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Sorted by (Issue date descending, Date of update descending, Date of creation descending, Number of collection descending) Add the result to your favourites Refine your searchSensitivity of mesoscale model urban boundary layer meteorology to the scale of urban representation
Atmospheric Chemistry and Physics (ACP), Vol. 11. N° 3. Flagg D.D.; Taylor P.A. - Copernicus GmbH, 2011Mesoscale modeling of the urban boundary layer requires careful parameterization of the surface due to its heterogeneous morphology. Model estimated meteorological quantities, including the surface energy budget and canopy layer variables, will respond accordingly to the scale of representation. This study examines the sensitivity of the surface energy balance, canopy layer and boundary layer meteorology to the scale of urban surface representation in a real urban area (Detroit-Windsor (USA-Canada)) during several dry, cloud-free summer periods. The model used is the Weather Research and Forec ...Long-term analysis of carbon dioxide and methane column-averaged mole fractions retrieved from SCIAMACHY
Atmospheric Chemistry and Physics (ACP), Vol. 11. N° 3. Schneising O.; Buchwitz M.; Reuter M.; et al. - Copernicus GmbH, 2011Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases contributing to global climate change. SCIAMACHY onboard ENVISAT (launch 2002) was the first and is now with TANSO onboard GOSAT (launch 2009) one of only two satellite instruments currently in space whose measurements are sensitive to CO2 and CH4 concentration changes in the lowest atmospheric layers where the variability due to sources and sinks is largest.Representation of tropical deep convection in atmospheric models – Part 1: Meteorology and comparison with satellite observations
Atmospheric Chemistry and Physics (ACP), Vol. 11. N° 3. Russo M.R.; Marécal V.; Hoyle C.R.; et al. - Copernicus GmbH, 2011Fast convective transport in the tropics can efficiently redistribute water vapour and pollutants up to the upper troposphere. In this study we compare tropical convection characteristics for the year 2005 in a range of atmospheric models, including numerical weather prediction (NWP) models, chemistry transport models (CTMs), and chemistry-climate models (CCMs). The model runs have been performed within the framework of the SCOUT-O3 (Stratospheric-Climate Links with Emphasis on the Upper Troposphere and Lower Stratosphere) project. The characteristics of tropical convection, such as seasonal c ...
Joint WMO/ IOC for Oceanographic and Marine Meteorology (JCOMM). Guide to Storm Surge Forecasting
The National Meteorological and Hydrological Services (NMHSs) of an increasing number of maritime countries are actively engaged in the provision of storm surge forecast services for a wide range of maritime and coastal activities, in particular for coastal defense, shipping, fisheries, offshore mining, commerce, coastal engineering, construction and recreation. This guide draws attention to vulnerabilities in coastal areas exposed to storm surges by focusing on risk forecasting, in addition to hazard forecasting.WWRP, 2011-3. WWRP/ETRP Workshop on Operational Monsoon Research and Forecast Issues : lecture notes
CAWCR technical report, 46. Abstracts of the Fifth International Verification Methods Workshop, 1 - 7 December 2011, Melbourne, Australia
This year's scientific workshop offers a stimulating and informative array of presentations on forecast verification relevant to a variety of topics including ensemble and probability forecasts, seasonal forecast and climate projections, aviation forecasts, user-focused verification, tropical cyclones and high impact weather forecasts and warnings, as well as methodologies and issues that apply to many areas. The workshop features five keynote talks by international experts, as well as a public lecture by renowned climate researcher, Professor Neville Nicholls of Monash University on, "Can wea ...CAWCR technical report, 40. Comparison of techniques for the calibration of coupled model forecasts of Murray Darling Basin seasonal mean rainfall
Charles Andrew; Hendon Harry H.; Wang Q.J.; et al. - Centre for Australian Weather and Climate Research, 2011Ensemble forecasts of South Eastern Australian rainfall from POAMA 1.5, a coupled oceanatmosphere dynamical model based seasonal prediction system run experimentally at the Bureau of Meteorology, tend to be under dispersed leading to overconfident probability forecasts. The poor reliability of seasonal forecasts based on dynamical coupled models is a barrier to their adoption as official outlooks by the Bureau of Meteorology. One approach to correcting this problem is model calibration, in which the probability distribution produced by the model is adjusted in light of available information ab ...Satellite Meteorology: GOES Channel Selection V2
This module is an update to the previous Satellite Meteorology: GOES Channel Selection module. It reviews the five GOES imager channels and their use, incorporating conceptual visualizations and numerous imagery examples. The module also includes updated information on improvements for the GOES-13, -14 and -15 satellites. Highlights include a higher resolution 13.3 micrometer CO2 channel (GOES-14 & -15), modified spectral response of the visible channel, improved radiometric performance and pixel geolocation, and shortened data outages during the fall and spring satellite eclipse periods.ASMET: Satellite Precipitation Products for Hydrological Management in Southern Africa
This module introduces a variety of meteorological and hydrological products that can improve the quality of heavy rainfall forecasts and assist with hydrological management during extensive precipitation events in Southern Africa. Among the products are the satellite-based ASCAT, SMOS, and ASAR GM soil moisture products and the hydro-estimator. The products are presented within the context of a case, the flooding of South Africa's Vaal Dam region in 2009/2010.Optimizing the Use of Model Data Products
Each model forecast tells a story about the weather events to unfold. As a forecaster, you employ diagnostics to understand and interpret that story, in order to modify it, blend it with other stories, and generate your own forecast. This lesson will help you sift through the abundance of model data so you can understand and interpret the model’s story. Other lessons cover evaluating the model’s story against observations and against your conceptual models of the evolving situation, blending the stories, and adjusting the forecast to add value over an objective forecast. The diagnostic approac ...Volcanic Ash: Observation Tools and Dispersion Models
This module is the fourth and final entry in the Volcanic Ash series. It covers the tools and techniques used for identifying and forecasting the transport of volcanic ash. Satellite and radar imagery are combined with observations and numerical model output to first identify the presence of volcanic ash and then to help forecast the transport of ash at various levels of the atmosphere.Preparing to Evaluate NWP Models
This lesson prepares the forecaster to evaluate NWP analyses and forecasts using physically based conceptual models of the atmosphere, and the "Vertical Phenomenon Analysis Funnel". This funnel divides the atmosphere into three sections: lower stratosphere and tropopause, mid-to-upper troposphere, and lower troposphere. We discuss tools to use and atmospheric features to assess for each section of the atmosphere, using interactive case examples, and summarize the methodology with a comprehensive example. Finally, we compare model capabilities and the time and space scales of assessment tools u ...
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