共查询到18条相似文献，搜索用时 593 毫秒
1.
This paper explores urban temperature in Hong Kong using long-term time series. In particular, the characterization of the urban temperature trend was investigated using the seasonal unit root analysis of monthly mean air temperature data over the period January 1970 to December 2013. The seasonal unit root test makes it possible to determine the stochastic trend of monthly temperatures using an autoregressive model. The test results showed that mean air temperature has increased by0.169?C(10 yr)~(-1)over the past four decades. The model of monthly temperature obtained from the seasonal unit root analysis was able to explain 95.9% of the variance in the measured monthly data — much higher than the variance explained by the ordinary least-squares model using annual mean air temperature data and other studies alike. The model accurately predicted monthly mean air temperatures between January 2014 and December 2015 with a root-mean-square percentage error of 4.2%.The correlation between the predicted and the measured monthly mean air temperatures was 0.989. By analyzing the monthly air temperatures recorded at an urban site and a rural site, it was found that the urban heat island effect led to the urban site being on average 0.865?C warmer than the rural site over the past two decades. Besides, the results of correlation analysis showed that the increase in annual mean air temperature was significantly associated with the increase in population, gross domestic product, urban land use, and energy use, with the R~2 values ranging from 0.37 to 0.43. 相似文献
2.
FAN Ke 《大气和海洋科学快报》2009,2(1):14-17
The author investigates the prediction of Northeast China’s winter surface air temperature (SAT),and first forecast the year to year increment in the predic-tand and then predict the predictand.Thus,in the first step,we determined the predictors for an increment in winter SAT by analyzing the atmospheric variability associated with an increment in winter SAT.Then,multi-linear re-gression was applied to establish a prediction model for an increment in winter SAT in Northeast China.The pre-diction model shows a high correlation coefficient (0.73) between the simulated and observed annual increments in winter SAT in Northeast China throughout the period 1965-2002,with a relative root mean square error of -7.9%.The prediction model makes a reasonable hindcast for 2003-08,with an average relative root mean square error of -7.2%.The prediction model can capture the in-creasing trend of winter SAT in Northeast China from 1965-2008.The results suggest that this approach to forecasting an annual increment in winter SAT in North-east China would be relevant in operational seasonal forecasts. 相似文献
3.
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
4.
FAN Ke 《大气和海洋科学快报》2009,2(5):251-254
The year-to-year increment prediction approach proposed by was applied to forecast the annual number of tropical cyclones (TCs) making landfall over China.The year-to-year increase or decrease in the number of land-falling TCs (LTCs) was first predicted to yield a net number of LTCs between successive years.The statistical prediction scheme for the year-to-year increment of annual LTCs was developed based on data collected from 1977 to 2007,which includes five predictors associated with high latitude circulations in both Hemispheres and the circulation over the local,tropical western North Pacific Ocean.The model shows reasonably high predictive ability,with an average root mean square error (RMSE) of 1.09,a mean absolute error (MAE) of 0.9,and a correlation coefficient between the predicted and observed annual number of LTCs of 0.86,accounting for 74% of the total variance.The cross-validation test further demonstrated the high predictive ability of the model,with an RMSE value of 1.4,an MAE value of 1.2,and a correlation coefficient of 0.74 during this period. 相似文献
5.
Monthly Extended Predicting Experiments with Nonlinear Regional Prediction.PartⅠ:Prediction of Zonal Mean Flow 
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下载免费PDF全文 Systematic errors have recently been founded to be distinct in the zonal mean component forecasts, which account for a large portion of the total monthly-mean forecast errors. To overcome the difficulty of numerical model, the monthly pentad-riean nonlinear dynamic regional prediction models of the zonal mean geopotential height at 200, 300, 500, and 700 hPa based on a large number of historical data (NCEP/NCAR reanalysis data) were constituted by employing the local approximation of the phase space reconstruction theory and nonlinear spatio-temporal series prediction method. The 12-month forecast experiments of 1996 indicated that the results of the nonlinear model are better than those of the persistent, climatic prediction, and T42L9 model either over the high- and mid-latitude areas of the Northern and Southern Hemispheres or the tropical area. The root-mean-square of the monthly-mean height of T42L9 model was considerably decreased with a change of 30.4%, 26.6%, 82.6%, and 39.4%, respectively, over the high- and mid-latitudes of the Northern Hemisphere, over the high- and mid-latitudes of the Southern Hemisphere, over the tropics and over the globe, and also the corresponding anomaly correlation coefficients over the four areas were respectively increased by 0.306-0.312, 0.304-0.429, 0.739-0.746, and 0.360-0.400 (averagely a relative change of 11.0% over the globe) by nonlinear correction after integration, implying that the forecasts given by nonlinear model include more useful information than those of T42L9 model. 相似文献
6.
A neuroid BP-type three-layer mapping model is used for monthly rainfall forecasting in terms of 1946-1985 Nanjing monthly precipitation records as basic sequences and the model has the form i × j ＝ 8 × 3, K = 1; by steadily modifying the weighing coefficient, long-range monthly forecasts for January to December, 1986 are constructed and 1986 month-to-month predictions are made based on, say, the January measurement for February rainfall and so on, with mean absolute error reaching 6,07 and 5,73 mm, respectively. Also, with a different monthly initial value for June through September, 1994, neuroid forecasting is done, indicating the same result of the drought in Nanjing dur-ing the summer, an outcome that is in sharp agreement with the observation. 相似文献
7.
Monthly Extended Predicting Experiments with Nonlinear Regional Prediction.PartⅡ:Improvement of Wave Component Prediction 下载免费PDF全文
下载免费PDF全文 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
8.
范可 《热带气象学报(英文版)》2012,18(4):543-550
The spring (March-April-May) rainfall over northern China (SPRNC) is predicted by using the interannual increment approach. DY denotes the difference between the current year and previous years. The seasonal forecast model for the DY of SPRNC is constructed based on the data that are taken from the 1965-2002 period (38 years), in which six predictors are available no later than the current month of February. This is favorable so that the seasonal forecasts can be made one month ahead. Then, SPRNC and the percentage anomaly of SPRNC are obtained by the predicted DY of SPRNC. The model performs well in the prediction of the inter-annual variation of the DY of SPRNC during 1965-2002, with a correlation coefficient between the predicted and observed DY of SPRNC of 0.87. This accounts for 76% of the total variance, with a low value for the average root mean square error (RMSE) of 20%. Both the results of the hindcast for the period of 2003-2010 (eight years) and the cross-validation test for the period of 1965-2009 (45 years) illustrate the good prediction capability of the model, with a small mean relative error of 10%, an RMSE of 17% and a high rate of coherence of 87.5% for the hindcasts of the percentage anomaly of SPRNC. 相似文献
9.
After the consideration of the nonlinear nature changes of monsoon index,and the subjective determination of network structure in traditional artificial neural network prediction modeling,monthly and seasonal monsoon intensity index prediction is studied in this paper by using nonlinear genetic neural network ensemble prediction（GNNEP）modeling.It differs from traditional prediction modeling in the following aspects： （1）Input factors of the GNNEP model of monsoon index were selected from a large quantity of preceding period high correlation factors,such as monthly sea temperature fields,monthly 500-hPa air temperature fields,monthly 200-hPa geopotential height fields,etc.,and they were also highly information-condensed and system dimensionality-reduced by using the empirical orthogonal function（EOF）method,which effectively condensed the useful information of predictors and therefore controlled the size of network structure of the GNNEP model.（2）In the input design of the GNNEP model,a mean generating function（MGF）series of predictand（monsoon index）was added as an input factor;the contrast analysis of results of predic- tion experiments by a physical variable predictor-predictand MGF GNNEP model and a physical variable predictor GNNEP model shows that the incorporation of the periodical variation of predictand（monsoon index）is very effective in improving the prediction of monsoon index.（3）Different from the traditional neural network modeling,the GNNEP modeling is able to objectively determine the network structure of the GNNNEP model,and the model constructed has a better generalization capability.In the case of identical predictors,prediction modeling samples,and independent prediction samples,the prediction accuracy of our GNNEP model combined with the system dimensionality reduction technique of predictors is clearly higher than that of the traditional stepwise regression model using the traditional treatment technique of predictors,suggesting that the GNNEP model opens up a vast range of possibilities for operational weather prediction. 相似文献
10.
A Monthly Atmospheric Circulation Classification and Its Relationship with Climate in Harbin 总被引：1，自引：0，他引：1 下载免费PDF全文
下载免费PDF全文 In this study,the classification scheme developed by Jenkinson and Collison (1977) based on a typing scheme of Lamb (1950) is applied to obtain circulation types from the mean sea-level pressure on a monthly basis.Monthly mean sea-level pressure data from 1951 to 2002 are used to derive six circulation indices and to provide a circulation catalogue with 27 circulation types.Five major types (N,NW,C,CSW,and SW) which occurred most frequently are analyzed to reveal their relationships with the temperature of Harbin on various time scales.Stepwise multiple regression is used to reconstruct temperature anomaly.The monthly mean rainfall of all types occurring and the composite maps of three major types (C,CSW,and SW) relevant to Harbin's precipitation are studied. The results show that the dominant types in winter are types N and NW.types C,CSW,and SW occur frequently in summer.Types N and NW favor a negative temperature anomaly and correspond to less rainfall,while types C,CSW,and SW often induce a positive temperature anomaly and correspond to more rainfall.Moreover,a successful statistical model can be established with only one of the six indices and large-scale mean temperature.Using the model,77.3% of the total variance in the temperature anomaly between 1951 and 2002 can be reconstructed.Type C has a close relationship with total rainfall and type C precipitation plays a major role in determining the total rainfall of Harbin in recent years.This classification scheme is a statistical downscaling model and its relationships with temperature and precipitation can be used to forecast regional climate. 相似文献
11.
用15年北半球夏季地面温度的资料分析了月平均场与该月前后一周左右的逐日平均场在时间和波数上的相关。发现越新、越靠后的日平均场与该月的平均场相关越强。用第0天外推的未来30天平均场与实况的相关比用前30天平均场作外推的相关要显著得多。由此得出结论认为各种预报方法的效果检验应与前者定义的惯性预报作比较。文中提出了几个用于作月预报的统计模式，分别用不同时间或不同波数作预报因子。其结果均使预报准确率有所提高。既用不同时间又用不同波数作预报因子的模式更为理想。文中最后讨论了一个源于动力学考虑的统计模式。近1400个月预报例子的结果与实况的平均相关系数高达0.75，显著优于惯性预报。 相似文献
12.
M. M. Smirnova K. G. Rubinshtein V. P. Yushkov 《Russian Meteorology and Hydrology》2011,36(12):777-785
Carried out is the comparison of the temporal courses of temperature and wind speed at different levels as well as of the
wind and temperature profiles in the atmospheric boundary layer obtained from the WRF regional model forecasts and using the
upper-air in situ and remote measurements in Moscow region. The errors in temperature and wind speed forecasts at different
levels are computed as well as the statistical estimates of the forecast of temperature inversions, atmospheric stratification
types, and monthly mean wind speed profiles on the basis of model forecasts and acoustic sounding. 相似文献
13.
William H. Klein 《大气与海洋》2013,51(2):155-176
Abstract Anomalies of monthly mean surface temperature observed at 55 stations in Canada and 13 in Alaska from 1951 through 1980 are related to concurrent anomalies of monthly mean 700‐mb height at a network of 107 grid points in North America and the surrounding oceans. The data are screened by a stepwise forward selection procedure to yield multiple regression equations for specifying the monthly mean temperature anomaly at each city and for each month from the field of simultaneous 700‐mb heights plus the previous month's local temperature anomaly. On the average, the specification equations explain 70% of the temperature variance and select as predictors approxiamtely 2 heights to the west of the reference station, 1.5 heights in the vicinity, 1 height to the east, and 0.5 previous temperatures. Most of this paper describes various properties of the specification equations and related atmospheric characteristics on a regional, seasonal and month‐to‐month basis. Five statistical features are mapped for the months of January, April, July and October, and marked regional differences are noted. The above features are then averaged for the entire region and graphed month by month; the annual cycle of other properties is also described. Systematic spatial and temporal variations in the characteristics of temperature variability, persistence, correlation with height, and specification equations are illustrated. 相似文献
14.
NASA/Goddard长波辐射方案在GRAPES_Meso模式中的应用研究 总被引：2，自引：0，他引：2
本文将NASA（National Aeronautics and Space Administration）/Goddard长波辐射方案引入到GRAPES_ Meso（Global/Regional Assimilation and PrEdiction System_Meso）模式中,对2006年4月中国地区进行了一个月的模拟试验,并与相应的NCEP（National Centers for Environmental Prediction）再分析资料进行了对比分析。试验结果表明:在模拟区域内,使用GRAPES_Meso模式进行24 h、48 h预报得到的晴空大气顶向外长波辐射通量（the clear sky outgoing longwave radiation flux,OLRC）、地面接收到向下长波辐射通量（the clear sky downward longwave radiation flux at ground,GLWC）分布形势与NCEP再分析资料具有较好的对应关系;模式预报24 h、48 h OLRC和NCEP再分析资料月平均误差百分比控制在－10%～＋10%以内,GLWC月平均误差百分比比OLRC略大,但总体上两者误差都在合理和可接受范围之内。OLRC和GLWC 24 h、48 h的预报和NCEP再分析资料的逐日距平相关系数及标准误差的对比显示,模式24 h预报OLRC、GLWC的距平相关系数月平均值分别为0.96、0.98,标准误差月平均值分别为24.54 W m-2、27.23 W m-2;模式48 h预报OLRC、GLWC的距平相关系数月平均值分别为0.9521、0.9804,标准误差月平均值分别为22.43 W m-2、27.64 W m-2。总体上,模式24 h、48 h预报OLRC和GLWC的距平相关系数都在0.93以上,标准误差都在31 W m-2以内,且GLWC预报和NCEP再分析资料的相关性比OLRC略好,OLRC预报与NCEP再分析资料的的标准误差比GLWC略小。通过和RRTM长波辐射方案对比可知,两者的预报水平基本一致。本文研究结果表明,引入NASA/Goddard长波辐射方案后的GRAPES_Meso模式整体上能够较好地预报OLRC和GLWC,该辐射方案可以作为模式GRAPES_Meso的备选辐射方案之一。 相似文献
15.
利用典型相关分析(CCA)方法建立统计气候预测模型，对我国冬季气温进行了预测试验，采用历史资料独立样本检验的方法，对预报技巧给出合理的评定。结果表明，使用CCA方法对我国冬季气温进行短期气候预测，有一定的预报技巧，对于特定地区和特定时期优选的因子场组合，可以取得较为满意的预报效果。大部分地区的季平均预报时效在2个季以内时，最佳预报相关系数在0.5以上。季平均的预报水平明显高于月平均的预报。海温场是所有因子场中最好的预报因子，不仅单独海温场的预报效果较好，而且与其他因子场组合后的预报水平还可以得到进一步提高。 相似文献
16.
为克服数值模式普遍存在的纬向平均环流预报误差 ,文中在 3 6aNCEP/NCAR再分析高度场资料的基础上 ,应用非线性时空序列预测理论的局域近似法构建了 2 0 0 ,3 0 0 ,50 0和 70 0hPa 4个等压面上的月尺度逐候纬向平均高度距平场非线性动力学区域预报模型。对 1996年 12个月所做的预报试验表明 ,无论是南、北半球中高纬度地区还是低纬度地区 ,非线性模型的候纬向平均高度预报结果均优于持续性预报、气候预报和T 42L9模式动力预报。用非线性结果对T42L9模式月平均高度场预报结果进行订正 ,则使该谱模式系统性预报误差显著减少 ,也大大减少了其预报高度场的均方根误差 ,相应地 ,高度场距平相关评分也有一定程度的提高 ,表明纬向平均高度的非线性预报比谱模式动力预报包含了更多的有用信息 相似文献
17.
为明确近60 a来在近对流层自由大气底部这一特定高度上河南省中岳嵩山气温变化特征,在对河南省登封气象站月平均气温数据均一化的基础上,采用该站均一化数据构建嵩山站月平均气温模拟模型,对1990—2002年缺测数据插补,建立中岳嵩山高山国家基准气候站1956—2017年时间序列连续的月平均气温资料,采用线性回归对其进行气温变化趋势分析。结果表明：均一化处理对登封站月平均气温因台站迁移的非自然因素引起的非均一性取得了明显的校正效果。均一化后,1969—2017年登封站年平均气温由显著上升速率0.218℃/10 a增至0.310℃/10 a。利用独立数据对模型进行验证表明,总体上,嵩山站各月平均气温推算模型模拟值与实测值的线性相关系数和斜率分别为0.999和0.989(n=204,P < 0.01);1—12月各月模型验证检验参数的平均值相关系数为0.958、均方根误差为11.7%、平均绝对偏差为0.3℃、平均偏差为0.1℃、拟合指数为0.973、模拟效率为0.900,模型具有较好的模拟效果。1956—2017年嵩山站年平均气温增温显著,其速率为0.223℃/10 a。四季之间,以春季增温速率最大,为0.350℃/10 a;冬季和秋季次之;夏季增温不显著。各月之间,以2月增温速率最大,达0.445℃/10 a。 相似文献
18.
对1952—1980年我国连续的月地面气温用时间序列ARMA（p、q）模型进行随机建模。月温度由60个站组成，用经验正交函数加以展开，取不同的样本长度即348,336和300月，以便考察经验正交展开的稳定性。前四个主成分，即z1,z2,z3,z4取为多维时间序列的变数，因为它们的总方差贡献达99.26%。在这四个主成分序列中的决定性周期用周期图和最大熵方法加以揭露。对一维变量zi,(i=1,2,3,4)的ARMA（p,q）的模型识别用Pandit-Wu方法进行，这样就可求得实验模型。用zi模型的外推值来预报月温度场。距平预报的命中率评分为78.3%，高于目前的业务长期天气预报。 相似文献