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1. Introduction The term “nowcasting” refers to short-term (0–6 h or less) forecasting. Nowcasts of high-impact weather events, such as flood-producing rains and hail, can be made with sufficient lead time accuracy and spatial specificity within this time frame such that appropriate actions can be taken to effectively mitigate the loss of life and property. Thus, the term nowcasting emphasizes specificity and the short time nature of a weather event forecast ( Browning 1982 ). In current
1. Introduction The term “nowcasting” refers to short-term (0–6 h or less) forecasting. Nowcasts of high-impact weather events, such as flood-producing rains and hail, can be made with sufficient lead time accuracy and spatial specificity within this time frame such that appropriate actions can be taken to effectively mitigate the loss of life and property. Thus, the term nowcasting emphasizes specificity and the short time nature of a weather event forecast ( Browning 1982 ). In current
1. Introduction Providing public warnings of impending thunderstorms is an important role of weather services. By observing the motion and evolution of thunderstorms using radar data, forecasters can reasonably predict the location and severity of thunderstorms up to 1 h into the future. This is an example of what is widely known as “nowcasting.” To help objectify and automate the nowcasting process, many radar-based systems have been developed in recent years. Among these are Thunderstorm
1. Introduction Providing public warnings of impending thunderstorms is an important role of weather services. By observing the motion and evolution of thunderstorms using radar data, forecasters can reasonably predict the location and severity of thunderstorms up to 1 h into the future. This is an example of what is widely known as “nowcasting.” To help objectify and automate the nowcasting process, many radar-based systems have been developed in recent years. Among these are Thunderstorm
1. Introduction The purpose of this paper is threefold. The first intent is to provide insights into the convective storm nowcasting challenges specific to Beijing, China. The second intent is to present the results of nowcasts made using a diverse variety of state-of-the-art nowcasting systems during the 2008 Beijing Summer Olympic Games. The third is to provide comments on the present status of nowcasting convective storms, and possible future directions based on these experiences. A
1. Introduction The purpose of this paper is threefold. The first intent is to provide insights into the convective storm nowcasting challenges specific to Beijing, China. The second intent is to present the results of nowcasts made using a diverse variety of state-of-the-art nowcasting systems during the 2008 Beijing Summer Olympic Games. The third is to provide comments on the present status of nowcasting convective storms, and possible future directions based on these experiences. A
1. Introduction This is the continuation of a two-part paper that describes a method for developing automated (strategic) forecasts and (tactical) nowcasts of energy dissipation rate to the one-third power (EDR) for aviation turbulence applications. Part I provided a description of the forecast method along with statistical-performance results from comparisons with observations ( Sharman and Pearson 2017 ). The turbulence-forecasting technique is an extension of the Graphical Turbulence
1. Introduction This is the continuation of a two-part paper that describes a method for developing automated (strategic) forecasts and (tactical) nowcasts of energy dissipation rate to the one-third power (EDR) for aviation turbulence applications. Part I provided a description of the forecast method along with statistical-performance results from comparisons with observations ( Sharman and Pearson 2017 ). The turbulence-forecasting technique is an extension of the Graphical Turbulence
A Study of Extrapolation Nowcasting Based on IVAP-Retrieved Wind1. Introduction Doppler weather radar is a useful tool in detecting convective storm, which provides reflectivity, radial velocity, and velocity spectral width at high temporal and spatial resolution. Radar reflectivity has been used in storm nowcasting via extrapolation methods, which are still being used in many operational nowcasting systems. An extensive review of earlier studies on thunderstorm nowcasting techniques can be found in Wilson et al. (1998) . Ligda (1953) did the earliest
1. Introduction Doppler weather radar is a useful tool in detecting convective storm, which provides reflectivity, radial velocity, and velocity spectral width at high temporal and spatial resolution. Radar reflectivity has been used in storm nowcasting via extrapolation methods, which are still being used in many operational nowcasting systems. An extensive review of earlier studies on thunderstorm nowcasting techniques can be found in Wilson et al. (1998) . Ligda (1953) did the earliest
1. Introduction The methods that are primarily used for nowcasting precipitation over a short period of time (e.g., <6 h) can be classified into two categories: 1) methods based on numerical weather prediction (NWP) models, and 2) methods based on extrapolating radar echoes ( Dixon and Wiener 1993 ; Li et al. 1995 ; Germann and Zawadzki 2002 ; Mandapaka et al. 2012 ; Hwang et al. 2015 ; Shi et al. 2015 ; Zou et al. 2019 ). To accurately nowcast precipitation at a local station using NWP
1. Introduction The methods that are primarily used for nowcasting precipitation over a short period of time (e.g., <6 h) can be classified into two categories: 1) methods based on numerical weather prediction (NWP) models, and 2) methods based on extrapolating radar echoes ( Dixon and Wiener 1993 ; Li et al. 1995 ; Germann and Zawadzki 2002 ; Mandapaka et al. 2012 ; Hwang et al. 2015 ; Shi et al. 2015 ; Zou et al. 2019 ). To accurately nowcast precipitation at a local station using NWP
1. Introduction Nowcasting is short-period weather forecasting concerned with current weather conditions and the changes over the next few tens of minutes to the ensuing 6 h. In contrast to the familiar synoptic weather forecast (beyond 6 h), nowcasting is also highly location specific and requires data of very high spatial and temporal resolution to produce accurate forecasts. The primary aim of nowcasting is to predict significant weather events with high specificity as to their onset
1. Introduction Nowcasting is short-period weather forecasting concerned with current weather conditions and the changes over the next few tens of minutes to the ensuing 6 h. In contrast to the familiar synoptic weather forecast (beyond 6 h), nowcasting is also highly location specific and requires data of very high spatial and temporal resolution to produce accurate forecasts. The primary aim of nowcasting is to predict significant weather events with high specificity as to their onset
1. Introduction Precipitation nowcasting for heavy precipitation events has great societal importance for early warning or disaster prevention purposes, yet is generally considered to be an unsolved problem because the performance of operational nowcasting models is still low. Kato et al. (2017) studied heavy rainfall events in Japan, and reported that the critical success index (CSI) for 30-min prediction on precipitation greater than 20 mm is as low as 0.2 for the Japan Meteorological
1. Introduction Precipitation nowcasting for heavy precipitation events has great societal importance for early warning or disaster prevention purposes, yet is generally considered to be an unsolved problem because the performance of operational nowcasting models is still low. Kato et al. (2017) studied heavy rainfall events in Japan, and reported that the critical success index (CSI) for 30-min prediction on precipitation greater than 20 mm is as low as 0.2 for the Japan Meteorological
data are used to evaluate performance; all temperature results reported in this paper are based on the test data and are directly comparable to the results in Roebber (2018) . b. Convection occurrence nowcasts The AutoNowCaster (ANC; Mueller et al. 2003 ; Lakshmanan et al. 2012 ) generates 60-min nowcasts of convective likelihood (CL). As described in BXCS, these data span the period 11 June 2012–30 September 2012 (from 1400 to 2359 UTC each day) and lie on a 0.02° × 0.02° latitude
data are used to evaluate performance; all temperature results reported in this paper are based on the test data and are directly comparable to the results in Roebber (2018) . b. Convection occurrence nowcasts The AutoNowCaster (ANC; Mueller et al. 2003 ; Lakshmanan et al. 2012 ) generates 60-min nowcasts of convective likelihood (CL). As described in BXCS, these data span the period 11 June 2012–30 September 2012 (from 1400 to 2359 UTC each day) and lie on a 0.02° × 0.02° latitude
A Deep Learning Network for Cloud-to-Ground Lightning Nowcasting with Multisource Dataof a growing thunderstorm ( Vincent et al. 2003 ). Radar reflectivity data can be used to indirectly identify the electrification process within a developing thunderstorm because graupel and hail particles return large reflectivity echoes ( Buechler and Goodman 1990 ; Vincent et al. 2003 ; Mosier et al. 2011 ). Hence, large reflectivity has been widely used as an indicator of the onset of cloud-to-ground (CG) lightning in studies of nowcasting (e.g., Mecikalski et al. 2013 ). The appearance of
of a growing thunderstorm ( Vincent et al. 2003 ). Radar reflectivity data can be used to indirectly identify the electrification process within a developing thunderstorm because graupel and hail particles return large reflectivity echoes ( Buechler and Goodman 1990 ; Vincent et al. 2003 ; Mosier et al. 2011 ). Hence, large reflectivity has been widely used as an indicator of the onset of cloud-to-ground (CG) lightning in studies of nowcasting (e.g., Mecikalski et al. 2013 ). The appearance of
