Characterizing and comparing control-run variability of eight coupled AOGCMs and of observations. Part 1: temperature

We examine the spatial patterns of variability of annual-mean temperature in the control runs of eight coupled atmosphere–ocean general circulation models (AOGCMs) and of observations. We characterize the patterns of variability using empirical orthogonal functions (EOFs) and using a new technique based on what we call quasi-EOFs. The quasi-EOFs are computed based on the spatial pattern of the correlation between the temperature variation at a given grid point and the temperature defined over a pre-determined reference region, with a different region used for each quasi-EOF. For the first four quasi-EOFs, the reference regions are: the entire globe, the Niño3 region, Western Europe, and Siberia. Since the latter three regions are the centers of strong anomalies associated with the El Niño, North Atlantic, and Siberian oscillations, respectively, the spatial pattern of the covariance with temperature in these regions gives the structure of the model or observed El Niño, North Atlantic, and Siberian components of variability. When EOF analysis is applied to the model control runs, the patterns produced generally have no similarity to the EOF patterns produced from observational data. This is due in some cases to large NAO-like variability appearing as part of EOF₁ along with ENSO-like variability, rather than as separate EOF modes. This is a disadvantage of EOF analysis. The fraction of the model time-space variation explained by these unrealistic modes of variability is generally greater than the fraction explained by the principal observed modes of variability. When qEOF analysis is applied to the model data, all three natural modes of variability are seen to a much greater extent. However, the fraction of global time-space variability that is accounted for by the model ENSO variability is, in our analysis, less than observed for all models except the HadCM2 model, but within 20% for another three models. The space-time variation accounted for by the other modes is comparable to or somewhat larger than that observed in all models. As another teleconnection indicator, we examined both Southern Oscillation Index (SOI) and its relation to tropical Pacific Ocean temperature variations (the qEOF₂ amplitude), and the North Atlantic Oscillation Index (NAOI) and its relation to North Atlantic region temperatures (the qEOF₃ amplitude). All models exhibit a relationship between these indices, and the qEOF amplitudes are comparable to those observed. Furthermore, the models show realistic spatial patterns in the correlation between local temperature variations and these indices.     

Long-Term Variability of the Wind Field over the Indian Ocean Based on ERA-Interim Reanalysis

A detailed study of long-term variability of winds using 30 years of data from the European Centre for Medium-range Weather Forecasts global reanalysis (ERA-Interim) over the Indian Ocean has been carried out by partitioning the Indian Ocean into six zones based on local wind extrema. The trend of mean annual wind speed averaged over each zone shows a significant increase in the equatorial region, the Southern Ocean, and the southern part of the trade winds. This indicates that the Southern Ocean winds and the southeast trade winds are becoming stronger. However, the trend for the Bay of Bengal is negative, which might be caused by a weakening of the monsoon winds and northeast trade winds. Maximum interannual variability occurs in the Arabian Sea due to monsoon activity; a minimum is observed in the subtropical region because of the divergence of winds. Wind speed variations in all zones are weakly correlated with the Dipole Mode Index (DMI). However, the equatorial Indian Ocean, the southern part of the trade winds, and subtropical zones show a relatively strong positive correlation with the Southern Oscillation Index (SOI), indicating that the SOI has a zonal influence on wind speed in the Indian Ocean. Monsoon winds have a decreasing trend in the northern Indian Ocean, indicating monsoon weakening, and an increasing trend in the equatorial region because of enhancement of the westerlies. The negative trend observed during the non-monsoon period could be a result of weakening of the northeast trade winds over the past few decades. The mean flux of kinetic energy of wind (FKEW) reaches a minimum of about 100?W?m^?2 in the equatorial region and a maximum of about 1500?W?m^?2 in the Southern Ocean. The seasonal variability of FKEW is large, about 1600?W?m^?2, along the coast of Somalia in the northern Indian Ocean. The maximum monthly variability of the FKEW field averaged over each zone occurs during boreal summer. During the onset and withdrawal of monsoon, FKEW is as low as 50?W?m^?2. The Southern Ocean has a large variation of about 1280?W?m^?2 because of strong westerlies throughout the year.     

Characterizing the annual-mean climatic effect of anthropogenic CO<Subscript>2</Subscript> and aerosol emissions in eight coupled atmosphere-ocean GCMs

This work examines the spatial patterns of the transient response of mean annual temperature and precipitation to CO₂ (or CO₂ plus aerosol or aerosol proxy) radiative forcing in eight coupled AOGCMs, generally for the period 1900–2099. Response patterns are characterized using empirical orthogonal functions (EOFs) and the quasi-EOFs of Harvey and Wigley (the first qEOF field, discussed here, is given by the correlation between local year-by-year temperature changes and the global mean temperature change). The first temperature EOF accounts for 80–95% of the space-time variation of the CO₂ run in all of the models, and is almost identical to qEOF₁ of the temperature response or to the temperature change pattern averaged over the last 30 years of the simulations. EOF₁ accounts for 80–95% of the space-time variation in the CO₂+aerosol runs in six of the eight models. The CO₂ response patterns of different models are highly correlated with one another (R ² generally >0.5), and are also highly correlated with the CO₂+aerosol response patterns (R ² 0.85 in all except one model). The difference between CO₂ and CO₂+aerosol runs can be represented by EOF₁ of the year-by-year differences, by qEOF₁ of the year-by-year differences, or by the difference in temperature averaged over the last 30 years of each run. In models where these representations are highly correlated with each other, they are also highly correlated with CO₂ EOF₁. In other cases, aerosol EOF₁ is modestly to highly correlated with control EOF₁ (i.e.: the year-by-year differences between CO₂ and CO₂+aerosol runs are dominated by internal variability), while aerosol qEOF₁ and the 30-year difference are highly correlated with each other. For all models, the decadal mean temperature change can be closely replicated by scaling the CO₂ EOF₁ pattern based on the global mean temperature changes (RMSE for the last decade is <6% of the RMS temperature change for CO₂ runs, <8% for CO₂+aerosol runs). The first EOF of the precipitation response to increasing CO₂ accounts for only 10–30% of the space-time variation, and is generally highly correlated (R ² up to 0.85) with control EOF₁. In all of the models, there is an increase in precipitation in the ITCZ and a decrease in bands at or near 30°S and 30°N. In many models there is an El Niño-like response, including a substantial decrease in precipitation over the Amazon. Global-mean precipitation increases in all models due to CO₂ forcing, but aerosols appear to have a disproportionally large effect in suppressing the increase compared to their effect in suppressing the warming. There is evidence in some models that the non-absorbing aerosols considered here reduce summer monsoon rainfall compared to the changes that would be expected based on the globally averaged effect of aerosols on precipitation. When regional precipitation changes over time are predicted by scaling a fixed precipitation-change pattern with the global mean temperature change, the global mean RMSE in the predicted change in decadal-mean precipitation is 25–35% of the global RMS precipitation changes by the end of the simulation.     

The potential to reconstruct broadscale climate indices associated with southeast Australian droughts from Athrotaxis species, Tasmania

Occurrence of drought and dry periods in southeastern Australia has been linked to broad scale climate phenomena including the Southern Oscillation, Interdecadal Pacific Oscillation (IPO), Indian Ocean Dipole (IOD), Southern Annular Mode (SAM) and persistence of blocking high pressure in the Tasman Sea. We examine relationships between Athrotaxis tree ring chronologies from southern Australia extending over much of the past millennia and these broad scale indices. We also examine relationships between the chronologies, temperature, precipitation and a standardised precipitation and evapotranspiration index. Timing of significant correlations with maximum temperature varies between species. The responses of the species with broadscale indices vary with location: northern Athrotaxis cupressoides (Pencil Pine) are more strongly related to the Interdecadal Pacific Oscillation (IPO) and Southern Oscillation Index (SOI) than southern sites. As an exception to this, a site in the far south had significant correlations with both the SOI and IPO, opposite in sign to those observed for the northern sites. Significant spectral power at frequencies consistent with the SOI and IPO occur in all chronologies. Western and southern sites are more strongly related to a seasonalised index of SAM. These three systems have played important roles in determining moisture conditions in southeastern Australia over the past millennium. Results suggest that reconstructions of the SOI, IPO or SAM are unlikely based solely on this Athrotaxis network. The Athrotaxis network of tree ring sites, is however, likely to be an important input to multi-proxy models reconstructing the SOI, IPO or SAM in the Australian sector. The Athrotaxis network of sites is also an important extension of the existing network of Australian tree ring sites that could be used to reconstruct historical drought in southeastern Australia.     

SOI and QBO signals in the African region

Summary Climatic determinants of summer (Nov-Mar) rainfall over southern Africa are investigated through analysis of sea surface temperatures (SST), outgoing longwage radiation (OLR) and tropospheric wind with respect to the Southern Oscillation Index (SOI) and the stratospheric quasi-biennial oscillation (QBO). Index-to-field correlation maps are presented at various lags for the austral spring and summer seasons to establish the spatial dependence and evolution of coherent, statistically significant features. The SOI signal is reflected in upper-level zonal wind anomalies over the equatorial Atlantic Ocean during spring. SSTs in the central Indian Ocean are significantly negatively correlated with the SOI in summer. On the other hand, OLR correlations are weak over southern Africa in the summer, implying that the SOI signal may not dominate interannual convective variability.QBO correlations with SST are relatively weak, but with 200 hPa zonal winds over the western equatorial Ocean, positive correlations are noted. A standing wave pattern is described in the sub-tropics. The OLR correlation pattern represents a dipole with increased convection over eastern and southern Africa in contrast to reduced convection over Madagascar when the QBO is in west phase.Contingency analyses indicate that the global indices are unreliable predictors in isolation. However the characteristics and domain of influence of SOI and QBO signals are identified and may offer useful inputs to objective multivariate models for different modes of southern African rainfall variability.With 12 Figures     

Simulation of the 2001–02 Anomalous Intrusion in the Northeast Pacific

Abstract

A numerical model, the Parallel Ocean Program (POP) was used to run a 46-year simulation of the North Pacific Ocean beginning in January 1960. The model had a horizontal resolution of 0.25°, 28 vertical levels, and employed spectral nudging that, unlike standard nudging, nudges only specific frequency and wavenumber bands. This simulation was nudged to the mean and monthly Levitus climatology of potential temperature and absolute salinity (S_A). The model was forced with the mean monthly winds, sea level pressure, net heat flux, and precipitation from the National Centers for Environmental Prediction (NCEP).

The simulation was used to examine the anomalous intrusions, previously observed from 2001 to 2002, of cooler and fresher (less spicy) water flowing southward along the coast of western North America. The simulated anomaly began in 1999 in the North Pacific, progressed southeastward towards the coast and then southward, at least as far south as southern California. The southward velocity signal, modulated by a strong annual cycle, reached Point Conception in 2000 while the temperature and S_A anomalies arrived later, in 2002–03. The simulated velocity anomalies were eastward at about 3?cm s^?1 in the northeast Pacific near 47°N in agreement with observations. Simulated coastal southward flow speeds reached 10–20?cm s^?1 during the summer from 2000 to 2002.

This intrusion was by far the largest to occur over the entire length of the simulation. It was also the only time during the simulation when the Victoria mode was positive (associated with enhanced flow to the east via the North Pacific Gyre Oscillation (NPGO)) and the Multivariate El Niño-Southern Oscillation (ENSO) Index (MEI) was negative (La Niña conditions), tending to cause a southward flow anomaly along the coast.     

Sensitivity of a GCM Simulation of two Contrasting Indian Monsoons to SST Anomaly Distributions

Summary  One of the major forcings for the interannual variability of the Asian Summer Monsoon is the Sea Surface Temperature (SST) distribution in the tropical Pacific Ocean. El Ni?o years are characterized by a negative Southern Oscillation Index (SOI) and decreased monsoon rainfall over India leading to drought conditions. On the other hand, La Nina years are characterized by a positive SOI and generally good monsoon conditions over India. The monsoon ENSO relation is not a consistent one. The monsoons of 1991 and 1994 are good examples. The spring SOI was the same (−1.3) during both years. However, the All India Summer Monsoon Rainfall (AISMR) was 91.4% of normal in 1991 and 110% in 1994. Though the SOI was same during the spring of both years, the spatial distribution of SSTs was different. In the present study, the impacts of different SST distributions in the tropical Pacific Ocean, on the monsoons of 1991 and 1994 have been examined, to assess the UKMO-unified model’s sensitivity of SST. It is observed that the simulated monsoon was much stronger in 1994 than in 1991, in terms of precipitation and circulation. The wind and the Outgoing Long-wave Radiation (OLR) simulated by the model are compared with NCEP/NCAR reanalyses data, while precipitation is compared with Xie-Arkin merged rainfall data. Received November 26, 1998     

Evidences linking ENSO and coral growth in the Southwestern-South Atlantic

Physical and biological changes in the marine environment, induced by oceanic-atmospheric processes, can be imprinted in massive coral skeletons. Herein, we present an evidence of potential El Niño impacts at the Southwestern South Atlantic Ocean (SWSA) inferred from the sclerochronology of the reef coral Favia leptophylla. The application of spectral analysis (wavelet decomposition and the iterative regression) to coral growth length and to meteorological-oceanographic parameters (air temperature, sea surface temperature and precipitation) as well as to Southern Oscillation Index (SOI) and solar irradiation indicated a major significant inverse relationship between SOI and coral growth length at the 4–8 years frequency band. We propose here that coral growth length from the SWSA could be affected by El Niño Southern Oscillation (ENSO) events through an “atmospheric bridge”, in contrast to its direct effect at the Pacific Ocean, related to the increase in sea surface temperature.     

Interannual Antarctic tropospheric circulation and precipitation variability

Main modes of variability of the Antarctic tropospheric circulation (500 hPa geopotential height) and precipitation are identified through their empirical orthogonal functions (EOF). This is done by combining various sources of information, including meteorological analyses and forecasts (NCEP and ECMWF), atmospheric general circulation model (LMDZ) simulations, and satellite data (GPCP). Unlike previous similar work on circulation variability, the mode analyses are restricted to the Antarctic region. The main modes that relate the Antarctic region to the mid and tropical latitudes, e.g. in association with ENSO, are nonetheless clearly identified and thus robust. The contribution of the sea-surface or of the circumpolar Antarctic atmospheric dynamics to the occurrence and to the chronology of these modes is evaluated through various atmospheric model simulations. EOF analyses results are somewhat less stable, across the various datasets, and more noisy for precipitation than for circulation. Yet, through moisture advection considerations, the two most significant precipitation modes can be well related to the three main modes of circulation variability. The signatures of both the Southern Oscillation Index (SOI) and the Antarctic Oscillation Index (AOI) are found in one same precipitation mode, suggesting that they have a substantially common spatial structure. In addition, the relative strength of the signature of the AOI and SOI appears to change in time. In particular, the signature of the SOI was weak in the 1980s precipitations, but turned very strong in the 1990s. Common spatial patterns and variable strength in time may explain why hints of an ENSO signature in Antarctic precipitation have been reported but not unequivocally demonstrated so far.     

Temperature and precipitation fluctuations in the Czech Republic during the period of instrumental measurements

The history of early meteorological observations using instruments in the Czech Lands is described (the longest temperature series for Prague-Klementinum starts in 1775, precipitation series for Brno in 1803). Using the PRODIGE method, long-term monthly temperature and precipitation series from selected secular stations were homogenised (for 10 and 12 stations, respectively). All the seasonal and annual temperature series for the common period 1882–2010 show a significant positive linear trend with accelerated warming from the 1970s onwards. No significant linear trends were disclosed in the series of seasonal and annual precipitation totals. Correlation coefficients between the Czech series analysed decrease as distances between measuring stations increase. A sharper decrease of correlations for precipitation totals displays much weaker spatial relationships than those for mean temperatures. The highest correlations between all stations appeared in 1921–1950, the lowest in 1891–1920 (temperature) and 1981–2010 (precipitation). Wavelet analysis reveals that very distinct annual cycles as well as the slightly weaker semi-annual ones are better expressed for temperature series than for precipitation. Statistically significant cycles longer than 1?year are temporally unstable and sporadic for precipitation, while in the temperature series cycles of 7.4–7.7 and 17.9–18.4?years were recorded as significant by all stations in 1882–2010 (quasi-biennial cycle of 2.1–2.2?years for half the stations). Czech homogenous temperature series correlate best with those of the Northern Hemisphere for annual, spring and summer values (with significant correlation coefficients between 0.60 and 0.70), but this relation is temporally unstable. Circulation indices, such as the North Atlantic Oscillation Index (NAOI) and the Central European Zonal Index (CEZI), may explain the greater part of Czech temperature variability, especially from December to March and for the winter; however, this relationship is much weaker, or even random, for precipitation series. Further, relationships with the Southern Oscillation Index (SOI) are weak and random. Relatively weak coincidences exist between statistically significant cycles in the Czech series and those detected in NAOI, CEZI and SOI series.     

The Enso-Fire Dynamic in Insular Southeast Asia

We examined the spatiotemporal patterns of fire in insular Southeast Asia from July 1996 to December 2001 using a set of consistent, nighttime fire observations provided by the Along Track Scanning Radiometer (ATSR) sensor. Monthly ATSR fire counts were analyzed relative to georeferenced climatic and land-cover data from a variety of sources. We found that fires were strongly correlated with Southern Oscillation Index (SOI) (r = ?0.75) and Niño 3.4 index (r = 0.72) in forested land-cover types within the equatorial belt (5.5^°S–5.5^°N). Cross-correlation analysis revealed that detrended SOI was modestly correlated (r = 0.42) with detrended monthly fire count with a positive lag of four months. However, our analysis also revealed that fire counts reached their maximum 6 months before the absolute maximum of SOI. Annual sums of SOI (∑_SOI) and fire counts revealed linearity for ∑_SOI≤ 0. Overall, the results suggest that ENSO indices may have limited predictive utility at a monthly time scale, but that temporal aggregation and additional fire observations may enhance our capacity to forecast fires in different cover types based on ENSO data.     

Large-scale variability modes of freshwater flux and precipitation over the Atlantic

 Precipitation (P) and freshwater (E-P) fluxes at the air-sea interface are investigated in the Atlantic Ocean sector using the reanalyses of the European Centre for Medium Range Weather Forecasts (ERA) and of the National Centers for Environmental Prediction (NCEP). A canonical correlation analysis method between these fields and sea level pressure (SLP) is used to identify patterns. We also test whether precipitation and freshwater fluxes can be reconstructed from SLP data. In the winter months, patterns associated with both the North Atlantic Oscillation (NAO) and the East Atlantic (EA) mode are identified. The signals are strong enough to be reconstructed from the reanalysis fields, and they correspond to a significant part of the variability. The NAO signal is more robust than the EA one. The NAO-related variability mode is also present when the monthly precipitation rate is averaged for the winter season and even for annual averages. However, in the later case, other variability of natural origin (for instance, ENSO variability) or noise from the model and assimilation system prevents the reconstruction of E-P associated with NAO from SLP variability. Difficulties are identified in the tropical Atlantic with a different behaviour of NCEP and ERA precipitation variability, especially near the Inter Tropical Convergence Zone (ITCZ). The ERA patterns suggest a NAO signature in the tropical Atlantic which has clear monthly patterns and indicates a link between the phase of NAO and changes in the position and intensity of ITCZ. However, the analysis of winter rainfall based on satellite and in situ data does not support the monthly tropical pattern of ERA precipitation although it suggests a relation between convection near 15°S and NAO during northern winter. Received: 10 February 2000 / Accepted: 7 May 2001     

Interannual variation of atmospheric CO2 concentration

A method is described for the analysis of the interannual variability of background atmospheric carbon dioxide concentration. The analysis is carried out on the data from 6 observatories for which records of >8 years were available.A global-scale interannual variation of CO₂ concentration in the troposphere with a characteristic time-scale of 2–3 years has been confirmed throughout the period of the records. These variations are estimated to be associated with carbon cycle imbalances of 2–3 Gt or annual net exchanges between the atmosphere and another carbon reservoir(s) at a rate of about 1.2 Gt of carbon per year. Lag correlations and amplitude comparisons between the records suggests a low latitude southern hemisphere origin to this phenomenon.The interannual variations of CO₂ increase are found to be correlated with those observed in data for Pacific sea surface temperatures and Pacific witd stress, the Southern Oscillation Index and the Quasi-Biennial Oscillation. However multiple regression studies found that once the Southern Oscillation index is used as an explanatory variable for CO₂ variations, the inclusion of additional geophysical variables does not give any significant improvement in the regression.     

Skill and reproducibility of seasonal rainfall patterns in the tropics in ECHAM-4 GCM simulations with prescribed SST

 The ECHAM4 atmospheric general circulation model (GCM) has been integrated at T30 resolution through the period 1960–1994 forced with the observed sea-surface temperatures (SSTs) as compiled at the Hadley Centre (GISST2.2). Three experiments were made starting from different initial conditions. The large-scale tropical precipitation patterns simulated by the model have been studied, focusing on the skill (i.e. the capability to simulate the observed anomaly over land areas) and reproducibility (i.e. the GCM’s interannual rainfall variance that is independent from the initial conditions). Analysis of variance is used to estimate the reproducibility amongst ensemble members at each grid-box, but most emphasis is placed on large-scale patterns, as revealed by various singular value decomposition analyses (SVDAs), between observed and model fields (OM analyses) and amongst the different model runs (MM analyses). Generally, it is found that the first model mode in the MM analysis is very similar to that in the OM analysis, suggesting the model mode with strongest reproducibility is also the mode which tallies best with observations. For the global tropics, the first MM mode is highly reproducible (external variance above 90%) and the first OM couplet is very skillful (correlation between observed and model SVDA time series is over 0.84). The extent to which skill and reproducibility is related to El Nino/Southern Oscillation (ENSO) has been investigated by comparing the OM and MM time series with the Southern Oscillation Index (SOI). For the global tropics, most of the OM and MM variance is common with the SOI, though in boreal summer, the first modes do also have some clear independence from the SOI. The analyses were repeated at the regional scale for Oceania, tropical America, tropical Africa and tropical Southeast Asia. A highly reproducible mode is found in all cases except October-December in Africa. Skill, while always positive, is more variable, strongest for Oceania and tropical America and weakest for Africa. Comparisons with the SOI suggest skill in tropical America and tropical Africa has substantial components that are independent of the SOI, especially in boreal spring and summer when the tropical Atlantic SSTs are strongly related to the leading OM and MM time series. Received: 1 January 1997 / Accepted: 28 July 1997     

Modification of the southern African rainfall variability/ENSO relationship since the late 1960s

Analysis of 149 raingauge series (1946–1988) shows a weak positive correlation between late summer rainfalls (January–March) in tropical southern Africa and the Southern Oscillation Index (SOI). The correlation coefficients have been unstable since World War II. They were close to zero before 1970 and significant thereafter. Before 1970, southern African late summer rainfalls were more specifically correlated with regional patterns of sea surface temperature (SST), mainly over the southwestern Indian Ocean. After 1970, teleconnections with near global SST anomaly patterns, i.e. over the central Pacific and Indian oceans, dominate the regional connections. The increase in the sensitivity of the southern African rainfall to the global SO-related circulation anomalies is simultaneous with the correlation between SOI and more extensive SST anomalies, particularly over the southern Indian Ocean. This feature is part of longer term (decadal), global SST variability, as inferred from statistical analyses. Numerical experiments, using the Météo-France general circulation model ARPEGE-Climat, are performed to test the impact of the observed SST warming in the southern Indian and extratropical oceans during El Niño Southern Oscillation (ENSO) events on southern African rainfall. Simulated results show that ENSO events, which occurred in the relatively cold background of the pre-1970 period in the southern oceans, had a little effect on southern Africa climatic conditions and atmospheric circulation. By contrast, more recent ENSO events, with warmer SST over the southern oceans, lead to a climatic bipolar pattern between continental southern African and the western Indian Ocean, which is characterized by reduced (enhanced) deep convection and rainfall over the subcontinent (the western Indian Ocean). A weaker subtropical high-pressure belt in the southwestern Indian Ocean is also simulated, along with a reduced penetration of the moist southern Indian Ocean trade winds over the southern African plateau. These results are consistent with the strong droughts observed over all southern Africa during ENSO events since 1970.     

空间分辨率对中国夏季降水时空演变特征的影响

本文使用1979—2021年国家气候中心160站(R₁₆₀)和国家级地面气象观测站2 314站(R₂₃₁₄)逐月降水观测资料,利用EOF (Empirical Orthogonal Function)分解和相关分析等方法,研究两类资料夏季降水时空变化特征及其与海气因素之间物理联系的表征水平差异,并分析了差异的可能原因。结果表明,R₁₆₀在我国西北、青藏高原等地区站点极为稀疏,导致其各EOF模态对上述地区降水的时空变化特征描述失真,中东部地区偏低的空间分辨率会使局地强降水的变化特征信号损失,造成降水的年际变率降低。而R₂₃₁₄主模态能够更为真实地反映我国降水的时空演变特征,特别是在极端降水频发的江淮地区以及降水受局地地形影响较大的山区,其EOF主模态的空间分布和时间系数演变与ENSO (El Niño-Southern Oscillation)、西太平洋副热带高压、青藏高原雪盖等气候强迫信号之间的相关性更为显著。     

Interdecadal changes in the relationship between Southern China winter-spring precipitation and ENSO

Winter-spring precipitation in southern China tends to be higher (lower) than normal in El Niño (La Niña) years during 1953–1973. The relationship between the southern China winter-spring precipitation and El Niño-Southern Oscillation (ENSO) is weakened during 1974–1994. During 1953–1973, above-normal southern China rainfall corresponds to warmer sea surface temperature (SST) in the equatorial central Pacific. There are two anomalous vertical circulations with ascent over the equatorial central Pacific and ascent over southern China and a common branch of descent over the western North Pacific that is accompanied by an anomalous lower-level anticyclone. During 1974–1994, above-normal southern China rainfall corresponds to warmer SST in eastern South Indian Ocean and cooler SST in western South Indian Ocean. Two anomalous vertical circulations act to link southern China rainfall and eastern South Indian Ocean SST anomalies, with ascent over eastern South Indian Ocean and southern China and a common branch of descent over the western North Pacific. Present analysis shows that South Indian Ocean SST anomalies can contribute to southern China winter-spring precipitation variability independently. The observed change in the relationship between southern China winter-spring rainfall and ENSO is likely related to the increased SST variability in eastern South Indian Ocean and the modulation of the Pacific decadal oscillation.     

Plant Phenological Anomalies in Germany and their Relation to Air Temperature and NAO

This paper analyses long-term (1951–2000) phenological observations of20 plant seasonal phases recorded within the phenological network of the German Weather Service in relation to climate data and NAO. Phenological inter-annual variability and temporal trends were determined by using mean anomaly curves for Germany. For all phases, the mean trends derived by this method are similar to German averages of linear trends of single station records. Trend analysis using anomaly curves appears to be effective in relating seasonal phenological trends to climate or satellite data: Spring and summer phenological anomalies, such as leaf unfolding and flowering of different species, strongly correlate with temperature of the preceding months (R² between 0.65 and 0.85, best one-variable model) andtheir onsets have advanced by 2.5 to 6.7 days per ° C warmer spring. Fruit ripening of Sambucus nigra and Aesculus hippocastanum, keyphenophases of early and mid autumn, correlate well with summer temperature (R² 0.74 and 0.84) and also advance by 6.5and 3.8 days per ° C (April–June). But the response of autumn colouringto warmer climate is more complex because two opposing factors influence autumn colouring dates. Higher spring and early summer temperatures advance leaf colouring, whereas warmer autumn temperatures delay leaf colouring. The percentage of variance explained by temperature (R² 0.22 to 0.51,best one-variable model) is less than for spring and summer phases. The length of the growing season is mainly increased by warmer springs (R² 0.48to 0.64, best one-variable model) and lengthened by 2.4 to 3.5 days/° C (February–April). The North Atlantic Oscillation Index (NAO) of January–March correlates with spring phenological anomalies(R² 0.37 to 0.56, best one-variable model), summer to mid autumn phases respond to NAO of February–March (R² 0.23 to 0.36) (both negativecorrelations). Leaf colouring is delayed by higher NAO of (August) September (R² 0.10to 0.18). NAO of January–February explains 0.41 to 0.44% of thevariance of the length of the growing season.     

The influence of geopotential heights on New South Wales rainfall

Summary An investigation of the relationships between New South Wales (NSW) seasonal rainfalls and fluctuations of geopotential height at four Australian radiosonde stations is presented. The connection between the Southern Oscillation Index (SOI) and the geopotential height was explored up to the mid-troposphere. The study determined that the 800 and 600 hPa heights at Woomera show stronger and more consistent correlations with winter and spring rainfalls respectively, than occur between SOI and rainfall. The 900 hPa height at Brisbane is also strongly correlated with autumn rainfall for much of coastal NSW. These correlations are found to be stable during high and low phases of the SO cycle. It was found that the effects of the considered geopotential data on rainfall are independent of the influence of the SO phenomenon. The study also found that the fluctuations of geopotential heights at Woomera are related to rainfall variability over a wide region of southern Australia. At Darwin the 800 hPa surface appears to be the highest altitude at which there is any influence from the Southern Oscillation during winter. Furthermore, airmass movement over inland NSW is quite strongly related to SOI but coastal airmass movement is only weakly related to SOI. A mechanism for the influence of the Southern Oscillation on NSW rainfall is suggested.With 9 Figures     

The impact of global warming on the Southern Oscillation Index

The Southern Oscillation Index (SOI)??a measure of air pressure difference across the Pacific Ocean, from Tahiti in the south-east to Darwin in the west??is one of the world??s most important climatic indices. The SOI is used to track and predict changes in both the El Ni?o-Southern Oscillation phenomenon, and the Walker Circulation (WC). During El Ni?o, for example, the WC weakens and the SOI tends to be negative. Climatic variations linked to changes in the WC have a profound influence on climate, ecosystems, agriculture, and societies in many parts of the world. Previous research has shown that (1) the WC and the SOI weakened in recent decades and that (2) the WC in climate models tends to weaken in response to elevated atmospheric greenhouse gas concentrations. Here we examine changes in the SOI and air pressure across the Pacific in the observations and in numerous WCRP/CMIP3 climate model integrations for both the 20th and 21st centuries. The difference in mean-sea level air pressure (MSLP) between the eastern and western equatorial Pacific tends to weaken during the 21st century, consistent with previous research. Here we show that this primarily arises because of an increase in MSLP in the west Pacific and not a decline in the east. We also show, in stark contrast to expectations, that the SOI actually tends to increase during the 21st century, not decrease. Under global warming MSLP tends to increase at both Darwin and Tahiti, but tends to rise more at Tahiti than at Darwin. Tahiti lies in an extensive region where MSLP tends to rise in response to global warming. So while the SOI is an excellent indicator of interannual variability in both the equatorial MSLP gradient and the WC, it is a highly misleading indicator of long-term equatorial changes linked to global warming. Our results also indicate that the observed decline in the SOI in recent decades has been driven by natural, internally generated variability. The externally forced signal in the June?CDecember SOI during 2010 is estimated to be approximately 5% of the standard deviation of variability in the SOI during the 20th century. This figure is projected to increase to 40% by the end of the 21st century under the A2 SRES scenario. The 2010 global warming signal is already a major contributor to interdecadal variability in the SOI, equal to 45% of the standard deviation of 30-year running averages of the SOI. This figure is projected to increase to nearly 340% by the end of the 21st century. Implications that these discoveries have for understanding recent climatic change and for seasonal prediction are discussed.