352
Eugene E. Clothiaux, Thomas P. Ackerman, David M. Babb
then the autocovariance of V at a lag corresponding to the interpulse period T. = 1/ jprf is
(DZ, 6.4)
1
N.-l
R = y;;:-- L V*(m)V(m + 1).
n -1 m=l
(13.70)
R is a complex number with a real part R,. given by
1
N.-l
Rr = N _ 1 L [I(m)I(m + 1) + Q(m)Q(m + 1)]
n
m=l
(13.71a)
and a complex part given by
1
N.-l
Rc = - - L [I(m)Q(m + 1) - Q(m)I(m + 1)].
Nn -1 m=l
(13.71b)
The amplitude of R is
(13.72a)
and the phase is
(13.72b)
The pulse pair estimate of the mean power-weighted radial velocity of the particles in the
resolution volume is (DZ, 6.4)
v = - (_A )
(13.73)
where
(13.74a)
where (DZ, 6.5)
1 N n
5 = N L IV( m W - Pn
n m=l
(13.74b)
and Pn is an estimate of the mean radar noise power. Applying (13.73) and (13.74) to the
simulated I and Q time series produces an estimate of -0.423 ms- 1 for the mean radial velocity
and 0.255 ms- 1 for the spectral width.
13.8 Cloud Properties from Ground-Based Remote
Sensing
13.S.1 A climate model perspective
The preceding sections have described radar wave propagation and signal processing and shown
how the measured power return can be related to the properties of the scatterers in the sample
volume. In our previous articles (Clothiaux et al., 1995; Syrett et al., 1995) we have shown how
millimeter-wave radar can be used to provide a unique and detailed look at clouds, including
both their three-dimensional structure and microphysical structure. Quite recently, we and
others interested in millimeter-wave radar technology have begun investigating how to translate
the radar observations into quantitative data on cloud properties. To some extent, this can be
Eugene E. Clothiaux, Thomas P. Ackerman, David M. Babb
then the autocovariance of V at a lag corresponding to the interpulse period T. = 1/ jprf is
(DZ, 6.4)
1
N.-l
R = y;;:-- L V*(m)V(m + 1).
n -1 m=l
(13.70)
R is a complex number with a real part R,. given by
1
N.-l
Rr = N _ 1 L [I(m)I(m + 1) + Q(m)Q(m + 1)]
n
m=l
(13.71a)
and a complex part given by
1
N.-l
Rc = - - L [I(m)Q(m + 1) - Q(m)I(m + 1)].
Nn -1 m=l
(13.71b)
The amplitude of R is
(13.72a)
and the phase is
(13.72b)
The pulse pair estimate of the mean power-weighted radial velocity of the particles in the
resolution volume is (DZ, 6.4)
v = - (_A )
(13.73)
where
(13.74a)
where (DZ, 6.5)
1 N n
5 = N L IV( m W - Pn
n m=l
(13.74b)
and Pn is an estimate of the mean radar noise power. Applying (13.73) and (13.74) to the
simulated I and Q time series produces an estimate of -0.423 ms- 1 for the mean radial velocity
and 0.255 ms- 1 for the spectral width.
13.8 Cloud Properties from Ground-Based Remote
Sensing
13.S.1 A climate model perspective
The preceding sections have described radar wave propagation and signal processing and shown
how the measured power return can be related to the properties of the scatterers in the sample
volume. In our previous articles (Clothiaux et al., 1995; Syrett et al., 1995) we have shown how
millimeter-wave radar can be used to provide a unique and detailed look at clouds, including
both their three-dimensional structure and microphysical structure. Quite recently, we and
others interested in millimeter-wave radar technology have begun investigating how to translate
the radar observations into quantitative data on cloud properties. To some extent, this can be