CARPE DIEM WP 7 Progress Report, November 2004

FINNISH METEOROLOGICAL INSTITUTE

CARPE DIEMWP 7 Progress Report, November 2004

Jarmo Koistinen and Heikki Pohjola Finnish Meteorological Institute


Main achievement

• A fully operational method has been created which estimates surface precipitation (SP) in a radar network


1(2)

Surface estimate: dBZ(0,r)=dBZ+S

),(

),0(log10

rhZ

rZS

e

e

Profile measurement volume

Scientific principle


1(2)

The SP scheme in a radar network applies time series of measured and climatological VPRs from each radar as well as spatial VPRs from all radars


1(2)

An automatic real time classification scheme of VPRs has been created

Statistics of VPR from March 2001 to August 2003 (556 471 profiles)


Climatological VPRs are modified applying the freezing level height field from hourly NWP model forecasts

•Freezing level height variation can be very large and irregular between radars, especially close to frontal zones.•Example: HIRLAM model freezing level height 21.8. 2003 17 UTC


Climatological (blue) and measured VPRs (red) in a rain case at IKA, ANJ and VAN radars, 11

UTC


13 UTC


Example: Occluded front, June 14th 2004

03 utc

10 utc

17 utc


1(2)

24 h accumulated precipitation June 14, 2004, 17 UTC 500 m PsCAPPI Surface precipitation


Validation of the method has been performed applying two methods

1. Overlapping radar pairs2. Gauges


1(2)

Validation of the SP scheme with overlapping radars

Measurement range 5 – 15 km

1. Precipitation profile diagnosed at Radar 2

2. > 50 overlapping bins pairs (Rad1, Rad2) in the common, overlapping area (max. 10020)

3. Difference (dB) in those bins (Rad 2 – Rad 1) tells under/overestimation at the distance r from Rad 1

4. Average bias and standard deviation calculated for several radar pairs.


Radar pair Ikaalinen-Vantaa Feb – May 2003, distance 193 km. Blue: 500 m PsCAPPI. Red: SP with measured and climatological VPRs. Black: only measured VPRs.


Validation: Gauge – Radar comparison• 375 WMO stations

• 24 hour accumulated precipitation

• Data: 1.4.-3.6, 12.6-20.10. 2004

• Log (G/R)






Range 150 – 200 km, 1 < G < 10 mmNote scatter and large G, large VPR

effect


Range 150 – 200 km, 1 < G < 100 mmNote scatter and small (!) VPR effect



Remaining challenges

· Elimination of overhanging precipitation, OP (should precede any SP scheme)

· Beam overshooting the VPR completely (no signal)· Highly variable VPR heights (e.g. embedded convection)· Errors in the assumed beam height (propagation, pointing

angle calibration errors)


OP diagnostics from radars: BASE height


OP diagnostics from NWP model fields

• 3D distribution of precipitation from NWP models• Relative humidity (RH)• Cloud water content (CWC)• Solid and liquid precipitation (not

available, yet?)

• Clouds when RH over selected threshold (Sundqvist scheme): Excessive humidity to liquid or solid CWC.


Example of overhanging precipitaiton at Vantaa radar

HIRLAM PsCAPPI

Relative

humidity

Vantaa radar

Cloud water content

VPR


Statistical comparison of OPs from the radars and from the NWP model HIRLAM

• Cloud water content profiles from HIRLAM 6 hour forecasts at the closest gridpoint vs. VPRs above the radars

• If correlation -> HIRLAM data can be used for OP diagnosis of radar data

• Totally 1827 OP profiles from March 2001 to May 2002

POD = 0,67 FAR = 0,71

Conclusion: Model performance not good enough


Example of overhanging precipitaiton at Vantaa radar

HIRLAM PsCAPPI

Relative

humidity

Vantaa radar

Cloud water content

VPR


Objective: Calculation of attenuation applying water phase distribution of hydrometeors along each ray

· Principle: freezing level height fixed at each radar, obtained from NWP and VPR, attenuation calculated separately in each water phase layer

· Liquid precipitation: k(dB/km)=1.12*10-4 Ze0.62

· Solid (dry) precipitation: k(dB/km)=1.1*10-7 Ze +

2.1*10-5 (Ze)0,5

· Bright band (constant thickness assumed): k=? (Hantwerker ERAD2004, Zawadzki pers. comm.)


Severe C-band attenuation in rain


Severe rain,hail and radome attenuation at 07:00


Less attenuation


ANJ lowest PPI, B-scan 07:00


B-scan after attenuation correction due to rain


B-scan of cumulative attenuation in rain


Attenuation10 dB

Azimuth angle

Attenuation due to rain at 250 km. Can’t recover the observed minima in the B-scan Radome and/or hail

attenuation significant.


WP 7 Summary, deliverables

– Diagnosis of hydrometeor liquid water fraction in 3D radar volumes, based on NWP model fields. Applied both in VPR scheme and in phase-dependant attenuation (done).

– At short ranges: 3D diagnosis of overhanging precipitation (OP) based on volumetric radar data i.e. VPR profile above the radar and BASE-composite (done).

– At long ranges: Improvement of radar derived surface precipitation by eliminating areas of OP based on radar network and NWP model data (tried but could not be achieved due to the poor performance of the NWP model data)


WP 7 Summary, deliverables

– Comparison of attenuation statistics applying 1. 3D water phase from a NWP model and specific attenuation for

rain, sleet and snow2. Attenuation due to rain only3. Attenuation due to snow only (ongoing).

– Automatic real time classification of the type of the measured VPRs (done)

– Improvement of radar derived surface precipitation using integrated surface precipitation scheme (“VPR correction”) from the radar network, applying freezing level height from a NWP model (ready, operational and validated). Writing of a Journal paper will be started next week.

Documents

CARPE DIEM WP 7 Progress Report, November 2004