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Baiquan Zhou and Panmao Zhai

Abstract

This study aims to establish an analog prediction model for forecasting daily persistent extreme precipitation (PEP) during a PEP event (PEPE) using the temporal sequences of predictors with different weights applied in the atmospheric spatial field. The predictors are atmospheric variables in areas where the key influential systems of a PEPE are active in the THORPEX Interactive Grand Global Ensemble (TIGGE) dataset. By means of the cosine similarity measure and the cuckoo search technique, a forecast model was established and named the Key Influential Systems Based Analog Model (KISAM). Validations through threat scores (TSs) and root-mean-square errors for PEP during 17–25 June 2010 indicate that KISAM is able to identify the approaching PEP earlier and yield a more accurate forecast for the location and intensity of PEP than direct model output (DMO) at 3-day and longer lead times in the Yangtze–Huai River valley. For the independent PEPE case on 17–19 June 2010, KISAM is able to predict the PEPE about 8 days in advance. That is much earlier than with DMO. In addition, KISAM produces better intensity forecasts and predicts the extent of the PEPE better than DMO at the same lead time of 5 days. In terms of the forecast experiments during June 2010 and 2015, KISAM shows relatively stronger capacity than DMO in predicting the occurrence and intensity of extreme precipitation (EP) and PEP events at lead times of 1 week or even longer. Through validation of more EP, better performance of KISAM compared to DMO on average is further confirmed at 3-day and longer lead times.

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Yang Chen and Panmao Zhai

Abstract

Using a composite analysis, the typical precursor circulation configuration from the lower to the upper troposphere responsible for persistent extreme precipitation events (PEPEs) of double-blocking-high type in central-eastern China is identified. The potential of these precursors is further assessed based on the composites of normalized anomalies. The composite results reveal that at 500 hPa, about 2 weeks prior to the onset of PEPEs, a positive height anomaly progresses toward the Ural Mountains region from 30°E and another positive anomaly extends southwest from high latitudes toward the Sea of Okhotsk. Afterward, these two positive anomalies grow in magnitude in situ. The double blocking highs are finally well established with height anomalies of 2.4 and 1.8 standard deviations above normal, respectively. At 850 hPa, an anomalous anticyclone originating from the equatorial western Pacific migrates northwestward 1 week prior to the event occurrence, resulting in a greatly intensified moisture transport toward central-eastern China with a magnitude anomaly over four standard deviations above normal. In the upper troposphere, the eastward-extended South Asia high and the southward-displaced westerlies combine to provide favorable upper-level divergence for PEPEs.

These composites of the anomalies and normalized anomalies may offer forecasters some useful clues in recognizing significant weather events about 1–2 weeks in advance of an event.

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Panmao Zhai and Robert E. Eskridge

Abstract

Twice daily radiosonde data from selected stations in the United States (period 1948 to 1990) and China (period 1958 to 1990) were sorted into time series. These stations have one sounding taken in darkness and the other in sunlight. The analysis shows that the 0000 and 1200 UTC time series are highly correlated. Therefore, the Easterling and Peterson technique was tested on the 0000 and 1200 time series to detect inhomogeneities and to estimate the size of the biases. Discontinuities were detected using the difference series created from the 0000 and 1200 UTC time series. To establish that the detected bias was significant, a t test was performed to confirm that the change occurs in the daytime series but not in the nighttime series.

Both U.S. and Chinese radiosonde temperature and humidity data include inhomogeneities caused by changes in radiosonde sensors and observation times. The U.S. humidity data have inhomogeneities that were caused by instrument changes and the censoring of data. The practice of reporting relative humidity as 19% when it is lower than 20% or the temperature is below −40°C is called censoring. This combination of procedural and instrument changes makes the detection of biases and adjustment of the data very difficult. In the Chinese temperatures, them are inhomogeneities related to a change in the radiation correction procedure.

Test results demonstrate that a modified Easterling and Peterson method is suitable for use in detecting and adjusting time series radiosonde data.

Accurate stations histories are very desirable. Stations histories can confirm that detected inhomogeneities are related to instrument or procedural changes. Adjustments can then he made to the data with some confidence.

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Panmao Zhai and Robert E. Eskridge

Abstract

Chinese radiosonde data from 1970 to 1990 are relatively homogeneous in time and are used to examine the climatology, trends, and variability of China’s atmospheric water vapor content. The climatological distribution of precipitable water (PW) is primarily dependent on surface temperature. Influenced by the east Asia monsoon, China’s precipitable water exhibits very large seasonal variations. Station elevation is also a dominant factor affecting water vapor distribution in China.

An increase (decrease) in precipitable water over China is associated with an increase (decrease) of precipitation in most regions. Increases in the percentage of PW relative to climatology are greater in winter and spring than in summer and autumn.

Interannual variation and trends in precipitable water and surface temperature are closely correlated in China, confirming a positive “greenhouse” feedback. Interannual variations between precipitable water and precipitation are also significantly correlated.

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Baiquan Zhou, Panmao Zhai, and Ruoyun Niu

Abstract

Two persistent extreme precipitation events (PEPEs) that caused severe flooding in the Yangtze–Huai River valley in summer 2016 presented a significant challenge to operational forecasters. To provide forecasters with useful references, the capacity of two objective forecast models in predicting these two PEPEs is investigated. The objective models include a numerical weather prediction (NWP) model from the European Centre for Medium-Range Weather Forecasts (ECMWF), and a statistical downscaling model, the Key Influential Systems Based Analog Model (KISAM). Results show that the ECMWF ensemble provides a skillful spectrum of solutions for determining the location of the daily heavy precipitation (≥25 mm day−1) during the PEPEs, despite its general underestimation of heavy precipitation. For lead times longer than 3 days, KISAM outperforms the ensemble mean and nearly one-half or more of all the ensemble members of ECMWF. Moreover, at longer lead times, KISAM generally performs better in reproducing the meridional location of accumulated rainfall over the two PEPEs compared to the ECMWF ensemble mean and the control run. Further verification of the vertical velocity that affects the production of heavy rainfall in ECMWF and KISAM implies the quality of the depiction of ascending motion during the PEPEs has a dominating influence on the models’ performance in predicting the meridional location of the PEPEs at all lead times. The superiority of KISAM indicates that statistical downscaling techniques are effective in alleviating the deficiency of global NWP models for PEPE forecasts in the medium range of 4–10 days.

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Ruoyun Niu, Panmao Zhai, and Baiquan Zhou

Abstract

The forecast performances of the East Asian summer monsoon (EASM) and South Asian summer monsoon (SASM) by six THORPEX Interactive Grand Global Ensemble (TIGGE) centers during the summers of 2008–13 were evaluated to reflect the current predictability of state-of-the-art numerical weather prediction. The results show that the EASM is overestimated by all TIGGE centers except the Canadian Meteorological Centre (CMC). The SASM is overestimated by the European Centre for Medium-Range Weather Forecasts (ECMWF), the China Meteorological Administration (CMA), and the CMC, but is underpredicted by the Japan Meteorological Agency (JMA). Additionally, the SASM is overestimated for early lead times and underestimated for longer lead times by the National Centers for Environmental Prediction (NCEP) and the Met Office (UKMO). Further analysis suggests that such biases are likely associated with land–sea thermal contrasts. The EASM surge is overestimated by the NCEP and CMA and mainly underestimated by the others. The bias predictabilities for the SASM surge are similar to those of the SASM. The peaks of the SASM and EASM, including their surges, are mainly underestimated, whereas the valleys are mostly overestimated. Overall, the ECMWF and UKMO have the highest forecast skill in predicting the SASM and EASM and both have respective advantages. The TIGGE centers generally show higher skill in predicting the SASM than the EASM, and their skill in forecasting the SASM and EASM is superior to that for their respective surges. Moreover, bias-correction forecast skills show improvement with higher correlation coefficients in raw forecast verification.

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Panmao Zhai, Xuebin Zhang, Hui Wan, and Xiaohua Pan

Abstract

Based on a newly developed daily precipitation dataset of 740 stations in China and more robust trend detection techniques, trends in annual and seasonal total precipitation and in extreme daily precipitation, defined as those larger than its 95th percentile for the year, summer, and winter half years, have been assessed for the period 1951–2000. Possible links between changes in total precipitation and frequency of extremes have also been explored. The results indicate that there is little trend in total precipitation for China as a whole, but there are distinctive regional and seasonal patterns of trends. Annual total precipitation has significantly decreased over southern northeast China, north China, and over the Sichuan Basin but significantly increased in western China, the Yangtze River valley, and the southeastern coast. In western China, precipitation increase has been observed for both cold and warm seasons. However, trends differ from one season to another in eastern China. Spring precipitation has increased in southern northeast China and north China but decreased significantly in the midreach of the Yangzte River. The summer precipitation trend is very similar to that of annual totals. Autumn precipitation has generally decreased throughout eastern China. In winter, precipitation has significantly decreased over the northern part of eastern China but increased in the south. The number of rain days has significantly decreased throughout most parts of China with northwest China being an exception. Meanwhile, precipitation intensity has significantly increased. This suggests that the precipitation increase in western China is due to the increase in both precipitation frequency and intensity. In eastern China, the impact of reduced number of rain days seems to be more dominant in the north while the influence of enhanced intensity prevails in the south. Over regions with increasing precipitation trends, there have been much higher than normal frequency of precipitation extreme events. For example, significant increases in extreme precipitation have been found in western China, in the mid–lower reaches of the Yangtze River, and in parts of the southwest and south China coastal area. A significant decrease in extremes is observed in north China and the Sichuan Basin. Trends in the number of extremes and total precipitation from nonextreme events are generally in phase. An exception is southwest China where an increase of extreme events is associated with a decrease in total nonextreme precipitation.

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Hui Li, Panmao Zhai, Yang Chen, and Er Lu

Abstract

In this study, cases of the East Asia–Pacific (EAP) teleconnection pattern not responsible for persistent precipitation processes in the Yangtze River valley (YRV) have been investigated. The results suggest that such a type of EAP pattern has some linkage with persistent precipitation processes in south China (SC) with the following properties: 1) in response to the negative SSTAs and anticyclone near the Philippines, the meridional energy propagates from the low latitudes over the north of the Philippines; 2) the western Pacific subtropical high (WPSH) then intensifies and extends westward; 3) a meridional triple structure of the EAP teleconnection pattern is established; 4) at the same time, the cyclonic circulation over northeastern China introduces cold and dry air to the lower latitudes, merging with the water vapor into SC and leading to heavy precipitation from the fringe of the WPSH, the South China Sea, and the Bay of Bengal and the combination of systems persists for at least 3 days, leading to the persistent precipitation processes in SC; and 5) compared with the EAP teleconnection responsible for the precipitation in YRV, the positions of the three centers in the mid- and low latitudes are more southerly located than the YRV EAP centers. Further study indicates that the ocean surface heat conditions in the areas near the Philippines seem to be important in affecting the EAP teleconnection pattern for persistent precipitation processes in SC. Finally, all of the cases with persistent precipitation in SC during 1961–2010 linked with the EAP pattern have been investigated; the results are consistent with the above conclusions.

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Yuwei Zhang, Donghai Wang, Panmao Zhai, and Guojun Gu

Abstract

The research explores the applicability of the gridded (level 3) monthly tropospheric water vapor (version 5) retrievals from the Atmospheric Infrared Sounder (AIRS) instrument and the Advanced Microwave Sounding Unit (AMSU) on board the NASA Aqua satellite over the Tibetan Plateau by comparing them with carefully processed radiosonde data. Local correlation analyses indicate that below 200 hPa, the AIRS/AMSU monthly water vapor retrievals are highly consistent with radiosondes over the whole plateau region, especially in the southeastern part and between 300 and 600 hPa. Relative deviation analyses further show that the differences between monthly mean AIRS/AMSU water vapor retrieval data and radiosondes are, in general, small below 250 hPa, in particular between 300 and 600 hPa and in high-altitude areas. Combined with a further direct comparison between AIRS/AMSU water vapor vertical retrievals and radiosonde observations averaged over the entire domain, these results suggest that the gridded monthly AIRS/AMSU water vapor retrievals can provide a very good account of spatial patterns and temporal variations in tropospheric water vapor content in the Tibetan Plateau region, in particular below 200 hPa. However, differences between AIRS/AMSU retrievals and radiosondes are seen at various levels, in particular above the level of 250 hPa. Therefore, for detailed quantitative analyses of water budget in the atmosphere and the entire water cycle, AIRS/AMSU retrieval data may need to be corrected or trained using radiosondes. Two fitting functions are derived for warm and cold seasons, although the seasonal difference is generally small.

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Pavel Ya. Groisman, Eugene L. Genikhovich, and Pan-Mao Zhai

This paper is a continuation of empirical studies of cloud and snow cover effects on climate based on a blend of observational meteorological data for the past several decades. It employs the idea that the analysis of climate variability observed during the period of intensive instrumental observations can provide “overall estimates” of these effects.

A climatology of clear skies for northern extratropical lands is presented in the form of deviations from the average climate conditions. Clouds are an internal component of the climate system, and these deviations indicate specific climate conditions associated with clear skies. At the same time, they may be considered as estimates of the overall cloud effect on the regional climate. A similar approach is applied to estimate the potential effect of snow on the ground, and an attempt is made to divide the effects of snow and clouds.

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