Andrew L. Pazmany

Quadrant Engineering, Inc., Amherst, Massachusetts

Millimeter-Wave Radar Field Measurements

and Inversion of Cloud Parameters for the

1999 Mt. Washington Icing Sensors Project

NASA/CR—2001-211103

August 2001
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NASA/CR—2001-211103

August 2001

National Aeronautics and

Space Administration

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Prepared under Contract C–75630–J

Andrew L. Pazmany

Quadrant Engineering, Inc., Amherst, Massachusetts

Millimeter-Wave Radar Field Measurements

and Inversion of Cloud Parameters for the

1999 Mt. Washington Icing Sensors Project
Available from

NASA Center for Aerospace Information

7121 Standard Drive

Hanover, MD 21076

National Technical Information Service

5285 Port Royal Road

Springfield, VA 22100

Available electronically at http://gltrs.grc.nasa.gov/GLTRS
NASA/CR2001-211103 iii 

I. DEFINITION OF VARIABLES...............................................................................................................1 

II. GLOSSARY..............................................................................................................................................2 

1. INTRODUCTION. ....................................................................................................................................4 

2. EXPERIMENT CONFIGURATION. .....................................................................................................4 

2.1 RADAR SYSTEM DESCRIPTION .........................................................................................................7 

2.1.1 NOAA-ETL X-band Atmospheric Radar ................................................................................7 

2.1.2 UMass 33/95 GHz CPRS System............................................................................................7

3. RADAR DATA ARCHIVE.......................................................................................................................8 

4. BACKGROUND ON THE MULTI-FREQUENCY RADAR INVERSION ALGORITHM .............9 

5. RESULTS OF NEURAL NETWORK INVERSIONS ON SELECTED DATA SETS.....................11 

6. COMPARISON OF RADAR-DERIVED LWC WITH IN-SITU DATA FROM ATEK PROBE...12 

REFERENCES ............................................................................................................................................14 

APPENDIX A: LIQUID WATER CONTENT, MVD, AND MZD EXTRACTED FROM 

MULTIFREQUENCY REFLECTIVITY PROFILES. ...........................................................................15 

NASA/CR2001-211103 1 

I. Definition of Variables 

α shape parameter for gamma distribution; larger values of α yield a narro wer 

distribution. 

c speed of light (2.997e8 m/s). 

C correlation factor (0<C<1) to determine overlap between range gates. 

D particle diameter (m). 

dBZ Radar Reflectivity Factor; proportional to 6 D . 

dBZe Radar Equivalent Reflectivity Factor; radar measured dBZ assuming Rayleigh 

scatterers (used with millimeter wave radars when particles are often Mie. 

ELWC RMS error of the neural net estimated LWC (g/m3

). 

EMVD relative RMS error of the neural net estimated MVD (%).

EMZD relative RMS error of the neural net estimated MZD (%). 

f frequency (Hertz). 

γ shape parameter for gamma distribution. Larger γ values yield narrower distributions. 

w k extinction due to liquid water (dB/km). 

K complex quantity related to the index of refraction of water or ice. 

λ electromagnetic wavelength (m). 

La atmospheric loss (dB/km). 

LWC liquid water content ( −3 g ⋅ m ). 

MD Mean Diameter ( μm ). 

MVD Mean Volume Diameter ( μm ). 

MZD Mean Z Diameter ( μm ). 

LWCNN Neural Net Estimated Liquid Water Content ( −3 g ⋅ m ). 

MVDNN Neural Net Estimated Mean Volume Diameter ( μm ). 

MZDNN Neural Net Estimated Mean Z Diameter ( μm ). 

η volume backscattering coefficient ( 2 −3m ⋅ m ). 

N index of refraction. 

Ni number of input nodes in neural network. 

Nr number of range gates sampled by neural network. 

Nf number of frequencies sampled by neural network.

Np number of output parameters of the neural network. 

No number of output nodes in neural network. 

Nave number of radar samples averaged (power average). 

N0 number density parameter for the Marshall-Palmer distribution. 

φ general angular variable. 

φ az scan range in azimuth (radians). 

φel scan range in elevation (radians). 

p(r) drop size distribution (number of drops per cubic meter per meter diameter). 

Pt radar transmit power (W). 

Prmin minimum detectable received power (W). 

rc mode radius (radius corresponding to the peak value of the drop size distribution). 

r particle radius ( μm ). 

R radar range (m). 

τ pulse length (s). 

Z cloud reflectivity ( 6 −3

mm ⋅ m ). Zvv is the copolarized reflectivity for transmission and 

reception of vertical polarization; Zhh is the copolarized reflectivity for transmission and 
NASA/CR2001-211103 2 

reception of horizontal polarization; Zvh is the cross-polarized reflectivity, for 

transmission of horizontal and reception of vertical polarization. 

II. Glossary 

• Drop-size Distribution - The measured or modeled distribution of drop diameters for clouds or rain. 

Units are number of drops per meter per cubic meter or −4

m . 

• Ka-band – The electromagnetic frequency interval between 28 and 40 GHz. 

• Liquid Water Content (LWC) - The water content, in grams per cubic meter, of the liquid portion of 

the cloud or precipitation. 

• Mean Volume Diameter (MVD) - Particle diameter corresponding to the mean of the volume 

distribution. Volume distribution is computed from the given drop size (diameter) distribution. Note 

that median volume diameter (denoted MeVD in this repo rt) is a much mo re co mmo nly used icing 

variable. 

• Median Volume Diameter (MeVD) - Particle diameter corresponding to the median of volume 

distribution. This is usually denoted by MVD in the icing literature. 

• Mean Z Diameter (MZD) - Particle diameter corresponding to mean cloud reflectivity. 

• Mie Scattering - Mie scattering refers to the complete solution for electromagnetic scattering from 

dielectric spheres as computed by G. Mie in 1908. This relatively complicated formulation is required 

when the particle size is within an order of magnitude of the electromagnetic wavelength. Approximate 

fo rmulas are o ften used in the o ptical limit (d>> λ ) and Rayleigh limit (d<< λ ) to simplify 

calculations. 

• Multiparameter Radar - Radar system capable of measuring a variety of parameters at one or more 

frequencies. For a meteorological radar, these parameters include cloud reflectivity, Doppler spectrum 

of the scattered signal (or its moments), and four additional polarimetric parameters, including linear 

depolarization ratio LDR, differential reflectivity Zdr , and the magnitude and phase of the copolarized 

correlation coefficient, ρ hv . 

• Neural Network - A software algorithm used to determine output parameters based on a network of 

interconnected summing nodes with non-linear response to the input. The neural network was 

originally developed to imitate the function of interconnected brain neurons. The basic building block 

of neural networks are non-linear summing nodes that are coupled to other nodes through connections 

with variable weighting factors. These weighting factors, along with the transfer function of the 

summing nodes, are adjusted to minimize estimation errors by using a set of known input and output 

vectors. 

• PPI (Plan Position Indicator) – A range versus azimuth angle display of radar parameters in polar 

coordinates. During a PPI scan, the antenna beam is scanned in azimuth at a fixed elevation angle. 

• RHI (Range Height Indicator) – A range versus elevation angle display of radar parameters in polar 

coordinates. During an RHI scan the radar beam is scanned in elevation at a constant azimuth angle. 
NASA/CR2001-211103 3 

• Rayleigh Scattering - Simplified scattering regime for particles much smaller than the 

electromagnetic wavelength. For larger particles, on the order of the radar wavelength, the complete 

Mie solution must be computed. Scattering from particles much larger than the electromagnetic 

wavelength can be approximated using optical limit formulas. 

• X-band – The electromagnetic frequency interval between 8 and 12 GHz. 

• W-band – The electromagnetic frequency interval between 75 and 100 GHz. 

• Reflectivity, Z - Frequency-independent parameter equal to the sixth moment of drop-size distribution. 

Reflectivity is proportional to backscattered power. The sixth moment arises from the fact that the 

radar cross-section of a small particle (d<< λ ) is proportional to the sixth power of particle diameter. 

Reflectivity is typically expressed on a decibel scale, as dBZ which equals 10log ( ) 10 Z . 
NASA/CR2001-211103 4 

1. Introduction. 

The Mount Washington Icing Sensors Project (MWISP) was a multi-investigator 

experiment with participants from Quadrant Engineering, NOAA Environmental 

Technology Laboratory (NOAA/ETL), the Microwave Remote Sensing Laboratory 

(MIRSL) of the University of Massachusetts (UMass) and others. Radar systems from 

UMass and NOAA/ETL were used to measure X-, Ka- and W-band backscatter data from 

the base of Mt. Washington, while simultaneous in-situ particle measurements were made 

from aircraft and from the observatory at the summit. This report presents range and time 

profiles of liquid water content and particle size parameters derived from range profiles 

of radar reflectivity as measured at X-band, Ka-band and W-band (9.3, 33.1 and 94.9 

GHz) using an artificial neural network inversion algorithm. 

In this report, we provide a brief description of the experiment configuration, radar 

systems and a review of the artificial neural network used to extract cloud parameters 

from the radar data. Time histories of liquid water content (LWC), mean volume diameter 

(MVD) and mean Z diameter (MZD) are plotted at 300 m range intervals for slant ranges 

between 1.1 and 4 km. Appendix A provides details on the extraction of radar reflectivity 

from measured radar power, and Appendix B provides summary logs of the weather 

conditions for each day in which we processed data. 

2. Experiment configuration. 

A diagram of the experiment configuration is shown in Figure 1. A variety of remote 

sensing instruments were set up at the cog rail base, summarized in Table 1. In-situ 

probes are summarized in Table 2. Figure 1, Tables 1 and 2, and other specific data 

included in this section were excerpted from two MWISP web sites: 

http://www.faa.gov/aua/awr/mwisp and http://www.rap.ucar.edu/projects/mwisp . 
NASA/CR2001-211103 5 

3

2

0

1 34 6 2 5

Horizontal Distance from CRB (km)

1

0

Height above CRB (km)

1

2

4

3

CRB

Summit

NASA Twin Otter

ATEK or CLASS balloons

Figure 1: MWISP layout. Profile is along an approximate west to east line 

connecting the Cog Railway Base (CRB) and the Mt. Washington Observatory at 

the summit (this figure was excerpted from the MWISP science plan). 

MWISP SITE COORDINATES 

(Based on hand-held GPS and topo map) 

Mount Washington Observatory (MWO): 

 Latitude = 44 deg., 16 min., 15 sec N 

 Longitude = 71 deg., 18 min., 14 sec W 

 Altitude = 6267 ft = 1910 m MSL 

 Declination = -16.0 deg. 

Cog Rail Base (CRB) remote sensors: 

 Latitude = 44 deg., 16 min., 10 sec. N 

 Longitude = 71 deg., 21 min., 11 sec. W 

 Altitude = 2660 ft = 811 m MSL 

 Declination = -16.6o

 (magnetic N is 16.6 degrees west of true N) 

CRB to MWO: 

 horiz. distance =3.9 km 

 slant range = 4.1 km 

 azimuth = 87 deg. from true north 

 elevation = 15.9 deg. 
NASA/CR2001-211103 6 

Table 1: MWISP Remote Sensors 

What Location Whose Funded By 

NOAA K Radar CRB NOAA ETL FAA (IFIPDT) 

NOAA X Radar CRB NOAA ETL FAA (IFIPDT) 

UMass Ka-band CRB UMass NASA 

UMass W-band CRB UMass NASA 

Polarimetric Scanning 

Radiometer (PSR) 

Summit NOAA ETL NASA 

Lidar CRB DREV NASA 

 Dual-channel 

microwave radiometer 

(Radiometrics) 

CRB WJHTC MWO (from FAA) 

Ceilometer CRB WJHTC MWO (from FAA) 

 Dual-channel tippable 

microwave radiometer 

CRB NOAA ETL FAA (IFIPDT) 

Table 2: MWISP In Situ Sensors 

What Location Who Funded By 

CLASS soundings Variable (from 

mobile unit) 

NCAR FAA (IFIPDT) 

ATEK soundings CRB/Bretton 

Woods 

ATEK Inc. CRREL, FAA (IFIPDT) 

Snowgages Heli pad near 

summit, CRB 

NCAR FAA (WWPDT, 

IFIPDT) 

 Particle 

Measuring 

Systems, Inc. 

Probes (FSSP, 2DG/12.5 μm and 

2D-G 100 μm) 

 Summit CRREL FAA (IFIPDT), CRREL 

Cloud Scope Summit Desert Research 

Institute/MWO 

MWO 

Cloud Particle 

Imager (CPI) 

Summit Stratton Park 

Engineering, Inc. 

(SPEC) 

NASA, FAA (IFIPDT) 

NASA Twin Otter 

Aircraft 

Aloft NASA Lewis 

Research Center 

NASA 
NASA/CR2001-211103 7 

2.1 Radar System Description 

2.1.1 NOAA-ETL X-band Atmospheric Radar

An X-band (9.34 GHz) radar provided by NOAA/ETL, termed NOAA/D shown in Figure 

2-a, is a high power, dual-polarization mobile radar. The radar transmits 25-kW of peak 

power in a 0.9-degree circular beam using a 10-ft (3.05-m)diameter parabolic dish. 

Radial velocity, reflectivity, and depolarization are measured at 328 range gates using 

PPI, RHI, or fixed-beam scans. Range resolution was set to 75 m for the MWISP 

experiment. Groups of four range gates were averaged together to match the resolution of 

the neural network training data set (300 m). Sensitivity is approximately 10 dBZ at 25-

km range. 

Summary of NOAA/D X-band radar operating parameters for MWISP:

Frequency: X-band (9.3 GHz)

Range resolution: 75 m (four range gates averaged). 

Azimuth resolution at 2 km: 31 m. 

Number time samples averaged per gate: 256 

Po larizatio n: Ho rizo ntal linear 

Figure 2-a. The NOAA/D, NOAA-ETL's X-band atmospheric radar . 

2.1.2 Umass 33/95 GHz CPRS System

The Cloud Profiling Radar System (CPRS) uses a dual-frequency, dual polarization 1.0 m

diameter lens antenna to produce co-axial beams at 33 and 95 GHz. The radar generates a 

peak power of 100 kW at 33 GHz and 1.2 kW at 95 GHz, providing sufficient sensitivity 

to study non-precipitating clouds to ranges of 15 km or greater. In order to maximize the 

sensitivity of the radar, only vertical polarized pulses were used for the measurements. 

Each measured data point was calculated by averaging the scattered power from 200 
NASA/CR2001-211103 8 

transmit pulses. The pulses were transmitted in groups of four, with pulses spaced 150 

μs within the groups and the groups were spaced at 1 ms. We estimate that the 

decorrelation time of a typical atmospheric target (velocity spectral width of 1.5 m/s) is 

approximately 3 ms at 33 GHz and 1 ms at 95 GHz. As a result, an equivalent of about 

16 independent samples at Ka-band and 50 independent samples at W-band were 

averaged for each recorded data point for the reduction of fading but all 200 pulses 

helped improve signal to thermal noise ratio. 

Summary of CPRS operating parameters for MWISP (Ka-band):

Frequency: 33.12 GHz 

Range Resolution: 30 m (ten range gates averaged) 

Azimuth resolution at 2 km: 22 m

Number of time samples averaged per gate: 200 (16 independent) 

Polarization: Vertical linear 

Summary of CPRS operating parameters at W-band:

Frequency: 94.92 GHz 

Range Resolution: 75 m (four range gates averaged) 

Azimuth resolution at 2 km slant range: 8 m

Number of time samples averaged per gate: 200 (50 independent) 

Po larizatio n: Vertical linear 

Figure 2-b. The UMass 33/95 GHz Cloud Profiling Radar 

System at the MWISP base camp. 

3. Radar data archive. 

The UMass Ka- and W-band radar system collected data from April 4 to April 26, 1999. 

The measured data, which was converted to Net CDF format, along with quick look 

images of various radar parameters, can be accessed via the Internet at 

http://abyss.ecs.umass.edu/CPRS. X-band data from NOAA/D was received directly from 

NOAA on tape. 
NASA/CR2001-211103 9 

4. Background on the Multi-frequency Radar Inversion Algorithm 

 In 1998 Quadrant Engineering Inc. completed a study to assess remote sensing 

techniques for the detection and mapping of aircraft icing potential. The problem was 

constrained to a forward looking volume imaging remote sensing system capable of 

measuring cloud and precipitation parameters, such as Liquid Water Content (LWC), and 

drop size at about 1 km range resolution out to 20-30 km. The measurement concept for 

an in-flight sensor system is illustrated in Figure 3. 

Figure 3. Measurement concept of an in-flight icing detection remote sensing 

system. 

After analyzing a variety of active and passive remote sensor combinations, multifrequency radar was identified as the most promising technology for the problem. The 

technique involves the simultaneous processing of 10, 35 and 95 GHz radar reflectivity 

profiles with an artificial neural network to estimate LWC and drop size in clouds and 

precipitation. Computer simulations indicated that LWC, and drop size measured as 

Medium Volume Diameter (MVD), and Mean Z Diameter (MZD), can be estimated with 

reasonable accuracy, even in the presence of significant (1 dB) estimation errors [1]. 

Multi-frequency radar has an excellent potential for probing cloud particle parameters 

due to the combination of moderate attenuation and adequate scattering cross-section. In 

the original 1998 study, Quadrant Engineering Inc. formulated a working hypothesis that 

cloud parameters could be extracted by measuring backscatter at a combination of 

attenuating and non-attenuating frequencies. Since scattering is a complex nonlinear 

function of particle size and frequency, it is impractical to consider an analytical solution 

to the inverse problem of computing particle size and liquid water content based on 

measured backscattered power at multiple frequencies. Quadrant therefore focused its 

efforts on an approximate numerical solution to the inversion, specifically, a neural 

network. The network was trained by simulating thousands of test cases of radar 

scattering from assumed particle size distributions. 
NASA/CR2001-211103 10 

The inverse problem of extracting cloud parameters from the measured range profiles of 

backscattered power is a good example of a problem without well defined rules for 

estimation. The forward problem is straightforward: for a given drop-size distribution, 

reflectivity and attenuation can easily be calculated using Mie scattering formulas [2]. 

Also, cloud and precipitation properties, such as liquid water content or rain rate, can be 

directly calculated from drop-size distribution. Solving the inverse problem, that is, 

calculating cloud parameters from measured reflectivity profiles, is very difficult, due to 

the non-linearity of the forward problem. Neural nets are ideal for solving problems 

where the forward problem is well characterized but the inverse is non-linear and 

complicated. The procedure of this computer simulation is summarized in Figure 4. The 

simulation first generated a large set of artificial cloud and precipitation conditions, 

specified in terms of profiles of drop size distributions. From these drop size 

distributions, the computer algorithm then calculated the corresponding radar observed 

reflectivity profiles at each operating frequency as well as LWC and drop size in each 

volume cell. Gaussian distributed random variables were added to the reflectivity profiles 

to simulate the effect of noise in the data, and this set of multi-frequency radar reflectivity 

(inputs) and cloud and precipitation parameter profiles (outputs) were then used to train 

an artificial neural network. A statistically independent, but still simulated, data set was 

used to evaluate the ability of the neural net to estimate LWC and drop size from the radar 

data. 

In an attempt to train the neural network for potential ice particles in the sample volumes, 

half of the training data set range cells were biased with a uniformly distributed ice 

reflectivity between 0 and 3 dB relative to the reflectivity of the liquid particles. It was 

assumed that the ice particles did not contribute to the attenuation of the cell. There were 

no other preparations made to the neural network algorithm or tests performed on the 

measured data to account for the presence or absence of ice particle. It is therefore 

expected that ice particles introduced additional errors in all the estimated cloud and 

precipitation parameters. The presence of significant ice particles, beyond the 3 dB 

reflectivity bias considered in the training data set, would lead to an overestimation of the 

retrieved liquid drop size parameters, because the algorithm would account for the 

additional reflectivity by increasing the liquid drop size parameter. The retrieved LWC

can also be affected, because ice crystals are often Mie scatterers at W-band (and 

sometimes at Ka-band), so size variations in range will appear as differential reflectivity 

gradients either lowering or increasing the neural net estimated LWC. The three 

frequency (X, Ka and W) network estimated LWC will be the least affected, however, as 

the third frequency will help estimate the Mie modulation. 

 
NASA/CR2001-211103 11 

Figure 4. Evaluation of the multi-frequency radar technique for the measurement of 

cloud and precipitation parameters with simulated data. 

 

 

5. Results of neural network inversions on selected data sets. 

In order to test the accuracy of the neural network algorithm, we processed seventeen 

data sets, each consisting of twelve minutes of data gathered at X, Ka and W-band. These 

data sets were interpolated to match up the sampling intervals in range and time. In 

addition to the averaging described in section 2.1, a sliding boxcar window was used to 

average over 20 range profiles (20 seconds total averaging) before processing by the 

neural network. 

Data were processed from April 14, 15, 17, 20 and 26, 1999. Figure 5 illustrates the slant 

ranges where the neural net estimated time series of liquid water content (LWC), mean 

volume diameter (MVD) and mean Z diameter (MZD). Figures A1-A17, found in 

Appendix A, show similar plots for all of the processed data. The X-band radar 

reflectivity image and the corresponding neural net retrieved LWC, MVD, and MZD, 

shown in Figure 5, were collected through a melting layer at a 19 deg slant angle. 

Although, in situ data was not available for comparison, the melting layer qualitatively 

verified the results of the algorithm. The top of the bright band (melting band) is around 
NASA/CR2001-211103 12 

1.3 km slant range - just below the second of four range cells of retrieved precipitation 

parameters. Above the melting band, LWC is just above 0.2 −3

gm and the particle size 

parameters are around 1.5 mm, indicating large ice crystals with some super-cooled 

liquid. The lowest range cell, centered at the bottom of the bright band, however, shows a 

much higher LWC, up to 0.8 −3 gm , and distinctly smaller drops ranging from 0.5 to 1 

mm, confirming the melting of the larger ice crystals into smaller liquid hydrometeors. 

Figure 5. X-band reflectivity image of a melting layer, measured on April 26, 1999, 

and the corresponding neural net estimated time series of liquid water content 

(LWC), mean volume diameter (MVD) and mean Z diameter (MZD) at slant ranges 

1.1 km, 1.4 km, 1.7 km and 2 km. 

6. Comparison of radar-derived LWC with in-situ data from ATEK probe. 

A comparison of LWC derived from three frequency radar data shows good agreement 

with in-situ measurements of liquid water content as derived from balloon soundings of 

LWC made with the ATEK probe. Figure 6 shows altitude profiles of LWC as measured 

by the ATEK probe at two times that coincide with radar measurements, April 14 at 

19:07 UTC, and April 17 at 17:19 UTC. The asterisks show the average LWC, as 

derived by the neural network. These points were computed by taking 12-minute 

averages of the neural network derived LWC at each altitude. The complete time histories 

of the neural network output used to compute these points can be found in Appendix A, 

figures A.6 and A.13. Note that slant range in A.6 and A.13 was converted to altitude 

using the formula in Appendix A. 
NASA/CR2001-211103 13 

Figure 6 shows good agreement between the in situ derived liquid water content and the 

water content measured by the neural network. On April 14, the two measurements show 

agreement both in the altitude distribution (within 100 m) and peak value (within 20 

percent). The agreement in height is not as good on April 17, although the trend towards 

higher water contents at higher altitudes is the same for both measurement techniques. 

Figure 6. Neural net estimated Liquid water content (LWC) averaged over the 12+ 

minute observation period (*) overlaid on the LWC measured in-situ with the ATEK 

probe (solid line) on April 14, 19:07 UTC (top, compare to Figure A.6), and April 

17, 17:19 UTC (bottom, compare to Figure A.13). The cog railway is located at an 

altitude of 811 m, while the summit of Mt. Washington is located at an altitude of 

1910 m. 
NASA/CR2001-211103 14 

 

REFERENCES 

[1] Quadrant Engineering, “Evaluation of Technologies for the Design of a Prototype InFlight Remote Aircraft Icing Potential Detection System,” Final R&D Report, 

Contract No. DACA39-97-M-1476, 85 pp., 1998. 

[2] Ulaby, F. T., R. K. Moore, A. K. Fung, “Microwave Remote Sensing”, Volume II, 

Artech House, 1982, pp. 1064 . 

[3] Doviak, R. J., D. S. Zrnic, “Doppler Radar and Weather Observations”, Academic 

Press, 1984, pp. 562. 
NASA/CR2001-211103 15 

Appendix A: LWC, MVD, and MZD extracted from multifrequency reflectivity profiles. 

Figures A1-A17 provide time histories of LWC, MVD and MZD as derived by the 

artificial neural network. Table A.1 summarizes the dates, time interval and slant ranges 

for which the neural network provided cloud parameters for each figure. Slant range, Rs

can be converted to altitude by the following formula: Altitude =0.3256Rs +811 m. 

Table A.1 Table of Figures, Appendix A. 

Figure Date Time (UTC) Slant ranges 

A.1 April 14, 1999 15:10-15:23 1.1-2.0 km 

A.2 April 14, 1999 15:23-15:35 1.1-2.0 km 

A.3 April 14, 1999 17:00-17:12 1.1-2.0 km 

A.4 April 14, 1999 17:30-17:42 1.1-2.0 km 

A.5 April 14, 1999 17:38-17:49 1.1-2.0 km 

A.6a/b April 14, 1999 19:06-19:18 1.4-3.5 km 

A.7 April 14, 1999 19:16-19:28 1.1-2.0 km 

A.8 April 14, 1999 19:30-19:42 1.1-2.0 km 

A.9 April 14, 1999 19:42-19:55 1.1-2.0 km 

A.10 April 15, 1999 18:34-18:47 1.1-2.0 km 

A.11 April 17, 1999 13:15-13:27 1.1-2.0 km 

A.12 April 17, 1999 13:30-13:43 1.1-2.0 km 

A.13a/b April 17, 1999 17:07-17:19 1.4-3.5 km 

A.14 April 17, 1999 17:14-17:28 1.1-2.0 km 

A.15 April 20, 1999 18:30-18:42 1.1-2.0 km 

A.16a/b April 20, 1999 18:42-18:55 1.4-3.5 km 

A.17 April 26, 1999 15:40-15:52 1.1-2.0 km 
NASA/CR2001-211103 16 

April 14, 1999

Weather log entry: 

Date:14 april 

Time: 2135z 

Entry by:m politovich 

Entry: 

Not a great day but not too bad either. 

Same clouds we have been seeing do a circle dance around that low over 

Labrador. Clouds were thick and thin, 1, 2, 3 layers. Some waves 

downwind (south/east) of the mountains. Liquid up and down all 

day. Did not look good enough for the plane to sample so we called 

them down, and then lo and behold the cloud thickened and the liquid 

came back. C'est la vie. Still, however, it was no great shakes for an 

airplane to sample. Lots of dendrites and plates in the cloud, snow 

showers at the cog base, snow and rime at the summit. Instruments 

worked well for the most part and we did get a good study in. 

The neural net retrieved cloud parameters reflect the snow and variable LWC. The 

estimated liquid drop equivalent sizes were consistently high, ranging from 100 to 600 

micron, while LWC was near zero in the first few files (Figures A.1 and 2) taken after 

15:00 UTC. Later files (Figures A.3-5) show sporadic concentrations of higher LWC, up 

to 0.3 −3

gm until the clouds thickened after 19:00 UTC, producing longer range radar 

data and retrieval out to 3.5 km (Figure A.6a and A.6b). At these upper layers much 

higher concentrations of liquid was found, up to 0.7 −3 gm . This liquid layer was 

confirmed by the ATEK probe measured LWC (Figure A.6a of the main text). 
NASA/CR2001-211103 17 

Figure A.1 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 15:10 to 15:23 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. X-band reflectivity shown for reference. 
NASA/CR2001-211103 18 

Figure A.2 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 15:23 to 15:35 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. X-band reflectivity shown for reference. 
NASA/CR2001-211103 19 

Figure A.3 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 17:00 to 17:12 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 20 

Figure A.4 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 17:30 to 17:42 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 21 

Figure A.5 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 17:38 to 17:49 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 22 

Figure A.6a Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 19:00 to 19:13 UTC at 1.4, 1.7, 2.0 and 2.3 

km slant range. 
NASA/CR2001-211103 23 

Figure A.6b Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 19:00 to 19:13 UTC at 2.6, 2.9, 3.2 and 3.5 

km slant range. 
NASA/CR2001-211103 24 

Figure A.7 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 19:18 to 19:30 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 25 

Figure A.8 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 19:30 to 19:42 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 26 

Figure A.9 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 14, 1999, 19:42 to 19:55 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 27 

April 15, 1999

Weather log entry: 

Date:15 april 

Time: 18z 

Entry by: m politovich 

Entry: 

A great day, well-coordinated and just about everything worked according to 

plan. 

Had cloud from about 3500-11,1000 ft MSL, lots of ice and lots of 

water. Ice in the form of dendrites, mountain was seeing most around 

200 microns, we down here at the crb saw snow as dendrites, up to 5 

mm, first light then moderate rime. Some aggregates. Snow was showery. 

Big event was the NASA Twin Otter over-flight. They made 6 passes over 

us from cloud top down to 8.3Kft, their minimum altitude. They saw at 

their lower levels lwc fairly sustained at 0.1g/m3, some values to 0.2 

g/m3. Lots of dendrites, aggregates and "irregulars". It takes them 

12 min to make a circuit -- coming south from north of the mountain, 

then turning toward the west at the crb and flying 20 miles out. Then 

do it again. 

crb sensors all working well during the flight in "scan" mode. Lidar 

off, of course. summit probes also all working during the 

flight. Radio communication was very smooth, and we had some nice 

comparisons between the airborne and ground measurements. 

In spite of being called a “great day”, April 15, 1999 only yielded 12 minutes worth of 

data in coordinated observation modes between the UMass CPRS and NOAA X-band 

radars. The retrieved data, however, did confirm the presence of liquid up to 0.4 −3

gm in 

the farthest retrieved volume cell and the presence of large particles (ice crystals) with 

MZD-s up to 1 mm. This, of course, is a liquid equivalent measure of drop size, so crystal 

sizes were likely several times larger the cog railway base reported snow and dendrites 

up to 5 mm in diameter. 
NASA/CR2001-211103 28 

Figure A.10 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 15, 1999, 18:34 to 18:47 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 29 

April 17, 1999

Weather log entry: 

Date:17 april 

Time: 0135z 

Entry by:m politovich 

Entry: Well, today was one of those days that OD's (operations 

directors) really dread. Weather is supposed to move in sometime in 

late afternoon through mid-evening. Plane can't fly after dark. 

Radars and summit sensors can't work too late or they won't be ready 

for the next day, when we'll have aircraft support. If we work late 

and say "sorry, can't work the next day" the aircraft may well pack up 

and go back to Cleveland. Yet the weather coming in looks to be quite 

interesting. arg. Weather finally came in about 21-22 pm. Plane 

more-or-less called itself down, since forecasts/progs/hopes/ were not 

too promising. Maybe we made a bad choice, should have held with a 

21z takeoff, would have caught some interesting weather. Maybe not. At 

any rate, sensors at the crb and summit were up and running for the 

passage, from the south (finally!) of a warm front. Clouds began from 

aloft, lowering, some precip, we had light rain at the crb but no 

bright band --- at first suggestive of a "warm rain" process but later 

revealed to be due to the freezing level being an arm's reach of the 

crb. Since the OD is only 5'4" this was not immediately apparent. 

Anyway, extremely interesting case then of southerly flow coming over 

the ridge formed by Mts Washington, Franklin, Eisenhower to the south, 

then sinking and flowing very near the surface to our 

valley. Refrigeration by the snow cover on the peaks? Very stable air? 

I vote for a cooling effect by snow cover making the airflow denser, 

but maybe there is a more realistic explanation. 

Radars are still working, they find this interesting. That's why we're here. 

Summit saw some water, then dendrites, slightly rimed, looked to be 

 somewhat sublimated since they were in and out of cloud. 

We'll break off this soon and then us early birds will head on up to 

the crb and launch a CLASS sonde at 6 am, to prepare some cloud top 

info for a 7 am telecon with NASA. Other ops slated to begin at 8 

am. Bad news is that this does not allow for a big Friday night in 

Bretton Woods. Good news is that Bretton Woods sees no action of 

Friday nights. 
NASA/CR2001-211103 30 

Date:17 april 

Time: 18z 

Entry by:m politovich 

Entry: Today was a different cloud, warm, with abundant liquid water 

and ice crystals in the form of needles and columns. A good cloud for 

the NOAA crew -- it filled a gap in their polarization data 

collection. No aircraft support since for most of the time the cloud 

was too low in altitude for them. In fact, they are returning to 

Cleveland to wait this out rather than burn up time and money sitting 

around in a hangar in Portland, ME. They will be available to us later 

this week when we hope this weather pattern changes. 

The neural net retrieved LWC varied from 0.2 to 0.4 −3 gm in the morning files. In 

Figures A.11 and A.12, the estimated LWC fluctuates rapidly, which may have been 

caused by large, Mie scattering ice crystals modulating the reflectivity gradient. The LWC 

retrieved from the afternoon data, in Figures A.13a and A.13b, is somewhat smoother 

and, after averaging the entire 12 minutes, estimated LWC shows good agreement with 

the base of a liquid layer measured by the ATEK probe. The neural net estimated liquid 

cloud base appears several hundred meters lower than that detected by the probe, which 

may be due to an elevating cloud, since the radar measurements preceded the probe at the 

liquid base by about 10 minutes.
NASA/CR2001-211103 31 

Figure A.11 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 17, 1999, 13:15 to 13:27 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 32 

Figure A.12 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 17, 1999, 13:30 to 13:43 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 33 

Figure A.13a Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 17, 1999, 17:07 to 17:19 UTC at 1.4, 1.7, 2.0 and 2.3 

km slant range. 
NASA/CR2001-211103 34 

Figure A.13b Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 17, 1999, 17:07 to 17:19 UTC at 2.6, 2.9, 3.2 and 3.5 

km slant range. 
NASA/CR2001-211103 35 

Figure A.14 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 17, 1999, 17:14 to 17:28 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 36 

April 20, 1999

Weather log enry: 

Date:20 april 

Time: 2130z 

Entry by:m politovich 

Entry: A day of low winds and lots of local convection. Winds all the 

way up, from our rawinsonde, were well below 10 m/s -- balloon stayed 

pretty much in our backyard its entire flight. Had several good, heavy 

graupel showers which the NOAA folks appreciated for some polarization 

studies. Also the convective clouds were deep and contained lots of 

liquid, so we may be able to get some lwc retrievals out of this. The 

only real problems were the highly variable conditions, which "come 

with the territory" when you're dealing with weakly forced convection, 

and the fact that the observatory was only in scud at best. Moreover, 

the weak winds made it very difficult for their probes to sample 

properly. 

Tomorrow looks to be similar, perhaps somewhat warmer. The whole 

weather pattern begins to shift north late tomorrow into Thursday, 

maybe putting us more in the path of whatever moisture impulses happen 

along --- as for now, they are just skimming to our south. We see a 

nice blob (for lack of a better term) of moisture entering the Great 

Lakes area at the present time, perhaps it's our weather feature for 

Friday. 

The retrieved drop sizes were large, up to 1 mm consistently throughout the day’s data, 

confirming the “heavy graupel shower” visual observations. LWC smoothly varied 

around 0.2 −3

gm with pockets of higher concentrations reaching above 0.4 −3gm .

Unfortunately, no in situ measurements were available on this day around the time 

periods of coordinated radar observations. 
NASA/CR2001-211103 37 

Figure A.15 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 20, 1999, 18:30 to 18:42 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
NASA/CR2001-211103 38 

Figure A.16a Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 20, 1999, 18:42 to 18:55 UTC at 1.4, 1.7, 2.0, and 2.3 

km slant range. 
NASA/CR2001-211103 39 

Figure A.16b Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 20, 1999, 18:42 to 18:55 UTC at 2.6, 2.9, 3.2 and 3.5 

km slant range. 
NASA/CR2001-211103 40 

April 26, 1999

Weather log entry:

Date:26 april 

Time: 21z 

Entry by:m politovich 

Entry: Busy day --- but not the weather we were led to expect. Best we 

could muster was some fairly decent convection. High liquid water 

content in the clouds but they were rather short-lived, scattered 

about, and in many cases, shallow. 

A cold surge came through at about 1015z with a snow shower followed 

by brief light rain, this came during our balloon launch. At that time 

things looked pretty good. Then it cleared after the surge -- however 

we had already launched the aircraft and they unfortunately missed the 

action. 

Just after they turned back for Portland, ME, their base of 

operations, local convection began popping. It started as 

orographically-induced light convection, then deepened and we began a 

series of squalls that moved through fairly methodically every half 

hour or so. Good graupel and rain showers, usually beginning as rain 

then going to graupel near the end. Some of the graupel was up to 0.5 to 0.75 cm 

in size, and conical. Got the aircraft into our last cell 

(well, now at 21z we're having one final fling with a shower passing 

through) where they made three passes before the storm cleared and 

measured liquid water contents up to 0.7g/m3. 

Had lightning in the area which not only made us nervous but popped 

the breakers on the K-band radar and blew out the intercom in the lidar 

van. Observatory had a hit at one of the chimneys on top --- Marsha, 

the volunteer cook of the week was putting some discarded food out 

nearby for the ravens, and was lucky not to be injured, but did get a 

good scare and a tingle. Did not hear if the ravens were also 

affected. 

The X-band radar reflectivity image and the corresponding neural net retrieved LWC, 

MVD, and MZD, shown in Figure A.17 (and Figure 5 in the main text), were collected 

through a melting layer at a 19 deg slant angle. Although, in situ data was not available 

for comparison, the melting layer qualitatively verified the results of the algorithm. The 

top of the bright band (melting band) is around 1.3 km slant range - just below the second 

of four range cells of retrieved precipitation parameters. Above the melting band LWC is 

just above 0.2 −3 gm and the particle size parameters are around 1.0 to 1.5 mm, indicating 

large ice crystals with some super-cooled liquid. The lowest range cell, centered at the 

bottom of the bright band, however, shows a much higher LWC, up to 0.8 −3

gm , and 
NASA/CR2001-211103 41 

distinctly smaller drops ranging from 0.5 to 1 mm, confirming the melting of the ice 

crystals into smaller liquid hydrometeors.

Figure A.17 Time profiles of LWC (solid line), MVD (lower dashed line) and MZD

(upper dashed line) for April 26, 1999, 15:40 to 15:42 UTC at 1.1, 1.4, 1.7 and 2.0 

km slant range. 
This publication is available from the NASA Center for AeroSpace Information, 301–621–0390.

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Available electronically at http://gltrs.grc.nasa.gov/GLTRS

August 2001

NASA CR—2001-211103

E–12948

WU–711–21–23–00

C–75630–J

48

Millimeter-Wave Radar Field Measurements and Inversion of Cloud

Parameters for the 1999 Mt. Washington Icing Sensors Project

Andrew L. Pazmany

Aircraft icing; Drop size; Liquid water content; Operations; Radar; Remote sensing

Unclassified -Unlimited

Subject Category: 03 Distribution: Nonstandard

Quadrant Engineering, Inc.

107 Sunderland Road

Amherst, Massachusetts 01002

Project Manager, Andrew Reehorst, Turbomachinery and Propulsion Systems Division, NASA Glenn Research

Center, organization code 5840, 216–433–3938.

The Mount Washington Icing Sensors Project (MWISP) was a multi-investigator experiment with participants from

Quadrant Engineering, NOAA Environmental Technology Laboratory (NOAA/ETL), the Microwave Remote Sensing

Laboratory (MIRSL) of the University of Massachusetts (UMass), and others. Radar systems from UMass and NOAA/

ETL were used to measure X-, Ka-, and W-band backscatter data from the base of Mt. Washington, while simultaneous

in-situ particle measurements were made from aircraft and from the observatory at the summit. This report presents range

and time profiles of liquid water content and particle size parameters derived from range profiles of radar reflectivity as

measured at X-, Ka-, and W-band (9.3, 33.1, and 94.9 GHz) using an artificial neural network inversion algorithm. In this

report, we provide a brief description of the experiment configuration, radar systems, and a review of the artificial neural

network used to extract cloud parameters from the radar data. Time histories of liquid water content (LWC), mean volume

diameter (MVD) and mean Z diameter (MZD) are plotted at 300 m range intervals for slant ranges between 1.1 and 4 km.

Appendix A provides details on the extraction of radar reflectivity from measured radar power, and Appendix B provides

summary logs of the weather conditions for each day in which we processed data.