variability and be more efficiently transported from the forcing region. Differences between the models and observations are identified. For GEN during El Ni?o, the convection does not carry energy to a sufficiently high altitude, while the spread of the tropospheric warming along the equator is slower and the anomaly magnitude smaller than observed. This impacts model ability to simulate realistic responses over Eurasia and the Indian Ocean. Similar biases exist in the ECM responses. In addition, the relationships between upper and lower tropospheric wind responses to SST forcing are not well reproduced by either model. The identification of these model biases leads to the conclusion that improvements in convective heat and momentum transport parametrizations and basic climate simulations could substantially increase predictive skill. Received: 25 April 1996 / Accepted: 9 December 1996  相似文献   

19.
Sea surface temperatures (SSTs) in the eastern tropical Atlantic are crucial for climate variability within the tropical belt. Despite this importance, state-of-the-art climate models show a large SST warm bias in this region. Knowledge about the seasonal mixed layer (ML) heat budget is a prerequisite for understanding SST mean state and its variability. Within this study all contributions to the seasonal ML heat budget are estimated at four locations within the Atlantic cold tongue (ACT) that are representative for the western (0°N, 23°W), central (0°N, 10°W) and eastern (0°N, 0°E) equatorial as well as the southern (10°S, 10°W) ACT. To estimate the contribution of the diapycnal heat flux due to turbulence an extensive data set of microstructure observations collected during ten research cruises between 2005 and 2012 is analyzed. The results for the equatorial ACT indicate that with the inclusion of the diapycnal heat flux the seasonal ML heat budget is balanced. Within the equatorial region, the diapycnal heat flux is essential for the development of the ACT. It dominates over all other cooling terms in the central and eastern equatorial ACT, while it is of similar size as the zonal advection in the western equatorial ACT. In contrast, the SST evolution in the southern ACT region can be explained entirely by air-sea heat fluxes.  相似文献   

20.
Peninsular India and Sri Lanka receive major part of their annual rainfall during the northeast monsoon season (October–December). The long-term trend in the northeast monsoon rainfall over the Indian Ocean and peninsular India is examined in the vicinity of global warming scenario using the Global Precipitation Climatology Project (GPCP) dataset available for the period 1979–2010. The result shows a significant increasing trend in rainfall rate of about 0.5 mm day?1 decade?1 over a large region bounded by 10 °S–10 °N and 55 °E–100 °E. The interannual variability of seasonal rainfall rate over peninsular India using conventional rain gauge data is also investigated in conjunction to the Indian Ocean dipole. The homogeneous rain gauge data developed by Indian Institute of Tropical Meteorology over peninsular India also exhibit the considerable upward rainfall trend of about 0.4 mm day?1 decade?1 during this period. The associated outgoing longwave radiation shows coherent decrease in the order of 2 W?m?2 decade?1 over the rainfall increase region.  相似文献   

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