• Estimation of some derived parameters from WP/RASS data sets

BY

Dr. (MRS) R.R. JoshiIndian Institute of Tropical Meteorology,

Pune

Project TitleProject Title

““Establishment of wind profiler data Establishment of wind profiler data archival and utilization Centre at archival and utilization Centre at IITM for Wind Profiler/Radio IITM for Wind Profiler/Radio Acoustic Sounding System”Acoustic Sounding System”

The system is now being continuously The system is now being continuously operated since June 2003. operated since June 2003.

Data Archival Status: Hourly Averaged Data Archival Status: Hourly Averaged Vector Wind Data for the period June Vector Wind Data for the period June 2003 upto date.2003 upto date.

Data is archived on 40 GB DAT and CDSData is archived on 40 GB DAT and CDS Data Format: Text File (Height, u, v, w, Data Format: Text File (Height, u, v, w,

ws & wd)ws & wd)

Quality Control checks of Quality Control checks of WP/RASS Data WP/RASS Data

1.1. Height continuity check on observed Height continuity check on observed radial velocities has been incorporated with a radial velocities has been incorporated with a multiple peak finding procedure for every multiple peak finding procedure for every range / height bin after an objective noise level range / height bin after an objective noise level estimation in the spectral domain using the estimation in the spectral domain using the Hildebrand and Sekhon(1) procedure as is Hildebrand and Sekhon(1) procedure as is standard in all wind profiler work including standard in all wind profiler work including that at NOAA profilers in USA.that at NOAA profilers in USA.

2.2. The signal tracking procedure checks for The signal tracking procedure checks for continuity of the signal in adjacent range bins continuity of the signal in adjacent range bins in the radial beam spectral data .The algorithm in the radial beam spectral data .The algorithm is similar, but not identical, to the adaptive is similar, but not identical, to the adaptive tracking procedure used at NMRF Gadanki. tracking procedure used at NMRF Gadanki. The signal tracking window for tilted (east & The signal tracking window for tilted (east & north) beams is typically set at of the north) beams is typically set at of the unambiguous velocity for the radar unambiguous velocity for the radar measurement set. For the current operations measurement set. For the current operations this translates to a velocity window of ±3m/sec this translates to a velocity window of ±3m/sec . For the vertical wind the tracking window is . For the vertical wind the tracking window is set at ±1 m/s. set at ±1 m/s.

Consensus AveragingConsensus Averaging The consensus averaging procedure operates on the time The consensus averaging procedure operates on the time

series of radial velocity values (for tilted beams) obtained series of radial velocity values (for tilted beams) obtained for a given range bin over the observation period (approx. for a given range bin over the observation period (approx. 10 values in one hour). It assign weight to individual 10 values in one hour). It assign weight to individual velocity values. Each velocity value is compared with itself velocity values. Each velocity value is compared with itself and other values in the time series to check how many of and other values in the time series to check how many of these values fall within a velocity window of ±5 mps. This these values fall within a velocity window of ±5 mps. This number of velocity value falling within the window is number of velocity value falling within the window is called weight of that (observed) value. Weights are called weight of that (observed) value. Weights are calculated for each velocity value. Only those observed calculated for each velocity value. Only those observed values which have weights more than 4 out of 10 are used values which have weights more than 4 out of 10 are used to calculate consensus average. For the vertical beam to calculate consensus average. For the vertical beam velocity window is set ±1 mps. velocity window is set ±1 mps.

Computation of wind componentsComputation of wind components From the consensusly averaged radial velocity values From the consensusly averaged radial velocity values

hourly average values of u and v are calculated by using hourly average values of u and v are calculated by using formulaformula

U = (Vre – wsin U = (Vre – wsin θθ) / cos ) / cos θθ V = (Vrn - wsin V = (Vrn - wsin θθ) / cos ) / cos θθ Where θ is the elevation angle of the tilted beam.Where θ is the elevation angle of the tilted beam.

This procedure helps to eliminate outliers due to spiky noise This procedure helps to eliminate outliers due to spiky noise or interference which is essential for quality control. The or interference which is essential for quality control. The velocity window parameters as used above are typically velocity window parameters as used above are typically same as used by NOAA researchers on the data of their 400 same as used by NOAA researchers on the data of their 400 MHZ profilers. After observing 6 minute and hourly data MHZ profilers. After observing 6 minute and hourly data large shear in u and/orv is seen it seems only consensusly large shear in u and/orv is seen it seems only consensusly average is not adequate; we need to introduce additional average is not adequate; we need to introduce additional shear check condition on the consensusly passed u and v shear check condition on the consensusly passed u and v values. values.

• If ui > ui+1 then < 2 and

If ui+1 > ui then < 2

• If the condition is satisfied add the weight of ui as one with respect to ui+1.

• Repeat this for all u’s (v’s). Only those values of consensusly passed u (v) values which have a weight of greater 40% should be used for further calculations.

1i

i

u

u

i

i

u

u 1

Trend validation of WP/RASS dataTrend validation of WP/RASS data WP data is therefore compared for the trends with WP data is therefore compared for the trends with

the available monthly average normal winds from the available monthly average normal winds from RS/RW Santacruz, Mumbai, from 1955-1970, Pilot RS/RW Santacruz, Mumbai, from 1955-1970, Pilot Balloon data of Pune from 1935-1970 and current Balloon data of Pune from 1935-1970 and current monthly average of RS/RW data for Santacruz for monthly average of RS/RW data for Santacruz for the months June-September 2003. Above data are the months June-September 2003. Above data are taken from IMD, Pune for both morning and taken from IMD, Pune for both morning and evening ascents. This data is compared with evening ascents. This data is compared with WP/RASS data for four months . It is generally WP/RASS data for four months . It is generally showing same trend for vector wind direction and showing same trend for vector wind direction and vector wind speed. vector wind speed.

Normal Vector w ind speed for P.B. Pune - July (evening) 1935-70

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Wind speed in mps

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ht

in k

ms

WP-RASS Average Vector Wind Speed for

July 2003 (evening)

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1011

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Wind Speed (m/s)

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(km

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RS/RW Normals of vector wind speed for July 1955-70 (evening), Mumbai

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RS/RW Vector w ind speed for July 2003 (evening), Mumbai

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Wind Speed for July2003 (Evening)

Normal Wind direction for P.B. Pune -July (Evening) 1935-70

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Wind direction in degrees

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sRS/RW Wind direction July 2003

(Evening), Mumbai

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Wind direction in degrees

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t in

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WP-RASS Average Wind Direction for

July 2003 (evening)

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Wind Direction

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RS/RW Normals of wind direction for July 1955-70 (evening ) Mumbai

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Wind Direction for July (evening)

Calculations of different atmospheric Calculations of different atmospheric parameters from WP/RASS dataparameters from WP/RASS data

►In addition to measuring wind vector radar In addition to measuring wind vector radar determines different atmospheric quantities determines different atmospheric quantities from power, Doppler shift and Spectral from power, Doppler shift and Spectral width of returned signal. These are:width of returned signal. These are:

►Strength of turbulence CnStrength of turbulence Cn22

►Eddy dissipation rate Є from σEddy dissipation rate Є from σww22

►Momentum flux u’w’ and v’w’Momentum flux u’w’ and v’w’

► The structure constant for refractive index The structure constant for refractive index fluctuations fluctuations CnCn22

► Atmospheric turbulence is usually characterized Atmospheric turbulence is usually characterized by the refractive index structure constant by the refractive index structure constant CnCn22 or or

eddy dissipation rate Є or eddy dissipation rate Є or σσww22 Radars are sensitive Radars are sensitive

to refractive index irregularities on scale half of to refractive index irregularities on scale half of the radar wave length. Backscattered power can the radar wave length. Backscattered power can therefore be used to infer the magnitude of therefore be used to infer the magnitude of refractive index structure constantrefractive index structure constant

► If refractive index is n(ro) at ro position and If refractive index is n(ro) at ro position and refractive index is n(ro+r) at ro+r position then refractive index is n(ro+r) at ro+r position then structure constant for refractivity turbulence in structure constant for refractivity turbulence in terms of the distance increment r is defined asterms of the distance increment r is defined as

►

2

00 )()( rnrrn

►(Green 1979, Gage 1990) defined Cn2 (Green 1979, Gage 1990) defined Cn2 for locally homogeneous and isotropic for locally homogeneous and isotropic inertial subrange turbulence as inertial subrange turbulence as

3/222

00 )()( rCrnrrn n

CnCn2 2 derived from RS/RWderived from RS/RW

Tatarskii (1971) shows that the turbulence structure constant for Tatarskii (1971) shows that the turbulence structure constant for the radio refractivity the radio refractivity

CnCn²² = =

Where aWhere a² = 2.8² = 2.8 = ratio of eddy diffusivities ~ 1= ratio of eddy diffusivities ~ 1 Lo = Outer scale length of turbulence spectrum.Lo = Outer scale length of turbulence spectrum. & M = Vertical gradient of the refractive index.& M = Vertical gradient of the refractive index.

The Lo is presumed to be around 10 meters, although no direct The Lo is presumed to be around 10 meters, although no direct evidence is available on the thickness of a turbulent layer – Lo evidence is available on the thickness of a turbulent layer – Lo being of the order of the later. The value of the M is given by being of the order of the later. The value of the M is given by the following relation. the following relation.

23/40

2 MLa

z

zq

T

q

zT

pM

/ln

/ln

2

11

155001

ln106.77 6

Where p = Atmospheric pressure in mbars. T = Absolute temperature. θ = potential temperature.

q =specific humidity gm/kg.And hence the Cn²(radar) can be given as:

Where F is the average fraction of the radar volume which is turbulent and its value is between .01and .1in lower troposphere.

FCC nradarn .22

►Radar will detect turbulence only if the radar Radar will detect turbulence only if the radar wave length lies in inertial subrange. If wave length lies in inertial subrange. If turbulence fills only a fraction F of radar turbulence fills only a fraction F of radar sampled volume then Cn2 measured from sampled volume then Cn2 measured from radar will be less than value computed from radar will be less than value computed from radiosonde and one may therefore write as radiosonde and one may therefore write as

► The value of F is ranging from 0.1 to 0.01 for The value of F is ranging from 0.1 to 0.01 for tropospheretroposphere

Equivalent ReflectivityEquivalent Reflectivity

The wavelength dependencies are combined in the The wavelength dependencies are combined in the following equation which gives the amount of Rayleigh following equation which gives the amount of Rayleigh scattering expressed as radar reflectivity factor Z, that scattering expressed as radar reflectivity factor Z, that would produce the same amount of backscattered power as would produce the same amount of backscattered power as a given amount of clear air refractive index variability, a given amount of clear air refractive index variability, which is denoted by the structure parameter Cnwhich is denoted by the structure parameter Cn²:²:

At the wavelengths typically used by radar wind profilers, At the wavelengths typically used by radar wind profilers, Rayleigh scattering from precipitation can equal or exceed Rayleigh scattering from precipitation can equal or exceed

the Bragg scattering.the Bragg scattering.

)13.15log(log10 311

102 nCdBZ

ZwheredBZ 10log10

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31July 2003 12GMT, RS/RW

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igh

t (

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 July 2003, 12G M T, W P/R ASS

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Refractive index structure parameter (logcn**2) for Wind Profiler

►Higher Higher CnCn22 values are observed in the active values are observed in the active phase for the month of July 2003 . Same trend phase for the month of July 2003 . Same trend is observed in the RS/RW observations taken is observed in the RS/RW observations taken at Chikhalthana (19.85 0 N, 75.400 E) which at Chikhalthana (19.85 0 N, 75.400 E) which is 230 kms away from Pune.is 230 kms away from Pune.

►Ottersten, 1969 gave the volume reflectivity Ottersten, 1969 gave the volume reflectivity from clear air turbulent scattering in terms of from clear air turbulent scattering in terms of CnCn22. .

Radar Refractive index structure Radar Refractive index structure constantconstant

► The mathematical expression for radar radio refractive The mathematical expression for radar radio refractive index structure constant is given asindex structure constant is given as

Reflectivity is calculated from SNR that we get from wind Reflectivity is calculated from SNR that we get from wind profiler observations.profiler observations.

Hence we can study the seasonal variation of refractive Hence we can study the seasonal variation of refractive

index structure constant using UHF radar.index structure constant using UHF radar.

)(2

RadarnC3/1.

)38.0(

►The noise is estimated by Hildebrand algorithm The noise is estimated by Hildebrand algorithm and then S/N ratio is calculated.and then S/N ratio is calculated.

►Substituting value of in above equation we Substituting value of in above equation we can calculate value of can calculate value of CnCn22

►Van Zandt proposed a method for the Van Zandt proposed a method for the estimation of Cn2 by above equation and radar estimation of Cn2 by above equation and radar SNR values asSNR values as

WhereWhere Pt – transmitted power Pt – transmitted power Ap – Physical area of the antennaAp – Physical area of the antenna M – No. of FFT pintsM – No. of FFT pints P - No. of bins occupied by signalP - No. of bins occupied by signal

P

Mnc

BTsTkR

cPtAp

N

S

Br

tr

dt

...

)(2ln64

)(2

-18 -17 -16 -15 -14 -131

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-18 -17 -16 -15 -14 -131

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-18 -17 -16 -15 -14 -131

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gh

t (K

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Average logCn2 (m-2/3)

(c) WP/RASS April 2004

Hei

gh

t (K

m)

Average logCn2 (m-2/3)

(a) WP/RASS July2003

Average logCn2 (m-2/3)

(b) WP/RASS Nov 2003

►Monthly averaged values of Monthly averaged values of CnCn22 have have been calculated for three seasons i.e been calculated for three seasons i.e April, July, November 2003 as April, July, November 2003 as premonsoon, monsson and premonsoon, monsson and postmonsson season respectively. postmonsson season respectively. The values of log The values of log CnCn22 vary from -17 vary from -17 to -14 order of magnitude.to -14 order of magnitude.

► Below 2 - 3 kms level of humidity is Below 2 - 3 kms level of humidity is higher therefore we observe high higher therefore we observe high values of values of CnCn22 which then decreases which then decreases with height and hence with height and hence CnCn22 correspondingly decreases. correspondingly decreases.

Diurnal variation of Cn2

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12th June 2003 WP/RASS Pune

LogCn2(m-2/3)

Heig

ht

(Km

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8Hrs 11Hrs 14Hrs 17Hrs

►On 12 June 2003 we obser diurnal variation in On 12 June 2003 we obser diurnal variation in the the CnCn22 of the order of 10dB. From 1 km of the order of 10dB. From 1 km values are increases and have peak values values are increases and have peak values around 1.85 kms which indicates the presence around 1.85 kms which indicates the presence of the top of the boundary layer and then it of the top of the boundary layer and then it starts decreasing.starts decreasing.

Kinetic energy dissipation Kinetic energy dissipation rate rate ЄЄ

Turbulent kinetic energy dissipation rate is one of Turbulent kinetic energy dissipation rate is one of the key parameter in the atmosphere turbulence the key parameter in the atmosphere turbulence theory. It represents rate of transfer of energy to theory. It represents rate of transfer of energy to smaller eddies in the inertial subrange of smaller eddies in the inertial subrange of inhomogeneties and rate of conversion of kinetic inhomogeneties and rate of conversion of kinetic energy of turbulence in to heat in the viscus energy of turbulence in to heat in the viscus subrange. Above boundary layer dissipation rate subrange. Above boundary layer dissipation rate decreases rapidly to near zero and rising again in the decreases rapidly to near zero and rising again in the vicinity of the jet stream. The estimation of epsilon vicinity of the jet stream. The estimation of epsilon is based on equations that follow from kolmogorov-is based on equations that follow from kolmogorov-obukhov laws of transformation of turbulent energy.obukhov laws of transformation of turbulent energy.

There are three methods proposed for the estimation There are three methods proposed for the estimation of epsilon from the radar measurements. All these of epsilon from the radar measurements. All these methods assume the turbulence is isotropic and in the methods assume the turbulence is isotropic and in the inertial subrange. It is also assumed that the spectrum inertial subrange. It is also assumed that the spectrum follows a Kolmogorov shape and the atmosphere is follows a Kolmogorov shape and the atmosphere is stably stratified. There are three methods of deriving stably stratified. There are three methods of deriving the turbulence kinetic energy dissipation rate ε from the turbulence kinetic energy dissipation rate ε from radar observationradar observation

Doppler spectral width methodDoppler spectral width method Radar backscatter signal power methodRadar backscatter signal power method Wind variance method.Wind variance method. The various assumptions and approximations The various assumptions and approximations

involved in these methods.involved in these methods.

In the first method for isotropic turbulence the velocity In the first method for isotropic turbulence the velocity half-variance is given byhalf-variance is given by

Where kinetic energy density is given by Where kinetic energy density is given by E(k) = α εE(k) = α ε2/32/3 k k -5/3-5/3

α - 1.6 Kolmogorov constantα - 1.6 Kolmogorov constant k – wave number k – wave number Thus ε is directly related to the total velocity half Thus ε is directly related to the total velocity half

variance. variance. Frisch and Clifford integrated above equation assuming Frisch and Clifford integrated above equation assuming

Gaussian beam width and pulse shape Gaussian beam width and pulse shape

dkkE

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2

σ σ vwvw22 - Variance in vertical beam w within - Variance in vertical beam w within

the pulse volume vthe pulse volume v

2

3

2

2

3

5

2

3

1

Vw

wherewhere

aforb

a

bh

hh

Ra

2

22

1

.......10515

1

2

AndAnd

2

22

1

.........105

8

15

41

2

b

ah

hh

cb

ab

a - half the diameter of the circular beam cross a - half the diameter of the circular beam cross sectionsection

b - half length of the pulseb - half length of the pulse γ2 - confluent hypergeometric expansion γ2 - confluent hypergeometric expansion

introduced by Labbitt for Frisch integralintroduced by Labbitt for Frisch integral td-Dwell time for vertical beam = Nc x IPP x P x Itd-Dwell time for vertical beam = Nc x IPP x P x I width described by above is the width of spectrum width described by above is the width of spectrum

from 76 pulse series returning from a turbulent pulse from 76 pulse series returning from a turbulent pulse volume.volume.

Gossard et al 1990 gave the equation as Gossard et al 1990 gave the equation as

Energy dissipation rateEnergy dissipation rate

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atVa Dt

w

The profile of eddy dissipation rate is also The profile of eddy dissipation rate is also estimated from the vertical beam spectral estimated from the vertical beam spectral width after applying due correction for the width after applying due correction for the finite beam width of the profiler antenna finite beam width of the profiler antenna Gossard (1998). Gossard (1998).

76.2

1.

22

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22

h

Sa W

If the profiler is operating when it is raining /or If the profiler is operating when it is raining /or hydrometers are present in the volume of atmosphere hydrometers are present in the volume of atmosphere sensed by it, it measures essentially the fall velocity sensed by it, it measures essentially the fall velocity of the hydrometeors in the zenith beam position. The of the hydrometeors in the zenith beam position. The presence of hydrometeors/raindrops is clearly presence of hydrometeors/raindrops is clearly indicated by the zenith beam radial velocity which indicated by the zenith beam radial velocity which rises to values of more than 1 m/sec (Ralph) as rises to values of more than 1 m/sec (Ralph) as against the clear air vertical velocities which are against the clear air vertical velocities which are much lower than 1 m/sec. Under these conditions, the much lower than 1 m/sec. Under these conditions, the observed variance needs to be further corrected for observed variance needs to be further corrected for the different fall speeds/spread in fall velocities of the different fall speeds/spread in fall velocities of raindrops/hydrometeors. raindrops/hydrometeors.

σσww22 = σ = σobsobs

22 – σ – σaa22 – σ – σDD

22

σσaa22 - contribution to observed variance - contribution to observed variance

because of the finite beam width of the because of the finite beam width of the profiler antenna profiler antenna

WS - hourly averaged wind velocityWS - hourly averaged wind velocity σσDD

2 2 - variance contribution because of the - variance contribution because of the different fall speeds of rain drops (Atlas different fall speeds of rain drops (Atlas et al). = 1 met al). = 1 m22 sec sec-2-2 as prescribed by as prescribed by Gossard & Strauch Gossard & Strauch

-4.2 -4.0 -3.8 -3.6 -3.4 -3.2 -3.0 -2.8 -2.61

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Average log€

Average energy dissipation rate for 25th July 2003

Second methodSecond methodRadar system constant poses some uncertainty unless Radar system constant poses some uncertainty unless a calibrated radar is used.a calibrated radar is used.

Third methodThird methodThe vertical wind data is taken for one-two hours The vertical wind data is taken for one-two hours subjected to Fourier transform analysis and the subjected to Fourier transform analysis and the resulting amplitude frequency spectrum is converted resulting amplitude frequency spectrum is converted to power frequency spectrum. Wild data points are to power frequency spectrum. Wild data points are removed before analysis. The power spectrum at removed before analysis. The power spectrum at each height is examined to identify the Brunt –Vaisala each height is examined to identify the Brunt –Vaisala (BV) frequency N for that height. Weinstock showed (BV) frequency N for that height. Weinstock showed inertial subrange extends upto the buoyancy scale inertial subrange extends upto the buoyancy scale (BV frequency).(BV frequency).

The variance of the vertical wind The variance of the vertical wind due to turbulence is obtained by due to turbulence is obtained by integrating the power spectrum of the integrating the power spectrum of the vertical wind from BV frequency to vertical wind from BV frequency to Nyquist frequency.Nyquist frequency.

Hence Є is obtained byHence Є is obtained by

21.6 2 NF

Some results by using WP/RASS dataSome results by using WP/RASS data

Findlater (1969) showed that the LLJ’s Findlater (1969) showed that the LLJ’s observed in peninsular/western India in July observed in peninsular/western India in July are a part of a branch of the Somali Jet (the are a part of a branch of the Somali Jet (the high speed wind flow from Kenya to eastern high speed wind flow from Kenya to eastern Ethiopia & Somalia) is well correlated with Ethiopia & Somalia) is well correlated with rainfall in western India. Since deep rainfall in western India. Since deep convection activity produces a significant convection activity produces a significant amount of middle/upper level cloudiness, the amount of middle/upper level cloudiness, the relationship between LLJ’s and convective relationship between LLJ’s and convective activity indicates that LLJ’s are important activity indicates that LLJ’s are important contributors to regional climate.contributors to regional climate.

The appearance of LLJ’s with its core around 850 to The appearance of LLJ’s with its core around 850 to 500 hPa during the Asian summer monsoon (June-500 hPa during the Asian summer monsoon (June-September) in the peninsular and western region of September) in the peninsular and western region of India is closely associated with the active/break India is closely associated with the active/break periods in the monsoon (P.V. Joseph et al) In periods in the monsoon (P.V. Joseph et al) In Defination of LLJ, Fay (1958) is Defination of LLJ, Fay (1958) is

The wind speed maximum exists below 6 km.The wind speed maximum exists below 6 km. The wind direction is substantially unaltered The wind direction is substantially unaltered

throughout the height range – approximately within throughout the height range – approximately within ± 40o around a mean persistent direction.± 40o around a mean persistent direction.

The wind speed should sharply decrease on either The wind speed should sharply decrease on either side of the wind maximum.side of the wind maximum.

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We have therefore analyzed the wind We have therefore analyzed the wind profiler data with respect to LLJ profiler data with respect to LLJ particularly during an active phase of particularly during an active phase of monsoon from 24 July to 28July monsoon from 24 July to 28July 2003 with emphasis on estimation of 2003 with emphasis on estimation of horizontal wind and associated shear, horizontal wind and associated shear, fluxes, energy dissipation rates and fluxes, energy dissipation rates and their diurnal variations. their diurnal variations.

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Vertical velocity (m/sec)

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The profile of eddy dissipation rate is also estimated The profile of eddy dissipation rate is also estimated from the vertical beam spectral width after applying from the vertical beam spectral width after applying all corrections. They have the peak near LLJ height.all corrections. They have the peak near LLJ height.

For the clear air case (precipitation cases excluded) For the clear air case (precipitation cases excluded) the epsilon values near the lowest wind maximum are the epsilon values near the lowest wind maximum are in the range of 2 ×10-4 to 4 ×10-4 m2 sec-3as shown in the range of 2 ×10-4 to 4 ×10-4 m2 sec-3as shown in figure . These Є values are comparable to those in figure . These Є values are comparable to those reported in the literature by Gossard et al. (1998), reported in the literature by Gossard et al. (1998), Satheesan et al. (2002), and Narayan Rao et al. Satheesan et al. (2002), and Narayan Rao et al. (2001). When observations corresponding to the (2001). When observations corresponding to the hydrometeors/rains are included such as on 24th, 25th hydrometeors/rains are included such as on 24th, 25th and 27th July, the epsilon values near the lowest wind and 27th July, the epsilon values near the lowest wind maximum are of the order of 10-3 increasing to 8.5 × maximum are of the order of 10-3 increasing to 8.5 × 10-3 m2 sec-3 on 27th July when heavy rains were 10-3 m2 sec-3 on 27th July when heavy rains were observed, thus indicating high turbulence activity observed, thus indicating high turbulence activity during rains .during rains .

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3.5

4.0

4.5

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Hei

ght (k

m)

Average Epsilon (m2s

-3 x 10

-3)

24 July Epsilon

Hei

ght (k

m)

Average Epsilon (m2s

-3 x 10

-3)

25 July Epsilon

Hei

ght (k

m)

Average Epsilon (m2s

-3 x 10

-3)

26 July Epsilon

Hei

ght (k

m)

Average Epsilon (m2s

-3 x 10

-3)

27 July Epsilon

Hei

ght (k

m)

Average Epsilon (m2s

-3 x 10

-3)

28 July Epsilon

The fluxes u`w` and v`w` are then calculated by calculating The fluxes u`w` and v`w` are then calculated by calculating

(where bar represents average (where bar represents average value)value)

The profiles of average momentum flux and observed The profiles of average momentum flux and observed vertical velocities (excluding the precipitation cases) for the vertical velocities (excluding the precipitation cases) for the period 24th to 28th July is plotted in figure (10). The period 24th to 28th July is plotted in figure (10). The presence of upward air motions (positive vertical presence of upward air motions (positive vertical velocities) is seen throughout the lower atmosphere on all velocities) is seen throughout the lower atmosphere on all these days with predominantly downward momentum flux. these days with predominantly downward momentum flux. The flux values lie in the range -0.7 to 0.3 m2 s-2 except on The flux values lie in the range -0.7 to 0.3 m2 s-2 except on 27th July where it shows mean upward flux at middle level. 27th July where it shows mean upward flux at middle level. The broad regions of ascending motions as seen from the The broad regions of ascending motions as seen from the fig (10) probably mean that the LLJ’s produce a favorable fig (10) probably mean that the LLJ’s produce a favorable thermodynamic environment for deep convection (Beebe thermodynamic environment for deep convection (Beebe and Bates 1955).and Bates 1955).

wwwvvvuuu &,

1

2

3

4

5

6

7

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

1

2

3

4

5

6

7

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

1

2

3

4

5

6

7

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

1

2

3

4

5

6

7

-0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5

-0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5

1

2

3

4

5

6

7

-0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5

-0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5

Flux (m2s

-2)

Vertical velocity (ms-1)

Hei

ght (k

m)

25 July Flux w

Flux (m2s

-2)

Vertical velocity (ms-1)

Hei

ght (k

m)

26 July Flux w

Flux (m2s

-2)

Vertical velocity (ms-1)

Hei

ght (k

m)

27 July Flux w

Flux (m2s

-2)

Vertical velocity (ms-1)

Hei

ght (k

m)

28 July Flux w

Flux (m2s

-2)

Vertical velocity (ms-1)

Hei

ght (k

m)

24 July Flux w

Atmospheric subsidence and the surface temperature variability Atmospheric subsidence and the surface temperature variability in the pre-monsoon month over a semi arid north peninsular in the pre-monsoon month over a semi arid north peninsular

Indian station: A case studyIndian station: A case study

The variability in the maximum temperature in the month The variability in the maximum temperature in the month of March 2004 over a station representative of semi arid of March 2004 over a station representative of semi arid region of north peninsular India has been studied. region of north peninsular India has been studied.

The vertical velocity data measured by UHF Wind Profiler, The vertical velocity data measured by UHF Wind Profiler, installed at Pune (18.310 N, 73.580 E) has been utilized. installed at Pune (18.310 N, 73.580 E) has been utilized. The wind profiler has typical height coverage of 6-10 km The wind profiler has typical height coverage of 6-10 km with a resolution of 300 meters.with a resolution of 300 meters.

Hourly averaged vertical wind velocity profiles were Hourly averaged vertical wind velocity profiles were obtained four times a day, on a three hourly basis from obtained four times a day, on a three hourly basis from 0800 to 1700 IST (Indian Standard Time) in March 2004. 0800 to 1700 IST (Indian Standard Time) in March 2004.

The factors governing the variability of surface temperature The factors governing the variability of surface temperature are; (1) radiation, (2) advection and (3) subsidence.are; (1) radiation, (2) advection and (3) subsidence. ..

'Heat wave' is one of the hazardous weather conditions in the premonsoon 'Heat wave' is one of the hazardous weather conditions in the premonsoon season (March-May) and early part (June and July) of monsoon season over season (March-May) and early part (June and July) of monsoon season over Indian subcontinent.Indian subcontinent.

The favorable factors for heat wave conditions to occur over a The favorable factors for heat wave conditions to occur over a particular region particular region

(1) large region of warm dry air prevailing in the surrounding of that region (1) large region of warm dry air prevailing in the surrounding of that region and appropriate flow pattern for transporting hot air into the region of the and appropriate flow pattern for transporting hot air into the region of the study study

(2) absence of moisture over a depth of atmospheric column and (2) absence of moisture over a depth of atmospheric column and

(3) large amplitude anticyclonic flow in the vertical levels above a place (3) large amplitude anticyclonic flow in the vertical levels above a place (Chaudhury et al., 2000). (Chaudhury et al., 2000).

Thus the key factor in the process is the subsidence or in more Thus the key factor in the process is the subsidence or in more general terms 'vertical velocity'.general terms 'vertical velocity'.

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1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

Maxi

mum

tem

pera

ture

(0 C)

March 2004

The time series of daily maximum temperatures over Pune in March 2004.

The dark line shows the climatological mean value. It is seen that on every day of the month the daily maximum temperature was above normal.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

M arch 2004

18.31

20.31

22.31

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28.31

Latit

ude

M axim um Surface Tem perature

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•The tilting of temperature isolines indicates the high temperatures are developed first in the northern latitudes and gradually move towards the southern latitudes.

•The three episodes are clearly seen.

•In the first one i.e. on 4th March a region of high temperatures is developed at latitude 28.31 N and after 5 days the high temperatures are observed at 18.53 N on 9th March.

•The second episode is from 16 to 20 March and the third episode is from 23 to 27 March.

•There was an advection of warm air from northern to southern latitudes. The effect of the advection is to make the temperature distribution uniformly high.

Role of advection in the surface temperature variability

Figure: The latitude-time cross section of the daily maximum temperature distribution in March 2004

The weather at any place is the ultimate result of actions of all the scales: The weather at any place is the ultimate result of actions of all the scales: planetary to meso scale. The anomaly at individual station is mainly controlled planetary to meso scale. The anomaly at individual station is mainly controlled by the mesoscale circulations. The collection of such individual anomalies at by the mesoscale circulations. The collection of such individual anomalies at number of stations forms the large-scale picture. Thus it becomes appropriate number of stations forms the large-scale picture. Thus it becomes appropriate to consider mesoscale behavior to understand the anomalies on the daily to consider mesoscale behavior to understand the anomalies on the daily scale. scale. Here is the advantage of the wind profiler Here is the advantage of the wind profiler

Role of subsidence in the surface temperature variability

• The study revealed the existence of two cell structure in the vertical in the pre-monsoon season

• The lower cell consists of upward motion extending up to 2 - 3 km and the upper cell consists of the subsidence motions confined between 3 to 6 km.

• In the morning hours, the upward motion in the lower levels extends to maximum height of about 3 km. With the progress of the day, the subsidence penetrates to the lower levels reaching around 1 km in the evening hours.

Vertical distribution of profiler mean velocity at four observational hours in March 2004.

-40 -30 -20 -10 0 10 20 30 400

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4

6

8

10

12March 1

He

igh

t (k

m)

Vertical velocity (cm/sec)

-20 -15 -10 -5 0 5 10 15 200

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4

6

8

10

12March 2

He

igh

t (k

m)

Vertical velocity (cm/sec)

-20 -15 -10 -5 0 5 10 15 200

2

4

6

8

10

12March 3

He

igh

t (k

m)

Vertical velocity (cm/sec)

-30 -20 -10 0 10 20 300

2

4

6

8

10

12March 10

Vertical velocity (cm/sec)

He

igh

t (k

m)

-50 -40 -30 -20 -10 0 10 20 30 40 500

2

4

6

8

10

12March 11

He

igh

t (k

m)

Vertical velocity (cm/sec)

-30 -20 -10 0 10 20 300

2

4

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8

10

12March 12

He

igh

t (k

m)

Vertical velocity (cm/sec)

-30 -20 -10 0 10 20 300

2

4

6

8

10

12

March 13

Heig

ht

(km

)

Vertical Velocity (cm/sec)

-20 -15 -10 -5 0 5 10 15 200

2

4

6

8

10

12

March 14

He

igh

t (k

m)

Vertical velocity (cm/sec)

-20 -15 -10 -5 0 5 10 15 200

2

4

6

8

10

12

March 15

Heig

ht

(km

)

Vertical velocity (cm/sec)

-20 -15 -10 -5 0 5 10 15 200

2

4

6

8

10

12

March 17

Heig

ht

(km

)

Vertical velocity (cm/sec)

-50 -40 -30 -20 -10 0 10 20 30 40 500

2

4

6

8

10

12

March 18

Heig

ht

(km

)

Vertical velocity (cm/sec)

-60 -40 -20 0 20 40 600

2

4

6

8

10

12

March 19

He

igh

t (k

m)

Vertical velocity (cm/sec)

•When compared with the reanalysis velocities, the profiler velocities are found higher by one order.

• Large variations (s.d. ~ 20 cm/sec) are observed in the individual wind profiler velocity profiles.

• The difference in the order of velocities is due to the fact that reanalysis velocities, computed using pressurewind relationships, are representative of synoptic scale motions.

•The profiler velocities are representative of meso scale motions.

The variation of profiler (shown by triangles) and reanalysis (shown by filled circles) velocities on individual days at 6 GMT for the period 1 to 19 March 2004.

The advection dominates in the initial period. When the horizontal The advection dominates in the initial period. When the horizontal temperature gradient vanishes, the effect of advection becomes temperature gradient vanishes, the effect of advection becomes small. small.

The effect of the solar radiation on the variability of the The effect of the solar radiation on the variability of the temperature has been removed by removing daily normals from temperature has been removed by removing daily normals from the daily maximum temperatures. the daily maximum temperatures.

The subsidence occurs in the form of alternating boxes overlaid on The subsidence occurs in the form of alternating boxes overlaid on each other. The total depth of the column, even if it is not each other. The total depth of the column, even if it is not continuous, adds to the warming and stability of the atmosphere. continuous, adds to the warming and stability of the atmosphere.

Hence the association between total depths of the atmosphere Hence the association between total depths of the atmosphere over which the subsidence occurs (subsidence depth) and the over which the subsidence occurs (subsidence depth) and the temperature anomaly has been studied. temperature anomaly has been studied.

The maximum temperature occurs in the afternoon hours. However The maximum temperature occurs in the afternoon hours. However the precursor to daily anomalies in the maximum temperature may the precursor to daily anomalies in the maximum temperature may be seen in the temperature anomalies of the previous hours. be seen in the temperature anomalies of the previous hours.

ConclusionsConclusions

In the beginning of the month, the surface In the beginning of the month, the surface temperatures over the northern regions become temperatures over the northern regions become high due to increased incoming solar radiations high due to increased incoming solar radiations (compared to previous month i.e. February) (compared to previous month i.e. February) assisted by extensive land mass and remoteness assisted by extensive land mass and remoteness of the sea.of the sea.

This develops a shallow low pressure area at the This develops a shallow low pressure area at the surface over the heated region. The advection of surface over the heated region. The advection of warm dry air due to northerly winds increases the warm dry air due to northerly winds increases the surface temperatures over the southern parts of surface temperatures over the southern parts of India. Once the advection occurs the temperature India. Once the advection occurs the temperature gradient reduces and then there is prevalence of gradient reduces and then there is prevalence of uniform high temperatures over the country. uniform high temperatures over the country.

The additional positive temperature anomalies are The additional positive temperature anomalies are generated due to the atmospheric subsidence. The generated due to the atmospheric subsidence. The anomalies are found to be proportional to the total depth anomalies are found to be proportional to the total depth of the atmospheric column over which the subsidence of the atmospheric column over which the subsidence occurs. The subsidence acts towards the increasing occurs. The subsidence acts towards the increasing temperatures. temperatures.

The unique vertical velocity data set obtained through The unique vertical velocity data set obtained through wind profiler system has revealed the important role of wind profiler system has revealed the important role of the subsidence in the surface temperature variability the subsidence in the surface temperature variability quite explicitly. quite explicitly.

The two cell structure and the order of the vertical The two cell structure and the order of the vertical velocity brought out in this study will find useful in the velocity brought out in this study will find useful in the validation of the meso scale models over the Indian validation of the meso scale models over the Indian region and in turn will be useful in improving the short region and in turn will be useful in improving the short range temperature forecasts over the region.range temperature forecasts over the region.

Future plans Future plans

Analysis of vertical velocity spectra: BV Analysis of vertical velocity spectra: BV frequency estimation-- Radar bright band frequency estimation-- Radar bright band characteristics characteristics

Reflectivity - rain rate (Z-R) interrelation Reflectivity - rain rate (Z-R) interrelation through determination of best fit drop size through determination of best fit drop size distribution of the observed velocity distribution of the observed velocity spectrum.spectrum.

Thank You Thank You