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1.
The present study investigates the influence of South China Sea (SCS) SST
and ENSO on winter (January--February--March; JFM) rainfall over South China
and its dynamic processes by using station observations for the period
1951--2003, Met Office Hadley Center SST data for the period 1900--2008, and
ERA-40 reanalysis data for the period 1958--2002. It is found that JFM
rainfall over South China has a significant correlation with Nino-3 and
SCS SST. Analyses show that in El Nino or positive SCS SST anomaly
years, southwesterly anomalies at 700 hPa dominate over the South China Sea,
which in turn transports more moisture into South China and favors increased
rainfall. A partial regression analysis indicates that the independent ENSO
influence on winter rainfall occurs mainly over South China,
whereas SCS SST has a larger independent influence on winter rainfall in
northern part of South China. The temperature over South China shows an obvious decrease at
300 hPa and an increase near the surface, with the former induced by
Nino-3 and the latter SCS SST anomalies. This enhances the convective
instability and weakens the potential vorticity (PV), which explains the
strengthening of ascending motion and the increase of JFM rainfall over
South China. 相似文献
2.
Prediction of summer monsoon rainfall over India using the NCEP climate forecast system 总被引:1,自引:0,他引:1
The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the
Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction’s
(NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with
a 15 ensemble members for 25 years period from 1981 to 2005. The CFS’s hindcast climatology during JJAS of March (lag-3),
April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification
climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well
simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon
region (IMR) bounded by 50°E–110°E and 10°S–35°N shows significant correlation coefficient (CCs). The skill of simulation
of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC
between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event
is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole
is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial
Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between
forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order
of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric
forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon Rainfall (AISMR;
only the land stations of India during JJAS), the predicted mean AISMR with March, April and May initial conditions is found
to be well correlated with actual AISMR and is found to provide skillful prediction. Thus, the calibrated CFS forecast could
be used as a better tool for the real time prediction of AISMR. 相似文献
3.
基于海气耦合环流模式的ENSO预测 总被引:5,自引:0,他引:5
Predictions of ENSO are described by using a coupled atmosphere-ocean general circulation model. The initial conditions are created by forcing the coupled system using SST anomalies in the tropical Pacific at the background of the coupled model climatology. A series of 24-month hindcasts for the period from November 1981 to December 1997 are carried out to validate the performance of the coupled system. Correlations of SST anomalies in the Nino3 region exceed 0.54 up to 15 months in advance and the rms errors are less than 0.9℃. The system is more skillful in predicting SST anomalies in the 1980s and less in the 1990s. The model skills are also seasonal-dependent, which are lower for the predictions starting from late autumn to winter and higher for those from spring to autumn in a year-time forecast length. The prediction, beginning from March, persists 8 months long with the correlation skill exceeding 0.6, which is important in predictions of summer rainfall in China. The predictions are succesful in many aspects for the 1997-2000 ENSO events. 相似文献
4.
Summary ?One hundred and thirty six years (1856–1991) of monthly sea-surface temperature (SST) data in the Tropical Atlantic Ocean
are used to investigate the propagating signals of the SST at a decadal (DD) time scale. The first and the third evolving
modes show a relationship between the equatorial and the inter-hemispheric patterns, one evolving into the other mode and
vice-versa. These modes describe two different evolutions of the SST at DD time-scale. The first EEOF features a 12-year period
oscillatory regime with a strong 2-year duration inter-hemispheric pattern evolving into a weak 1-year duration equatorial
pattern and vice-versa. This mode exhibits also a northward displacement of the anomalies in the band 15° S–15° N. The third
EEOF also shows an oscillatory regime, but with a period of 10 years and with a relatively strong 2-year duration equatorial
pattern evolving into a weak 1-year duration inter-hemispheric pattern and vice-versa. For this mode, the SST anomalies show
a southward displacement in the band 15° S–15° N. These results have not yet been documented in previous works and explain
some of the previous findings on the DD variability in the Tropical Atlantic.
Received December 31, 2001; revised April 9, 2002; accepted September 4, 2002
Published online: March 20, 2003 相似文献
5.
Ramiro I. Saurral Javier Garca-Serrano Francisco J. Doblas-Reyes Leandro B. Daz Carolina S. Vera 《Climate Dynamics》2020,54(9):3945-3958
The South Pacific Ocean is a key driver of climate variability within the Southern Hemisphere at different time scales. Previous studies have characterized the main mode of interannual sea surface temperature (SST) variability in that region as a dipolar pattern of SST anomalies that cover subtropical and extratropical latitudes (the South Pacific Ocean Dipole, or SPOD), which is related to precipitation and temperature anomalies over several regions throughout the Southern Hemisphere. Using that relationship and the reported low predictive skill of precipitation anomalies over the Southern Hemisphere, this work explores the predictability and prediction skill of the SPOD in near-term climate hindcasts using a set of state-of-the-art forecast systems. Results show that predictability greatly benefits from initializing the hindcasts beyond the prescribed radiative forcing, and is modulated by known modes of climate variability, namely El Niño-Southern Oscillation and the Interdecadal Pacific Oscillation. Furthermore, the models are capable of simulating the spatial pattern of the observed SPOD even without initialization, which suggests that the key dynamical processes are properly represented. However, the hindcast of the actual phase of the mode is only achieved when the forecast systems are initialized, pointing at SPOD variability to not be radiatively forced but probably internally generated. The comparison with the performance of an empirical prediction based on persistence suggests that initialization may provide skillful information for SST anomalies, outperforming damping processes, up to 2–3 years into the future. 相似文献
6.
Summary The main objective of this study was to develop empirical models with different seasonal lead time periods for the long range
prediction of seasonal (June to September) Indian summer monsoon rainfall (ISMR). For this purpose, 13 predictors having significant
and stable relationships with ISMR were derived by the correlation analysis of global grid point seasonal Sea-Surface Temperature
(SST) anomalies and the tendency in the SST anomalies. The time lags of the seasonal SST anomalies were varied from 1 season
to 4 years behind the reference monsoon season. The basic SST data set used was the monthly NOAA Extended Reconstructed Global
SST (ERSST) data at 2° × 2° spatial grid for the period 1951–2003. The time lags of the 13 predictors derived from various
areas of all three tropical ocean basins (Indian, Pacific and Atlantic Oceans) varied from 1 season to 3 years. Based on these
inter-correlated predictors, 3 predictor sub sets A, B and C were formed with prediction lead time periods of 0, 1 and 2 seasons,
respectively, from the beginning of the monsoon season. The selected principal components (PCs) of these predictor sets were
used as the input parameters for the models A, B and C, respectively. The model development period was 1955–1984. The correct
model size was derived using all-possible regressions procedure and Mallow’s “Cp” statistics.
Various model statistics computed for the independent period (1985–2003) showed that model B had the best prediction skill
among the three models. The root mean square error (RMSE) of model B during the independent test period (6.03% of Long Period
Average (LPA)) was much less than that during the development period (7.49% of LPA). The performance of model B was reasonably
good during both ENSO and non-ENSO years particularly when the magnitudes of actual ISMR were large. In general, the predicted
ISMR during years following the El Ni?o (La Ni?a) years were above (below) LPA as were the actual ISMR. By including an NAO
related predictor (WEPR) derived from the surface pressure anomalies over West Europe as an additional input parameter into
model B, the skill of the predictions were found to be substantially improved (RMSE of 4.86% of LPA). 相似文献
7.
Coupled ocean-atmosphere surface variability and its climate impacts in the tropical Atlantic region
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
8.
Renguang Wu 《Climate Dynamics》2010,34(5):629-642
Analysis of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) data for the period 1998–2007 reveals large
subseasonal fluctuations in sea surface temperature (SST) of the South China Sea during the summer monsoon onset. These subseasonal
SST changes are closely related to surface heat flux anomalies induced by surface wind and cloud changes in association with
the summer monsoon onset. The SST changes feed back on the atmosphere by modifying the atmospheric instability. The results
suggest that the South China Sea summer monsoon onset involves ocean–atmosphere coupling on subseasonal timescales. While
the SST response to surface heat flux changes is quick and dramatic, the time lag between the SST anomalies and the atmospheric
convection response varies largely from year to year. The spatial–temporal evolution of subseasonal anomalies indicates that
the subseasonal variability affecting the South China Sea summer monsoon onset starts over the equatorial western Pacific,
propagates northward to the Philippine Sea, and then moves westward to the South China Sea. The propagation of these subseasonal
anomalies is related to the ocean–atmosphere interaction, involving the wind-evaporation and cloud-radiation effects on SST
as well as SST impacts on lower-level convergence over the equatorial western Pacific and atmospheric instability over the
Philippine Sea and the South China Sea. 相似文献
9.
D. Manatsa W. Chingombe H. Matsikwa C. H. Matarira 《Theoretical and Applied Climatology》2008,92(1-2):1-14
Summary The dominant climatic mode responsible for seasonal rainfall variability across central southern Africa has been well-established
as ENSO. Hence, the El Ni?o signal of the equatorial Pacific has been used extensively to predict droughts in this sub-region.
Although this paper acknowledges that El Ni?o influences rainfall deficits over eastern southern Africa, an earlier signal
of extreme positive sea level pressure (SLP) anomalies at Darwin for the averaged March to June period (MAMJ Darwin) has proved
to have a superior remote connection to droughts in the sub-region. Simple linear statistical tools including composite techniques
and correlation methods have been employed on century long data sets (1901–2000) to identify the emerging paramount connection
between MAMJ Darwin SLP anomalies and southern African rainfall.
Both MAMJ Darwin SLP anomalies and the Zimbabwe seasonal rainfall time series are significantly correlated (above the 95%
significant level) with sea surface temperature anomalies. These represent the Indian Ocean Dipole mode in the tropical Indian
Ocean and ENSO in the tropical Pacific for the averaged September to December period. ‘Pure’ MAMJ Darwin (that occur in the
absence of El Ni?o in the Pacific) coincide with droughts more significantly (83% hit rate) than ‘pure’ El Ni?o events (not
preceded by a high MAMJ Darwin) (38% hit rate). Co-occurrences (MAMJ Darwin preceded by El Ni?o) do not only have the highest
hit rate of 93% but subsequent droughts are noticeably more severe. The ‘pure’ El Ni?os however, are not only poorly related
to Zimbabwe seasonal rainfall deficits, but are apparently not connected to extreme droughts of the 20th century. Thus, MAMJ Darwin is a good simple predictor of droughts associated with or without ENSO in the Pacific. The high
prediction skill of these results, especially the inherent longer lead-time than ENSO, makes MAMJ Darwin SLP anomalies an
ideal additional input candidate for sub-regional drought monitoring and forecasting schemes. In this way, drought early warning
and disaster preparedness activities can be enhanced over the sub-region.
Authors’ addresses: D. Manatsa, W. Chingombe, H. Matsikwa, Faculty of Science, Bindura University of Science Education, P.
Bag 1020, Bindura, Zimbabwe; C. H. Matarira, Department of Geography and Environmental Science, National University of Lesotho,
Roma 180, Lesotho. 相似文献
10.
S. K. Deb H. C. Upadhyaya O. P. Sharma A. Chakraborty 《Meteorology and Atmospheric Physics》2006,94(1-4):43-64
Summary Hindcasts for the Indian summer monsoons (ISMs) of 2002 and 2003 have been produced from an ensemble of numerical simulations
performed with a global model by changing SST. Two sets of ensemble simulations have been produced without vegetation: (i)
by prescribing the weekly observed SST from ECMWF (European Centre for Medium Range Weather Forecasting) analyses, and (ii)
by adding weekly SST anomalies (SSTA) of April to the climatological SST during the simulation period from May to August.
For each ensemble, 10 simulations have been realized with different initial conditions that are prepared from ECMWF data with
five each from April and May analyses of both the years. The predicted June–July monsoon rainfall over the Indian region shows
good agreement with the GPCP (observed) pentad rainfall distribution when 5 member ensemble is taken from May initial conditions.
The All-India June–July simulated rainfall time series matches favourably with the observed time series in both the years
for the five member ensemble from May initial condition but drifts away from observation with April initial conditions. This
underscores the role of initial conditions in the seasonal forecasting. But the model has failed to capture the strong intra-seasonal
oscillation in July 2002. Heating over equatorial Indian Ocean for June 2002 in a particular experiment using 29th May 12
GMT as initial conditions shows some intra-seasonal oscillation in July 2002 rainfall, as in observation. Further evaluation
of the seasonal simulations from this model is done by calculating the empirical orthogonal functions (EOFs) of the GPCP rainfall
over India. The first four EOFs explain more than 80% of the total variance of the observed rainfall. The time series of expansion
coefficients (principal components), obtained by projecting on the observed EOFs, provide a better framework for inter-comparing
model simulations and their evaluation with observed data. The main finding of this study is that the All-India rainfall from
various experiments with prescribed SST is better predicted on seasonal scale as compares to prescribed SST anomalies. This
is indicative of a possible useful seasonal forecasts from a GCM at least for the case when monsoon is going to be good. The
model responses do not differ much for 2002 and 2003 since the evolution of SST during these years was very similar, hence
July rainfall seems to be largely modulated by the other feedbacks on the overall circulation. 相似文献
11.
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
12.
Summary Estimates of the predictability of New Zealand monthly and seasonal temperature and rainfall anomalies are calculated using
a cross-validated linear regression procedure. Predictors are indices of the large scale circulation, sea-surface temperatures,
the Southern Oscillation Index and persistence. Statistical significance is estimated through a series of Monte Carlo trials.
No significant forecast relationships are found for rainfall anomalies at either the monthly or seasonal time scale. Temperature
forecasts are however considered to exhibit significant skill, with variance reductions of the order of 10–20% in independent
trials. Temperature anomalies are most skilfully predicted over the North Island, and skill is greatest in Spring and Summer
in most areas. At the monthly time scale, predictors local to the New Zealand region account for most of the forecast skill,
while at the seasonal time scale, skill depends strongly upon “remote” predictors defined over regions of the southern hemisphere
distant from New Zealand. Indices of meridional flow over the Tasman Sea/New Zealand region are found to be useful predictors,
especially for monthly forecasts, perhaps as a proxy for atmospherically-forced sea surface temperature anomalies. Sea surface
temperature anomalies to the west of New Zealand and in the tropical Indian Ocean are also useful, especially for seasonal
predictions. Forecast skill is more reliably estimated at the monthly time scale than at the seasonal time scale, as a result
of the larger sample size of monthly mean data. While long-term mean levels of skill may be estimated reliably over the whole
data set, statistically significant decadal-scale variations are found in the predictability of temperature anomalies. Therefore,
even if long-term forecast skill levels are reliably estimated, it may be impossible to predict the short-term skill of operational
seasonal climate forecasts. Implications for operational climate predictions in mid-latitudes are discussed.
Received July 18, 1997 Revised April 2, 1998 相似文献
13.
Both seasonal potential predictability and the impact of SST in the Pacific on the forecast skill over China are investigated by using a 9-level global atmospheric general circulation model developed at the Institute of Atmospheric Physics under the Chinese Academy of Sciences (IAP9L-AGCM). For each year during 1970 to 1999, the ensemble consists of seven integrations started from consecutive observational daily atmospheric fields and forced by observational monthly SST. For boreal winter, spring and summer,the variance ratios of the SST-forced variability to the total variability and the differences in the spatial correlation coefficients of seasonal mean fields in special years versus normal years are computed respectively. It follows that there are slightly inter-seasonal differences in the model potential predictability in the Tropics. At northern middle and high latitudes, prediction skill is generally low in spring and relatively high either in summer for surface air temperature and middle and upper tropospheric geopotential height or in winter for wind and precipitation. In general, prediction skill rises notably in western China, especially in northwestern China, when SST anomalies (SSTA) in the Nino-3 region are significant. Moreover,particular attention should be paid to the SSTA in the North Pacific (NP) if one aims to predict summer climate over the eastern part of China, i.e., northeastern China, North China and southeastern China. 相似文献
14.
The relative influence of soil moisture and SST in climate predictability explored within ensembles of AMIP type experiments 总被引:4,自引:1,他引:4
Three ensembles of AMIP-type simulations using the Arpege-climat coupled land–atmosphere model have been designed to assess the relative influence of SST and soil moisture (SM) on climate variability and predictability. The study takes advantage of the GSWP2 land surface reanalysis covering the 1986–1995 period. The GSWP2 forcings have been used to derive a global SM climatology that is fully consistent with the model used in this study. One ensemble of ten simulations has been forced by climatological SST and the simulated SM is relaxed toward the GSWP2 reanalysis. Another ensemble has been forced by observed SST and SM is evolving freely. The last ensemble combines the observed SST forcing and the relaxation toward GSWP2. Two complementary aspects of the predictability have been explored, the potential predictability (analysis of variance) and the effective predictability (skill score). An analysis of variance has revealed the effects of the SST and SM boundary forcings on the variability and potential predictability of near-surface temperature, precipitation and surface evaporation. While in the tropics SST anomalies clearly maintain a potentially predictable variability throughout the annual cycle, in the mid-latitudes the SST forced variability is only dominant in winter and SM plays a leading role in summer. In a similar fashion, the annual cycle of the hindcast skill (evaluated as the anomalous correlation coefficient of the three ensemble means with respect to the “observations”) indicates that the SST forcing is the dominant contributor over the tropical continents and in the winter mid-latitudes but that SM is supporting a significant part of the skill in the summer mid-latitudes. Focusing on boreal summer, we have then investigated different aspects of the SM and SST contribution to climate variations in terms of spatial distribution and time-evolution. Our experiments suggest that SM is potentially an additional source of climate predictability. A realistic initialization of SM and a proper representation of the land–atmosphere feedbacks seem necessary to improve state-of-the-art dynamical seasonal predictions, but will be actually efficient only in the areas where SM anomalies are themselves predictable at the monthly to seasonal timescale (since remote effects of SM are probably much more limited than SST teleconnections). 相似文献
15.
Twenty-one-year hindcasts of sea surface temperature (SST) anomalies in the tropical Pacific were performed to validate the influence of ocean subsurface entrainment on SST prediction.A new hybrid coupled model was used that considered the entrainment of subsurface temperature anomalies into the sea surface.The results showed that predictions were improved significantly in the new coupled model.The predictive correlation skill increased by about 0.2 at a lead time of 9 months,and the root-mean-square (RMS) errors were decreased by nearly 0.2°C in general.A detailed analysis of the 1997-98 El Nio hindcast showed that the new model was able to predict the onset,peak (both time and amplitude),and decay of the 1997-98 strong El Nio event up to a lead time of one year,factors that are not represented well by many other forecast systems.This implies,in terms of prediction,that subsurface anomalies and their impact on the SST are one of the controlling factors in ENSO cycles.Improving the presentation of such effects in models would increase the forecast skill. 相似文献
16.
Virginie Guemas David Salas-Mélia Masa Kageyama Hervé Giordani Aurore Voldoire Emilia Sanchez-Gomez 《Climate Dynamics》2010,34(4):527-546
This study aims at understanding the summer ocean-atmosphere interactions in the North Atlantic European region on intraseasonal
timescales. The CNRMOM1d ocean model is forced with ERA40 (ECMWF Re-Analysis) surface fluxes with a 1-h frequency in solar
heat flux (6 h for the other forcing fields) over the 1959–2001 period. The model has 124 vertical levels with a vertical
resolution of 1 m near the surface and 500 m at the bottom. This ocean forced experiment is used to assess the impact of the
North Atlantic weather regimes on the surface ocean. Composites of sea surface temperature (SST) anomalies associated with
each weather regime are computed and the mechanisms explaining these anomalies are investigated. Then, the SST anomalies related
to each weather regime in the ocean-forced experiment are prescribed to the ARPEGE Atmosphere General Circulation Model. We
show that the interaction with the surface ocean induces a positive feedback on the persistence of the Blocking regime, a
negative feedback on the persistence of the NAO-regime and favours the transition from the Atlantic Ridge regime to the NAO-regime
and from the Atlantic Low regime toward the Blocking regime. 相似文献
17.
G. A. Meehl P. R. Gent J. M. Arblaster B. L. Otto-Bliesner E. C. Brady A. Craig 《Climate Dynamics》2001,17(7):515-526
Historically, El Nino-like events simulated in global coupled climate models have had reduced amplitude compared to observations.
Here, El Nino-like phenomena are compared in ten sensitivity experiments using two recent global coupled models. These models
have various combinations of horizontal and vertical ocean resolution, ocean physics, and atmospheric model resolution. It
is demonstrated that the lower the value of the ocean background vertical diffusivity, the greater the amplitude of El Nino
variability which is related primarily to a sharper equatorial thermocline. Among models with low background vertical diffusivity,
stronger equatorial zonal wind stress is associated with relatively higher amplitude El Nino variability along with more realistic
east–west sea surface temperature (SST) gradient along the equator. The SST seasonal cycle in the eastern tropical Pacific
has too much of a semiannual component with a double intertropical convergence zone (ITCZ) in all experiments, and thus does
not affect, nor is it affected by, the amplitude of El Nino variability. Systematic errors affecting the spatial variability
of El Nino in the experiments are characterized by the eastern equatorial Pacific cold tongue regime extending too far westward
into the warm pool. The time scales of interannual variability (as represented by time series of Nino3 SSTs) show significant
power in the 3–4 year ENSO band and 2–2.5 year tropospheric biennial oscillation (TBO) band in the model experiments. The
TBO periods in the models agree well with the observations, while the ENSO periods are near the short end of the range of
3–6 years observed during the period 1950–94. The close association between interannual variability of equatorial eastern
Pacific SSTs and large-scale SST patterns is represented by significant correlations between Nino3 time series and the PC
time series of the first EOFs of near-global SSTs in the models and observations.
Received: 17 April 2000 / Accepted: 17 August 2000 相似文献
18.
Forecasting the equatorial Pacific sea surface temperatures by neural network models 总被引:2,自引:0,他引:2
We used neural network models to seasonally forecast the tropical Pacific sea surface temperature anomalies (SSTA) in the
Ni?o 3.4 region (6 °S–6 °N, 120 °W–170 °W). The inputs to the neural networks (i.e., the predictors) were the first seven wind stress empirical orthogonal function
(EOF) modes of the tropical Pacific (20 °S–20 °N, 120 °E–70 °W) for four seasons and the Ni?o 3.4 SSTA itself for the final season. The period of 1952–1981 was used for training the neural
network models, and the period 1982–1992 for forecast validation. At 6-month lead time, neural networks attained forecast
skills comparable to the other El Ni?o-Southern Oscillation (ENSO) models. Our results suggested that neural network models
were viable for ENSO forecasting even at longer lead times of 9 to 12 months. We hypothesized that at these longer leads,
the underlying relationship between the wind stress and Ni?o 3.4 SSTA became increasingly nonlinear. The neural network results
were interpreted in light of current theories, e.g., the role of the “off-equatorial” Rossby waves in triggering the onset
of an ENSO event and the delayed-oscillator theory in the development and termination of an ENSO event.
Received: 31 October 1995 / Accepted: 25 July 1996 相似文献
19.
Summary ?The interannual variability of broad-scale Asian summer monsoon was studied using a general circulation model (GCM) and NCEP
(National Center for Environmental Prediction) data set during 1979–95. In the GCM experiment, the main emphasis was given
to isolate the individual role of surface boundary conditions on the existence of winter-spring time circulation anomalies
associated with the interannual variability of Asian summer monsoon.
In order to understand the role of sea-surface temperatures (SSTs) alone on the existence of precursory signals, we have conducted
17 years numerical integration with a GCM forced with the real-time monthly averaged SSTs of 1979 to 1995. In this experiment,
among the many surface boundary conditions only SSTs are varying interannually. The composite circulation anomalies simulated
by the GCM have good resemblance with the NCEP circulation anomalies over subtropical Asia. This suggests that the root cause
of the existence of winter-spring time circulation anomalies associated with the interannual variability of Asian summer monsoon
is the interannual variability of SST.
Empirical Orthogonal Functions (EOFs) of 200-mb winds and OLR were constructed to study the dynamic coupling between SST anomalies
and winter-spring time circulation anomalies. It is found that the convective heating anomalies associated with SST anomalies
and stationary eddies undergo systematic and coherent interannual variations prior to summer season. We have identified Matsuno-Gill
type mode in the velocity potential and stream function fields. This suggests the existence of dynamic links between the SST
anomalies and the precursory signals of Asian summer monsoon.
Received June 9, 1999/Revised April 7, 2000 相似文献
20.
Guojun Gu 《Climate Dynamics》2009,32(4):457-471
Intraseasonal (30–80 days) variability in the equatorial Atlantic-West African sector during March–June is investigated using
various recently-archived satellite measurements and the NCEP/DOE AMIP-II reanalysis daily data. The global connections of
regional intraseasonal signals are first examined for the period of 1979–2006 through lag-regression analyses of convection
(OLR) and other dynamic components against a regional intraseasonal convective (OLR) index. The eastward-propagating features
of convection can readily be seen, accompanied by coherent circulation anomalies, similar to those for the global tropical
intraseasonal mode, i.e., the Madden–Julian oscillation (MJO). The regressed TRMM rainfall (3B42) anomalies during the TRMM
period (1998–2006) manifest similar propagating features as for the regressed OLR anomalies during 1979–2006. These coherent
features hence tend to suggest that the regional intraseasonal convective signals might be mostly a regional response to,
or closely associated with the MJO, and probably contribute to the MJO’s global propagation. Atmospheric and surface intraseasonal
variability during March–June of 1998–2006 are further examined using the high-quality TRMM Microwave Imager (TMI) sea surface
temperature (SST), columnar water vapor, and cloud liquid water, and the QuikSCAT oceanic winds (2000–2006). Enhanced (suppressed)
convection or positive (negative) rainfall anomalies approximately cover the entire basin (0°–10°N, 30°W–10°E) during the
passage of intraseasonal convective signals, accompanied by anomalous surface westerly (easterly) flow. Furthermore, a unique
propagating feature seems to exist within the tropical Atlantic basin. Rainfall anomalies always appear first in the northwestern
basin right off the coast of South America, and gradually extend eastward to cover the entire basin. A dipolar structure of
rainfall anomalies with cross-equatorial surface wind anomalies can thus be observed during this evolution, similar to the
anomaly patterns on the interannual time scale discovered in past studies. Coherent intraseasonal variations and patterns
can also be found in other physical components.
相似文献
Guojun GuEmail: |