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  • Author or Editor: Qing Wang x
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Jamie MacMahan
,
Ed Thornton
,
Jessica Koscinski
, and
Qing Wang

Abstract

Surfzone sensible heat flux (H S,SZ) obtained through direct eddy-covariance estimates was measured at four different sandy beach sites along Monterey Bay, California. The H S,SZ source region is estimated from a footprint probability distribution function (pdf) model and is only considered when at least 70% of the footprint pdf occupies the surfzone. The measured H S,SZ is 2 times the modeled interfacial sensible heat (H S,int) using COARE3.5. A formulation for estimating sensible heat flux from spray droplets (H S,spray) generated during depth-limited wave breaking is developed. The sea-spray generation function for droplet radii ranging over 0.1 < r o < 1000 μm is based on self-similar spectra of spray droplets measured from the surfzone forced by the average depth-limited breaking wave dissipation across the surfzone. However, it is shown that the size of the spume droplets that contribute to H S,spray is limited owing to the relatively short residence time in air as the droplets fall to the sea surface during wave breaking. The addition of the surfzone-modeled H S,spray to the COARE3.5 H S,int gives values similar to the observed surfzone H S,SZ, highlighting the importance of depth-limited wave-breaking processes to sensible heat flux. Measured H S,SZ values are an order of magnitude larger than simultaneous open ocean observations.

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Trent W. Ford
,
Qing Wang
, and
Steven M. Quiring

Abstract

The ability to use in situ soil moisture for large-scale soil moisture monitoring, model and satellite validation, and climate investigations is contingent on properly standardizing soil moisture observations. Percentiles are a useful method for homogenizing in situ soil moisture. However, very few stations have been continuously monitoring in situ soil moisture for 20 years or more. Therefore, one challenge in evaluating soil moisture is determining whether the period of record is sufficient to produce a stable distribution from which to generate percentiles. In this study daily in situ soil moisture observations, measured at three separate depths in the soil column at 15 stations in the United States and Canada, are used to determine the record length that is necessary to generate a stable soil moisture distribution. The Anderson–Darling test is implemented, both with and without a Bonferroni adjustment, to quantify the necessary record length. The authors evaluate how the necessary record length varies by location, measurement depth, and month. They find that between 3 and 15 years of data are required to produce stable distributions, with the majority of stations requiring only 3–6 years of data. Not surprisingly, more years of data are required to obtain stable estimates of the 5th and 95th percentiles than of the first, second, and third quartiles of the soil moisture distribution. Overall these results suggest that 6 years of continuous, daily in situ soil moisture data will be sufficient in most conditions to create stable and robust percentiles.

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Yu Wang
,
Hong-Qing Wang
,
Lei Han
,
Yin-Jing Lin
, and
Yan Zhang

Abstract

This study was designed to provide basic information for the improvement of storm nowcasting. According to the mean direction deviation of storm movement, storms were classified into three types: 1) steady storms (S storms, extrapolated efficiently), 2) unsteady storms (U storms, extrapolated poorly), and 3) transitional storms (T storms). The U storms do not fit the linear extrapolation processes because of their unsteady movements. A 6-yr warm-season radar observation dataset was used to highlight and analyze the differences between U storms and S storms. The analysis included geometric features, dynamic factors, and environmental parameters. The results showed that storms with the following characteristics changed movement direction most easily in the Beijing–Tianjin region: 1) smaller storm area, 2) lower thickness (echo-top height minus base height), 3) lower movement speed, 4) weaker updrafts and the maximum value located in the mid- and upper troposphere, 5) storm-relative vertical wind profiles dominated by directional shear instead of speed shear, 6) lower relative humidity in the mid- and upper troposphere, and 7) higher surface evaporation and ground roughness.

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Cheng-Dong Xu
,
Jin-Feng Wang
,
Mao-Gui Hu
, and
Qing-Xiang Li

Abstract

A probabilistic spatiotemporal approach based on a spatial regression test (SRT-PS) is proposed for the quality control of climate data. It provides a quantitative probability that represents the uncertainty in each temperature observation. The assumption of SRT-PS is that there might be large uncertainty in the station record if there is a large residual difference between the record estimated in the spatial regression test and the true station record. The result of SRT-PS is expressed as a confidence probability ranging from 0 to 1, where a value closer to 1 indicates less uncertainty. The potential of SRT-PS to estimate quantitatively the uncertainty in temperature observations was demonstrated using an annual temperature dataset for China for the period 1971–2000 with seeded errors. SRT-PS was also applied to assess a real dataset, and was compared with two traditional quality control approaches: biweight mean and biweight standard deviation and SRT. The study provides a new approach to assess quantitatively the uncertainty in temperature observations at meteorological stations.

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Yuan-Chien Lin
,
Wen-Hsin Wang
,
Chun-Yeh Lai
, and
Yong-Qing Lin

Abstract

Heavy rainfall and strong wind are the two main sources of disasters that are caused by tropical cyclones (TCs), and typhoons with different characteristics may induce different agricultural losses. Traditionally, the classification of typhoon intensity has not considered the amount of rainfall. Here, we propose a novel approach to calculate the typhoon type index (TTI). A positive TTI represents a “wind type” typhoon, where the overall damage in a certain area from TCs is dominated by strong wind. On the other hand, a negative TTI represents a “rain type” typhoon, where the overall damage in a certain area from TCs is dominated by heavy rainfall. From the TTI, the vulnerability of crop losses from different types of typhoons can be compared and explored. For example, Typhoon Kalmaegi (2008) was classified as a rain-type typhoon (TTI = −1.22). The most affected crops were oriental melons and leafy vegetables. On the contrary, Typhoon Soudelor (2015) was classified as a significant wind-type typhoon in most of Taiwan (TTI = 1.83), and the damaged crops were mainly bananas, bamboo shoots, pomelos, and other crops that are easily blown off by strong winds. Through the method that is proposed in this study, we can understand the characteristics of each typhoon that deviate from the general situation and explore the damages that are mainly caused by strong winds or heavy rainfall at different locations. This approach can provide very useful information that is important for the disaster analysis of different agricultural products.

Open access
Marcela Ulate
,
Qing Wang
,
Tracy Haack
,
Teddy Holt
, and
Denny P. Alappattu

Abstract

In this study, we use observational and numerical model data from the Coupled Air Sea Processes and Electromagnetic Ducting Research (CASPER) field campaign to describe the mean refractive conditions offshore Duck, North Carolina. The U.S. Navy operational numerical weather prediction model known as the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) performed well forecasting large-scale conditions during the experiment, with an observed warm bias in SST and cold and dry biases in temperature and humidity in the lowest 2000 m. In general, COAMPS underpredicted the number of ducts, and they were weaker and at lower height than those seen in observations. It was found that there is a noticeable diurnal evolution of the ducts, more over land than over the ocean. Ducts were found to be more frequent over land but overall were stronger and deeper over the ocean. Also, the evaporative duct height increases as one moves offshore. A case study was chosen to describe the electromagnetic properties under different synoptic conditions. In this case the continental atmospheric boundary layer dominates and interacts with the marine atmospheric boundary layer. As a result, the latter moves around 80 km offshore and then back inland after 2 h.

Open access
Yingbin He
,
Dongmei Liu
,
Yanmin Yao
,
Qing Huang
,
Jianping Li
,
Youqi Chen
,
Shuqin Shi
,
Li Wan
,
Shikai Yu
, and
Deying Wang

Abstract

In this paper, an integrated indicator-based system is established to map the suitability of spring soybean cultivation in northeast China. The indicator system incorporates both biophysical and socioeconomic factors, including the effects of temperature, precipitation, and sunshine on the individual development stages of the spring soybean life cycle. Spatial estimates of crop suitability derived using this indicator system are also compared with spring soybean planting areas to identify locations where there is scope for structural adjustment in soybean farming. Results of this study indicate that northeast China is moderately suited to spring soybean cultivation. Areas classified as suitable, moderately suitable, and unsuitable for soybean cultivation, respectively, occupy approximately 9.09 × 104, 11.45 × 104, and 7.99 × 104 km2, accounting for 11.5%, 10.11%, and 14.49% of the total area of northeast China. The Songnen and Sanjiang Plains are identified as the most and least suitable places, respectively, for spring soybean growth. A comparative analysis indicates that the suitable, moderately suitable, and unsuitable areas account for 24.78%, 46.30%, and 28.92%, respectively, of the total area presently under soybean cultivation. The analysis suggests that soybean cultivation in Heilongjiang Province is generally unfavorable, with equivalent percentages of 15.39%, 51.70%, and 32.91%. Results suggest that agricultural structural adjustment may be required to encourage farmers to grow spring soybeans. It is anticipated that this study will provide a basis for follow-up studies on crop cultivation suitability.

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Fanxiang Meng
,
Zongliang Wang
,
Qiang Fu
,
Tianxiao Li
,
Xu Yang
,
Ennan Zheng
,
Ge Zhang
,
Qing Zhuang
,
Qiyang Fu
, and
Yuan Zhang

Abstract

The evolution of the average freezing depth and maximum freezing depth of seasonal frozen soil and their correlations with the average winter half-year temperature in Heilongjiang Province in China are analyzed. Linear regression, the Mann–Kendall test, and kriging interpolation are applied to freezing depth data from 20 observation stations in Heilongjiang Province from 1972 to 2016 and daily average temperature data from 34 national meteorological stations collected in the winters of 1972–2020. The results show that the average freezing depth decreases at a rate of 4.8 cm (10 yr)−1 and that the maximum freezing depth decreases at a rate of 10.1 cm (10 yr)−1. The winter half-year average temperature generally shows a fluctuating upward trend in Heilongjiang Province, increasing at a rate of 0.3°C (10 yr)−1. The correlations between the average and maximum freezing depths and the winter half-year average temperature are −0.53 and −0.49, respectively. For every 1°C increase in the average temperature during the winter half of the year, the average freezing depth decreases by 3.85 cm and the maximum freezing depth decreases by 7.84 cm. The average freezing depth sequence mutated in 1987, and the maximum freezing depth sequence mutated in 1988. The average temperature in the winter half-year displayed multiple abrupt changes from 1972 to 2020. The spatial variations in the average and maximum freezing depths are basically consistent with those in the average winter half-year temperature. These research results provide a theoretical basis for the design and site selection of hydraulic structures in cold areas and for regional development and agricultural planning.

Significance Statement

The freeze–thaw balance in the frozen soil environment has been disrupted in recent years, and various degrees of degradation have occurred in the frozen soil. The degradation of frozen soil will further aggravate the greenhouse effect, which in turn will affect the accumulation of water in the soil and will have a significant impact on local agricultural production. This article uses Heilongjiang Province in China as an example. The results show that 1) the temperature in the winter half-year has exhibited an upward trend in recent years, 2) the temperature in the winter half-year has a considerable impact on the frozen soil environment, and 3) the response of the spatial distribution of frozen soil to temperature changes in the winter half-year is revealed.

Free access
Qiong Wu
,
Hong-Qing Wang
,
Yi-Zhou Zhuang
,
Yin-Jing Lin
,
Yan Zhang
, and
Sai-Sai Ding

Abstract

Three infrared (IR) indicators were included in this study: the 10.8-μm brightness temperature (BT10.8), the BT difference between 12.0 and 10.8 μm (BTD12.0–10.8), and the BT difference between 6.7 and 10.8 μm (BTD6.7–10.8). Correlations among these IR indicators were investigated using MTSAT-1R images for summer 2007 over East Asia. Temporal, spatial, and numerical frequency distributions were used to represent the correlations. The results showed that large BTD12.0–10.8 values can be observed in the growth of cumulus congestus and associated with the boundary of different terrain where convection was more likely to generate and develop. The results also showed that numerical correlation between any two IR indicators could be expressed by two-dimensional histograms (HT2D). Because of differences in the tropopause heights and in the temperature and water vapor fields, the shapes of the HT2Ds varied with latitude and the type of underlying surface. After carefully analyzing the correlations among the IR indicators, a conceptual model of the convection life cycle was constructed according to these HT2Ds. A new cloud convection index (CCI) was defined with the combination of BTD12.0–10.8 and BTD6.7–10.8 on the basis of the conceptual model. The preliminary test results demonstrated that CCI could effectively identify convective clouds. CCI value and its time trend could reflect the growth or decline of convective clouds.

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