Transcript Are Next Generation Networks Viable? A Model to Evaluate

Elevation and Climatological Dependence
of the SSI Capabilities to Discriminate Atmospheric
Propagation Conditions
Ada V. Bosisio 1, Ermanno Fionda 2, Piero Ciotti 3, Antonio Martellucci 4
1) CNR\IEIIT, Milano, Italy; [email protected]
2) Fondazione Ugo Bordoni (FUB), Roma, Italy; [email protected]
3) Dept. Of Elect. And Info. Eng., Univ. Of L’aquila, L’aquila, Italy; [email protected]
4) ESA-ESTEC, TEC-EEP, Noordwijk (NL); [email protected]
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SCENARIO
Microwave Propagation Phenomena
Key parameter: Frequency (f)




O2, Water Vapor emissions: (Clear Sky)
Cloud emissions: relevant at f > 15 GHz
Rain events: relevant at f > 10 GHz
Snow and Ice, not relevant below f = 30 GHz
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MOTIVATION
Rain events can be source of strong scatter processes extremely
severe for space communications at K/Q/W band
1. For satellite communications purposes, the knowledge in real
time of rain events, in the volume of the operative beacon, could
suggest the adoption of dynamic fading mitigation techniques
to overcome the lost of signal quality
2. For Water Vapor and Cloud Liquid retrieval, the availability of a
user-friendly tool (able to detect microwave radiometric
observations affected by rain) is welcomed in case of massive
measurements (radiometric-networks) or for analyzing large
database
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CANDIDATE INDICATOR (SSI)
• Indicator should be generated from ground-based
brightness temperature values Tb(f)
• It could benefit from the different sensitivity of the
microwave radiometric channels to the various
atmospheric constituents
Candidate:
• The Sky Status Indicator (SSI) issues from the ratio
between available Tb(f) @ 23.8, 31.4 GHz
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OUTLINE
• Sky Status Indicator
– SSI features
– SSI computation
– Clear sky Tb(f) and calibration check
• Sensitivity analysis on SSI coefficients (synthetic data)
– elevation angle and site (climatology & latitude) dependence
– erroneous calibration procedure and/or apparatus uncertainty
• Sensitivity analysis on SSI coefficients (measured data)
– elevation angle dependence
• SSI classification results
• Final remarks
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SSI FEATURES
• ASSUMPTIONS
The ratio T31/T23 of concurrent ground-based radiometric data depends
on the thermodynamic state of the atmosphere.
• This ratio detects the status of the sky along the path as it neutralizes the
contribution of the water vapor plateau (continuum) and of the dry gases
by defining a modified brightness temperature T31 value:
T31 = T31 - c0
T31
SSI =
T23
• The coefficient c0 is frequency-, location-, and elevation-dependent.
• It is computed either from measurements or from simulation data.
• Specifically, c0 is the intercept of the straight line that relates the couple
(T31,T23) of values under clear sky condition
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SSI COMPUTATION
The key point is c0 calculation, i.e. the identification of the linear fit
between T23 and T31 under clear sky conditions
 from simulated Tb(f):
Forward
RT
RAOBs
Tb(f),IWV, LWP
 from measured Tb(f):
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CLEAR SKY TB AND CALIBRATION CHECK
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SENSITIVITY ANALYSIS ON SSI COEFFICIENTS
The sensitivity analysis aims at assessing the dependence
of ci coefficients on the elevation angle and on the
climatological region.
INPUT
• RAOBs database + forward RT model including:
– Rosenkranz absorption model (water vapor)
– Mattioli et al. (cloud model)
• Classification criteria
• 3 sites (De Bilt, Roma, Milano)
• 5 elevation angles q= 27.6°, 35.5°,40.2°, 69.6°, 90°
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RAOBS and SIMULATED Tb(f) DATABASE
Period
# samples
Lat, Long
% clear sky
conditions
De Bilt
2002 -2008
3618
(52.1N,5.18E)
29
Milano
2002 -2008
6518
(45.43N,9.28E)
41
Roma
2002 -2008
5984
(41.65N,12.48E)
50
Classification criteria according to the outcome of cloud liquid model
• Clear sky conditions: LWP <0.001 cm
• Cloudy sky conditions: 0.001< LWP< 0.07 cm
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SENSITIVITY ANALYSIS ON SSI COEFFICIENTS
Climatologylatitude
joint effect
Rome (I)
De Bilt (NL)
90°
1
7.07
7.51
C0
Elevation angle/air mass
69.6°
40.2°
35.5°
1.07
1.55
1.72
7.38
9.57
10.33
7.85
10.37
11.23
27.6°
2.16
12.13
13.33
Milan (I)
6.94
7.23
11.82
RAOB
Station
Observed variability @ 90° :
8%
9.38
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10.08
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NOISE AND IMPROPER CALIBRATION EFFECTS
Robustness is evaluated on simulated Tb(f)
Tbn(f)=Tb(f) +N(0, s2 )
N is AWGN with s = 0.5 K.
It accounts for the instrument radiometric resolution.
Tbne(f)=Tbn(f) ± i where i=1,2 K
The bias reproduces measurements
improper calibration periods
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under
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NOISE AND IMPROPER CALIBRATION EFFECTS
Sensitivity due to ± 1 and ± 2 of about ±6% and ±12 %
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ESA ATPROP System
EXPERIMENTAL FIELD IN CABAUW (NL)
(RPG-HATPRO & RPG-15-90 Radiometers)
Version 2.00 (10. Oct. 2008)
14 channel HATPRO radiometer
Antenna beam parameters
2 channel R-15-90 radiometer
ESA ATPROP
Frequency [GHz]
15.3
22-31
90
Side lobe level [dBc]
<- 30
<- 30
<- 40
Directivity [dB]
28.4
33.2
33.0
HPBW [°]
6.2
3.3 -3.7
3.0
System User’s Manual
RAOB
by Th. Rose
Radiometer Physics GmbH,
53340 Meckenheim, Germany
(www.radiometer-physics.com)
22 km
DataSet
A
B
ESA ATPROP
Julian time
# Samples
18/05/09 3395161
12/07/09
12/07/09 31/07/09
about 6x106
1/10/09 30/11/09
Elevation [°]
90.0
69.6
-i-
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SENSITIVITY ANALYSIS ON SSI COEFFICIENT
• the T23 domain ranging from its minimum
value to 50 K is divided in 200 bins
• for each bin the minimum T31 value is
selected
• linear fit over the selected couples T23 - T31
discrepancy from 6% to 9%
for co and of about 1% for c1
DataSet
A (90°)
B(69.6°)
SSI coefficients
from measurements
c0 [K]
c1
6.81
0.35
7.35
0.35
SSI coefficients
from simulations
co[K]
c1
7.51
0.36
7.85
0.36
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SSI PROBABILITY DENSITY FUNCTIONS
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SSI CLASSIFICATION RESULTS: CABAUW(NL)
SSI range variability and boundary threshold values with
respect to the clear, cloudy and rainy sky conditions.
The SSI values are referred to brightness temperature
values measured in Cabauw during 2009.
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TB(15.3) AS POSSIBLE RAIN DETECTOR TOOL
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TB(15.3) DURING RAIN EVENTS
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FINAL REMARKS: RESULTS AND OUTLOOK
•SSI has easy software implementation and online performance capability
•Clear/cloudy and cloudy/rainy sky conditions were discriminated by two SSI
boundary threshold values: 0.39 (at q equal to 90° and 69.6°) and 0.86 or
0.88 (at q equal to 90° and 69.6°).
•A robustness analysis on SSI considering simulated Tb AWGN with s = 0.5 K
and a bias of ±1 and ±2 K:
– Sensitivity of about ±6% and ±12 %
•Precipitation prediction through plane parallel rain slab to extend
classification criteria to rainy sky conditions
•Database of meteorological information such as rain gauges and/or radar
data for experimental validation
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