2014 Goes-R Science Seminar December 01, 2014 Low ceiling and visibility is a weather hazard that nearly every forecaster, in nearly every National Weather Service (NWS) Weather Forecast Office (WFO), must regularly address. In addition, national forecast centers such as the Aviation Weather Center (AWC) Alaska Aviation Weather Unit (AAWU), and the Ocean Prediction Center (OPC) are responsible for issuing low ceiling and visibility related products. As such, reliable methods for detecting and characterizing hazardous low clouds are needed. Traditionally, hazardous areas of Fog/Low Stratus (FLS) are identified using a simple stand-alone satellite product that is constructed by subtracting the 3.9 and 11 m brightness temperatures. The 3.9-11 m brightness temperature difference (BTD) has several major limitations. In an effort to address the limitations of the BTD product, the GOES-R Algorithm Working Group (AWG) developed an approach that fuses satellite, Numerical Weather Prediction (NWP) model, Sea Surface Temperature (SST) analyses, and other data sets (e.g. digital surface elevation maps, surface emissivity maps, and surface type maps) to determine the probability that Instrument Flight Rules (IFR) conditions are present. IFR conditions are characterized by a cloud ceiling below 1000 ft and/or a surface visibility less than 3 miles. Satellite and non-satellite predictors are used in a naïve Bayes model to determine the probability of IFR at the resolution of the satellite data. The GOES-R fog/low cloud algorithm is an enterprise system in that it can use satellite data from a variety of current data sensors (VIIRS, GOES, MTSAT, MODIS, AVHRR and SEVIRI) and future operational sensors (ABI and AHI) and NWP data from a variety of models (GFS, RUC, and RAP). In addition, recent research aimed at blending GOES with VIIRS to create a very high-resolution depiction of fog boundaries within valleys has shown great promise. The FLS products are available in AWIPS and have been evaluated within NWS operations during the last three years as part of the Satellite Proving Ground. Forecaster feedback collected so far has been predominantly positive and product improvements have been made as a result of the feedback. References to these products within Area Forecast Discussions (AFD’s) indicate that the products are influencing operational forecasts. An overview of the FLS algorithm, with an emphasis on the efforts to blend GOES with VIIRS, will be given. In addition, the relevance of the FLS products to NWS operations will be discussed. https://web.archive.org/web/*/http://www.goes-r.gov/users/sci-sem/2014_12_01.html

Policysupport.org is home to a range of web-based policy support systems developed, since 2003, collaboratively by AmbioTEK CIC, and applied by King's College London and a range of other partners as specified for each system. The systems are based on the common ecoengine framework for developing web based policy support systems (AmbioTEK) and SimTerra databases (AmbioTEK) but are very varied in their applications (King's College London). Applications in the Policy Support Suite include: WaterWorld: a testbed for the development and implementation of land and water related policies for sites and regions globally, enabling their intended and unintended consequences to be tested in silico before they are tested in vivo. WaterWorld can also be used to understand the hydrological and water resources baseline and water risk factors associated with specific activities under current conditions and under scenarios for land use, land management and climate change. It incorporates detailed spatial datasets at 1-square km and 1 hectare resolution for the entire world, spatial models for biophysical and socio-economic processes along with scenarios for climate, land use and economic change. A series of interventions (policy options) are available which can be implemented and their consequences traced through the socio-economic and biophysical systems. The model integrates with a range of geobrowsers for immersive visualisation of outcomes. AguAAndes: a testbed for the development and implementation of land and water related policies in the Andes, enabling intended and unintended consequences to be tested in silico before they are tested in vivo . It incorporates detailed spatial datasets at 1-square km and 1 hectare resolution for the entire Andes, spatial models for biophysical and socioeconomic processes along with scenarios for climate, land use and economic change. A series of interventions (policy options) are available which can be implemented and their consequences traced through the socio-economic and biophysical systems. CompAndes: a web based tool based on AguAAndes and is developed as a Negotiation Support System (NSS) for negotiations around benefit sharing mechanisms for water. This NSS is a testbed for negotiations around benefit sharing mechanisms for water focusing on sustaining equitable flows of water for all through appropriate land, ecosystem and water management. It is focused on enabling the intended and unintended consequences of benefit sharing mechanisms to be tested in silico before they are tested in vivo. Co$ting Nature: a web based tool for natural capital accounting and analysing the ecosystem services provided by natural environments (i.e. nature's benefits), identifying the beneficiaries of these services and assessing the impacts of human interventions. This PSS is a testbed for the development and implementation of conservation strategies focused on sustaining and improving ecosystem services. MENARA: a web based policy support system for understanding strength, weakness, opportunity and threat (SWOT) at scales from pixel through regional to national considering environment, water, energy, food, economy and population. It is an horizon scanning tool to identify material threats, opportunities and choke points that may precipitate conflict and is designed to help to think through locally appropriate policy responses. FIESTA-FOGINT: a research model to quantify fog inputs in absolute terms and as a proportion of rainfall. Commonly applied to tropical montane cloud affected forests. Also maps the distribution of these forests. EcoActuary: a testbed for the development and implementation of green and grey infrastructure investments focused on reducing the risk to insured assets of multi-hazard risks, including flooding and drought. It incorporates detailed spatial datasets at 1-square km and 1 hectare resolution for the entire world, spatial models for biophysical and socioeconomic processes along with scenarios for climate, land use and economic change. A series of investments can be implemented and their consequences traced through the socio-economic and biophysical systems. An actuary determines the probability (and financial consequences) of risks. They work with accountants, underwriters (and catastrophe modellers) to set insurance rates (premiums). The Eco:Actuary determines mitigation of risk by specific configurations of green infrastructure (GI) and by asset adaptation. It helps understand the asset value protected by GI, alongside other GI co-benefits (ecosystem services). The Eco:Actuary helps advise risk reduction, resilience to avoid losses.