Long-Term Extreme Wave Characteristics in the Water Adjacent to China Based on ERA5 Reanalysis Data

Extreme waves have a profound impact on coastal infrastructure;thus,understanding the variation law of risky analysis and disaster prevention in coastal zones is necessary.This paper analyzed the spatiotemporal characteristics of extreme wave heights adjacent to China from 1979 to 2018 based on the ERA5 datasets.Nonstationary extreme value analysis is undertaken in eight repre-sentative points to investigate the trends in the values of 50-and 100-year wave heights.Results show that the mean value of extreme waves is the largest in the eastern part of Taiwan Island and the smallest in the Bohai Sea from 1979 to 2018.Only the extreme wave height in the northeastern part of Taiwan Island shows a significant increase trend in the study area.Nonstationary analysis shows remarkable variations in the values of 50-and 100-year significant wave heights in eight points.Considering the annual mean change,E1,E2,S1,and S2 present an increasing trend,while S3 shows a decreasing trend.Most points for the seasonal mean change demon-strate an increasing trend in spring and winter,while other points show a decreasing trend in summer and autumn.Notably,the E1 point growth rate is large in autumn,which is related to the change in typhoon intensity and the northward movement of the typhoon path.

Evaluating the Accuracy of ERA5 Wave Reanalysis in the Water Around China

Wave parameters, such as wave height and wave period, are important for human activities, such as navigation, ocean engineering and sediment transport, etc. In this study, wave data from six buoys around Chinese waters, are used to assess the quality of wave height and wave period in the ERA5 reanalysis of the European Centre for Medium-Range Weather Forecasts. Annual hourly data with temporal resolution are used. The difference between the significant wave height(SWH) of ERA 5 and that of the buoy varies from-0.35 m to 0.30 m for the three shallow locations;for the three deep locations, the variation ranges from-0.09 m to 0.09 m. The ERA5 SWH data show positive biases, indicating an overall overestimation for all locations, except for E2 and S1 where underestimation is observed. During the tropical cyclone period, a large(about 32%) underestimation of the maximum SWH in the ERA5 data is observed. Hence, the ERA5 SWH data cannot be used for design applications without site-specific validation. The difference between the annual wave period from ERA5 and the mean wave period from the buoys varies from-1.31 s to 0.4 s. Inter-comparisons suggest that the ERA5 dataset is consistent with the annual mean SWH. However, for the average period, the performance is not good, and half of the correlation coefficients in the four points are less 50%. Overall, the deep water area simulation effect is better than that in the shallow water.

Decadal trends in precipitable water vapor over the Indus River Basin using ERA5 reanalysis data

Precipitable Water Vapor(PWV)constitutes a pivotal parameter within the domains of atmospheric science,and remote sensing due to its profound influence on Earth’s climate dynamics and weather patterns.It exerts a significant impact on atmospheric stability absorption and emission of radiation,thus engendering alterations in the Earth’s radiative equilibrium.As such,precise quantification of PWV holds the potential to enhance weather prognostication and fortify preparedness against severe meteorological phenomena.This study aimed to elucidate the spatial and temporal changes in seasonal and annual PWV across the Indus River Basin and its sub-basins using ERA5 reanalysis datasets.The present study used ERA5 PWV(entire atmospheric column),air temperature at 2 m(t2m)and 500 hPa(T_500hPa),evapotranspiration,and total cloud cover data from 1960 to 2021.Theil Sen slope estimator and Mann-Kendall test were used for trend analysis.Correlation and multiple regression methods were used to understand the association of PWV with other factors.The findings have unveiled the highest increase in mean PWV during the monsoon(0.40 mm/decade),followed by premonsoon(0.37 mm/decade),post-monsoon(0.27 mm/decade),and winter(0.19 mm/decade)throughout the study period.Additionally,the mean PWV exhibited the most pronounced positive trend in the sub-basin Lower Indus(LI),followed by Panjnad(P),Kabul(K),and Upper Indus(UI)across all seasons,except winter.Annual PWV has also risen in the Indus basin and its sub-basins over the last six decades.PWV exhibits a consistent upward trend up to an elevation of 3500 m within the basin which is most pronounced during the monsoon season,followed by the pre-monsoon.The escalating PWV within the basin is reasonably ascribed to increasing air temperatures,augmented evapotranspiration,and heightened cloud cover.These findings hold potential utility for pertinent authorities engaged in water resource management and planning.

Application of ERA5 Reanalysis to the Construction of Initial Conditions for WACCM Simulations

This study uses ECMWF fifth-generation reanalysis, ERA5, which extends to the mesopause, to construct the Initial Conditions(IC) for WACCM(Whole Atmosphere Community Climate Model) simulations. Because the biases between ERA5 and Sounding of the Atmosphere using Broadband Emission Radiometry(SABER) temperature data are within ±5 K below the lower mesosphere,ERA5 reanalysis is used to construct IC in the lower atmosphere. Four experiments are performed to simulate a Stratospheric Sudden Warming(SSW) event from 5 to 15 February 2016. The simulation using the WACCM default climatic IC cannot represent the sharp meteorological variation during SSW. In contrast, the 0～4 d forecast results driven by ERA5-constructed IC is consistent with ERA5 reanalysis below the middle mesosphere. Comparing with WACCM climatology ICs scheme, the ICs constructing method based on ERA5 reanalysis can obtain 67%, 40%, 22%, 4% and 6% reduction of temperature forecast RMSE at 10 hPa, 1 hPa, 0.1 hPa, 0.01 hPa and 0.001 hPa respectively. However,such improvement is not shown in the lower thermosphere.

Applicability evaluation of ERA5 wind and wave reanalysis data in the South China Sea

Wind and wave data are essential in climatological and engineering design applications.In this study,data from 15 buoys located throughout the South China Sea(SCS)were used to evaluate the ERA5 wind and wave data.Applicability assessment are beneficial for gaining insight into the reliability of the ERA5 data in the SCS.The bias range between the ERA5 and observed wind-speed data was-0.78-0.99 m/s.The result indicates that,while the ERA5 wind-speed data underestimation was dominate,the overestimation of such data existed as well.Additionally,the ERA5 data underestimated annual maximum wind-speed by up to 38%,with a correlation coefficient>0.87.The bias between the ERA5 and observed significant wave height(SWH)data varied from-0.24 to 0.28 m.And the ERA5 data showed positive SWH bias,which implied a general underestimation at all locations,except those in the Beibu Gulf and centralwestern SCS,where overestimation was observed.Under extreme conditions,annual maximum SWH in the ERA5 data was underestimated by up to 30%.The correlation coefficients between the ERA5 and observed SWH data at all locations were greater than 0.92,except in the central-western SCS(0.84).The bias between the ERA5 and observed mean wave period(MWP)data varied from-0.74 to 0.57 s.The ERA5 data showed negative MWP biases implying a general overestimation at all locations,except for B1(the Beibu Gulf)and B7(the northeastern SCS),where underestimation was observed.The correlation coefficient between the ERA5 and observed MWP data in the Beibu Gulf was the smallest(0.56),and those of other locations fluctuated within a narrow range from 0.82 to 0.90.The intercomparison indicates that during the analyzed time-span,the ERA5 data generally underestimated wind-speed and SWH,but overestimated MWP.Under non-extreme conditions,the ERA5 wind-speed and SWH data can be used with confidence in most regions of the SCS,except in the central-western SCS.

A Preliminary Analysis on the Applicability of ERA5 Reanalysis Data in Guangdong Province

In order to effectively use the ERA5 reanalysis data,observation data in and around Guangdong Province was used to evaluate the reanalysis data by analyzing the correlation coefficient and deviation. The results showed that among the surface elements,the sea level pressure and air temperature performed the best reproducibility,second the relative humidity and wind speed,and they had better performance in the Pearl River Delta and its surrounding areas,while the worst was wind direction. Except the relative humidity,elements had better performance at higher levels than lower levels among the ERA5 reanalysis upper-air data.

Applicability analysis of the sea surface pressure and wind speed of ERA5 reanalysis data in the Bohai Sea and the Northern Huanghai Seas

A preliminarily assessment of the applicability of the sea surface pressure and wind speed of ERA5 reanalysis data is carried out using the observation data at 10 m height observation data of 9 buoys in the Bohai Sea and the Northern Huanghai Sea.The results show that:the sea surface pressure and wind speed of ERA5 reanalysis data has high correlation coefficients with the observation data,the correlation between sea surface pressure and wind speed is different in different time scales.The correlation of monthly average is better than that of daily average and daily extreme value,and the correlation coefficient is the lowest in extreme weather.In generally,the deviation between statistical products of the ERA5 and the observed products is negative.It means that the high pressure is weaker than the observed data,and the low pressure is stronger than the observed data,and there is some systematic deviation between ERA5 reanalysis data and the observed data.The deviation varies with the different wind speed level,when the wind is high,the reanalysis wind speed is generally less than the measured.By analyzing the monthly average data,the reanalysis data reveal the seasonal variation of sea surface pressure in the study area,and the deviation from the observed data also show seasonal variation characteristics,the applicability in winter is better than in summer.The error of reanalysis data of sea surface pressure and wind speed is large under extreme weather conditions,especially the typhoon process,further evaluation and revision of the data are needed.

Study on the Applicability of ERA5 Reanalysis Data at Lake Taihu

Lakes are an important component of the earth climate system. They play an important role in the study of basin weather forecasting, air quality forecasting, and regional climate research. The accuracy of driving variables is the basic premise to ensure the rationality of lake mode simulation. Based on the in-situ observations at Bifenggang site of the Lake Taihu Eddy flux Network from 2012 to 2017, this paper investigated temporal variations in temperature, relative humidity, wind speed, radiation components at different time scales (hourly, seasonal and interannual). ERA5 reanalysis data were compared with in-situ observation to quantify the error and evaluate the performance of reanalysis data. The results show that: 1) On the hourly scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. 2) On the seasonal variation scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. However, the descriptions of wind speed, relative humidity and downward short-wave have large deviations. 3) On the interannual scale, the ERA5 reanalysis data show a good performance for temperature, followed by downward longwave radiation, downward shortwave radiation and relative humidity.

Comparison of ERA5 turbulent fluxes at the air-sea interface with measurements from a wave-following platform

Turbulent fluxes at the air-sea interface were estimated with data collected in 2011-2020 with a low-profile platform named OCARINA during eight experiments in five regions:2011,2015,and 2016 in the Iroise Sea;2012 in the tropical Atlantic;2014 in the Chilie-Peru upwelling;2017 and 2018 in the Mediterranean Sea,and 2018 and 2020 in Barbados.The observations were carried out with moderate winds(2-10 m s^(-1))and average wave heights of 1.5 m.In this study,the authors used the fluxes calculated by the bulk method using OCARINA-sampled data as the input.These data can validate the fluxes estimated from ERAS reanalysis data.The OCARINA and ERA5 data were taken concomitantly.To do this,the authors established an algorithm to extract the OCARINA data as closely as possible to the reanalysis data in time and position.The measurements of the OCARINA platform can conclude on the relevance of the widely used reanalysis data.

基于ERA5海浪再分析数据的风浪涌浪分离方法

为了探究和分析海浪中的主要成分,本文基于ERA5海浪再分析数据,依据能量因子分离风、涌浪的原理,研究了风、涌浪的平均波周期与风速的分布规律。利用最小二乘拟合方法,提出了一种分离风、涌浪的方法,并将其命名为TU方法。通过将TU方法与波龄方法进行比较分析,验证TU方法的可行性和可靠性。结果显示:在本文的研究区域中,TU方法与波龄方法识别风浪的正确率为98.57%和98.55%,TU方法与波龄方法识别涌浪的正确率为78.9%和65.1%,表明根据风速与平均波周期2个参数识别涌浪,TU方法效果比波龄方法更好。对高度计等缺少风向信息情况下分离风浪与涌浪有着重要的意义。

基于ERA5再分析数据的中国邻近海域极端波高特征分析

极端波浪对沿海地区基础设施有着深远的影响,了解它们的变化规律是进行海岸带风险分析和灾害预防的基础。文章基于欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasting,ECMWF)第五代再分析数据集(ECMWFreanalysisv5,ERA5),对中国邻近海域1979~2018年间极端波高展开时空特征分析,并统计了40a厄尔尼诺系数,利用广义极值分布(generalized extreme value,GEV)函数探究了近40 a厄尔尼诺现象对我国海域极端波高的影响,结果显示:统计1979~2018年整个研究区域前2%极端波浪年均值在6~10 m间浮动,且整体趋势递增,在四季趋势变化中,春夏极端波高增长趋势较秋冬高,且波动明显,在年际极端波高变化趋势中有较大波动时大多伴随着厄尔尼诺或是拉尼娜现象的发生,结合厄尔尼诺现象对GEV分布中位置参数的影响分布图和极端波高年、季节际趋势变化分布图,厄尔尼诺现象影响大的地区极端波高大多呈现增长趋势,表明厄尔尼诺现象对极端波高有较高影响。

Intercomparison of CRA-Interim Precipitation Products with ERA5 and JRA-55

Based on the hourly observational data during 2007-2016 from surface meteorological stations in China,this paper compares the influence of 3-hourly precipitation data,mainly from the Chinese Reanalysis-Interim(CRA-Interim),ECMWF Reanalysis 5(ERA5)and Japanese Reanalysis-55(JRA-55),on the simulation of the spatial and temporal distribution of regional precipitation in China and the bias distribution of the simulation.The results show that:(1)The three sets of reanalysis datasets can all reflect the basic spatial distribution characteristics of annual average precipitation in China.The simulation of topographic forced precipitation in complex terrain by using CRA-interim is more detailed,while CRA-interim has larger negative bias in central and East China,and larger positive bias in southwest China.(2)In terms of seasonal precipitation,the three sets of reanalysis datasets overestimate the precipitation in the heavy rainfall zone in spring and summer,especially in southwest China.According to CRA-interim,location of the rain belt in the First Rainy Season in South China is west by south,and the summer precipitation has positive bias in southwest and South China.(3)All of the reanalysis datasets can basically reflect the distribution difference of inter-annual variation of drought and flood,but overall the CRA-Interim generally shows negative bias,while the ERA5 and JRA-55 exhibit positive bias.(4)For the diurnal variation of precipitation in summer,all the reanalysis datasets perform better in simulating the daytime precipitation than in the night,and the bias of CRA-interim is less in the Southeast and Northeast than elsewhere.(5)The ERA5 generally performs the best on the evaluation of quantitative precipitation forecast,the JRA-55 is the next,followed by the CRA-Interim.The CRA-Interim has higher missing rate and lower threat score for heavy rains;however,at the level of downpour,the CRA-Interim performs slightly better.

Assessment of ERA5 and ERA-Interim in Reproducing Mean and Extreme Climates over West Africa

In situ data in West Africa are scarce,and reanalysis datasets could be an alternative source to alleviate the problem of data availability.Nevertheless,because of uncertainties in numerical prediction models and assimilation methods,among other things,existing reanalysis datasets can perform with various degrees of quality and accuracy.Therefore,a proper assessment of their shortcomings and strengths should be performed prior to their usage.In this study,we examine the performance of ERA5 and ERA-interim(ERAI)products in representing the mean and extreme climates over West Africa for the period 1981-2018 using observations from CRU and CHIRPS.The major conclusion is that ERA5 showed a considerable decrease in precipitation and temperature biases and an improved representation of inter-annual variability in much of western Africa.Also,the annual cycle is better captured by ERA5 in three of the region’s climatic zones;specifically,precipitation is well-reproduced in the Savannah and Guinea Coast,and temperature in the Sahel.In terms of extremes,the ERA5 performance is superior.Still,both reanalyses underestimate the intensity and frequency of heavy precipitations and overestimate the number of wet days,as the numerical models used in reanalyses tend to produce drizzle more often.While ERA5 performs better than ERAI,both datasets are less successful in capturing the observed long-term trends.Although ERA5 has achieved considerable progress compared to its predecessor,improved datasets with better resolution and accuracy continue to be needed in sectors like agriculture and water resources to enable climate impact assessment.

An ERA5 tropospheric parameters-augmented approach for improving GNSS precise point positioning

Precise Point Positioning(PPP) technology has developed into a potent instrument for geodetic positioning, ionospheric modeling, tropospheric atmospheric parameter detection, and seismic monitoring.As atmospheric reanalysis data products’ accuracy and spatiotemporal resolution have improved recently, it has become important to apply these products to obtain high-accuracy tropospheric delay parameters, like zenith tropospheric delay(ZTD) and tropospheric horizontal gradient. These tropospheric delay parameters can be applied to PPP to reduce the convergence time and to increase the accuracy in the vertical direction of the position. The European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5) atmospheric reanalysis data is the latest product with a high spatiotemporal resolution released by the European Center for Medium-Range Weather Forecasts(ECMWF). Only a few researches have evaluated the application of ERA5 data to Global Navigation Satellite System(GNSS)PPP. Therefore, this study compared and validated the ZTD products derived from ERA5 data using ZTD values provided by 290 global International GNSS Service(IGS) stations for 2016-2017. The results indicated a stable performance for ZTD, with annual average bias and RMS values of 0.23 cm and 1.09 cm,respectively. Further, GNSS observations for one week in each of the four seasons(spring: DOY 92-98;summer: DOY 199-205;autumn: DOY 275-281;and winter: DOY 22-28) from 34 multi-GNSS experiments(MGEX) stations distributed globally in 2016 were considered to evaluate the performance of ERA5-derived tropospheric delay products in GNSS PPP. The performance of ERA5-enhanced PPP was compared with that of the two standard GNSS PPP schemes(without estimated tropospheric horizontal gradient and with estimated tropospheric horizontal gradient). The results demonstrated that ERA5-enhanced GNSS PPP showed no significant improvement in the convergence times in both the Eastern(E) and Northern(N) directions, while the average convergence time over four weeks in the vertical(U)direction improved by 53.3% and 52.7%, respectively(in the case of pngm station). The average convergence times for each week in the U direction of the northern and southern hemisphere stations indicated a decrease of 16.3%, 12.6%, 9.6%, and 9.1%, and 16.9%, 9.6%, 8.9%, and 14.5%, respectively.Regarding positioning accuracy, ERA5-enhanced PPP showed an improvement of 13.3% and 16.2% over the two standard PPP schemes in the U direction, respectively. No significant improvement in the positioning performance was observed in both the E and N directions. Thus, this study demonstrated the potential application of the ERA5 tropospheric parameters-augmented approach to Beidou navigation and positioning.

Influence of vapor pressure deficit on vegetation growth in China

Vapor pressure deficit(VPD)plays a crucial role in determining plant physiological functions and exerts a substantial influence on vegetation,second only to carbon dioxide(CO_(2)).As a robust indicator of atmospheric water demand,VPD has implications for global water resources,and its significance extends to the structure and functioning of ecosystems.However,the influence of VPD on vegetation growth under climate change remains unclear in China.This study employed empirical equations to estimate the VPD in China from 2000 to 2020 based on meteorological reanalysis data of the Climatic Research Unit(CRU)Time-Series version 4.06(TS4.06)and European Centre for Medium-Range Weather Forecasts(ECMWF)Reanalysis 5(ERA-5).Vegetation growth status was characterized using three vegetation indices,namely gross primary productivity(GPP),leaf area index(LAI),and near-infrared reflectance of vegetation(NIRv).The spatiotemporal dynamics of VPD and vegetation indices were analyzed using the Theil-Sen median trend analysis and Mann-Kendall test.Furthermore,the influence of VPD on vegetation growth and its relative contribution were assessed using a multiple linear regression model.The results indicated an overall negative correlation between VPD and vegetation indices.Three VPD intervals for the correlations between VPD and vegetation indices were identified:a significant positive correlation at VPD below 4.820 hPa,a significant negative correlation at VPD within 4.820–9.000 hPa,and a notable weakening of negative correlation at VPD above 9.000 hPa.VPD exhibited a pronounced negative impact on vegetation growth,surpassing those of temperature,precipitation,and solar radiation in absolute magnitude.CO_(2) contributed most positively to vegetation growth,with VPD offsetting approximately 30.00%of the positive effect of CO_(2).As the rise of VPD decelerated,its relative contribution to vegetation growth diminished.Additionally,the intensification of spatial variations in temperature and precipitation accentuated the spatial heterogeneity in the impact of VPD on vegetation growth in China.This research provides a theoretical foundation for addressing climate change in China,especially regarding the challenges posed by increasing VPD.

Wind power potential over northern South America using ERA5-Land global reanalysis

The northernmost region of South America has great potential for wind energy production and is a strategic area for the energy transition.We analysed data from ERA5-Land global reanalysis from 1980 to 2020 to determine the wind power potential in this area.Our aim was to identify areas with a high potential for wind energy that could be used to supply energy in case of drought in the region or increases in fuel prices.We compared data from 19 meteorological stations located in Colombia with ERA5-Land reanalysis data to generate reliable information for the feasibility and operation of wind farms.According to our analysis,the Colombian Caribbean and Coastal Plain have monthly average wind speeds at 90 m ranging from 4.85 to 10.34 m/s and 3.79 to 6.62 m/s,respectively.Based on wind power density calculations,these regions have the highest wind power density in our study,with a monthly average of between 250 and 399 W/m^(2).The Caribbean Region had a 69%increase in wind power density from January to July compared with the annual average.The wind power density in the plains increased from January to March,while the Mountain Region had higher anomalies from May to October.The Alta Guajira and ParaguanáPeninsula have great potential to generate wind energy due to their privileged geographical location.Although ERA5 offers valuable information about wind availability in time and space,it cannot represent the influence of local effects on wind patterns for the Mountain Region.

A Study on Reconstruction of Surface Wind Speed in China Due to Various Climate Variabilities

Using European Centre for Medium-Range Weather Forecasts Reanalysis V5(ERA5)reanalysis data,this study investigated the reconstruction effects of various climate variabilities on surface wind speed in China from 1979 to 2022.The results indicated that the reconstructed annual mean wind speed and the standard deviation of the annual mean wind speed,utilizing various climate variability indices,exhibited similar spatial modes to the reanalysis data,with spatial correlation coefficients of 0.99 and 0.94,respectively.In the reconstruction of six major wind power installed capacity provinces/autonomous regions in China,the effects were notably good for Hebei and Shanxi provinces,with the correlation coefficients for the interannual regional average wind speed time series being 0.65 and 0.64,respectively.The reconstruction effects of surface wind speed differed across seasons,with spring and summer reconstructions showing the highest correlation with reanalysis data.The correlation coefficients for all seasons across most regions in China ranged between 0.4 and 0.8.Among the reconstructed seasonal wind speeds for the six provinces/autonomous regions,Shanxi Province in spring exhibited the highest correlation with the reanalysis,with a coefficient of 0.61.The large-scale climate variability indices showed good reconstruction effects on the annual mean wind speed in China,and could explain the interannual variability trends of surface wind speed in most regions of China,particularly in the main wind energy provinces/autonomous regions.

Comprehensive applicability evaluation of four precipitation products at multiple spatiotemporal scales in Northwest China

Precipitation plays a crucial role in the water cycle of Northwest China.Obtaining accurate precipitation data is crucial for regional water resource management,hydrological forecasting,flood control and drought relief.Currently,the applicability of multi-source precipitation products for long time series in Northwest China has not been thoroughly evaluated.In this study,precipitation data from 183 meteorological stations in Northwest China from 1979 to 2020 were selected to assess the regional applicability of four precipitation products(the fifth generation of European Centre for Medium-Range Weather Forecasts(ECMWF)atmospheric reanalysis of the global climate(ERA5),Global Precipitation Climatology Centre(GPCC),Climatic Research Unit gridded Time Series Version 4.07(CRU TS v4.07,hereafter CRU),and Tropical Rainfall Measuring Mission(TRMM))based on the following statistical indicators:correlation coefficient,root mean square error(RMSE),relative bias(RB),mean absolute error(MAE),probability of detection(POD),false alarm ratio(FAR),and equitable threat score(ETS).The results showed that precipitation in Northwest China was generally high in the east and low in the west,and exhibited an increasing trend from 1979 to 2020.Compared with the station observations,ERA5 showed a larger spatial distribution difference than the other products.The overall overestimation of multi-year average precipitation was approximately 200.00 mm and the degree of overestimation increased with increasing precipitation intensity.The multi-year average precipitation of GPCC and CRU was relatively close to that of station observations.The trend of annual precipitation of TRMM was overestimated in high-altitude regions and the eastern part of Lanzhou with more precipitation.At the monthly scale,GPCC performed well but underestimated precipitation in the Tarim Basin(RB=-4.11%),while ERA5 and TRMM exhibited poor accuracy in high-altitude regions.ERA5 had a large bias(RB≥120.00%)in winter months and a strong dispersion(RMSE≥35.00 mm)in summer months.TRMM showed a relatively low correlation with station observations in winter months(correlation coefficients≤0.70).The capture performance analysis showed that ERA5,GPCC,and TRMM had lower POD and ETS values and higher FAR values in Northwest China as the precipitation intensity increased.ERA5 showed a high capture performance for small precipitation events and a slower decreasing trend of POD as the precipitation intensity increased.GPCC had the lowest FAR values.TRMM was statistically ineffective for predicting the occurrence of daily precipitation events.The findings provide a reference for data users to select appropriate datasets in Northwest China and for data developers to develop new precipitation products in the future.

融合物理信息的热带气旋强度估计

热带气旋强度的精确估计是进行有效强度预测的基础工作,对于灾害预报至关重要.当前基于深度学习的热带气旋强度估计技术展现出了优越的性能,但仍然存在着物理信息融合不足的问题.因此,本文基于深度学习框架,提出一种融合物理信息的热带气旋强度估计模型(physical factor fusion for tropical cyclone intensity estimation,PF-TCIE),来估计西北太平洋的热带气旋强度.PF-TCIE由多通道卫星云图学习分支和物理信息提取分支组成.多通道卫星云图学习分支用于提取热带气旋云系特征,物理信息提取分支用于提取物理因子特征,来约束云系特征的学习.本文数据选用葵花-8卫星资料和ERA-5再分析资料.实验证明,在引入多个通道后,模型的RMSE误差较单通道降低了3.7%.同时,物理信息的引入使模型的误差进一步下降了8.5%.PF-TCIE的RMSE最终达到了4.83 m/s,优于大部分深度学习方法.

ERA-5降水数据在雨量站稀疏地区的适用性研究--以缅甸密支那流域为例

为探究降水产品在雨量站稀疏地区的适用性,选择位于缅甸的密支那流域作为研究流域,以雨量站数据作为参考数据,评估了ERA-5再分析降水数据的精度;并使用ERA-5数据率定和驱动CREST模型,探究了该数据应用于径流模拟的可行性。结果表明:在整个研究区域内,ERA-5数据和雨量站数据之间的相关程度高,差距较小;而在径流模拟方面,ERA-5数据可以较好地模拟中低水位的日径流过程,对于高水位流量则存在着一定的低估,但不同观测时段的NSCE系数均在0.7以上,总体而言精度仍较高;对于月径流量,该数据在不同观测时段的NSCE系数均大于0.85,相关系数均在0.9以上,能够较好地描述径流的年内变化特征。因此,ERA-5降水数据在一定程度上可以代替雨量站数据作为研究区域的降水数据来源,应用于流域水资源管理、水利工程设计等领域。