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( Rasmussen et al. 2001 ); to fog and visibility ( Fabbian et al. 2007 ; Gultepe et al. 2006 ); and to more general systems ( Huang et al. 2012 ; Isaacs et al. 2014 ). The Applications of Research to Operations at Mesoscale (AROME) nowcasting system (AROME NWC; Auger et al. 2014, manuscript submitted to Quart. J. Roy. Meteor. Soc. ) is based on the operational mesoscale weather forecasting model of Météo-France ( Seity et al. 2011 ) and AROME Airport is developed using AROME NWC as a base. The purpose
( Rasmussen et al. 2001 ); to fog and visibility ( Fabbian et al. 2007 ; Gultepe et al. 2006 ); and to more general systems ( Huang et al. 2012 ; Isaacs et al. 2014 ). The Applications of Research to Operations at Mesoscale (AROME) nowcasting system (AROME NWC; Auger et al. 2014, manuscript submitted to Quart. J. Roy. Meteor. Soc. ) is based on the operational mesoscale weather forecasting model of Météo-France ( Seity et al. 2011 ) and AROME Airport is developed using AROME NWC as a base. The purpose
western African coastline. 5. Discussion and conclusions The forecasting of developing tropical cyclones over the extreme eastern Atlantic remains challenging because of limited observations, the Guinea Highlands, and the interaction between mesoscale convective systems and larger-scale AEWs (2500–3000-km wavelength). Here, we have demonstrated the simulation of the disturbance associated with TD 4 (i.e., TS Debby) using 25- and 5-km grid spacings in the WRF model. This simulation, although not
western African coastline. 5. Discussion and conclusions The forecasting of developing tropical cyclones over the extreme eastern Atlantic remains challenging because of limited observations, the Guinea Highlands, and the interaction between mesoscale convective systems and larger-scale AEWs (2500–3000-km wavelength). Here, we have demonstrated the simulation of the disturbance associated with TD 4 (i.e., TS Debby) using 25- and 5-km grid spacings in the WRF model. This simulation, although not
Re-Analysis ESMF Earth System Modeling Framework FAR False-alarm ratio GFS Global Forecast System GoC Gulf of California GOES Geostationary Operational Environmental Satellite GPM Global Precipitation Measurement GPS Global positioning system GSMaP Global Satellite Mapping of Precipitation HAS Department of Hydrology and Atmospheric Sciences IV Inverted trough JAXA Japan Aerospace Exploration Agency LT Local time MCS Mesoscale convective system NAM North American Mesoscale Forecast System NAME
Re-Analysis ESMF Earth System Modeling Framework FAR False-alarm ratio GFS Global Forecast System GoC Gulf of California GOES Geostationary Operational Environmental Satellite GPM Global Precipitation Measurement GPS Global positioning system GSMaP Global Satellite Mapping of Precipitation HAS Department of Hydrology and Atmospheric Sciences IV Inverted trough JAXA Japan Aerospace Exploration Agency LT Local time MCS Mesoscale convective system NAM North American Mesoscale Forecast System NAME
floats aliases mesoscale variability. It is generally accepted that such data have to be assimilated into dynamically based models in order to map ocean states, and also to physically interpret the observed variability. Many practical schemes for sequentially assimilating ocean data are variants of the Kalman filter. For example the ensemble Kalman filter (e.g., Evensen 2006 ) is being used to make 10-day forecasts of the North Atlantic and Arctic Ocean on a weekly schedule (more information is
floats aliases mesoscale variability. It is generally accepted that such data have to be assimilated into dynamically based models in order to map ocean states, and also to physically interpret the observed variability. Many practical schemes for sequentially assimilating ocean data are variants of the Kalman filter. For example the ensemble Kalman filter (e.g., Evensen 2006 ) is being used to make 10-day forecasts of the North Atlantic and Arctic Ocean on a weekly schedule (more information is
–1-h forecasts and SPC mesoscale analyses using VORTEX2 soundings . Wea. Forecasting , 27 , 667 – 683 , https://doi.org/10.1175/WAF-D-11-00096.1 . 10.1175/WAF-D-11-00096.1 Coniglio , M. C. , and M. D. Parker , 2020 : Insights into supercells and their environments from three decades of targeted radiosonde observations . Mon. Wea. Rev. , 148 , 4893 – 4915 , https://doi.org/10.1175/MWR-D-20-0105.1 . 10.1175/MWR-D-20-0105.1 Coniglio , M. C. , J. Correia Jr ., P. T. Marsh , and
–1-h forecasts and SPC mesoscale analyses using VORTEX2 soundings . Wea. Forecasting , 27 , 667 – 683 , https://doi.org/10.1175/WAF-D-11-00096.1 . 10.1175/WAF-D-11-00096.1 Coniglio , M. C. , and M. D. Parker , 2020 : Insights into supercells and their environments from three decades of targeted radiosonde observations . Mon. Wea. Rev. , 148 , 4893 – 4915 , https://doi.org/10.1175/MWR-D-20-0105.1 . 10.1175/MWR-D-20-0105.1 Coniglio , M. C. , J. Correia Jr ., P. T. Marsh , and
). In 2014, E-4DWX was extended to three more government test sites in the Great Basin of the United States: White Sands Missile Range (WSMR), New Mexico; Yuma Proving Ground (YPG), Arizona; and Electronic Proving Ground (EPG), Arizona. For brevity, this paper focuses on just DPG’s experience with E-4DWX. b. Testing and forecasting at DPG One of DPG’s primary missions is to test equipment that detects chemical and biological hazards. Such tests are very sensitive to mesoscale and microscale weather
). In 2014, E-4DWX was extended to three more government test sites in the Great Basin of the United States: White Sands Missile Range (WSMR), New Mexico; Yuma Proving Ground (YPG), Arizona; and Electronic Proving Ground (EPG), Arizona. For brevity, this paper focuses on just DPG’s experience with E-4DWX. b. Testing and forecasting at DPG One of DPG’s primary missions is to test equipment that detects chemical and biological hazards. Such tests are very sensitive to mesoscale and microscale weather
prediction (NWP) models, dedicated aerosol forecast models, or a combination of both to produce solar exposure forecasts on daily time scales. Breitkreuz et al. (2009) examined the capability of mesoscale forecasts to predict clear-sky conditions. Their studies focused on aerosol chemical transport, which is a significant atmospheric parameter that determines solar exposure on clear-sky days. Breitkreuz et al. (2009) developed Aerosol-Based Forecasts of Solar Irradiance for Energy Applications (AFSOL
prediction (NWP) models, dedicated aerosol forecast models, or a combination of both to produce solar exposure forecasts on daily time scales. Breitkreuz et al. (2009) examined the capability of mesoscale forecasts to predict clear-sky conditions. Their studies focused on aerosol chemical transport, which is a significant atmospheric parameter that determines solar exposure on clear-sky days. Breitkreuz et al. (2009) developed Aerosol-Based Forecasts of Solar Irradiance for Energy Applications (AFSOL
1. Introduction Mesoscale convective systems (MCSs) are the primary source of precipitation across the Great Plains and Midwest during the summer months ( Fritsch et al. 1986 ; Stensrud 1996 ; Ashley et al. 2003 ; Jirak and Cotton 2007 ; Coniglio et al. 2010 ) and provide the rainfall needed for agricultural purposes; thus, better forecasts of nocturnal convection benefit farmers ( Jirak et al. 2003 ). Nocturnal MCS development and sustenance is often tied to the occurrence of the Great
1. Introduction Mesoscale convective systems (MCSs) are the primary source of precipitation across the Great Plains and Midwest during the summer months ( Fritsch et al. 1986 ; Stensrud 1996 ; Ashley et al. 2003 ; Jirak and Cotton 2007 ; Coniglio et al. 2010 ) and provide the rainfall needed for agricultural purposes; thus, better forecasts of nocturnal convection benefit farmers ( Jirak et al. 2003 ). Nocturnal MCS development and sustenance is often tied to the occurrence of the Great
and coastal regions compared to raw mesoscale ensemble forecasts, with modest skill increases after sunrise. The challenge in adding skill to the ensemble by statistically adjusting zero or near-zero q c predictions from the members is in knowing whether fog is likely. The strategy is intentionally conservative such that the fog prediction is taken directly from the NWP model when fog is predicted. The probability of light fog can only be increased from zero, reducing complexity while adding
and coastal regions compared to raw mesoscale ensemble forecasts, with modest skill increases after sunrise. The challenge in adding skill to the ensemble by statistically adjusting zero or near-zero q c predictions from the members is in knowing whether fog is likely. The strategy is intentionally conservative such that the fog prediction is taken directly from the NWP model when fog is predicted. The probability of light fog can only be increased from zero, reducing complexity while adding
our space observations were mesoscale convective systems (MCSs), including squall lines. Because these observations were to be predetermined on the basis of these forecasts, it was important to assess their accuracy. To this end we compared the location and top heights of the MCSs that were predicted for the area between 40°S and 40°N latitude with actual observed ones using satellite imagery. Section 2 describes the methodology used for the assessment, section 3 presents the results, and
our space observations were mesoscale convective systems (MCSs), including squall lines. Because these observations were to be predetermined on the basis of these forecasts, it was important to assess their accuracy. To this end we compared the location and top heights of the MCSs that were predicted for the area between 40°S and 40°N latitude with actual observed ones using satellite imagery. Section 2 describes the methodology used for the assessment, section 3 presents the results, and
