赤道中东太平洋海温相似预报研究

通过寻找过程相似的有效指标 ,建立了一个适合于时间序列分析的相似预报模式。将该模式应用于 ENSO的重要指标—— NINO3区海温指数预报 ,结果表明 :海温相似预报较持续性预报在预报效果 (如误差和相关系数 )上有明显的提高 ,特别是在 6～ 8个月时效上更为突出 ;模式的有效预报时效为 8个月 ,基本上达到国际上同期的模式水平。在有效预报时效 8个月内 ,冬半年的预报相关性普遍高于夏半年 ,其中 ,1 2月份的预报相关性最高 ,而 6,7月份的预报相关性最低。对于所有时效 ,2～ 4月份的预报误差最小 ,而 1 2月份的预报误差最大。相似预报对于转折事件具有较好的预报能力 ,尤其是对于 El Nino结束和强 El Nino开始     

Wind-generated waves in Hurricane Juan

We present numerical simulations of the ocean surface waves generated by hurricane Juan in 2003 as it reached its mature stage (travelling from deep waters off Bermuda to Nova Scotia and making landfall near Halifax) using SWAN (v.40.31) nested within WAVEWATCH-III (v.2.22; denoted WW3) wave models, implemented on multiple-nested domains. As for all storm-wave simulations, spectral wave development is highly dependent on accurate simulations of storm winds during its life cycle. Due to Juan’s rapid translation speed (accelerating from 2.28 m s⁻¹ on 27 September, 1200 UTC to 20 m s⁻¹ on 29 September, 1200 UTC), an interpolation method is developed to blend observed hurricane winds with numerical weather prediction (NWP) model winds accurately. Wave model results are compared to in situ surface buoys and ADCP wave data along Juan’s track. At landfall, Juan’s maximum waves are mainly swell-dominated and peak waves lag the occurrence of the maximum winds. We explore the influence of surface waves on the wind and show that the accuracy of the wave simulation is enhanced by introducing swell and Stokes drift feedback mechanisms to modify the winds, and by limiting the peak drag coefficient under high wind conditions, in accordance with recent theoretical and experimental results.     

Transformation of Wave Energy Spectrum in Shallow Water

- Combined with irregular wave-maker, the growing process of Wave Energy Spectrum in shallow water can be studied in wind wave channel on different water depth conditions, and its transformation characteristics and rules can be obtained.     

Shallow Water Dissipation Processes for Wind Waves off the Mackenzie Delta

This study focuses on two physical processes for waves in shallow waters off the Mackenzie Delta: bottom friction and depth-induced breaking terms. We use field observations of winds and waves, the state-of-the-art Simulating Waves Nearshore (SWAN) model, and reanalysis wind and wave data. The two field observation periods are an August 2008 field experiment, during which in situ field data were collected, and an Arctic storm when data were recorded by buoy measurements from 4 to 6 August 1991. Wind and wave development processes are analyzed during these two periods with comparisons to observed winds and waves. Our analyses show that bottom friction is the main shallow water physical process during the August 2008 field experiment, whereas depth-induced breaking is the dominant shallow water physical process during the 4–6 August 1991 storm, in conjunction with the effects of bottom friction. The SWAN wave model is used to investigate the shallow water physical processes during these two observation periods. Simulation results indicate that the model can give reasonable results, with an appropriate Collins coefficient of 0.006 and a wave breaking parameter of 0.55 to represent bottom friction and depth-induced breaking physics, respectively.

RÉSUMÉ?[Traduit par la rédaction] Cette étude porte sur deux processus physiques concernant les vagues dans les eaux peu profondes au large du delta du Mackenzie : les termes du frottement contre le fond et du déferlement lié à la profondeur. Nous utilisons des observations du vent et des vagues, le modèle d'avant-garde SWAN (Simulating Waves Nearshore) et des données de vent et de vagues réanalysées. Les deux périodes d'observations sont une expérience sur le terrain réalisée en août 2008, au cours de laquelle des données de terrain ont été recueillies, et une tempête arctique lors de laquelle des mesures faites par bouée du 4 au 6 août 1991 ont été enregistrées. Nous analysons les processus dévolution du vent et des vagues durant ces deux périodes, et comparons avec le vent et les vagues observées. Nos analyses montrent que le frottement contre le fond est le processus physique en eaux peu profondes le plus important durant l'expérience sur le terrain d'août 2008, alors que le déferlement lié à la profondeur est le processus physique en eaux peu profondes dominant pendant la tempête arctique du 4 au 6 août 1991, en combinaison avec les effets du frottement contre le fond. Nous nous servons du modèle de vagues SWAN pour étudier les processus physiques en eaux peu profondes durant ces deux périodes d'observations. Les résultats des simulations indiquent que le modèle peut donner des résultats raisonnables, avec un coefficient de Collins approprié de 0,006 et un paramètre de déferlement de 0,55 pour représenter la physique du frottement contre le fond et du déferlement lié à la profondeur, respectivement.     

ON CHANGES OF CHINA'S MAXIMUM AND MINIMUM TEMPERATURES IN 1951——1990

Based on China's observational data in 1951-1990,after minimizing the possible biasescaused by station relocation and urban heat island,the spatial and temporal distributions of trendsfor maximum and minimum temperatures are studied.The results show that increasing trends ofmaximum temperatures are in the areas west to 95°E,and north to the Huanghe(Yellow)River,while decreasing trends exist in eastern China south to the Yellow River.Minimum temperaturesare generally increasing throughout China,with dominant warming trends at the higher latitudes.This resulted in very obvious decreasing trends in diurnal temperature ranges.The periodic cycles are consistent between the maximum and minimum temperatures,butasymmetric trends are very obvious.The significant increase of minimum(nighttime)temperaturesreflects the evidence of enhancement of greenhouse effect.Further analysis shows that the changesof maximum and minimum temperatures are mainly related to sunshine duration and atmosphericwater vapor content.     

表层声速误差对多波束测深数据的影响分析

针对多波束水深测量中未明确定义表层声速限差范围,导致在数据采集过程中无法实时监控表层声速误差的问题,结合多波束数据采集与归算流程,分析并推导了 SSP误差影响下的波束指向角与点位归算误差模型.结合数值计算,研究了不同水深下测深误差随SSP之间的变化规律与量级大小,从而针对SSP限差范围提出合理化建议,对提高数据质量具有...     

An application of the LTP＿DSEF model to heavy precipitation forecasts of landfalling tropical cyclones over China in 2018

Recently, a track-similarity-based Dynamical-Statistical Ensemble Forecast(LTP_DSEF) model has been developed in an attempt to predict heavy rainfall from Landfalling Tropical cyclones(LTCs). In this study, the LTP_DSEF model is applied to predicting heavy precipitation associated with 10 LTCs occurring over China in 2018. The best forecast scheme of the model with optimized parameters is obtained after testing 3452 different schemes for the 10 LTCs. Then, its performance is compared to that of three operational dynamical models. Results show that the LTP_DSEF model has advantages over the three dynamical models in predicting heavy precipitation accumulated after landfall, especially for rainfall amounts greater than 250 mm. The model also provides superior or slightly inferior heavy rainfall forecast performance for individual LTCs compared to the three dynamical models. In particular, the LTP_DSEF model can predict heavy rainfall with valuable threat scores associated with certain LTCs, which is not possible with the three dynamical models. Moreover, the model can reasonably capture the distribution of heavier accumulated rainfall, albeit with widespread coverage compared to observations. The preliminary results suggest that the LTP_DSEF model can provide useful forecast guidance for heavy accumulated rainfall of LTCs despite its limited variables included in the model.     

Wave Numerical Model for Shallow Water

The history of forecasting wind waves by wave energy conservation equation is briefly des-cribed.Several currently used wave numerical models for shallow water based on different wave theoriesare discussed.Wave energy conservation models for the simulation of shallow water waves are introduced,with emphasis placed on the SWAN model,which takes use of the most advanced wave research achieve-ments and has been applied to several theoretical and field conditions.The characteristics and applicabilityof the model,the finite difference numerical scheme of the action balance equation and its source termscomputing methods are described in detail.The model has been verified with the propagation refractionnumerical experiments for waves propagating in following and opposing currents;finally.the model is ap-plied to the Haian Gulf area to simulate the wave height and wave period field there,and the results arecompared with observed data.     

自容式压力验潮仪水位观测值影响因素与改正

自容式压力验潮仪是目前海道测量水位观测的常用设备。在实际应用中,由于忽略了环境因素及其变化对水位观测精度的影响,可能获取不到高质量的水位观测数据,进而影响到海道测量成果的数据质量。在简要分析自容式压力验潮仪水位测量原理的基础上,利用数值计算方法,探讨了气压、密度和重力加速度变化对自容式压力验潮仪观测水位的影响规律,并提出了提高自容式压力验潮仪水位观测精度的一般改正方法。     

飓风Juan(2003)路径附近实测飓风浪的谱特性研究

Hurricane Juan provides an excellent opportunity to probe into the detailed wave spectral patterns and spectral parameters of a hurricane system, with enough wave spectral observations around Juan＇s track in the deep ocean and shallow coastal water. In this study, Hurricane Juan and wave observation stations around Juan＇s track are introduced. Variations of wave composition are discussed and analyzed based on time series of one-dimensional frequency spectra, as well as wave steepness around Juan＇s track： before, during, and after Juan＇s passing. Wave spectral involvement is studied based on the observed one-dimensional spectra and two-dimensional spectra during the hurricane. The standardization method of the observed wave spectra during Hurricane Juan is discussed, and the standardized spectra show relatively conservative behavior, in spite of the huge variation in wave spectral energy, spectral peak, and peak frequency during this hurricane. Spectral widths＇ variation during Hurricane Juan are calculated and analyzed. A two-layer nesting WW3 model simulation is applied to simulate the one-dimensional and two-dimensional wave spectra, in order to examine WW3＇s ability in simulating detailed wave structure during Hurricane Juan.