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1.
Based on Chen et al. (2006), the scheme of the combination of the pentad-mean zonal height departure nonlinear prediction with the T42L9 model prediction was designed, in which the pentad zonal heights at all the 12-initial-value-input isobar levels from 50 hPa to 1000 hPa except 200, 300, 500, and 700 hPa were derived from nonlinear forecasts of the four levels by means of a good correlation between neighboring levels. Then the above pentad zonal heights at 12 isobar-levels were transformed to the spectrum coefficients of the temperature at each integration step of T42L9 model. At last, the nudging was made. On account of a variety of error accumulation, the pentad zonal components of the monthly height at isobar levels output by T42L9 model were replaced by the corresponding nonlinear results once more when integration was over. Multiple case experiments showed that such combination of two kinds of prediction made an improvement in the wave component as a result of wave-flow nonlinear interaction while reducing the systematical forecast errors. Namely the monthly-mean height anomaly correlation coefficients over the high- and mid-latitudes of the Northern Hemisphere, over the Southern Hemisphere and over the globe increased respectively from 0.249 to 0.347, from 0.286 to 0.387, and from 0.343 to 0.414 (relative changes of 31.5%, 41.0%, and 18.3%). The monthly-mean root-mean-square error (RMSE) of T42L9 model over the three areas was considerably decreased, the relative change over the globe reached 44.2%. The monthly-mean anomaly correlation coefficients of wave 4-9 over the areas were up to 0.392, 0.200, and 0.295, with the relative change of 53.8%, 94.1%, and 61.2%, and correspondingly their RMSEs were decreased respectively with the rate of 8.5%, 6.3%, and 8.1%. At the same time the monthly-mean pattern of parts of cases were presented better.  相似文献   

2.
A new seasonal prediction model for annual tropical storm numbers(ATSNs)over the western North Pacific was developed using the preceding January-February(JF)and April-May(AM)grid-point data at a resolution of 2.5°×2.5°.The JF and AM mean precipitation and the AM mean 500-hPa geopotential height in the Northern Hemisphere,together with the JF mean 500-hPa geopotential height in the Southern Hemisphere,were employed to compose the ATSN forecast model via the stepwise multiple linear regression technique.All JF and AM mean data were confined to the Eastern Hemisphere.We established two empirical prediction models for ATSN using the ERA40 reanalysis and NCEP reanalysis datasets,respectively,together with the observed precipitation.The performance of the models was verified by cross-validation.Anomaly correlation coefficients(ACC)at 0.78 and 0.74 were obtained via comparison of the retrospective predictions of the two models and the observed ATSNs from 1979 to 2002.The multi-year mean absolute prediction errors were 3.0 and 3.2 for the two models respectively,or roughly 10% of the average ATSN.In practice,the final prediction was made by averaging the ATSN predictions of the two models.This resulted in a higher score,with ACC being further increased to 0.88,and the mean absolute error reduced to 1.92,or 6.13% of the average ATSN.  相似文献   

3.
Climate Change in the Subtropical Jetstream during 1950–2009   总被引：1，自引：0，他引：1  
A study of six decades(1950–2009) of reanalysis data reveals that the subtropical jetstream(STJ) of the Southern(Northern) Hemisphere between longitudes 0°E and 180°E has weakened(strengthened) during both the boreal winter(January,February) and summer(July, August) seasons. The temperature of the upper troposphere of the midlatitudes has a warming trend in the Southern Hemisphere and a cooling trend in the Northern Hemisphere. Correspondingly, the north–south temperature gradient in the upper troposphere has a decreasing trend in the Southern Hemisphere and an increasing trend in the Northern Hemisphere, which affects the strength of the STJ through the thermal wind relation. We devised a method of isotach analysis in intervals of 0.1 m s-1in vertical sections of hemispheric mean winds to study the climate change in the STJ core wind speed, and also core height and latitude. We found that the upper tropospheric cooling of the Asian mid-latitudes has a role in the strengthening of the STJ over Asia, while throughout the rest of the globe the upper troposphere has a warming trend that weakens the STJ. Available studies show that the mid-latitude cooling of the upper troposphere over Asia is caused by anthropogenic aerosols(particularly sulphate aerosols) and the warming over the rest of the global mid-latitude upper troposphere is due to increased greenhouse gases in the atmosphere.  相似文献   

4.
Based on time series and linear trend analysis, the authors evaluated the performance of the fourth generation atmospheric general circulation model developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP AGCM4.0), in simulating surface air temperature (SAT) during the twentieth century over China and the globe. The numerical experiment is conducted by driving the model with the observed sea surface temperature and sea ice. It is shown that IAP AGCM4.0 can simulate the warming trend of the global SAT, with the major warming regions in the high latitudes of the Northern Hemisphere and the mid-latitudes of the Southern Hemisphere. While the simulated trend over the whole globe is close to the observation, the model under-estimates the observed trend over the continents. More-over, the model simulates the spatial distribution of SAT in China, with a bias of approximately-2°C in eastern China, but with a more serious bias in western China. Compared with the global mean, however, the correlation coefficient between the simulation and observation in China is significantly lower, indicating that there is large uncertainty in simulating regional climate change.  相似文献   

5.
With the Zebiak–Cane model, the present study investigates the role of model errors represented by the nonlinear forcing singular vector(NFSV) in the "spring predictability barrier"(SPB) phenomenon in ENSO prediction. The NFSV-related model errors are found to have the largest negative effect on the uncertainties of El Nio prediction and they can be classified into two types: the first is featured with a zonal dipolar pattern of SST anomalies(SSTA), with the western poles centered in the equatorial central–western Pacific exhibiting positive anomalies and the eastern poles in the equatorial eastern Pacific exhibiting negative anomalies; and the second is characterized by a pattern almost opposite to the first type. The first type of error tends to have the worst effects on El Nin?o growth-phase predictions, whereas the latter often yields the largest negative effects on decaying-phase predictions. The evolution of prediction errors caused by NFSVrelated errors exhibits prominent seasonality, with the fastest error growth in spring and/or summer; hence,these errors result in a significant SPB related to El Nin?o events. The linear counterpart of NFSVs, the(linear) forcing singular vector(FSV), induces a less significant SPB because it contains smaller prediction errors. Random errors cannot generate an SPB for El Nio events. These results show that the occurrence of an SPB is related to the spatial patterns of tendency errors. The NFSV tendency errors cause the most significant SPB for El Nio events. In addition, NFSVs often concentrate these large value errors in a few areas within the equatorial eastern and central–western Pacific, which likely represent those areas sensitive to El Nio predictions associated with model errors. Meanwhile, these areas are also exactly consistent with the sensitive areas related to initial errors determined by previous studies. This implies that additional observations in the sensitive areas would not only improve the accuracy of the initial field but also promote the reduction of model errors to greatly improve ENSO forecasts.  相似文献   

6.
This study examines the time and regime dependencies of sensitive areas identified by the conditional nonlinear optimal perturbation(CNOP) method for forecasts of two typhoons.Typhoon Meari(2004) was weakly nonlinear and is herein referred to as the linear case,while Typhoon Matsa(2005) was strongly nonlinear and is herein referred to as the nonlinear case.In the linear case,the sensitive areas identified for special forecast times when the initial time was fixed resembled those identified for other forecast times.Targeted observations deployed to improve a special time forecast would thus also benefit forecasts at other times.In the nonlinear case,the similarities among the sensitive areas identified for different forecast times were more limited.The deployment of targeted observations in the nonlinear case would therefore need to be adapted to achieve large improvements for different targeted forecasts.For both cases,the closer the forecast time,the higher the similarities of the sensitive areas.When the forecast time was fixed,the sensitive areas in the linear case diverged continuously from the verification area as the forecast period lengthened,while those in the nonlinear case were always located around the initial cyclones.The deployment of targeted observations to improve a special forecast depends strongly on the time of deployment.An examination of the efficiency gained by reducing initial errors within the identified sensitive areas confirmed these results.In general,the greatest improvement in a special time forecast was obtained by identifying the sensitive areas for the corresponding forecast time period.  相似文献   

7.
The horizontal diffusion coefficients of the operational model (T42L9) in numerical weather prediction are optimized by the steepest descent search of multi-dimensional optimization. In order to improve prediction accuracy in low latitudes, the optimum horizontal diffusion coefficients are chosen, with changing variation of the basic diffusion coefficient with the passage of time, and later forecasts are also made better. In view of the averages of forecast verifications of 9 cases, the forecasts with optimum diffusion coefficients are an improvement on operational forecasts. It means that the forecasts are got much better with optimum values of some important parameters by optimization in numerical weather prediction.  相似文献   

8.
It has been demonstrated that ensemble mean forecasts, in the context of the sample mean, have higher forecasting skill than deterministic(or single) forecasts. However, few studies have focused on quantifying the relationship between their forecast errors, especially in individual prediction cases. Clarification of the characteristics of deterministic and ensemble mean forecasts from the perspective of attractors of dynamical systems has also rarely been involved. In this paper, two attractor statistics—namely, the global and local attractor radii(GAR and LAR, respectively)—are applied to reveal the relationship between deterministic and ensemble mean forecast errors. The practical forecast experiments are implemented in a perfect model scenario with the Lorenz96 model as the numerical results for verification. The sample mean errors of deterministic and ensemble mean forecasts can be expressed by GAR and LAR, respectively, and their ratio is found to approach2~(1/2) with lead time. Meanwhile, the LAR can provide the expected ratio of the ensemble mean and deterministic forecast errors in individual cases.  相似文献   

9.
This paper presents a study on the statistical forecasts of typhoon tracks. Numerical models have their own systematic errors, like a bias. In order to improve the accuracy of track forecasting, a statistical model called DLM (dynamic linear model) is applied to remove the systematic error. In the analysis of typhoons occurring over the western North Pacific in 1997 and 2000, DLM is useful as an adaptive model for the prediction of typhoon tracks.  相似文献   

10.
Since the last International Union of Geodesy and Geophysics General Assembly(2003),predictability studies in China have made significant progress.For dynamic forecasts,two novel approaches of conditional nonlinear optimal perturbation and nonlinear local Lyapunov exponents were proposed to cope with the predictability problems of weather and climate,which are superior to the corresponding linear theory.A possible mechanism for the"spring predictability barrier"phenomenon for the El Ni(?)o-Southern Oscillation (ENSO)was provided based on a theoretical model.To improve the forecast skill of an intermediate coupled ENSO model,a new initialization scheme was developed,and its applicability was illustrated by hindcast experiments.Using the reconstruction phase space theory and the spatio-temporal series predictive method, Chinese scientists also proposed a new approach to improve dynamical extended range(monthly)prediction and successfully applied it to the monthly-scale predictability of short-term climate variations.In statistical forecasts,it was found that the effects of sea surface temperature on precipitation in China have obvious spatial and temporal distribution features,and that summer precipitation patterns over east China are closely related to the northern atmospheric circulation.For ensemble forecasts,a new initial perturbation method was used to forecast heavy rain in Guangdong and Fujian Provinces on 8 June 1998.Additionally, the ensemble forecast approach was also used for the prediction of a tropical typhoons.A new downscaling model consisting of dynamical and statistical methods was provided to improve the prediction of the monthly mean precipitation.This new downsealing model showed a relatively higher score than the issued operational forecast.  相似文献   

11.
This paper summarizes recent progress at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics(LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences in studies on targeted observations, data assimilation, and ensemble prediction, which are three effective strategies to reduce the prediction uncertainties and improve the forecast skill of weather and climate events. Considering the limitations of traditional targeted observation approaches, LASG researchers have developed a conditional nonlinear optimal perturbation-based targeted observation strategy to optimize the design of the observing network. This strategy has been employed to identify sensitive areas for targeted observations of the El Ni?o–Southern Oscillation, Indian Ocean dipole, and tropical cyclones, and has been demonstrated to be effective in improving the forecast skill of these events. To assimilate the targeted observations into the initial state of a numerical model, a dimension-reducedprojection-based four-dimensional variational data assimilation(DRP-4DVar) approach has been proposed and is used operationally to supply accurate initial conditions in numerical forecasts. The performance of DRP-4DVar is good, and its computational cost is much lower than the standard 4DVar approach. Besides, ensemble prediction,which is a practical approach to generate probabilistic forecasts of the future state of a particular system, can be used to reduce the prediction uncertainties of single forecasts by taking the ensemble mean of forecast members. In this field, LASG researchers have proposed an ensemble forecast method that uses nonlinear local Lyapunov vectors(NLLVs) to yield ensemble initial perturbations. Its application in simple models has shown that NLLVs are more useful than bred vectors and singular vectors in improving the skill of the ensemble forecast. Therefore, NLLVs represent a candidate for possible development as an ensemble method in operational forecasts. Despite the considerable efforts made towards developing these methods to reduce prediction uncertainties, much challenging but highly important work remains in terms of improving the methods to further increase the skill in forecasting such weather and climate events.  相似文献   

12.
It is proved in this paper that NWP systematic forecast errors in the zonal mean circulation aredue to the difference in westerly acceleration process during the forecasting period between model andreal atmospheres.Those forcing factors which evoke the zonal mean wind variation can be split into various linearterms according to the non-acceleration theorem in a primitive equation system,By applying this tech-nique to the diagnosis of the forecast produets of the T42L9 model in January 1992 and in July 1992,it is indicated that the model has the ability to forecast the zonal mean wind to a reasonable extent,but there are still some errors in several places,especially in the upper troposphere and lower strato-sphere in the mid-latitude region as well as near the surface.The results of analysis by employing thisscheme reveal the reason responsible for the systematic forecast errors of the zonal mean wind in themodel and the possible way of improving it.It is also shown that non-acceleration theorem can be used as an efficient tool to diagnose thephysical processes of NWP models.  相似文献   

13.
The ensemble based forecast sensitivity to observation method by Liu and Kalnay is applied to the SPEEDY-LETKF system to estimate the observation impact of three types of simulated observations. The estimation results show that all types of observations have positive impact on short-range forecast. The largest impact in Northern Hemisphere is produced by rawinsondes, followed by satellite retrieved profiles and cloud drift wind data, which in Southern Hemisphere is produced by satellite retrieved profiles, rawinsondes and cloud drift wind data. Satellite retrieved profiles influence more on the Southern Hemisphere than on the Northern Hemisphere due to few observations from rawinsondes in the Southern Hemisphere. At the level of 200 to 300 hPa, the largest impact is attributed to wind observations from rawinsondes and cloud drift wind.  相似文献   

14.
The characteristics of the atmospheric boundary layer height over the global ocean were studied based on the Constellation Observation System of Meteorology, Ionosphere and Climate (COSMIC) refractivity data from 2007 to 2012. Results show that the height is much characteristic of seasonal, inter-annual and regional variation. Globally, the spatial distribution of the annual mean top height shows a symmetrical zonal structure, which is more zonal in the Southern Hemisphere than in the Northern Hemisphere. The boundary layer top is highest in the tropics and gradually decreases towards higher latitudes. The height is in a range of 3 to 3.5 km in the tropics, 2 to 2.5 km in the subtropical regions, and 1 to 1.5 km or even lower in middle and high latitudes. The diurnal variation of the top height is not obvious, with the height varying from tens to hundreds of meters. Furthermore, it is different from region to region, some regions have the maximum height during 9:00 to 12:00, others at 15:00 to 18:00.  相似文献   

15.
By using of an ensemble method,the tests of rainfall for the predictions of the seasonal,interseasonal and annual scales in China during 1982—1995 have been made by the atmosphericGCM/mixed layer ocean and ice model(OSU/NCC).Contrasts between forecasts by the OSU/NCC and the observations show that the model has a certain ability in the prediction ofprecipitation for summer over China in all of the three different time scales.And it indicates thatthe interseasonal prediction is the best among the forecasts of three scales.It is also indicated thatthe prediction is especially acceptable in certain areas.  相似文献   

16.
A reduced-gravity barotropic shallow-water model was used to simulate the Kuroshio path variations.The results show that the model was able to capture the essential features of these path variations.We used one simulation of the model as the reference state and investigated the effects of errors in model parameters on the prediction of the transition to the Kuroshio large meander (KLM) state using the conditional nonlinear optimal parameter perturbation (CNOP-P) method.Because of their relatively large uncertainties,three model parameters were considered:the interfacial friction coefficient,the wind-stress amplitude,and the lateral friction coefficient.We determined the CNOP-Ps optimized for each of these three parameters independently,and we optimized all three parameters simultaneously using the Spectral Projected Gradient 2 (SPG2) algorithm.Similarly,the impacts caused by errors in initial conditions were examined using the conditional nonlinear optimal initial perturbation (CNOP-I) method.Both the CNOP-I and CNOP-Ps can result in significant prediction errors of the KLM over a lead time of 240 days.But the prediction error caused by CNOP-I is greater than that caused by CNOP-P.The results of this study indicate not only that initial condition errors have greater effects on the prediction of the KLM than errors in model parameters but also that the latter cannot be ignored.Hence,to enhance the forecast skill of the KLM in this model,the initial conditions should first be improved,the model parameters should use the best possible estimates.  相似文献   

17.
With the Zebiak-Cane(ZC)model,the initial error that has the largest effect on ENSO prediction is explored by conditional nonlinear optimal perturbation(CNOP).The results demonstrate that CNOP-type errors cause the largest prediction error of ENSO in the ZC model.By analyzing the behavior of CNOP- type errors,we find that for the normal states and the relatively weak El Nino events in the ZC model,the predictions tend to yield false alarms due to the uncertainties caused by CNOP.For the relatively strong El Nino events,the ZC model largely underestimates their intensities.Also,our results suggest that the error growth of El Nino in the ZC model depends on the phases of both the annual cycle and ENSO.The condition during northern spring and summer is most favorable for the error growth.The ENSO prediction bestriding these two seasons may be the most diffcult.A linear singular vector(LSV)approach is also used to estimate the error growth of ENSO,but it underestimates the prediction uncertainties of ENSO in the ZC model.This result indicates that the different initial errors cause different amplitudes of prediction errors though they have same magnitudes.CNOP yields the severest prediction uncertainty.That is to say,the prediction skill of ENSO is closely related to the types of initial error.This finding illustrates a theoretical basis of data assimilation.It is expected that a data assimilation method can filter the initial errors related to CNOP and improve the ENSO forecast skill.  相似文献   

18.
The low frequency oscillation in both hemispheres and its possible role in the dust weather storm events over North China in 2002 are analyzed as a case study. Results show that the Aleutian Low is linked with the Circumpolar Vortex in the Southern Hemisphere on a 30-60-day oscillation, with a weak Circumpolar Vortex tending to deepen the Aleutian Low which may be helpful for the generation of dust storm events. The possible mechanism behind this is the inter-hemispheric interaction of the mean meridional circulation, with the major variability over East Asia. The zonal mean westerly wind at high latitudes of the Southern Hemisphere in the upper level troposphere may lead that of the Northern Hemisphere, which then impacts the local circulation in the Northern Hemisphere. Thus, the low frequency oscillation teleconnection is one possible linkage in the coupling between the Southern Hemisphere circulation and dust events over North China. However, the interannual variation of the low frequency oscillation is unclear.  相似文献   

19.
数值预报误差订正技术中相似-动力方法的发展   总被引：3，自引：0，他引：3       下载免费PDF全文
Due to the increasing requirement for high-level weather and climate forecasting accuracy, it is necessary to exploit a strategy for model error correction while developing numerical modeling and data assimilation techniques. This study classifies the correction strategies according to the types of forecast errors, and reviews recent studies on these correction strategies. Among others, the analogue-dynamical method has been developed in China, which combines statistical methods with the dynamical model, corrects model errors based on analogue information, and effectively utilizes historical data in dynamical forecasts. In this study, the fundamental principles and technical solutions of the analogue-dynamical method and associated development history for forecasts on different timescales are introduced. It is shown that this method can effectively improve medium- and extended-range forecasts, monthly-average circulation forecast, and short-term climate prediction. As an innovative technique independently developed in China, the analogue- dynamical method plays an important role in both weather forecast and climate prediction, and has potential applications in wider fields.  相似文献   

20.
The calculating schemes of underlying surface processes in the model described by Li et al.(1989)are modified with inclusion of simple land surface processes and oceanic mixed layer processes,then a simulation on the zonal wind along 90°E from the Northern to the Southern Hemisphere with moun-tains is performed.Comparisons of the results and the observations show that the modified model not onlyhas an excellent stability in calculation but also can better display the seasonal change of the wind field,theability of the present model is improved as compared with that of the previous one.Based on the simulations,the authors investigate the effects of Qinghai-Xizang Plateau snow cover on theformation of South Asian monsoon by thickcning the snow depth and by increasing the snow albedo.Themain results arc as follows:The summer meridional circulation over the south of the Plateau and its vicinityis weakeued,and the precipitation reduced.However,over the northern tropics,the circulation is enhanced,and the ecipitation is increased,and the land and the air above it become warmer,the tropical easterly jetis weakened.  相似文献   

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