Lessons learnt from checking the quality of openly accessible river flow data worldwide

ABSTRACT

Advances in open data science serve large-scale model developments and, subsequently, hydroclimate services. Local river flow observations are key in hydrology but data sharing remains limited due to unclear quality, or to political, economic or infrastructure reasons. This paper provides methods for quality checking openly accessible river-flow time series. Availability, outliers, homogeneity and trends were assessed in 21 586 time series from 13 data providers worldwide. We found a decrease in data availability since the 1980s, scarce open information in southern Asia, the Middle East and North and Central Africa, and significant river-flow trends in Africa, Australia, southwest Europe and Southeast Asia. We distinguish numerical outliers from high-flow peaks, and integrate all investigated quality characteristics in a composite indicator. We stress the need to maintain existing gauging networks, and highlight opportunities in extending existing global databases, understanding drivers for trends and inhomogeneity, and in innovative acquisition methods in data-scarce regions.     

Large-sample hydrology: recent progress,guidelines for new datasets and grand challenges

ABSTRACT

Large-sample hydrology (LSH) relies on data from large sets (tens to thousands) of catchments to go beyond individual case studies and derive robust conclusions on hydrological processes and models. Numerous LSH datasets have recently been released, covering a wide range of regions and relying on increasingly diverse data sources to characterize catchment behaviour. These datasets offer novel opportunities, yet they are also limited by their lack of comparability, uncertainty estimates and characterization of human impacts. This article (i) underscores the key role of LSH datasets in hydrological studies, (ii) provides a review of currently available LSH datasets, (iii) highlights current limitations of LSH datasets and (iv) proposes guidelines and coordinated actions to overcome these limitations. These guidelines and actions aim to standardize and automatize the creation of LSH datasets worldwide, and to enhance the reproducibility and comparability of hydrological studies.     

Approaches to analyse and model changes in impacts: reply to discussions of “How to improve attribution of changes in drought and flood impacts”*

ABSTRACT

We thank the authors, Brunella Bonaccorso and Karsten Arnbjerg-Nielsen for their constructive contributions to the discussion about the attribution of changes in drought and flood impacts. We appreciate that they support our opinion, but in particular their additional new ideas on how to better understand changes in impacts. It is great that they challenge us to think a step further on how to foster the collection of long time series of data and how to use these to model and project changes. Here, we elaborate on the possibility to collect time series of data on hazard, exposure, vulnerability and impacts and how these could be used to improve e.g. socio-hydrological models for the development of future risk scenarios.     

用NCEP／NCAR再分析辐射资料估算月平均地表反照率

本文利用１９７９年￣１９９５年１７年平均的ＮＣＥＰ／ＮＣＡＲ（Ｎａｔｉｏｎａｌ Ｃｅｎｔｅｒ ｆｏｒ Ｅｎｖｉｒｏｎｍｅｎ－ｔａｌ Ｐｒｅｄｉｃｔｉｏｎ／Ｎａｔｉｏｎａｌ Ｃｅｎｔｅｒ ｆｏｒ Ａｔｍｏｓｐｈｅｒｉｃ Ｒｅｓｅａｒｃｈ,美国国家环境预报中心／美国国家大气研究中心）再分析辐射资料估算了全球月平均地表反照率．从所得结果的时空分布来看,用ＮＣＥＰ／ＮＣＡＲ辐射资料得到的全球地表反照率基本     

Big spatial data for urban and environmental sustainability

ABSTRACT

Eighty percent of big data are associated with spatial information, and thus are Big Spatial Data (BSD). BSD provides new and great opportunities to rework problems in urban and environmental sustainability with advanced BSD analytics. To fully leverage the advantages of BSD, it is integrated with conventional data (e.g. remote sensing images) and improved methods are developed. This paper introduces four case studies: (1) Detection of polycentric urban structures; (2) Evaluation of urban vibrancy; (3) Estimation of population exposure to PM2.5; and (4) Urban land-use classification via deep learning. The results provide evidence that integrated methods can harness the advantages of both traditional data and BSD. Meanwhile, they can also improve the effectiveness of big data itself. Finally, this study makes three key recommendations for the development of BSD with regards to data fusion, data and predicting analytics, and theoretical modeling.     

A hyperspectral experiment over tropical forests based on the EO-1 orbit change and PROSAIL simulation

ABSTRACT

We designed a unique hyperspectral experiment from the Earth Observing One (EO-1) orbit change to evaluate solar illumination effects over tropical forests in Brazil. Ten nadir-viewing Hyperion images collected over a fixed site and period of the year (July to August) were selected for analysis. We evaluated variations in reflectance and in 16 narrowband vegetation indices (VIs) with increasing solar zenith angle (SZA) from the pre-drift (2004–2008) to the EO-1 drift period (2011–2016). To detect changes in reflectance and shadows, we applied spectral mixture analysis (SMA) and principal component analysis (PCA) and calculated the similarity spectral angle (θ) between the vegetation spectra measured with variable SZA. The magnitude of the illumination effects was also evaluated from change-point analysis and nonparametric Mann-Whitney U tests applied over the time series. Finally, we complemented our experiment using the PROSAIL model to simulate the VIs variation with increasing SZA resultant from satellite drift. The results showed significant changes in Hyperion reflectance and VIs, especially when the EO-1 crossed the study area at earlier times and larger SZA in 2015 (9:05 a.m.; SZA = 59°) and 2016 (8:30 a.m.; SZA = 67°). Compared to the pre-drift period (10:30 a.m.; SZA = 45°), the SZA differences of 14° (2015) and 22° (2016) increased the shade fractions and decreased the vegetation brightness. PCA separated the pre-drift and drift reflectance datasets, showing shifts in scores due to changes in brightness. θ increased with SZA, indicating changes in the shape of the vegetation spectra with drift. For most VIs, the change-point analysis indicated 2015 (SZA = 59°) as the predominant year of detected changes. Compared to the EO-1 original orbit, the Plant Senescence Reflectance Index (PSRI), Anthocyanin Reflectance Index (ARI) and Structure Insensitive Pigment Index (SIPI) presented the largest positive changes during drift, while the Photochemical Reflectance Index (PRI), Visible Atmospherically Resistant Index (VARI) and Enhanced Vegetation Index (EVI) had the largest negative changes. The effect size of the illumination geometry on these VIs was large, as indicated by increasing values of the Cohen’s r metric toward 2016. The anisotropy of the Hyperion VIs was generally consistent with that from PROSAIL in the simulated pre-drift and drift periods. Focusing on structural indices, it affected the relationships between VIs and simulated leaf area index (LAI) at large SZA.     

Big Earth data: disruptive changes in Earth observation data management and analysis?

ABSTRACT

Turning Earth observation (EO) data consistently and systematically into valuable global information layers is an ongoing challenge for the EO community. Recently, the term ‘big Earth data’ emerged to describe massive EO datasets that confronts analysts and their traditional workflows with a range of challenges. We argue that the altered circumstances must be actively intercepted by an evolution of EO to revolutionise their application in various domains. The disruptive element is that analysts and end-users increasingly rely on Web-based workflows. In this contribution we study selected systems and portals, put them in the context of challenges and opportunities and highlight selected shortcomings and possible future developments that we consider relevant for the imminent uptake of big Earth data.     

顾及边界入射信号的多模水汽层析方法

利用GNSS三维水汽层析技术全天候地获取高时空采样率的水汽垂直分布信息,已成为GNSS气象学中一大研究热点。当前,基于单一导航系统的传统层析方法存在观测数据利用率低、观测分布不均等不足。本文设计和实现了一种顾及边界入射信号的多模水汽层析方法,采用香港CORS网观测数据和无线电探空产品进行精度验证,并详细分析边界入射信号和多模层顶信号的引入对层析水汽结果的改善程度。结果表明:相较于传统GPS层析方法,本文采用的融合两类多模层顶信号和边界入射信号的新水汽层析方法,兼备边界入射信号和多模层顶信号的优点,可得到更高精度和更可靠的三维水汽信息。     

基于昆明市精细化GIS的天气雷达标准格式基数据应用

以国家地理信息公共服务平台、云南数字乡村、Mapinfo公共数据为数据源,在C#开发环境下实现了精细到乡镇、公路、行政村、自然村的昆明市精细化地理信息系统(GIS)的自主研发,解决了基层气象部门缺乏精细化GIS的难题。介绍了标准格式基数据的解析、成图过程及注意事项,在全国范围内较早实现了天气雷达标准格式基数据在基层气象部门的业务应用。在业务应用过程中,发现了CC天气雷达标准格式早期基数据存在回波强度严重减弱的问题;昆明市精细化GIS与昆明天气雷达回波图的融合应用,可以精确定位雷达强回波区,对精细化气象服务具有指导作用,提高了强天气精细化预警能力、短时临近精细化预报能力和防灾减灾能力。     

风廓线雷达水平风数据质量控制

基于九龙站风廓线雷达实时水平风数据制定了水平风数据的质量控制方法，首先求取中位数水平风场，其次构建实际观测风场和中位数风场的差值序列，然后求取差值序列的均方差，再根据差值均方差得到质控判别式，最后试验求取质控判别式中的质控阈值。通过对九龙站2017年风廓线雷达水平风数据质量控制发现，实测风向数据有2044185个，25721个没有通过质控，未通过质控的风向数据占总观测的比例是1.258%，风向数据在近地层通过质控的数据最多，随高度增加通过质控的数据量有所下降。实测风速数据有2044185个，18296个没有通过质控，未通过质控的风速数据占总观测的比例是0.895%，风速数据在2000～4000 m出错的最少，近地层次之，4500～7000 m出错的数据最多。质控后风廓线雷达和探空观测风数据的均方根误差减小，相关系数增加，风向数据质量在500～7000 m提升明显，风速数据在1500～8000 m之间提升明显。