J. David Neelin 1,2 , Katrina Hales 1 , Ole Peters 1,5 , Ben Lintner 1,2,7 , Baijun Tian 1,4 , Chris Holloway 3 , Rich Neale 10 , Qinbin Li 1 , Li Zhang 1 , Sam Stechmann 6 , Prabir Patra 8 , Mous Chahine 9 1 Dept. of Atmospheric Sciences & 2 Inst. of Geophysics and Planetary Physics, UCLA 3 University of Reading 4 Joint Institute for Regional Earth System Science and Engineering, UCLA 5 Imperial College, Grantham Inst. 6 Dept. Of Mathematics, UCLA 7 Dept. of Environmental Sciences, Rutgers 8 Frontier Research Center for Global Change, Japan 9 Jet Propulsion Laboratory 10 National Center for Atmospheric Research Deep convection --- transition Deep convection --- transition and tails and tails haracterizing transition to deep convection ong tails in distributions of column tracers
Transcript
J. David Neelin1,2,
Katrina Hales1, Ole Peters1,5, Ben Lintner1,2,7,
Baijun Tian1,4, Chris Holloway3, Rich Neale10, Qinbin Li1,
Li Zhang1, Sam Stechmann6, Prabir Patra8, Mous Chahine9 1Dept. of Atmospheric Sciences & 2Inst. of Geophysics and Planetary Physics, UCLA
3University of Reading4Joint Institute for Regional Earth System Science and Engineering, UCLA
5Imperial College, Grantham Inst.6Dept. Of Mathematics, UCLA
7Dept. of Environmental Sciences, Rutgers8Frontier Research Center for Global Change, Japan
9Jet Propulsion Laboratory10National Center for Atmospheric Research
Deep convection --- transition and tailsDeep convection --- transition and tails
•Characterizing transition to deep convection
•Long tails in distributions of column tracers
2. Transition to strong convection
• Convective quasi-equilibrium assumptions: Above onset threshold, convection/precip. increase keeps system close to onset Arakawa & Schubert 1974; ; Betts & Miller 1986; Moorthi & Suarez 1992; Randall & Pan 1993; Zhang & McFarlane 1995; Emanuel 1993; Emanuel et al 1994; Bretherton et al. 2004; …
• Pick up a function of buoyancy-related fields – temperature T & moisture (here column integrated moisture w)
• Elsewhere: Onset of strong convection conforms to list of properties for continuous phase transition with critical phenomena (Peters & Neelin 2006, Nature Physics); mesoscale implications (Peters, Neelin & Nesbitt 2009, JAS)
• Stochastic convective schemes (and old-fashioned schemes too) need to better characterize the transition to deep convection
• Precip increases with column water vapor at monthly, daily time scales (e.g., Bretherton et al 2004). What happens at shorter time scales needed for stochastic convective parameterization, and for strong precip/mesoscale events?
• Simple e.g. of convective closure (Betts-Miller 1996) shown for vertical integral:
Precip = (w wc( T) + )/c (if positive, zero otherwise)w vertical integrated column water vapor
wc convective threshold, dependent on temperature T c time scale of convective adjustment Stochastic modification ( Lin &Neelin, 2000)
Transition to strong, deep convection: BackgroundTransition to strong, deep convection: Background
Precip. dependence on tropospheric temperature & Precip. dependence on tropospheric temperature & column water vapor from TMIcolumn water vapor from TMI**
•Averages conditioned on vert. avg. temp. T, as well as w (T 200-1000mb from ERA40 reanalysis)
• Precip. mean & variance dependence on w normalized by critical value wc; occurrence probability for precipitating points (for 4 T values); Event size distribution at Nauru
Neelin, Peters, Lin, Holloway & Hales, Phil Trans. Roy. Soc. A, 2008
Example from Manna (1991) lattice model (hopping particles—not a model of convection! 20x20 grid shown)
• Activity (order parameter) & variance dependence on particle density (tuning parameter) [conserving case]
• Occurrence probability (log scale; very Gaussian) & event size distribution [self organizing case]
Neelin, Peters, Lin, Holloway & Hales, Phil Trans. Roy. Soc. A, 2008
TMI precipitation and column water vapor spatial TMI precipitation and column water vapor spatial correlationscorrelations
TMI-AMSRE precipitation and column water vapor TMI-AMSRE precipitation and column water vapor temporal correlationstemporal correlations
Entraining convective available potential energy and precipitation binned by column water vapor, w
• buoyancy & precip. pickup at high w•boundary layer and lower free troposph. moisture contribute comparably*•consistent with importance of lower free tropospheric moisture (Austin 1948; Yoneyama and Fujitani 1995; Wei et al. 1998; Raymond et al. 1998; Sherwood 1999; Parsons et al. 2000; Raymond 2000; Tompkins 2001; Redelsperger et al. 2002; Derbyshire et al. 2004; Sobel et al. 2004; Tian et al. 2006)
*Brown & Zhang 1997 entrainment; scheme and microphysics affect onset value, though not ordering.
Neelin, Peters, Lin, Holloway & Hales, Phil Trans. Roy. Soc. A, 2008 Holloway & Neelin, JAS, 2009
Obs. Freq. of occurrence of Obs. Freq. of occurrence of w/ww/wcc (precipitating pts) (precipitating pts)
Gaussian core
Critical
Eastern Pacific for various tropospheric temperatures
•But exponential tail above critical pt. more large events• with Gaussian core, akin to forced tracer advection- diffusion problems
•Peak just below critical pt. self-organization toward wc
Passive tracer advection-diffusion---probability density function from simple flow configuration
S. Stechmann following methods of Bourlioux & Majda 2002 Phys. Fluids
“Vertical” flow (across gradient) const in vertical, sinusoidal in horizontal, Gaussian in time; horizontal flow constant in space, sinusoid in time
Varying Peclet number
Pe=
Passive tracer advection-diffusion---probability density function from simple flow configuration
Adapted from Bourlioux & Majda 2002 Phys. Fluids
“Vertical” flow (across gradient) const in vertical, sinusoidal in horizontal, Gaussian in time; horizontal flow constant in space, sinusoid in time
High Peclet number (low diffusivity)
Pe=104
Varying autocorrelation-time
jof flow´
TMI probability density function for observed column water vapor
Analysis: Baijun Tian
Anomalies relative to monthly mean, tropical oceans 20S-20N
Gaussian core(fit at half power)
~exponential on high side
NCEP reanalysis daily column water vapor NCEP reanalysis daily column water vapor probability density functionprobability density function
• Anomalies relative to 30-day running mean • Asymmetric exponential tails, assoc. with ascent/descent• Low precip.: symmetric exponential tails
Analysis:Ben Lintner
Distribution of Column-int. MOPITT CO obs. &Distribution of Column-int. MOPITT CO obs. &GEOS-Chem simulations 20S-20N & subregionsGEOS-Chem simulations 20S-20N & subregions
~exponentialtails
2000-20052001-2006
Analysis: B. Tian, Q. Li, L. Zhang
Distribution of daily CODistribution of daily CO22 anomalies anomalies
• AIRS retrievals(Chahine et al 2005, 2008)
• GEOS-Chem simulations projected on AIRS weighting functions
(Analysis: Ben Lintner)
(Analysis: Qinbin Li, Li Zhang)
• These statistics for precipitation and buoyancy related variables at short time scales provide promising means to quantify the transition to tropical deep convection --- collapse of dependences on temperature and water vapor to simple forms is handy; properties known to appear together in much simpler systems--- it should be possible to capture these in stochastic convection schemes
• Tracer distributions consistent with simple prototypes; core with stretched exponential tails ubiquitous for various tracers
• Corroborating evidence that the forced tracer advection problem, with the leading effect due to maintained vertical gradient, creates the long tails above critical in column water vapor--- TBD: implications for extreme events
