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高质量全球气候数据管理框架手册
本手册就高质量气候数据集的开发、提供、交换和维护提供了指导和要求。手册中介绍的标准和推荐规范旨在确保可用于气候评估、监测、应用和相关服务的数据可持续地满足关于质量、治理、可访问性和可用性的最低要求。
Manual del Marco Mundial de Gestión de Datos Climáticos de Alta Calidad
En el presente Manual se proporcionan directrices y requisitos sobre la creación, el suministro, el intercambio y el mantenimiento de conjuntos de datos climáticos de alta calidad. Las normas y prácticas recomendadas que se describen tienen por objeto garantizar que los datos que se proporcionan para la evaluación, la vigilancia, las aplicaciones y los servicios relacionados con el clima cumplan de forma sostenible un conjunto mínimo de requisitos con respecto a la calidad, la gobernanza, la accesibilidad y la facilidad de uso.
Manuel sur le Cadre mondial pour la gestion de données climatologiques de qualité
Le présent manuel contient des indications et des exigences relatives à l'élaboration, la fourniture, l'échange et l’actualisation de jeux de données climatologiques de haute qualité. Les normes et pratiques recommandées qu'il décrit visent à garantir que les données mises à disposition pour l'évaluation et la surveillance du climat ainsi que pour les applications et les services connexes répondent de manière durable à un ensemble minimal d'exigences en matière de qualité, de gouvernance, d'accessibilité et d’exploitabilité.The Forecast Process: Using the Forecast Funnel
This lesson was developed by meteorologist, Dr. Mick Pope, with sponsorship from the Australian Bureau of Meteorology (BoM). The lesson is a somewhat broad-brush review of the overall forecast process, but with specific application of the forecast funnel approach as used by Australia's Bureau of Meteorology (BoM). The forecast process components include decision support and communication, use of numerical weather prediction, and applying the forecast funnel approach. The forecast funnel is described in detail, along with the forecaster time pyramid, and it is applied using a BoM forecast polic ...Basic Satellite and NWP Integration
NWP is one of the most important forecasting tools in our toolbox. Yet identifying when/where it isn’t capturing reality is difficult. In the short-term forecasting range, it is important as a forecaster to identify when/where NWP output isn’t matching reality. Then you can make appropriate changes to the forecast output. To find those mismatches anywhere in the world, one of the best tools is satellite imagery. In this lesson, we will focus on a few cases using satellite imagery to help identify mismatched features/processes between the satellite imagery and the NWP. Anyone trying to add valu ...GOES-R Geostationary Lightning Mapper (GLM) North America Examples
The Geostationary Lightning Mapper (GLM) aboard the GOES-R series satellites provides continuous lightning detection from space, giving forecasters a unique tool to monitor developing thunderstorms. This 45 minute lesson introduces learners to the benefits of using GLM gridded products, primarily Flash Extent Density (FED). Learners will explore several North American convective events and use Flash Extent Density, in combination with other satellite and radar data, to diagnose convective initiation, storm intensification, and areal extent of lightning activity. Helpful hints to keep in mind w ...Maize Suitability in the Lowlands of Lesotho
The Food and Agriculture Organization (FAO) defined that the suitability is a function of crop climate requirements and land characteristics and it is a measure of how will the qualities of land unit matches the requirements of a particular form of land use. The aim of this research is to improve maize production in the lowlands of Lesotho, this is one of the agro-ecological zones with the most arable land and good soils so it is best to determine the suitability of each crop across this region. This will be achieved by quantitatively and qualitatively looking at the climate conditions require ...Mesoscale Model Components of the National Blend of Models Version 3.0
The National Weather Service National Blend of Models (NBM) was updated to version 3.0 on 27 July 2017. Changes include: Eight new components for the contiguous U.S. (CONUS) and Alaska, including four deterministic models, two ensemble systems, and two post-processed statistical components Five new components for Hawaii and Puerto Rico Expanded forecast domains for the CONUS and Alaska A “Time of Day” (ToD), rather than NWP model, initial time concept Hourly NBM forecasts, with short, day 2-4, and extended forecasts Updated NBM guidance available 50-60 minutes after hourly run time New weather ...GOES-R Series Multilingual Training Resources
This listing of multilingual training materials for the GOES-R series includes both foundational lessons and quick guides developed by various partners at the request of the U.S. National Weather Service and NESDIS. The selections included here represent materials translated to Spanish and Portuguese. Training contributors include COMET, RAMMB/CIRA, CIMSS, and SPoRT. Translation contributors/reviewers include the Servicio Meteorológico Nacional (SMN) in Argentina and the University of São Paulo in Brazil.GOES-16 GLM Case Exercise: Buenos Aires Tornado and Hail Event
The Geostationary Lightning Mapper (GLM) flies aboard the GOES-R series satellites and provides lightning detection data at a quality and resolution not previously available from space. The GLM's continuous lightning monitoring capability is a valuable asset to detecting and monitoring developing thunderstorms 24 hours a day. This 30 minute lesson introduces learners to the benefits of using Geostationary Lightning Mapper (GLM) observations in assessing convection. Learners will explore a severe weather event near Buenos Aires, Argentina, and practice using GLM observations to determine initia ...
WMO for the 21st Century
This restructuring of the Organization will enhance proactive regional engagement and capacity development. In our response to the growing global demand for weather, climate and water expertise, the reform provisions assure that no Member is left behind.
编制WMO改革路线图 : 技术委员会和其他机构
世界气象组织 (WMO) - 世界气象组织 (WMO), 2018إن إعادة ھیكلة المنظمة ( WMO ) المشار إلیھا أعلاه ستعزز المشاركة الإقلیمیة الاستباقیة وبناء القدرات. وعملاً على تلبیة الطلب العالمي المتنامي على الخبرة المتخصصة في مجالات الطقس والمناخ والماء، تكفل أحكام الإصلاح ألا یتخلف أي عضو عن الركب.
خریطة إصلاح المنظمة : اللجان الفنية والهيئات الأخرى
إن إعادة ھیكلة المنظمة ( WMO ) المشار إلیھا أعلاه ستعزز المشاركة الإقلیمیة الاستباقیة وبناء القدرات. وعملاً على تلبیة الطلب العالمي المتنامي على الخبرة المتخصصة في مجالات الطقس والمناخ والماء، تكفل أحكام الإصلاح ألا یتخلف أي عضو عن الركب.
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