Extended-range Forecasts Research Articles

Extended-Range Forecasts of Atlantic Tropical Cyclone Events during 2012 Using the ECMWF 32-Day Ensemble Predictions*

Abstract Previous studies have demonstrated the capability of the European Centre for Medium-Range Weather Forecasts (ECMWF) 51-member, 32-day ensemble to forecast tropical cyclone (TC) events (formation and tracks) in the western North Pacific on the extended range (5–30 days). In this study, the performance of the ECMWF ensemble in extended-range forecasting of Atlantic TCs during May–December 2012 is evaluated using similar approaches. The conclusion from this evaluation is that Atlantic TC events have lower forecastability using the ECMWF ensemble than in the western North Pacific. Hurricanes Kirk and Leslie and Tropical Storms (TSs) Joyce and Oscar were successfully forecast in weeks 1–4 and, thus, are labeled as highly forecastable. Somewhat forecastable storms that are only forecast in three of the four weeks include Hurricanes Ernesto, Isaac, Nadine, and Sandy plus TS Florence. The limited forecastable storms that were successful in only the first two weeks include Hurricanes Gordon and Rafael plus TS Debby. The surprising result was that two hurricanes (Chris and Michael) and three TSs (Helene, Patty, and Tony) were not even forecast in week 1 before the starting time in the National Hurricane Center working best track (WBT) for these storms. As was the case in the western North Pacific, a substantial number of false alarm storms (no matches with any WBT) are predicted, with about 35% occurring in the first week. Except for the African wave–type false alarms, three other false alarm types may be easily recognized. A larger sample will be required to statistically verify the reliability of the probabilistic forecasts for the African wave–type ensemble storms.

Meteorological subdivisional-level extended range forecast over India during southwest monsoon 2012

The real-time multi-model ensemble (MME)-based extended range (up to 3 weeks) forecast of monsoon rainfall over India during the 2012 monsoon season is analyzed using the outputs of European Centre for Medium Range Weather Forecasts (ECMWF) monthly forecast coupled model, National Centre for Environmental Prediction (NCEP) Climate Forecast System version 2 coupled model and Japan Meteorological Agency (JMA)’ ensemble prediction system. Although the individual models show useful skill in predicting the extended range forecast of monsoon, the MME forecast is found to be superior compared to these. For the country as a whole, the correlation coefficient (CC) between the observed and MME forecast rainfall departure is found to be statistically significant (99 % level) at least for 2 weeks (up to 18 days). Over the four homogeneous regions of India, the CC is found to be significant (above 95 % level) up to 2 weeks except in case of northeast India, which shows significant CC for week 1 (days 5–11) only. On the meteorological subdivision level (India is divided into 36 meteorological subdivisions) the mean percentage of correct forecast is found to be much higher than the climatology forecast. Considering the complex problem of forecasting of monsoon in the extended range timescales, the MME-based predictions for 2–3 weeks provide skillful results and useful guidance for application in agriculture and other sectors in India.

Extended complex autoregressive model of low-frequency rainfalls over the lower reaches of Yangtze river valley for extended range forecast in 2013

Low-frequency rainfall over the lower reaches of Yangtze river valley (LYRV) and the principal component of the global 850 hPa meridional wind anomalies are adopted to construct an extended complex autoregressive (ECAR) model, which can be applied to the daily forecasting of the low-frequency rainfall component over LYRV in 2013 for the extended range forecast. Results show that this model for the forecasting of the 2030-day rainfalls over LYRV has a good predictive skill up to 43 days, which is able to well predict the nonlinear enhancement processes of low-frequency rainfall component associated with heavy rainstorm process. And the correlation skill of the extended range forecast produced form the ECAR model is superior to the autoregressive model (AR) forecast. This method, in which the complex autoregressive (CAR) models are set up via constructing the extended complex matrix (ECM) for the principal low-frequency time series, provides a new description for the emerging dynamic processes of the interactions between components in climate systems. Based on the development and evolution of the principal 2030-day oscillations of the global circulation, it is help for better forecast the process of heavy rainfall in the early October of 2013 over LYRV for times ahead of about 27 days. In these low-frequency variabilities, the 2030-day oscillation in extratropics over the Southern Hemisphere is one of the main factors causing the changes of the heavy rainfall over LYRV for the extended range during the summer and fall in 2013.

Clustering of Tibetan Plateau Vortices by 10–30-Day Intraseasonal Oscillation*

Abstract Tibetan Plateau (TP) vortices and the related 10–30-day intraseasonal oscillation in May–September 1998 are analyzed using the twice-daily 500-hPa synoptic weather maps, multiple reanalysis datasets, and satellite-retrieved brightness temperature. During the analysis period, distinctively active and suppressed periods of TP vortices genesis are noticed. In 1998, nine active periods of TP vortices occurred, which were largely clustered by the cyclonic circulations associated with the intraseasonal oscillation of 500-hPa relative vorticity. In addition to the well-recognized 30–60-day oscillation, the clustering of TP vorticity in the 1998 summer are more likely modulated by the 10–30-day oscillation, because all active periods of TP vortices fall into the positive phase of the 10–30-day oscillation in 1998. Even in the negative (i.e., anticyclonic) phases of the 30–60-day oscillation, the positive (i.e., cyclonic) 500-hPa 10–30-day oscillation can excite the clustering of TP vortices. This result indicates that the 10–30-day oscillation more directly modulates the activities of TP vortices by providing a favorable (unfavorable) cyclonic (anticyclonic) environment. The analysis of the 10–30-day atmospheric oscillation suggests that the westerly trough disturbances, in conjunction with convective instability due to low-level warm advection from the Indian monsoon region, are important in the clustering of TP vortex activities. In particular, the moisture flux from the southwest boundary of TP is essential to the accumulation of convective energy. Thus, a better understanding and prediction of the 10–30-day intraseasonal oscillation is needed to advance the extended-range forecasting of TP vortices and their downstream impacts on the weather and climate over East Asia.

Analysis of stable components in the extended-range forecast for the coming 10–30 days in winter 2010 and 2011

In this paper we try to extract stable components in the extended-range forecast for the coming 10–30 days by using empirical orthogonal function (EOF) analysis, similarity coefficient, and some other methods based on the National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis daily data. The comparisons of the coefficient of variance of climatological background field and truth data in winter between 2010 and 2011 are made. The method of extracting stable components and climatological background field can be helpful to increase forecasting skill. The forecasting skill improvement of air temperature is better than geopotential height at 500 hPa. Moreover, this method improves the predictability better in the Pacific Ocean. In China, the forecast in winter in Northeast China is more uncertain than in the other parts.

Synoptic verification of medium-extended-range forecasts of the northwest pacific subtropical high and South Asian high based on multi-center TIGGE data

Synoptic verification of medium-extended-range forecasts of the Northwest Pacific subtropical high (NWPSH) and South Asian high (SAH) is performed for the summers of 2010–2012 using TIGGE data from four operational centers at the CMA, ECMWF, JMA, and NCEP. The overall activities of the NWPSH and SAH are examined along with their local characteristics such as the spatial coverage of each high in the East Asian key area (10°–40°N, 105°–130°E), the mean position of the ridge of each high over 110°–122.5°E, the westward extent of the NWPSH ridge, and the eastward extent of the SAH ridge. Focus on the NWPSH and SAH is justified because these two systems have pronounced influences on the summertime persistent heavy rainfall in China. Although the overall activities of both highs are reproduced reasonably well in the TIGGE data, their spatial coverages are reduced in the East Asian key area and both of them are weaker compared with observations. On average, their ridges shift more northward relative to observations. The NWPSH ridge is less westward while the SAH ridge is generally more eastward early in the forecast but too westward later in the forecast. The JMA ensemble prediction system (EPS) produces the best mediumrange (1–10 days) forecasts of the NWPSH based on these metrics, while the ECMWF EPS produces the best medium-range forecasts of the SAH and the most reliable extended-range (11–15 days) forecasts of both highs. Forecasts of the spatial coverage of both highs in the East Asian key area and the mean positions of the ridges are generally valid out to lead times of 7–12 days. By contrast, forecasts of the longitudinal extent of the ridges are typically only valid to lead times of 5–7 days. All the four operational centers’ models produce excellent forecasts of the mean zonal position of the SAH ridge. The ensemble mean forecast is more reliable than the control forecast over the areas where the NWPSH (20°–30°N, 135°–165°E) and SAH (23°–30°N, 70°–100°E) are most active. Forecasts of both highs have advantages and disadvantages in the peripheral areas away from their respective center of high activity.

Advances in research and forecasting of tropical cyclones from 1963–2013

A review of progress over the past 50 years in observing and forecasting of tropical cyclones is presented. Tremendous progress has been made in track forecasting in the past 20 years with the improvement in numerical model guidance and the use of consensus forecasting, and this has contributed to a number of warning centers now issuing five-day track forecasts that are as accurate as three-day forecasts of a decade ago. Techniques are now available to specify the track forecast uncertainty for assessing the risk of a tropical cyclone. With the advent of five-day forecasts, a focus on improved understanding of formation has led to two field experiments. A recent advance has been in extended-range (5–30 days) forecasts of tropical cyclone events (formations and tracks) in the western North Pacific from the ECMWF 32-day ensemble predictions. This advance is a contribution to a goal of seamless forecasting from one day to a season for tropical cyclones. Little progress has been made in intensity forecasting, although the Hurricane Forecast Improvement Project in the United States and recent field experiments may offer some future advances. Some advances in forecasting tropical cyclone impacts such as storm surge, surface waves, and precipitation have been achieved. Future opportunities for continued advances are possible such that improved warnings can lead to reductions in losses of lives and minimizing damages from tropical cyclones.

Diagnosing Santa Ana Winds in Southern California with Synoptic-Scale Analysis

Abstract Santa Ana winds (SAW) are among the most notorious fire-weather conditions in the United States and are implicated in wildfire and wind hazards in Southern California. This study employs large-scale reanalysis data to diagnose SAW through synoptic-scale dynamic and thermodynamic factors using mean sea level pressure gradient and lower-tropospheric temperature advection, respectively. A two-parameter threshold model of these factors exhibits skill in identifying surface-based characteristics of SAW featuring strong offshore winds and extreme fire weather as viewed through the Fosberg fire weather index across Remote Automated Weather Stations in southwestern California. These results suggest that a strong northeastward gradient in mean sea level pressure aligned with strong cold-air advection in the lower troposphere provide a simple, yet effective, means of diagnosing SAW from synoptic-scale reanalysis. This objective method may be useful for medium- to extended-range forecasting when mesoscale model output may not be available, as well as being readily applied retrospectively to better understand connections between SAW and wildfires in Southern California.

Extended range prediction of active-break spells of Indian summer monsoon rainfall using an ensemble prediction system in NCEP Climate Forecast System

This study analyses skill of an extended range prediction system to forecast Indian Summer Monsoon Rainfall (ISMR) 3-4 pentads in advance. A series of 45-d forecast integrations starting from 1 May to 29 September at 5-d interval for 7 years from 2001 to 2007 are performed with an ensemble prediction system (EPS) in NCEP Climate Forecast System Version 1 (CFSV1) model. The sensitivity experiments with different amount of perturbation suggest that full tendency perturbation experiment on all basic variables including humidity at all vertical level shows higher dispersion among forecast than other experiments. Spread-error relationship shows that the present EPS system is under-dispersive. The lower bound of predictability is about 10-12 d and upper bound of predictability is found to be 20-25 d for zonal wind at 850 and 200 hPa. The signal-to-noise ratio (SNR) of precipitation (500 hPa geopotential height) reveals that the predictability limit is about 15(18) d over Indian monsoon region. The monsoon zone area averaged precipitation forecasts averaged over 5-d period (pentads) up to 4 pentad lead time are also evaluated and compared with observation. The anomaly correlation coefficients (ACC) reaches zero after pentad 3 (pentad 5) lead for precipitation (dynamical variables). A probabilistic approach is developed from the EPS for extended range forecast applications. The relative operating characteristic (ROC) curves for three categories of precipitation shows that the prediction skill for active and break is slightly higher compared to that of normal category and skillful probabilistic forecasts can be generated for precipitation even beyond pentad 4 lead.

A preliminary study about the prospects of extended range forecast of tropical cyclogenesis over the north Indian Ocean during 2010 post-monsoon season

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 There were two cyclonic storms formed during the post monsoon season of 2010 viz., “Giri” a very severe cyclonic storm (VSCS) formed on 19th October and crossed the Myanmar coast on 22nd and the second system “Jal” a severe cyclonic storm (SCS) formed on 2nd November and crossed north Tamil Nadu-south Andhra Pradesh coasts, close to north of Chennai on 7th November, which caused lot of damage in Tamil Nadu and south Andhra Pradesh coast associated with not only strong wind but also due to associated heavy rainfall. 
 The real time extended range forecasts in terms of weekly mean of dynamical variables are prepared for two weeks based on the coupled model outputs from ECMWF, NECP and the 2 models average (2MAVE) of both. The operational forecast for days 5-11 of weekly mean wind and relative vorticity based on 14th October, 2010 initial condition indicates cyclonic circulation at low level over the central Bay of Bengal during the period from 18-24 October associated with the very severe cyclone “Giri”. The genesis of the cyclone “Jal” was very much captured in the 2MAVE forecast valid for 12-18 days forecast based on the initial condition of 21st October, 2010. The 2MAVE forecast valid for 1-7 November based on 28 October and 21 October initial conditions (with forecast period of days 5-11 and days 12-18 respectively) also clearly indicated large positive rainfall anomalies over Tamil Nadu coast and adjoining coastal Andhra Pradesh region like that of observed rainfall anomalies. This preliminary study further indicates that the model forecasts anomaly of weekly cyclonic vorticity maximum of about 2.5´10-5 sec-1 combined with a low level convergence anomaly of about -0.8 to -1.0 ´ 10-5 sec-1 may lead to formation of a tropical cyclone. However, more number of cases required to be analysed for the proper identification of the threshold values for intensification of the system into a cyclone.

Opportunities and challenges for extended-range predictions of tropical cyclone impacts on hydrological predictions

Summary An opportunity exists to extend support to the decision-making processes of water resource management and hydrological operations by providing extended-range tropical cyclone (TC) formation and track forecasts in the western North Pacific from the 51-member ECMWF 32-day ensemble. A new objective verification technique demonstrates that the ECMWF ensemble can predict most of the formations and tracks of the TCs during July 2009 to December 2010, even for most of the tropical depressions. Due to the relatively large number of false-alarm TCs in the ECMWF ensemble forecasts that would cause problems for support of hydrological operations, characteristics of these false alarms are discussed. Special attention is given to the ability of the ECMWF ensemble to predict periods of no-TCs in the Taiwan area, since water resource management decisions also depend on the absence of typhoon-related rainfall. A three-tier approach is proposed to provide support for hydrological operations via extended-range forecasts twice weekly on the 30-day timescale, twice-daily on the 15-day timescale, and up to four times a day with a consensus of high-resolution deterministic models.

Extended-range forecasts of the principal 20–30-day oscillation of the circulation over East Asia during the summer of 2002

Daily 850-hPa meridional wind fields in East Asia from March to September 2002 were used to establish a model of the principal oscillation pattern (POP). This model was then used to conduct independent extended-range forecasts of the principal temporal and spatial variations in the low-frequency meridional wind field on a time scale of 20–30 days. These variations affect the occurrence of heavy precipitation events in the lower reaches of the Yangtze River valley (LYRV). The results of 135 forecast experiments during the summer half year show that the predicted and observed anomalies are strongly correlated at a lead time of 20 days (mean correlation greater than 0.50). This strong correlation indicates that the model is capable of accurately forecasting the low-frequency variations in meridional wind that corresponded to the 3 heavy precipitation events in the LYRV during the summer of 2002. Further forecast experiments based on data from multiple years with significant 20–30-day oscillations show that these prediction modes are effective tools for forecasting the space-time evolution of the low-frequency circulation. These findings offer potential for improving the accuracy of forecasts of heavy precipitation over the LYRV at lead times of 3–4 weeks.

Forecast scheme and strategy for extended-range predictable components

Although extended-range forecasting has exceeded the limit of daily predictability of weather, there are still partially predictable characteristics of meteorological fields in such forecasts. A targeted forecast scheme and strategy for extended-range predictable components is proposed. Based on chaotic characteristics of the atmosphere, predictable components and unpredictable random components are separated by using the standpoint of error growth in a numerical model. The predictable components are defined as those with slow error growth at a given range, which are not sensitive to small errors in initial conditions. A numerical model for predictable components (NMPC) is established, by filtering random components with poor predictability. The aim is to maintain predictable components and avoid the influence of rapidly growing forecast errors on small scales. Meanwhile, the analogue-dynamical approach (ADA) is used to correct forecast errors of predictable components, to decrease model error and statistically take into account the influence of random components. The scheme is applied to operational dynamical extended-range forecast (DERF) model of the National Climate Center of China Meteorological Administration (NCC/CMA). Prediction results show that the scheme can improve forecast skill of predictable components to some extent, especially in high predictability regions. Forecast skill at zonal wave zero is improved more than for ultra-long waves and synoptic-scale waves. Results show good agreement with predictability of spatial scale. As a result, the scheme can reduce forecast errors and improve forecast skill, which favors operational use.

The impact of the MJO on clusters of wintertime circulation anomalies over the North American region

Recent studies have shown that the Madden–Julian Oscillation (MJO) impacts the leading modes of intraseasonal variability in the northern hemisphere extratropics, providing a possible source of predictive skill over North America at intraseasonal timescales. We find that a k-means cluster analysis of mid-level geopotential height anomalies over the North American region identifies several wintertime cluster patterns whose probabilities are strongly modulated during and after MJO events, particularly during certain phases of the El Nino-Southern Oscillation (ENSO). We use a simple new optimization method for determining the number of clusters, k, and show that it results in a set of clusters which are robust to changes in the domain or time period examined. Several of the resulting cluster patterns resemble linear combinations of the Arctic Oscillation (AO) and the Pacific/North American (PNA) teleconnection pattern, but show even stronger responses to the MJO and ENSO than clusters based on the AO and PNA alone. A cluster resembling the positive (negative) PNA has elevated probabilities approximately 8–14 days following phase 6 (phase 3) of the MJO, while a negative AO-like cluster has elevated probabilities 10–20 days following phase 7 of the MJO. The observed relationships are relatively well reproduced in the 11-year daily reforecast dataset from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). This study statistically links MJO activity in the tropics to common intraseasonal circulation anomalies over the North American sector, establishing a framework that may be useful for improving extended range forecasts over this region.

An Indian monsoon intraseasonal oscillations (MISO) index for real time monitoring and forecast verification

The wet/dry spells of the Indian summer monsoon (ISM) rainfall are governed by northward propagating boreal summer monsoon intraseasonal oscillations (MISO). Unlike for the Madden Julian Oscillation (e.g. RMM indices, Wheeler and Hendon in Mon Weather Rev 132:1917–1932, 2004), a low dimensional real-time monitoring and forecast verification metric for the MISO is not currently available. Here, for the first time, we present a real time monitoring index developed for identifying the amplitude and phase of the MISO over the ISM domain. The index is constructed by applying extended empirical orthogonal function (EEOF) analysis on daily unfiltered rainfall anomalies averaged over the longitudinal domain 60.5°E–95.5°E. The gravest two modes of the EEOFs together explain about 23 % of the total variance, similar to the variance explained by MISO in observation. The pair of first two principal components (PCs) of the EEOFs is named as MISO1 and MISO2 indices which together represent the evolution of the MISOs in a low dimensional phase space. Power spectral analysis reveals that the MISO indices neatly isolate the MISO signal from the higher frequency noise. It is found that the current amplitude and phase of the MISO can be estimated by preserving a memory of at least 15 days. Composite pictures of the spatio-temporal evolution of the MISOs over the ISM domain are brought out using the MISO indices. It is further demonstrated that the MISO indices can be used in the quantification of skill of extended range forecasts of MISOs. Since the MISO index does not rely on any sort of time filtering, it has great potential for real time monitoring of the MISO and may be useful in developing some prediction scheme.

Association of U.S. tornado occurrence with monthly environmental parameters

Monthly U.S. tornado numbers are here related to observation‐based monthly averaged atmospheric parameters. Poisson regression is used to form an index which captures the climatological spatial distribution and seasonal variation of tornado occurrence, as well as year‐to‐year variability, and provides a framework for extended range forecasts of tornado activity. Computing the same index with predicted atmospheric parameters from a comprehensive forecast model gives some evidence of the predictability of monthly tornado activity.

Study of the stable components in extended-range forecasting for the coming 1030 days during the snow storm event in January 2008

In this paper we extract components in extended-range forecast for the coming 10-30 days by the Butterworth Band-pass filter using the NCEP/NCAR reanalysis daily data of geopotential height from 1978 to 2007 and from January 6th to February 4th, and at the same time extract the basic function of climate state by empirical orthogonal function (EOF). And we use the same way to deal with the daily data of geopotential height during the snow storm event in January 2008 by the Butterworth Band-pass Filter. We use the contribution rate to explain the variance of EOF and the elements which influence this weather process in a period of 1030 days. Stable components in extended-range forecast for the coming 1030 days can be divided into two parts according to the contribution rate analysis: climatic stable components and abnormal stable components. Results show that climatic stable components are in the subject status during the snow storm event in January 2008 while abnormal stable components are equivalent to a disturbed value superimposed on climatic stable components. The influence of abnormal stable components cannot be neglected, and they can play quite a significant role. The circulation patterns of abnormal stable components correspond well to anomalies in Pacific region. These conclusions deepen our understanding of 1030 days components and provide a new way to think and solve the problem of extended range forecast for the coming 1030 days.

동아시아 여름몬순 지수의 자기조직화지도(SOM)에 의한 강수량의 계절 내 진동 분류

The nonlinear characteristics of summer monsoon intraseasonal oscillation (ISO) in precipitation, which is manifested as fluctuations in convection and circulation, is one of the major difficulty on the prediction of East Asian summer monsoon (EASM). The present study aims to identify the spatial distribution and time evolution of nonlinear phases of monsoon ISO. In order to classify the different phases of monsoon ISO, Self-Organizing Map(SOM) known as a nonlinear pattern recognition technique is used. SOM has a great attractiveness detecting self- similarity among data elements by grouping and clustering such self-similar components. The four important patterns are demonstrated as Meiyu-Baiu, Changma, post-Changma, and dry-spell modes. It is found that SOM well captured the formation of East Asian monsoon trough during early summer and its northward migration together with enhanced convection over subtropical western Pacific and regionally intensive precipitation including Meiyu, Changma and Baiu. The classification of fundamental large scale spatial pattern and evolutionary history of nonlinear phases of monsoon ISO provides the source of predictability for extended-range forecast of summer precipitation.

Invariant measures and asymptotic Gaussian bounds for normal forms of stochastic climate model

The systematic development of reduced low-dimensional stochastic climate models from observations or comprehensive high dimensional climate models is an important topic for atmospheric low-frequency variability, climate sensitivity, and improved extended range forecasting. Recently, techniques from applied mathematics have been utilized to systematically derive normal forms for reduced stochastic climate models for low-frequency variables. It was shown that dyad and multiplicative triad interactions combine with the climatological linear operator interactions to produce a normal form with both strong nonlinear cubic dissipation and Correlated Additive and Multiplicative (CAM) stochastic noise. The probability distribution functions (PDFs) of low frequency climate variables exhibit small but significant departure from Gaussianity but have asymptotic tails which decay at most like a Gaussian. Here, rigorous upper bounds with Gaussian decay are proved for the invariant measure of general normal form stochastic models. Asymptotic Gaussian lower bounds are also established under suitable hypotheses.

Origin and predictability of the extreme negative NAO winter of 2009/10

[1] The winter of 2009/2010 was one of the most negative winters of the North Atlantic Oscillation (NAO) during the last 150 years. While most operational extended-range forecasting systems had difficulties in predicting the onset of the negative NAO phase, once established, extended-range forecasts were relatively skilful in predicting its persistence. Here, the origin and predictability of the unusual winter of 2009/10 are explored through numerical experimentation with the ECMWF Monthly forecasting system. More specifically, the role of anomalies in sea surface temperature (SST) and sea ice, the tropical atmospheric circulation, the stratospheric polar vortex, solar insolation and near surface temperature (proxy for snow cover) are examined. None of these anomalies is capable of producing the observed NAO anomaly, especially in terms of its magnitude. The results of this study support the hypothesis that internal atmospheric dynamical processes were responsible for the onset and persistence of the negative NAO phase during the 2009/10 winter.