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Jian Shi and Weihong Qian

Abstract

Using the daily mean anomalies of atmospheric variables from the NCEP Reanalysis-1 (NCEP R1), this study reveals the connection between anomalous zonal activities of the South Asian high (SAH) and Eurasian climate anomalies in boreal summer. An analysis of variance identifies two major domains with larger geopotential height variability located in the eastern and western flanks of the SAH at around 100 and 150 hPa, respectively. For both eastern and western domains, extreme events are selected during 1981–2014 when normalized height anomalies are greater than 1.0 (less than −1.0) standard deviation for at least 10 consecutive days. Based on these events, four SAH modes that include strong and weak Tibetan modes (STM and WTM, respectively) and strong and weak Iranian modes (SIM and WIM, respectively) are defined to depict the zonal SAH features. The positive composite in the eastern (western) domain indicates the STM (SIM) manifests a robust wavelike pattern with an anomalous low at 150 hPa, and surface cold and wet anomalies over Mongolia and northern China (Kazakhstan and western Siberia) are surrounded by three anomalous highs at 150 hPa and surface warm and dry anomalies over Eurasia. Opposite distributions are also evident in the negative composites of the two domains (WTM and WIM). The surface air temperature anomalies are the downward extension of an anomalous air column aloft while the precipitation anomalies are directly associated with the height anomalies above the air column.

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Weihong Qian, Ning Jiang, and Jun Du

Abstract

Mathematical derivation, meteorological justification, and comparison to model direct precipitation forecasts are the three main concerns recently raised by Schultz and Spengler about moist divergence (MD) and moist vorticity (MV), which were introduced in earlier work by Qian et al. That previous work demonstrated that MD (MV) can in principle be derived mathematically with a value-added empirical modification. MD (MV) has a solid meteorological basis. It combines ascent motion and high moisture: the two elements necessary for rainfall. However, precipitation efficiency is not considered in MD (MV). Given the omission of an advection term in the mathematical derivation and the lack of precipitation efficiency, MD (MV) might be suitable mainly for heavy rain events with large areal coverage and long duration caused by large-scale quasi-stationary weather systems, but not for local intense heavy rain events caused by small-scale convection. In addition, MD (MV) is not capable of describing precipitation intensity. MD (MV) worked reasonably well in predicting heavy rain locations from short to medium ranges as compared with the ECMWF model precipitation forecasts. MD (MV) was generally worse than (though sometimes similar to) the model heavy rain forecast at shorter ranges (about a week) but became comparable or even better at longer ranges (around 10 days). It should be reiterated that MD (MV) is not intended to be a primary tool for predicting heavy rain areas, especially in the short range, but is a useful parameter for calibrating model heavy precipitation forecasts, as stated in the original paper.

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Weihong Qian, Lingshen Quan, and Shaoyin Shi

Abstract

In previous studies, limited meteorological observations were used to investigate the temporal–spatial changes of dust storms in China. Here, the authors use the daily 850-hPa geopotential height of NCEP–NCAR reanalysis for 1948–99 to examine the vortex fluctuations, which represent daily cyclone activity in east Asia. They also use the 1000-hPa air temperature data to explain the decadal change of the cyclone activity. In addition, the grid cyclone frequency for 1948–99 and the temperature and precipitation for 1950–98 are used to calculate the correlation with the dust weather frequency (for 1954–98) in China.

Results show that the interannual variability and long-term trend among dust storm frequency, dust weather frequency, air temperature, and cyclone frequency exist in northern China. In the eastern part of China, the frequencies of dust storms and dust weather in the 1950s–70s were about twice that after the mid-1980s. The reason for this feature may be due to the warming in Mongolia and cooling in northern China that reduced the meridional temperature gradient, resulting in the reduced cyclone frequency in northern China. In the Tarim Basin, the high-frequency dust storms have been attributed to less precipitation and to the arid-heating climate.

The frequency of dust storms (dust weather) is strongly related to the low air temperature in the prior winter season and the high-frequency cyclone activity in the spring season for most parts of eastern China. Based on this relationship, an index describing the dust weather (dust storm) frequency has been formulated. This index can well calibrate the variability of dust weather (dust storms) in northern China, except for the Xinjiang region in far northwest China.

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Weihong Qian, Ning Jiang, and Jun Du

Abstract

Although the use of anomaly fields in the forecast process has been shown to be useful and has caught forecasters’ attention, current short-range (1–3 days) weather analyses and forecasts are still predominantly total-field based. This paper systematically examines the pros and cons of anomaly- versus total-field-based approaches in weather analysis using a case from 1 July 1991 (showcase) and 41 cases from 1998 (statistics) of heavy rain events that occurred in China. The comparison is done for both basic atmospheric variables (height, temperature, wind, and humidity) and diagnostic parameters (divergence, vorticity, and potential vorticity). Generally, anomaly fields show a more enhanced and concentrated signal (pattern) directly related to surface anomalous weather events, while total fields can obscure the visualization of anomalous features due to the climatic background. The advantage is noticeable in basic atmospheric variables, but is marginal in nonconservative diagnostic parameters and is lost in conservative diagnostic parameters. Sometimes a mix of total and anomaly fields works the best; for example, in the moist vorticity when anomalous vorticity combines with total moisture, it can depict the heavy rain area the best when comparing to either the purely total or purely anomalous moist vorticity. Based on this study, it is recommended that anomaly-based weather analysis could be a valuable supplement to the commonly used total-field-based approach. Anomalies can help a forecaster to more quickly identify where an abnormal weather event might occur as well as more easily pinpoint possible meteorological causes than a total field. However, one should not use the anomaly structure approach alone to explain the underlying dynamics without a total field.

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Weihong Qian, Jun Du, and Yang Ai

Abstract

Comparisons between anomaly and full-field methods have been carried out in weather analysis and forecasting over the last decade. Evidence from these studies has demonstrated the superiority of anomaly to full-field in the following four aspects: depiction of weather systems, anomaly forecasts, diagnostic parameters and model prediction. To promote the use and further discussion of the anomaly approach, this article summarizes those findings.

After examining many types of weather events, anomaly weather maps show at least five advantages in weather system depiction: (1) less vagueness in visually connecting the location of an event with its associated meteorological conditions; (2) clearer and more complete depictions of vertical structures of a disturbance; (3) easier observation of time and spatial evolution of an event and its interaction or connection with other weather systems; (4) simplification of conceptual models by unifying different weather systems into one pattern; and (5) extension of model forecast length due to earlier detection of predictors. Anomaly verification is also mentioned. The anomaly forecast is useful for raising one’s awareness of potential societal impact. Combining the anomaly forecast with an ensemble is emphasized, where a societal impact index is discussed. For diagnostic parameters, two examples are given: an anomalous convective instability index for convection, and seven vorticity and divergence related parameters for heavy rain. Both showed positive contributions from the anomalous fields. For model prediction, the anomaly version of the beta-advection model consistently outperformed its full-field version in predicting typhoon tracks with clearer physical explanation. Application of anomaly global models to seasonal forecasts is also reviewed.

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Jing Huang, Jun Du, and Weihong Qian

Abstract

A total of 163 tropical cyclones (TCs) occurred in the eastern China seas during 1979–2011 with four types of tracks: left turning, right turning, straight moving, and irregular. The left-turning type is unusual and hard to predict. In this paper, 133 TCs from the first three types have been investigated. A generalized beta–advection model (GBAM) is derived by decomposing a meteorological field into climatic and anomalous components. The ability of the GBAM to predict tracks 1–2 days in advance is compared with three classical beta–advection models (BAMs). For both normal and unusual tracks, the GBAM apparently outperformed the BAMs. The GBAM’s ability to predict unusual TC tracks is particularly encouraging, while the BAMs have no ability to predict the left-turning and right-turning TC tracks. The GBAM was also used to understand unusual TC tracks because it can be separated into two forms: a climatic-flow BAM (CBAM) and an anomalous-flow BAM (ABAM). In the CBAM a TC vortex is steered by the large-scale climatic background flow, while in the ABAM, a TC vortex interacts with the surrounding anomalous flows. This decomposition approach can be used to examine the climatic and anomalous flows separately. It is found that neither the climatic nor the anomalous flow alone can explain unusual tracks. Sensitivity experiments show that two anomalous highs as well as a nearby TC played the major roles in the unusual left turn of Typhoon Aere (2004). This study demonstrates that a simple model can work well if key factors are properly included.

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Weihong Qian, Jun Du, Xiaolong Shan, and Ning Jiang

Abstract

Properly including moisture effects into a dynamical parameter can significantly increase the parameter’s ability to diagnose heavy rain locations. The relative humidity–based weighting approach used to extend the moist potential vorticity (MPV) to the generalized moist potential vorticity (GMPV) is analyzed and demonstrates such an improvement. Following the same approach, two new diagnostic parameters, moist vorticity (MV) and moist divergence (MD), have been proposed in this study by incorporating moisture effects into the traditional vorticity and divergence. A regional heavy rain event that occurred along the Yangtze River on 1 July 1991 is used as a case study, and 41 daily regional heavy rain events during the notorious flooding year of 1998 in eastern China are used for a systematic evaluation. Results show that after the moisture effects were properly incorporated, the improved ability of all three parameters to capture a heavy rain area is significant (statistically at the 99% confidence level): the GMPV is improved over the MPV by 194%, the MD over the divergence by 60%, and the MV over the vorticity by 34% in terms of the threat score (TS). The average TS is 0.270 for the MD, 0.262 for the MV, and 0.188 for the GMPV. Application of the MV and MD to assess heavy rain potential is not intended to replace a complete, multiscale forecasting methodology; however, the results from this study suggest that the MV and MD could be used to postprocess a model forecast to potentially improve heavy rain location predictions.

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Weihong Qian, Yun Chen, Man Jiang, and Qi Hu

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Abnormally low temperature (LT) events in spring and autumn can cause severe damage to spring and autumn rice production in the mid- to lower Yangtze River valley in China. Advanced predictions of such events can help mitigate their damage. However, the current methods have limited success in describing and predicting those weather events. In this study, a new method is proposed to decompose any one of the meteorological variables into its climatic component and an anomaly, and the anomaly is used in identifying signals of the LT events. The method is used in 20 strong spring LT events and 44 autumn events during 1960–2008. The results show the advanced ability of this method to clearly describe the LT events as compared with the vague indications of such events that are produced by conventional methods currently in practice in China. In addition, the composite profile of vertical anomalies shows that a negative center of geopotential height anomalies at around 300 hPa, coexisting with a strong cold center of temperature anomalies at 850 hPa, is a signature for LT events. For the 44 autumn LT events and 20 spring LT events during 1960–2008, their early disturbances were identified up to 10.2 days and 6.9 days, respectively, before the occurrence of the LT events in the valley. This result suggests that identifying the early disturbances and extracting anomalous signals from the products of current medium-range weather forecast models may be a potential way to improve the prediction skill for LT events in the valley.

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