Search Results
well as a physical interpretation, are provided in Table 1 . For 2004–06, the MB06 algorithm has been transitioned from a “proof of concept” into a real-time product, one designed for use in broader applications over larger domains. These applications include, in addition to 0–1-h day and night CI nowcasting at 1 km-resolution, CI climatological applications, 0–90-min lightning initiation nowcasting, delineation of surface convergent boundaries (Jay Hanna, NOAA, 2005, personal communication
well as a physical interpretation, are provided in Table 1 . For 2004–06, the MB06 algorithm has been transitioned from a “proof of concept” into a real-time product, one designed for use in broader applications over larger domains. These applications include, in addition to 0–1-h day and night CI nowcasting at 1 km-resolution, CI climatological applications, 0–90-min lightning initiation nowcasting, delineation of surface convergent boundaries (Jay Hanna, NOAA, 2005, personal communication
entrainment zone, were estimated from profiles of θ υ from the ISS soundings, based on the definition given in Wyngaard and LeMone (1980) and Stull (1988) . One-minute averages of z i were determined from HARLIE aerosol backscatter profiles using an automated algorithm that employs the Haar wavelet technique documented by Davis et al. (2000) . The algorithm finds the center of the aerosol gradient at the top of the CBL. The layer identified by the algorithm between altitudes of 0.6 and 0.8 km from
entrainment zone, were estimated from profiles of θ υ from the ISS soundings, based on the definition given in Wyngaard and LeMone (1980) and Stull (1988) . One-minute averages of z i were determined from HARLIE aerosol backscatter profiles using an automated algorithm that employs the Haar wavelet technique documented by Davis et al. (2000) . The algorithm finds the center of the aerosol gradient at the top of the CBL. The layer identified by the algorithm between altitudes of 0.6 and 0.8 km from
radiation so that sunset was a half-hour too early. 2 e. Convective boundary layer depth Figures 8 and 9 show the CBL depth as a function of time and longitude, respectively, based on observations and ARW-WRF. As noted in the foregoing, the wind profiler CBL depth z i _Prof is based on an algorithm that identifies the CBL top as immediately beneath the maximum vertical SNR gradient, which typically occurs in the middle of the transition layer between the CBL and the free
radiation so that sunset was a half-hour too early. 2 e. Convective boundary layer depth Figures 8 and 9 show the CBL depth as a function of time and longitude, respectively, based on observations and ARW-WRF. As noted in the foregoing, the wind profiler CBL depth z i _Prof is based on an algorithm that identifies the CBL top as immediately beneath the maximum vertical SNR gradient, which typically occurs in the middle of the transition layer between the CBL and the free
a , b ). A statistical retrieval was combined with hourly Rapid Update Cycle (RUC) model profiles to provide a nominal hybrid first guess of temperature and moisture to the AERI physical retrieval algorithm. AERI downwelling radiance measurements provided temperature and moisture profile corrections in the planetary boundary layer (PBL) below 2.5 km. The AERI data have a vertical resolution of 50 m in the 0–1-km layer, degrading to 250 m in the 2–3-km layers. The NCAR Integrated Sounding System
a , b ). A statistical retrieval was combined with hourly Rapid Update Cycle (RUC) model profiles to provide a nominal hybrid first guess of temperature and moisture to the AERI physical retrieval algorithm. AERI downwelling radiance measurements provided temperature and moisture profile corrections in the planetary boundary layer (PBL) below 2.5 km. The AERI data have a vertical resolution of 50 m in the 0–1-km layer, degrading to 250 m in the 2–3-km layers. The NCAR Integrated Sounding System
. Part II: Feedbacks within the continental United States. J. Hydrometeor. , 4 , 570 – 583 . Fulton , R. A. , J. P. Briedenbach , D-J. Seo , D. A. Miller , and T. O’Bannon , 1998 : The WSR-88D rainfall algorithm. Wea. Forecasting , 13 , 377 – 395 . Garratt , J. R. , 1992 : The Atmospheric Boundary Layer . Cambridge University Press, 316 pp . Gutman , G. , and A. Ignatov , 1998 : The derivation of green vegetation fraction from NOAA/AVHRR data for use in numerical
. Part II: Feedbacks within the continental United States. J. Hydrometeor. , 4 , 570 – 583 . Fulton , R. A. , J. P. Briedenbach , D-J. Seo , D. A. Miller , and T. O’Bannon , 1998 : The WSR-88D rainfall algorithm. Wea. Forecasting , 13 , 377 – 395 . Garratt , J. R. , 1992 : The Atmospheric Boundary Layer . Cambridge University Press, 316 pp . Gutman , G. , and A. Ignatov , 1998 : The derivation of green vegetation fraction from NOAA/AVHRR data for use in numerical
. Miller , and T. O’Bannon , 1998 : The WSR-88D rainfall algorithm. Wea. Forecasting , 13 , 377 – 395 . Giorgi , F. , L. O. Mearns , C. Shields , and L. Mayer , 1996 : A regional model study of the importance of local versus remote controls of the 1988 drought and 1993 flood over the central United States. J. Climate , 9 , 1150 – 1162 . Gutman , G. , and A. Ignatov , 1997 : Satellite-derived green vegetation fraction for the use in numerical weather prediction models
. Miller , and T. O’Bannon , 1998 : The WSR-88D rainfall algorithm. Wea. Forecasting , 13 , 377 – 395 . Giorgi , F. , L. O. Mearns , C. Shields , and L. Mayer , 1996 : A regional model study of the importance of local versus remote controls of the 1988 drought and 1993 flood over the central United States. J. Climate , 9 , 1150 – 1162 . Gutman , G. , and A. Ignatov , 1997 : Satellite-derived green vegetation fraction for the use in numerical weather prediction models
