Long-range forecasting of seasonal air temperature using the time analog method

A method is proposed to forecast monthly mean anomalies of air temperature for three months of the moving season, on the basis of statistical analysis of a selected set of processes with temperature changes analogous to that in the initial season. The set of the analogous processes is used to reveal the most frequent values of temperature anomalies in their grouping by three equiprobable categories. The set of analyses for each station gives a field of predicted anomalies at the CIS area for every month of the season. The anomaly sign forecast verification is presented for 1981–2004.     

Measuring persistence in time series of temperature anomalies

Studies on persistence are important for the clarification of statistical properties of the analyzed time series and for understanding the dynamics of the systems which create these series. In climatology, the analysis of the autocorrelation function has been the main tool to investigate the persistence of a time series. In this paper, we propose to use a more sophisticated econometric instrument. Using this tool, we obtain an estimate of the persistence in global land and ocean and hemispheric temperature time series.     

时间序列预报方法的推广

文中讨论了车贝雪夫多项式值计算误差对作者以前提出的一种新的时间序列预报方法的预报结果的影响,并在此基础上对原来的计算方案作了推广,推广后的算法有利于提高预报准确率。     

Detecting primary precursors of January surface air temperature anomalies in China

This study aims to detect the primary precursors and impact mechanisms for January surface temperature anomaly (JSTA) events in China against the background of global warming, by comparing the causes of two extreme JSTA events occurring in 2008 and 2011 with the common mechanisms inferred from all typical episodes during 1979–2008. The results show that these two extreme events exhibit atmospheric circulation patterns in the mid–high latitudes of Eurasia, with a positive anomaly center over the Ural Mountains and a negative one to the south of Lake Baikal (UMLB), which is a pattern quite similar to that for all the typical events. However, the Eurasian teleconnection patterns in the 2011 event, which are accompanied by a negative phase of the North Atlantic Oscillation, are different to those of the typical events and the 2008 event. We further find that a common anomalous signal appearing in early summer over the tropical Indian Ocean may be responsible for the following late-winter Eurasian teleconnections and the associated JSTA events in China. We show that sea surface temperature anomalies (SSTAs) in the preceding summer over the western Indian Ocean (WIO) are intimately related to the UMLB-like circulation pattern in the following January. Positive WIOSSTAs in early summer tend to induce strong UMLB-like circulation anomalies in January, which may result in anomalously or extremely cold events in China, which can also be successfully reproduced in model experiments. Our results suggest that the WIOSSTAs may be a useful precursor for predicting JSTA events in China.     

Indian Ocean Dipole mode events and austral surface air temperature anomalies

The impact of Indian Ocean Dipole (IOD) mode events on austral surface air temperature (SAT) variability was studied both by statistical analysis of observed/assimilated data and experiments with a mechanistic baroclinic atmospheric model.During the period of analysis (January 1958–December 1999), IOD events had the strongest impact on SAT anomalies during austral spring and hence, the analysis was focussed on this season. IOD events induced large scale, intercontinental correlations of SAT anomalies amongst Australia, Africa and South America. Surface temperature consistently rose (fell) abnormally and coherently in the subtropical regions of these continents during positive (negative) IOD events. Variability during non-IOD years was considerably weaker than during IOD years over these regions.Analysis of stream function anomalies at the 200 hPa level (source: NCEP/NCAR reanalysis) revealed a Rossby-wave train extending from the eastern Indian Ocean into the subtropical regions of the Pacific and Atlantic oceans. Further, the diagnosed Rossby-wave activity flux emanated from the eastern Indian Ocean and propagated along the subtropical and subpolar jet streams qualitatively in agreement with linear wave dynamics. Experiments with idealized forcing in a primitive equation mechanistic atmospheric model suggested that tropical convective anomalies in the Indian Ocean during IOD events likely affects the austral subtropics through stationary Rossby-wave propagation.     

Simulation of maximum surface air temperature over India using the UK Met Office Global Seasonal (GloSea) Model

Summary A comparative study was performed to evaluate the performance of the UK Met Office’s Global Seasonal (GloSea) prediction General Circulation Model (GCM) for the forecast of maximum surface air temperature (T_max) over the Indian region using the model generated hindcast of 15-members ensemble for 16 years (1987–2002). Each hindcast starts from 1^st January and extends for a period of six months in each year. The model hindcast T_max is compared with T_max obtained from verification analysis during the hot weather season on monthly and seasonal scales from March to June. The monthly and seasonal model hindcast climatology of T_max from 240 members during March to June and the corresponding observed climatology show highly significant (above 99.9% level) correlation coefficients (CC) although the hindcast T_max is over-estimated (warm bias) over most parts of the Indian region. At the station level over New Delhi, although the forecast error (forecast-observed) at the monthly scale gradually increases from March to June, the forecast error at the seasonal scale during March to May (MAM) is found to be just 1.67 °C. The GloSea model also simulates well T_max anomalies on monthly and seasonal scales during March to June with the lower Root Mean Square Error (RMSE) of bias corrected forecast (less than 1.2 °C), which is much less than the corresponding RMSE of climatology (reference) forecast. The anomaly CCs (ACCs) over the station in New Delhi are also highly significant (above 95% level) on monthly to seasonal time scales from March to June, except for April. The skill of the GloSea model for the seasonal forecast of T_max as measured from the ACC map and the bias corrected RMSE map is reasonably good during MAM and April to June (AMJ) with higher ACC (significant at 95% level) and lower RMSE (less than 1.5 °C) found over many parts of the Indian regions. Authors’ addresses: D. R. Pattanaik, H. R. Hatwar, G. Srinivasan, Y. V. Ramarao, India Meteorological Department (IMD), New Delhi, India; U. C. Mohanty, P. Sinha, Centre for Atmospheric Sciences, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India; Anca Brookshaw, UK Met Office, UK.     

An improved method for correction of air temperature measured using different radiation shields

The variation of air temperature measurement errors using two different radiation shields （DTR502B Vaisala,Finland,and HYTFZ01,Huayun Tongda Satcom,China） was studied.Datasets were collected in the field at the Daxing weather station in Beijing from June 2011 to May 2012.Most air temperature values obtained with these two commonly used radiation shields were lower than the reference records obtained with the new Fiber Reinforced Polymers （FRP） Stevenson screen.In most cases,the air temperature errors when using the two devices were smaller on overcast and rainy days than on sunny days; and smaller when using the imported rather than the Chinese shield.The measured errors changed sharply at sunrise and sunset,and reached maxima at noon.Their diurnal variation characteristics were,naturally,related to changes in solar radiation.The relationships between the record errors,global radiation,and wind speed were nonlinear.An improved correction method was proposed based on the approach described by Nakamura and Mahrt （2005） （NM05）,in which the impact of the solar zenith angle （SZA） on the temperature error is considered and extreme errors due to changes in SZA can be corrected effectively.Measurement errors were reduced significantly after correction by either method for both shields.The error reduction rate using the improved correction method for the Chinese and imported shields were 3.3％ and 40.4％ higher than those using the NM05 method,respectively.     

Estimation of surface air temperature trends over the Russian Federation territory using the quantile regression method

The results are presented of the estimation of surface air temperature variations in different climatically quasi-homogeneous regions of Russia using the nonparametric method of regression analysis (quantile regression). Daily observation records from 517 weather stations were used. The quantile regression technique used for analyzing the trends in long-term series allows obtaining information on trends for the whole range of quantile values from 0 to 1 of dependent variable distributions. Seasonal and regional features of daily minimum, mean, and maximum air temperature trends are considered in a wide range of quantile values. The proposed method that generalizes long-term trends obt ained for groups of stations by quantile regression, is applied to quasi-homogeneous climate regions identified on the territory of Russia.     

Specification of monthly mean anomalies of surface air temperature in Canada and Alaska

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.     

Seasonal variations of spectra of wind speed and air temperature in the mesoscale frequency range

Seasonal variations of the spectra of wind speed and air temperature in the mesoscale frequency range from 1.3 × 10^-4 to 1.5 × 10^-3 Hz (10 min to 2 h periods) have been studied through observations over land for one year. Spectrographs [time series of isopleths of spectral densities, f · S(f) vs f] of wind speed and air temperature contain occasional peaks that are attributed to short-lived mesoscale atmospheric activity with narrow frequency bands. Significant spectral peaks of wind speed were found in 19% of the total observations in winter, and in 15–16% in the other seasons; for air temperature, they occured in 12% of observations in autumn, and in 16–19% in the other seasons. The peaks most often occurred in the period range from 30 min to 1 h; most had durations less than 24 h. Mesoscale fluctuations of wind speed and air temperature were highly correlated, and in most cases, phase differences were 90–180 ° with air temperature leading wind speed. Significant spectral peaks of wind speed often occurred during northerly seasonal cold winds in winter, and accompanied tropical and/or mid-latitude cyclones in the other seasons. When the peaks occurred, wind speed was usually relatively high and the atmospheric surface layer was unstable.     

用时实资料结合数值产品做温度预报的尝试

通过在Micaps系统中建立一个按钮，实现自动读取当天的最低、最高（用14时值代）气温值以及T10608时和14时的温度预报值，多后自动求解△T，得出温度预告值。     

用时实资料结合数值产品做温度预报的尝试

通过在Micaps系统中建立一个按纽,实现自动读取当天的最低、最高(用14时值代)气温值以及T10608时和14时的温度预报值,然后自动求解△T,得出温度预告值.     

Complexity analysis of the air temperature and the precipitation time series in Serbia

Regional Atmospheric Modeling System (RAMS) was applied to the study of the effect of the topographical altitude of the Tibetan Plateau (TP) on a severe drought event which took place in eastern China from November 2008 to January 2009. Two simulations of this drought event were conducted: a control simulation (CNTRL run) using original model settings and a sensitive simulation (TOPO run), where no change other than to reduce the TP topography by 50 %. The results show that the CNTRL simulation validates RAMS by reproducing this drought event fairly accurately. However, as part of the TOPO simulation, the total heat flux showed a decrease over most parts of the TP, latent heat flux underwent a significant increase over the southeastern TP, contrary to sensible heat, and a universal decrease over eastern China; this led to an increase in precipitation over the southeastern TP and a decrease in precipitation over eastern China. The decrease of total heat flux over the TP is collocated with an anomalous anticyclonic circulation from the TP to the coasts of southeastern China. Changes in atmospheric circulation and low-level water vapor transport pathways were consistent with changes in precipitation. In general, reducing the topographical altitude of the TP worsens drought in eastern China and moreover causes a significant decrease in precipitation over southern China.     

Teleconnections between Ethiopian summer rainfall and sea surface temperature: part II. Seasonal forecasting

A seasonal forecasting system that is capable of skilfully predicting rainfall totals on a regional scale would be of great value to Ethiopia. Here, we describe how a statistical model can exploit the teleconnections described in part 1 of this pair of papers to develop such a system. We show that, in most cases, the predictors selected objectively by the statistical model can be interpreted in the light of physical teleconnections with Ethiopian rainfall, and discuss why, in some cases, unexpected regions are chosen as predictors. We show that the forecast has skill in all parts of Ethiopia, and argue that this method could provide the basis of an operational seasonal forecasting system for Ethiopia.     

用神经网络试报极端气温

用人工神经元技术,筛选出与气温相关性较大的１０个物理量,建立几组样本资料,经过学习和训练,建立预报专家网络,来试报哈尔滨市夏季最高和最低气温。     

Multischeme ensemble forecasting of surface temperature using neural network over Turkey

The ensemble method has long been used to reduce the errors that are caused by initial conditions and/or parameterizations of models in forecasting problems. In this study, neural network (NN) simulations are applied to ensemble weather forecasting. Temperature forecasts averaged over 2 weeks from four different forecasts are used to develop the NN model. Additionally, an ensemble mean of bias-corrected data is used as the control experiment. Overall, ensemble forecasts weighted by NN with feed forward backpropagation algorithm gave better root mean square error, mean absolute error, and same sign percent skills compared to those of the control experiment in most stations and produced more accurate weather forecasts.     

A new multidimensional time series forecasting method based on the EOF iteration scheme

In this paper a new multidimensional time series forecasting scheme based on the empirical orthogonal func-tion (EOF) stepwise iteration process is introduced. The scheme is tested in a series of forecast experiments of Nino3 SST anomalies and Tahiti-Darwin SO index. The results show that the scheme is feasible and ENSO predictable.     

Numerical simulations of anomalies of precipitation and surface air temperature in china in the summer of 1997

1.IntroductionStatisticalstudiesdemonstratedthatinEINinoyearstheprecipitationinsummerintheChangjiangRiverandHuaiheRiverBasinsisprobablyabovethenormalwhileitispossiblybelowthenormalinthenorthernChinaandtheHetao(theGreatBendoftheHuangheRiver)region.ThetemperatureinsummerisusuallylowerthannormalinEastAsia,especiallyinNortheastChina.Therewere6yearswithseverelowtemperaturesince1951,andtheyare1954,1957,1964,1972,1976and1983,whichareallrelatedtotheEINinoyears(seeHuangetal.,1989,1992;Xiangand…