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91.
Because the sound speeds of seawater and seafloor sediment both increase with temperature,the influence of tempera-ture on the bottom reflection characteristics of seafloor sediments needs to be investigated.Based on the calculation of the temperature-controlled experimental measurement data of typical seafloor surface sediment samples,the temperature-dependent acoustic characteristics,including acoustic impedance,acoustic impedance ratio between surface sediment and seawater,and reflection coefficient,were analyzed.The effective density fluid model was used to analyze and explain the reflection coefficient variation of surface sediments with temperature and predict the dispersion characteristics.Results show that the acoustic impedance of the seabed sediment increases with temperature,whereas the acoustic impedance ratio and acoustic reflection coefficient slightly decrease.The acoustic impedance,acoustic impedance ratio,and acoustic reflection coefficient of sandy,silty,and clayey sediments vary similarly with tem-perature variation.Moreover,the influence of temperature on these acoustic characteristics is independent of detection frequencies. 相似文献
92.
Record ozone loss was observed in the Arctic stratosphere in spring 2020. This study aims to determine what caused the extreme Arctic ozone loss. Observations and simulation results are examined in order to show that the extreme Arctic ozone loss was likely caused by record-high sea surface temperatures(SSTs) in the North Pacific. It is found that the record Arctic ozone loss was associated with the extremely cold and persistent stratospheric polar vortex over February–April, and the extremely cold vortex was a result of anomalously weak planetary wave activity. Further analysis reveals that the weak wave activity can be traced to anomalously warm SSTs in the North Pacific. Both observations and simulations show that warm SST anomalies in the North Pacific could have caused the weakening of wavenumber-1 wave activity, colder Arctic vortex, and lower Arctic ozone. These results suggest that for the present-day level of ozone-depleting substances, severe Arctic ozone loss could form again, as long as certain dynamic conditions are satisfied. 相似文献
93.
Land surface temperature(LST) is one of the most important factors in the land-atmosphere interaction process. Raw measured LSTs may contain biases due to instrument replacement, changes in recording procedures, and other non-climatic factors. This study attempts to reduce the above biases in raw daily measurements and achieves a homogenized daily LST dataset over China using 2360 stations from 1960 through 2017. The high-quality land surface air temperature(LSAT)dataset is used to correct the LST warming biases especially evident during cold months in regions north of 40°N due to the replacement of observation instruments around 2004. Subsequently, the Multiple Analysis of Series for Homogenization(MASH) method is adopted to detect and then adjust the daily observed LST records. In total, 3.68 × 103 effective breakpoints in 1.65 × 106 monthly records(about 20%) are detected. A large number of these effective breakpoints are located over large parts of the Sichuan Basin and southern China. After the MASH procedure, LSTs at more than 80% of the breakpoints are adjusted within +/– 0.5°C, and of the remaining breakpoints, only 10% are adjusted over 1.5°C.Compared to the raw LST dataset over the whole domain, the homogenization significantly reduces the mean LST magnitude and its interannual variability as well as its linear trend at most stations. Finally, we perform preliminary analysis upon the homogenized LST and find that the annual mean LST averaged across China shows a significant warming trend [0.22°C(10 yr)–1]. The homogenized LST dataset can be further adapted for a variety of applications(e.g.,model evaluation and extreme event characterization). 相似文献
94.
The role of sea surface temperature (SST) forcing in the development and predictability of tropical cyclone (TC) intensity is examined using a large set of idealized numerical experiments in the Weather Research and Forecasting (WRF) model. The results indicate that the onset time of rapid intensification of TC gradually decreases, and the peak intensity of TC gradually increases, with the increased magnitude of SST. The predictability limits of the maximum 10 m wind speed (MWS) and minimum sea level pressure (MSLP) are ~72 and ~84 hours, respectively. Comparisons of the analyses of variance for different simulation time confirm that the MWS and MSLP have strong signal-to-noise ratios (SNR) from 0-72 hours and a marked decrease beyond 72 hours. For the horizontal and vertical structures of wind speed, noticeable decreases in the magnitude of SNR can be seen as the simulation time increases, similar to that of the SLP or perturbation pressure. These results indicate that the SST as an external forcing signal plays an important role in TC intensity for up to 72 hours, and it is significantly weakened if the simulation time exceeds the predictability limits of TC intensity. 相似文献
95.
96.
卡尔曼滤波递减平均方法对模式直接输出的气温预报进行订正,能有效提高预报准确率,但有时会造成显著负订正的现象,使订正预报效果反而不及模式直接输出。利用消除偏差集合平均方法(BREM)选择最优滑动训练期对2019年10月至2020年4月ECMWF预报(EC)、经过卡尔曼滤波递减平均法订正的预报(EC_COR)及中央台网格指导预报(SCMOC)等3种气温预报在黑龙江省的结果进行集成,并将BREM方法对EC_COR的修正效果进行评估,结果表明:不同预报结果都表现为冬季和夜间预报的准确率更低,气温偏低的11月至翌年1月更倾向于表现出预报较实况系统性偏高的特点。BREM方法能有效地修正EC_COR对EC负订正的现象,且可显著高于任何一种参与集成的单一预报效果。可在对单一模式进行卡尔曼滤波递减平均订正的基础上,进一步提升预报质量。另外,利用集成方法对高质量预报产品的融合(不局限于模式直接输出预报或是订正预报)可获取较单一预报更优的预报结果。 相似文献
97.
Uncertainty in projections of the South Asian summer monsoon under global warming by CMIP6 models: Role of tropospheric meridional thermal contrast 下载免费PDF全文
本文基于第六次国际耦合模式比较计划共18个模式的工业革命前实验和CO2浓度突然四倍实验,发现在CO2四倍强迫下,南亚夏季风环流呈显著减弱趋势,但减弱强度存在较大模式间差异.利用Webster-Yang指数和经向哈得莱环流指数的下降趋势表征SASM减弱强度,发现该下降趋势与欧亚大陆-印度洋之间对流层上层经向温度梯度的变化值(EUTT-IUTT)高度相关.进一步利用气候反馈-响应分析方法进行分析,发现EUTT-IUTT变化的模式间差异主要来自于大气动力过程,其次是云的短波辐射效应的贡献.地表潜热通量和云的长波辐射效应缩小了EUTT-IUTT变化的模式间差异. 相似文献
98.
基于2016-2018年ECMWF模式温度预报和浙江省72个国家基本站观测资料,根据温度日变化特征,采用K-近邻(KNN)回归算法进行误差订正,改进浙江省172 h精细化温度预报。在KNN回归算法中,将模式起报时刻的温度视作“背景”,由模式预报减去起报时刻温度消除“背景”影响,得到温度日变化曲线,通过温度日变化曲线构建差异指标,选取历史相似个例。根据历史相似个例的误差特征,对温度预报进行订正,得到改进的温度预报。检验结果表明,KNN方案的温度预报平均绝对误差较ECMWF和30 d滑动平均误差订正方案(OCF)的分别减小26.2%和5.2%;日最高和最低温度预报误差绝对值小于2℃,准确率较ECMWF的分别提高14.8%和4.3%,较OCF的分别提高3.0%和1.3%。KNN方案对地形复杂地区的温度预报改进效果更为明显,对冷空气活动和夏季高温等天气过程预报改善效果也较稳定。 相似文献
99.
针对离散站点资料格点化的业务需求及 Cressman 方法在地形复杂区域客观分析存在的问 题,利用山东及周边省自动气象站观测的 2 m气温和 ECMWF预报的海上 2 m气温,结合山东省中尺度数值预报位温递减率、90 m分辨率 SRTM高程数据,采用统一高度 Cressman 方法对山东省地面2 m气温进行客观分析,生成了逐 1 h、0.01°×0.01°高分辨率的地面 2 m气温格点产品。结果表明,统一高度 Cressman 方法的客观分析格点产品在地形复杂区域的分析更合理,月平均误差基本在±1 ℃以内,鲁中山区地形高度较高区域月平均误差略大于鲁西北、鲁西南、鲁东南和山东半岛等地的平原地区,气温偏低的10、11、12月温度准确率均略低于 5、6、7、8、9 月;2020 年 5—12 月平均误差为-0.0039 ℃,平均绝对误差为 0.1469 ℃,均方根误差为 0.3597 ℃,2 ℃以内准确率为 99.64%,1 ℃以内准确率为 98.24%,各项检验指标均较优。总体上统一高度 Cressman 客观分析格点产品质量接近中国气象局陆面数据同化系统( HRCLDAS )高分辨率格点实况产品。 相似文献
100.
全球气温气压(GPT)系列模型可用于计算全球任意位置的气温、气压和水汽压等各种气象参数,目前国内外广泛使用且精度较高的全球气温气压模型主要为GPT2w模型.本文利用2012—2016年中国大陆地区102个国家气象站实测的气温、气压和水汽压数据对GPT2w模型进行精度分析.结果表明:GPT2w模型的气温误差均值为-0.45 ℃,标准偏差均值为10.04 ℃;气压误差均值为2.05 hPa,标准偏差均值为6.55 hPa;水汽压误差均值为0.11 hPa,标准偏差均值为6.15 hPa.总体而言,GPT2w模型计算出的气温、气压和水汽压值在中国大陆大部分地区具有较高的精度.同时,三种气象参数的精度在中国大陆地区分布不均匀,不同纬度区间存在一定差异且以年为周期均具有明显的季节性. 相似文献