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Lightning Observations During NAME

Lightning Observations During NAME. Walt Petersen 1 * , Rich Blakeslee 2 * , Steve Goodman 2 , Phil Krider 3 , Steve Rutledge 4 , and Bob Maddox 3 1 UAH - NSSTC/ESSC; 2 NASA-MSFC/NSSTC; 3 UA; 4 CSU. *Contacts: walt.petersen@msfc.nasa.gov richard.blakeslee@msfc.nasa.gov.

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Lightning Observations During NAME

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  1. Lightning Observations During NAME Walt Petersen1*, Rich Blakeslee2*, Steve Goodman2, Phil Krider3, Steve Rutledge4, and Bob Maddox3 1UAH-NSSTC/ESSC; 2 NASA-MSFC/NSSTC; 3UA; 4CSU *Contacts: walt.petersen@msfc.nasa.gov richard.blakeslee@msfc.nasa.gov

  2. GAP FILLING CONTRIBUTIONS TO NAME • Hydrometeorology • Lightning observations can help to fill existing observational network gaps in NAME, providing continuous long-term climatological/hydrological observations of convection and rainfall. • Established connections between lightning, cloud physics and improvement of QPE (e.g., rainfall, convective structure, precipitation microphysics, latent heating) • Climate • Multi-year sampling of convective processes and precipitation in the NAME Tier-1 domain via installation of Cloud-to-Ground (CG) lightning network – provide an enhancement/complementto observation network, including satellites • Continuous, wide-area detection [O(105 km2)] • 500-1000 m location accuracy; 70-90 % Detection efficiency

  3. DIRECT APPLICATIONS TO NAME SCIENCE • Lightning is forced by, and varies with, outbreaks of convective activity over a variety of temporal/spatial scales (storm to climate) • Storm-scale convective structure • Intraseasonal changes in convective regime and bursts/breaks in SW monsoon convection • Diurnal cycle of convection • Interannual variability of convection • Lightning location is a strong function of topography in SW monsoon region. • Indicate preferred locations/timing of convection/convective rainfall in NAME domain as a function of underlying land surface characteristics. • Valuable/useful over complex terrain of the SMO where gaps exist in current observational network

  4. Hail/Graupel Rain Snow/Ice THE SCIENTIFIC BASIS Well-established physical links between lightning, cloud dynamics, and precipitation microphysics Latent heating + -40oC -10oC + + = Positive Charge = Negative Charge

  5. Climatologically from TRMM LIS/PR…………. Mixed Phase - Lightning Mixed Phase - Rainrate Warm season statistics for 20 10o x 10o boxes across the Tropics. Lightning - Rainrate Petersen et al., 2001

  6. = East anomaly* regime * defined by 700 mb u-wind NASA-MSFC Brazilian Lightning Detection Network deployed in the Amazon since 1/99 TRMM-LBA • Intraseasonal variability apparent • East (west) anomaly=more (less) lightning. Petersen et al., 2002 • But, similar daily mean rain rates? • True reflection of varying cloud physics and vertical structure as a function of intraseasonal regime.

  7. 10 TRMM-LBA: Polarimetric Comparison Easterly Regime (Frequent Lightning) Westerly Regime (Reduced Lightning) 5 LDR ZDR • 990126 ZDR-LDR signature suggests hail production via drop freezing Cifelli et al., 2002

  8. RECENT APPLICATIONS RELATED TO QPE • Direct estimation of bulk rain-yields (rain mass/flash count) ranging from storm to climate scales (identification of climatological convective regimes) • Continuous and instantaneous measurement of rainfall, periodically calibrated by external radar or passive microwave (PM) measurements • Constraint on convective structure identification (e.g., convective/stratiform partitioning) leading to blended IR/Lightning or IR/PM/Lightning satellite rainfall estimation algorithms (e.g., Goodman et al,. 1988; Grecu et al., 2000) • Assimilation of lightning data into regional forecast models to improve QPE/QPF (operational NWP/NIMROD, Golding, 1997, 2000; research- MM5, Alexander et al., 1999). • Use items 1-3 as needed to tune/nudge rain rates • Constrain integrated latent heating (also adjust profile shape) • Assimilate nudged heating profile • BEST WHEN ICE PROCESSES MAKE A SIGNIFICANT CONTRIBUTION TO RAINWATER BUDGET!

  9. 20+ dBZ 35+ dBZ 43+ dBZ 49+ dBZ 52+ dBZ Courtesy D. Cecil, UAH/NSSTC 0% 25% 50% 75% 100% The presence of robust ice processes near the SMO is NOT an Issue! Tier-1 Courtesy D. Cecil UAH/NSSTC • Max precipitation feature reflectivity at ~-30oC. Ice processes are plentiful. • One of the most electrically active areas in the world Courtesy D. Cecil UAH/NSSTC 0% 25% 50% 75% 100% • 50-75 % of Rainfall associated with lightning-producing storms over SMO • 28-33 dBZ @ -30oC; 0.7-2.2 Flashes/min • Comprise 3.3% of sample but 50-75% of the rainfall!!

  10. Potential NAME ALDF network geometry 300 km • 5-station Advanced Lightning Direction Finder (ALDF) network • TOA/DF technique, = Potential ALDF site = Current NALDN site

  11. NAME offers Atmos. Elec./Hydrology/Meteorology/Climatology communities a UNIQUE INTERDISCIPLINARY OPPORTUNITY • Plans • Pending • Endorsement of this idea by NAME SWG • Identification of Univ./Govt. collaborators from Mexico • Identification of suitable sites (EM noise reasonable, require security, internet access for real-time data processing) • Pursue funding via NSF Hydrology and Physical Meteorology programs • NASA-MSFC will supply antenna/computer hardware (cost sharing = $235 K) • Vaisala-GAI (current NALDN operators) may acquire network if NALDN expanded all the way into Mexico- this would ensure long term sampling over all of the NAME Tiers.

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