Search Results
Mesonets play a critical role in near-surface weather and climate observations. It is essential that we continue to maintain, operate, and expand these networks. Mesoscale in situ meteorological observations, roughly spanning a 30-km (∼20 mi) radius or grid box around a given location, are essential to better foster weather and climate forecasting and decision-making by a myriad of stakeholder communities. The latter include, for example, state environmental and emergency management agencies
Mesonets play a critical role in near-surface weather and climate observations. It is essential that we continue to maintain, operate, and expand these networks. Mesoscale in situ meteorological observations, roughly spanning a 30-km (∼20 mi) radius or grid box around a given location, are essential to better foster weather and climate forecasting and decision-making by a myriad of stakeholder communities. The latter include, for example, state environmental and emergency management agencies
on geographic location. For example, extreme heat in Wisconsin would differ from what is considered as extreme heat in Texas. This is also true of winter storms, since a particular amount of heavy snowfall in the northern United States would not impact that region the same as the equivalent snowfall amount would affect a southern state. These examples reflect another issue of how to define an extreme event, which is not discussed in this study. DEFINITION ANALYSIS. To begin this analysis, all
on geographic location. For example, extreme heat in Wisconsin would differ from what is considered as extreme heat in Texas. This is also true of winter storms, since a particular amount of heavy snowfall in the northern United States would not impact that region the same as the equivalent snowfall amount would affect a southern state. These examples reflect another issue of how to define an extreme event, which is not discussed in this study. DEFINITION ANALYSIS. To begin this analysis, all
monitoring systems. Quantitatively understanding the metadata of such datasets helps recognize their value and clarify their limitations. The USGS NWIS, for example, represents a hydrologic data source of tremendous geographic scope, time span, and total volume. Users can perform large-scale streamflow modeling and computations with such a dataset and it serves as a central source of such information for locations across the nation. However, users may have difficulty finding water-quality measurements of
monitoring systems. Quantitatively understanding the metadata of such datasets helps recognize their value and clarify their limitations. The USGS NWIS, for example, represents a hydrologic data source of tremendous geographic scope, time span, and total volume. Users can perform large-scale streamflow modeling and computations with such a dataset and it serves as a central source of such information for locations across the nation. However, users may have difficulty finding water-quality measurements of
Since its start in 2006, the WxChallenge has become so ingrained in the higher education experience across North America that some participants put results on their resumes and continue competing after graduation. Forecast competitions serve as an excellent teaching tool in the meteorology and atmospheric science communities. Many students become geographically focused on everyday local conditions with regard to understanding meteorology and its impacts with respect to forecasting, which
Since its start in 2006, the WxChallenge has become so ingrained in the higher education experience across North America that some participants put results on their resumes and continue competing after graduation. Forecast competitions serve as an excellent teaching tool in the meteorology and atmospheric science communities. Many students become geographically focused on everyday local conditions with regard to understanding meteorology and its impacts with respect to forecasting, which
technology has created new contemporary means for people to access weather forecasts, pointing to the need to update past literature in this specific niche of weather research. With the onset of smartphones and the increasing use of mobile weather applications (MWAs) today, this technology is rapidly becoming the public face of weather forecasting (the entity that the public most associates with weather forecasts). A smartphone is defined as “a cell phone that includes additional software functions (as
technology has created new contemporary means for people to access weather forecasts, pointing to the need to update past literature in this specific niche of weather research. With the onset of smartphones and the increasing use of mobile weather applications (MWAs) today, this technology is rapidly becoming the public face of weather forecasting (the entity that the public most associates with weather forecasts). A smartphone is defined as “a cell phone that includes additional software functions (as
model (GCM) outputs and station-based local climate. Current regional capacities for station-scale climate prediction using GCMs are limited. Figure 5 shows the resolution of GCMs and their prediction skill for the local climate. The three stations considered, Afiamalu, Faleolo, and Apia, are geographically close to each other (with a distance of around 10−30 km from each other) and have different topographical features. The rainfall gauges for the stations are placed in mountains, an airport, and
model (GCM) outputs and station-based local climate. Current regional capacities for station-scale climate prediction using GCMs are limited. Figure 5 shows the resolution of GCMs and their prediction skill for the local climate. The three stations considered, Afiamalu, Faleolo, and Apia, are geographically close to each other (with a distance of around 10−30 km from each other) and have different topographical features. The rainfall gauges for the stations are placed in mountains, an airport, and
requested automatically through traditional platforms such as mobile phones or desktop workstations, the sharing of and access to pooled resources regardless of geographic proximity, rapid scalability of those resources to match end-user demand, and metered usage that ensures transparent cost accounting for resources used in a given application. Cloud environments are further subcategorized based upon their intended use and availability. Private clouds are those used and maintained by a single
requested automatically through traditional platforms such as mobile phones or desktop workstations, the sharing of and access to pooled resources regardless of geographic proximity, rapid scalability of those resources to match end-user demand, and metered usage that ensures transparent cost accounting for resources used in a given application. Cloud environments are further subcategorized based upon their intended use and availability. Private clouds are those used and maintained by a single
daytime solar heating. Therefore, the diurnal cycle in temperature can be substantial, making for large swings between stable and convective boundary layers. Sampling this transition required distributed profiling of the lower (0–400 m) atmosphere, with measurement sites distributed geographically across different surface types and across different parts of the valley. Deep convection initiation : Thunderstorms routinely form over the mountains surrounding the SLV. However, on some days these storms
daytime solar heating. Therefore, the diurnal cycle in temperature can be substantial, making for large swings between stable and convective boundary layers. Sampling this transition required distributed profiling of the lower (0–400 m) atmosphere, with measurement sites distributed geographically across different surface types and across different parts of the valley. Deep convection initiation : Thunderstorms routinely form over the mountains surrounding the SLV. However, on some days these storms
evolved to include daily estimates of wildfire danger, and has become an integral tool used by fire managers across the United States as well as other state and local entities to assess potential fire conditions. WFAS relies primarily on data from Remote Automated Weather Stations (RAWS), a network of more than 3,000 stations that collect and transmit hourly weather information from which indices in the National Fire Danger Rating System (NFDRS) are then calculated. Information about the presence of
evolved to include daily estimates of wildfire danger, and has become an integral tool used by fire managers across the United States as well as other state and local entities to assess potential fire conditions. WFAS relies primarily on data from Remote Automated Weather Stations (RAWS), a network of more than 3,000 stations that collect and transmit hourly weather information from which indices in the National Fire Danger Rating System (NFDRS) are then calculated. Information about the presence of
engaged in EO-based capacity building across various themes for the stakeholder community and from the satellite EO data community, as well as several international stakeholder agencies with a need for real-world application of EO systems and data. Participants were selected by invitation to represent as much breadth in various themes (such as water, health, ecosystem function, agriculture, and disasters) as possible, as well as geographic relevance (Asia, Africa, and the Americas). Numerous and
engaged in EO-based capacity building across various themes for the stakeholder community and from the satellite EO data community, as well as several international stakeholder agencies with a need for real-world application of EO systems and data. Participants were selected by invitation to represent as much breadth in various themes (such as water, health, ecosystem function, agriculture, and disasters) as possible, as well as geographic relevance (Asia, Africa, and the Americas). Numerous and
