Improving data quality with dual-

polarisation weather radars

Miguel Angel Rico-Ramirez26th Feb 2014, University of Bristol

Outline

• Precipitation measurement

• Errors in radar rainfall measurements

• Identification of non-meteorological echoes with

DP radar

• Attenuation correction with DP radar

• Hydrometeor classification and BB identification

• Concluding comments

Precipitation measurementThere are three ways to measure precipitation:

1. Point measurements (raingauges, snow pillows, disdrometers)

• Traditional, long established ⇒ long time series

• Point measurement ⇒ prone to sampling error because the

spatial variability in precipitation is not known

• Raingauges prone to instrumental errors and siting bias

2. Ground-based radar measurements

• Spatially-distributed measurements

• Real-time

• Measurements prone to error

• Difficult to measure rates of snowfall

• New, recently established ⇒ no long time series

3. Satellite-based measurements

• Experimental

• Potential for global coverage including inaccessible regions

and oceans

• Currently no snow fall products available

• Temporal sampling problem (snapshot available when a

satellite is overhead)

Increasingly, merged products are developed that combine a number

of these data sources to develop a best-estimate precipitation

product.

>1km2

5min

~200cm2

0.2mm tips

Global Precipitation Measurement

>25km2

3hr

Precipitation measurement with weather radars

RADAR – Radio Detection and Ranging

Principle:

• Transmit pulse of electromagnetic

radiation in a known, changing direction

with moving antenna.

• Some of the radiation is reflected back by

hydrometeors (e.g. rain, snow, hail, etc)

• Measure the strength of the return as a

function of time to find the distance of the

reflection from the radar system.

The relationship between the rainfall rate (R in

mm/hr) and the radar reflectivity (Z in mm6 m-3) is

given by an empirical Z-R relationship Z=aRb,

where the coefficients a and b depend on the

storm characteristics and can vary within the storm

(Z=200R1.6 is used in the UK and Z=300R1.4 is

used in the US).

Quantitative rain estimation with radars is dubious

without ground-based rain gauges to provide

absolute calibration.

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But radar measurements are prone to error …

1. Radar beam overshooting the shallow precipitation at long ranges. Radar beam is at

several kilometers above the ground at long ranges.

2. Low level evaporation of precipitation beneath the radar beam

3. Orographic enhancement above hills which goes undetected beneath

4. Vertical profile of reflectivity. There is a variation of reflectivity in the vertical.

Uncertainty in the extrapolation of the reflectivity measured aloft to the ground.

5. Overestimation of precipitation in the melting layer (bright band). If the radar beam

intercepts the ML, the result is an increase of power reflected back to the radar.

Errors can be up to a factor of 5 in the bright band.

6. Changes in the Drop Size Distribution N(D). This affects the Z-R relationship.

7. Partial beam blocking. Hills close to the radar block the beam path. This blocking can

be total or partial.

8. Representativeness errors. Radar scans with a given spatial and temporal resolution

9. Attenuation by hydrometeors and atmospheric gases. Affects higher frequencies

(e.g. C-band=5GHz or X-band = 10GHz).

10.Ground clutter. Ground echoes because radar scans at low elevation angles.

11.Anomalous propagation of the radar beam due to changes in the atmospheric

conditions. The path of the beam departs from standard propagation and in some

cases it is bent towards the earth surface producing ground echoes.

12.Radar miscalibration. This can bias the rainfall estimations.

Moist

Dry

But radar measurements are prone to error …

Areas where dual-polarisation radar can help

9. Attenuation by hydrometeors and atmospheric gases. Affects higher frequencies

(e.g. C-band=5GHz or X-band = 10GHz).

10.Ground clutter Ground echoes because radar scans at low elevation angles.

11.Anomalous propagation of the radar beam due to changes in the atmospheric

conditions. The path of the beam departs from standard propagation and in some

cases it is bent towards the earth surface producing ground echoes.

12.Radar miscalibration This can bias the rainfall estimations.

13.Hydrometeor Classification To classify rain, snow, melting snow, hail.

14.Rainfall estimation – Use of phase measurements in heavy rain and to correct for

attenuation.

Background on dual-polarisation radars

[ ]r

rdDDNDfDf

kK vvhhdp

d

)(d5.0)()()(Re

2 dp

0

Φ=−= ∫

π

hhσ

∫∫ ≈= dDDNDdDDND

K

Zhhhh

)()()( 6

25

4

σ

π

λ

∫≈ dDDNDR )(67.3

vvσ

Raindrops falling to the ground are

distorted into oblate spheroids due to

aerodynamic forces, being in average their

larger dimensions horizontally oriented

b

hhaRZ =

vv

hh

Z

ZZDR log10=

Size of raindrops

hvρ LDR V W

Clutter signals in weather radars

Clutter are those unwanted echoes on

weather radar scans:

• Fixed ground echoes (predictable)

• Anomalous propagation echoes

(unpredictable)

• Sea echoes (unpredictable)

• Birds, airplanes, ships (unpredictable)

• Wind farms

Predictable Ground Clutter

Anomalous Propagation (anaprop)

Non-meteorological echoes in radar rainfall measurements

Rico-Ramirez & Cluckie (2008) Classification of ground clutter and anomalous propagation

using dual-polarization weather radar, IEEE Trans. On Geoscience and Remote Sensing, 46,

1892-1904.

Training of the classifiersClutter Precipitation

Zh

ZDR

Φdp

ρhv

The noisier the dual-pol radar measurement for a

particular pixel, the more likely to be clutter

Identification of non-meteorological echoes in radar rainfall measurements

Rico-Ramirez & Cluckie (2008) Classification of ground clutter and anomalous

propagation using dual-polarization weather radar, IEEE Trans. On Geoscience and

Remote Sensing, 46, 1892-1904.

clutter

precipitation

Radar measurement

),...,(

)|()(

),...,|(1

1

1

n

n

i

i

n

xxP

cxPcP

xxcP

∏=

=

Raw reflectivity Clutter Corrected Reflectivity

Identification of non-meteorological echoes in radar rainfall measurements – Thurnham Radar

Raw reflectivity Clutter Corrected Reflectivity

Identification of non-meteorological echoes in radar rainfall measurements – Wardon Hill Radar

Using the classifier developed for Thurnham!

Uniform rain rate of 20 mm/h

10 km path

20 mm/h

PIA=0.1 dB

1 dB

5 dB

(3 GHz)

(5.5 GHz)

(10 GHz)

Radar measurements are affected by attenuation at higher frequencies

Chenies radar Thurnham radar

Radar signal attenuation in heavy rain at C-band

Polarimetric Measurements

dp∆Φ

Zh

ZDR

Φdp

ρhv

Attenuation is a function of Φdp

Raw reflectivity Attenuation-corrected reflectivity

Attenuation Correction at C-band

Rico-Ramirez (2012) Adaptive attenuation correction techniques for C-band

Polarimetric Weather Radars, IEEE Trans. On Geoscience and Remote Sensing,

50, 5061-5071.

Attenuation correction – Does it work?

Bringi, Rico-Ramirez & Thurai (2011) Rainfall Estimation with an Operational Polarimetric C-Band Radar in the

United Kingdom: Comparison with a Gauge Network and Error Analysis, J. Hydrometeorology, 12, 935-954.

Total rain in mm

19-24 Jul 2007

Radar rain

accumulations

shown in colour;

Gauge

accumulations

shown with

numbers

Errors:

Attenuation correction – Does it work?

Rico-Ramirez (2012) Adaptive attenuation correction techniques for

C-band Polarimetric Weather Radars, IEEE Trans. On Geoscience

and Remote Sensing, 50, 5061-5071.

Polarimetric Radar Rainfall Estimation

Bringi, Rico-Ramirez and Thurai (2011), J. Hydrometeorology

R2≡ Z-R, Z attenuation uncorrected

R1≡ Z-R, Z attenuation corrected

RC≡ f(Zh, Zdr and Kdp)

RK ≡ f(Kdp)

Bright band (melting ice)

Raindrops(below the bright band)

Snowflakes(above the bright band)

Range

He

igh

t (

km

)

Z R

Variation of the Vertical Profile of Reflectivity

Rico-Ramirez et al (2007), A high-resolution experiment in

the Island of Jersey, Meteorological Applications, 14, 117-

129.

Variation of the Vertical Profile of Reflectivity

Snow

Rain

Zh

Zdr

Melting Snow

Rico-Ramirez et al. (2005), Atmos. Science Letters, 6, 40-46.

Classification of rain, snow and melting snow @ S-band frequencies

Zh

Ldr

Real-time bright band correction

Kitchen et al (1994)

Rico-Ramirez et al (2005), Atmos Letters

The bright band was identified using

Zh, ZDR and LDR in a fuzzy classifier.

Snow

Melting

Snow

Rain

Concluding comments

• Weather radar has the advantage of providing rainfall measurements with high- spatial and temporal resolution.

• The use of DP radar for automatic removal of clutter echoes improves data quality. This is particularly important during anomalous propagation conditions.

• The use of ΦDP to correct Zh for attenuation improves the estimation of precipitation.

• There is still a lot of work to do to fully exploit the potential of DP radar to improve rain estimation in real-time operation (e.g. BB identification/correction, auto-calibration, dynamic compositing)

Thanks!

References

• Rico-Ramirez, MA. 'Adaptive attenuation correction techniques for C-band

polarimetric weather radars', IEEE Transactions on Geoscience and Remote

Sensing, 50, (5061-5071), 2012. DOI: 10.1109/TGRS.2012.2195228

• Islam, T, Rico-Ramirez, MA, Han, D & Srivastava, PK. 'Artificial Intelligence

Techniques for Clutter Identification with Polarimetric Radar Signatures', Atmospheric

Research, 109-110, (pp. 95-113), 2012. DOI: 10.1016/j.atmosres.2012.02.007

• Bringi, VN, Rico-Ramirez, MA & Thurai, M. 'Rainfall Estimation with an Operational

Polarimetric C-band Radar in the UK: Comparison with a Gauge Network and Error

Analysis', Journal of Hydrometeorology, 12, (pp. 935-954), 2011. ISSN: 1525-755X

DOI: 10.1175/JHM-D-10-05013.1

• Rico-Ramirez, MA & Cluckie, ID. 'Classification of ground clutter and anomalous

propagation using dual-polarization weather radar', IEEE Transactions on

Geoscience and Remote Sensing, 46 (7), (pp. 1892-1904), 2008. ISSN: 0196-2892

DOI: 10.1109/TGRS.2008.916979

• Rico-Ramirez, MA, Cluckie, ID & Han, D. 'Correction of the bright band using dual-

polarisation radar', Atmospheric Science Letters, 6 (1), (pp. 40-46), 2005. ISSN:

1530-261X DOI: 10.1002/asl.89