Kohin Hirano([email protected], National Research ......Jan 28, 2014 · C3-34 28 th Conference on...
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C3-34 28 th Conference on Hydrology - 94 th AMS Annual Meeting (February 2014, Atlanta, GA) Studies on Mean Areal Rain Rate using Dual-Polarization X-Band Radar over a Small River Basin, Japan Kohin Hirano([email protected], National Research Institute for Earth Science and Disaster Prevention, JAPAN), Masayuki Maki , Takeshi Maesaka, Koyuru Iwanami Background areal rain-rate estimators 139 2 .° 139 4 .° 139 6 .° 139 8 .° 35° 35.2 ° 35.4 ° 35.6 ° 35.8 ° 36° L ON G I T U D E L A T I T UD E T o k y o B a y Tokyo Ka n a g a wa P r e f e c t u r e Ebina Radar 3 7 ° 50 km 5 0 k m Hayabuchi - 5 5 ° - 500 0 500 1000 1500 2000 Kisarazu Radar Elevation [m] 139 53 . ° 139 55 . ° 139 57 . ° RR [mm/hr] 35.54° 35.55° 35.56° 35.57° 35.58° 35.59° 35.60° 0 10 20 30 40 50 60 LONGITUDE L AT IT UDE 37° 35° 39° 33° 31° 41° Ebina Radar Kisarazu Radar r ) ( 1 2 r 1° ) ( 2 2 r ) ( 3 2 r ) ( 4 2 r ) ( 4 1 r ) ( 3 1 r ) ( 2 1 r ) ( 1 1 r r 1 ,r 2 changes with dp is constant ቊ ݎݐݏݐݎ ݎ → ൌ 3.96 ൈ 10 ଶ , ൌ 0.551 ݒݐݒ ݎ → ൌ 4.26 ൈ 10 ଶ , ൌ 0.644 (1) Z-R method (2) K DP -R method (3) DP -AR-Ryzhkov method (4) DP -AR-Bringi method 0 1 2 3 4 5 6 0 10 20 30 40 50 60 70 80 90 100 R=23.4･K DP (0.1～0.5) R=20.4･K DP (0.5～1.0) R=18.1･K DP (1.0～2.0) R=14.7･K DP (2.0～7.0) K DP [deg/km] Rain rate [mm/h] R=18.9･K DP 0.856 R=c･K DP (5) Composite DP -AR method ( DP -AR-NIED) DP ARRyzhkov ଵ DP ARBringi (6) MK DP –R method ( ܦ ) ୀ ୀ ୀ ୀ Since National Research Institute for Earth Science and Disaster Prevention (NIED) deployed the first dual- polarization X-band radar around the Tokyo metropolitan area in 2000, a widespread use of dual- polarization X-band radars has gained significant momentum in Japan. Rainfall estimators using polarimetric parameters from X-band radar have been proved to be in the best harmony with rain gauge measurements without any corrections from surface observations. Most of the common used hydrological models still rely on rain gauges and are usually based on the assumption of uniform rainfall over the catchment. What is the best rainfall estimating method in the catchment areas for X-band radars? Can radar derived rainfall take the place of traditional gauges be used in hydrological models? XRAIN 38 Radars up to 2013 Objective results verification 139.52 139.54 139.56 LONGITUDE 35.54 35.55 35.56 35.57 35.58 35.59 0 5 10 20 30 40 50 60 LATITUDE [mm/hr] 139.52 139.54 139.56 LONGITUDE 35.54 35.55 35.56 35.57 35.58 35.59 0 5 10 20 30 40 50 60 LATITUDE [mm/hr] 139.52 139.54 139.56 LONGITUDE 35.54 35.55 35.56 35.57 35.58 35.59 0 5 10 20 30 40 50 60 LATITUDE [mm/hr] 139.52 139.54 139.56 LONGITUDE 35.54 35.55 35.56 35.57 35.58 35.59 0 5 10 20 30 40 50 60 LATITUDE [mm/hr] Estimate the areal rainfall rate using dual-polarization X- band radar and compare the derived results against a high density rain gauge network of 30 rain gauges within the area of 20 km 2 around a very small river basin in Japan. experiment area Hayabuchi river basin Flow along Yokoama city Merge into Tsurumi river and flow into Tokyo Bay Length : about 13.7 km Max. width: about 20 m Many water parks along the Hayabuchi river Typical city river prone to flash flood Rain gauges 12 rain gauges in the Hayabuchi river basin, 18 outside 11 rain gauges between 36 – 38 azimuth angles of Ebina Radar Figure1. Location of experiment area , rain gauges, and radars used in this study Figure2. PPI images of Ebina Radar * Volume scan covers 12 elevations within 5 minutes. *K DP (NIED stable) is estimated using the iterative filter and local linear regression. conclusion and future work Mean areal rain-rate estimators using differential propagation phase shift return the best harmony to Thiessen (gauge) – derived rainfall rates. Mean areal rain-rate estimators using reflectivity tends to underestimate rainfall rate, while classic K DP gives negative values because the differential propagation phase is contaminated by noise sometimes . Although MK DP (estimated using variational method) avoids the negative K DP values, the computation cost is heavy. Introduce mean areal rain-rate estimators into hydrological models to forecast real time flash flood is our future work. : 05 00 : 07 00 : 09 00 A V ER A G E RR P E R 5 MI N 0 10 20 30 40 5 0 RainGauge Ref Kdp Pdp Ryzhkov _ Pdp Bringi _ Pdp NIED _ MKdp : 15 00 : 16 00 : 07 00 : 08 00 : 18 00 : 19 00 AV E RA G E R R PE R 5 M I N 0 10 20 30 40 5 0 [mm/hr] LOCAL TIME (UTC+9) LOCAL TIME (UTC+9) LOCAL TIME (UTC+9) LOCAL TIME (UTC+9) RA I N F AL L AM O U N T 0 5 10 15 20 25 3 0 RainGauge Ref Kdp Pdp Ryzhkov _ Pdp Bringi _ Pdp NIED _ MKdp R AI N F A L L A MO U N T 0 10 20 30 40 50 6 0 [mm] C A S E 0 4 - 2 0 1 1 . 0 7 . 3 0 C AS E 0 3 - 2 0 1 1 . 0 7 . 1 9 C AS E 0 2 - 2 0 1 1 . 0 6 . 3 0 C A S E 0 1 - 2 0 1 1 . 0 6 . 1 1 : 05 00 : 07 00 : 09 00 : 15 00 : 16 00 : 07 00 : 08 00 : 18 00 : 19 00 Case studies were carried out for the verification of 6 areal rainfall rate estimators 4 rainfall events occurred in 2011 summer season, which included 1 stratiform rainfall (CASE01) and 3 convective rainfalls (CASE02 - 04) Radar ray-based verification, and basin-based verification are conducted respectively Basin-based verification result is shown in this poster Areal rainfall rate for rain gauges was obtained by applying Thiessen algorism Results are noise in the case of stratiform case compared with convective cases Only DP estimators produced time-continuous results, missing data occurs while using other parameters Figures on the right Upper panels : distributions of rain rate at a sample time for each case Middle panels : basin averaged areal rainfall rates with respect to time for each case Bottom panels : basin-based rainfall amounts with respect to time for each case Rainfall amount Rainfall rate DP estimators One no data period When using other estimators DP gives negative values DP do over estimate do under estimate
Transcript of Kohin Hirano([email protected], National Research ......Jan 28, 2014 · C3-34 28 th Conference on...
C3-3428
thC
onfe
renc
e on
Hyd
rolo
gy -
94th
AMS
Annu
al M
eetin
g (F
ebru
ary
2014
, Atla
nta,
GA)
Studies on Mean Areal Rain Rate using Dual-Polarization X-Band Radar over a Small River Basin, Japan
Kohin Hirano([email protected], National Research Institute for Earth Science and Disaster Prevention, JAPAN), Masayuki Maki , Takeshi Maesaka, Koyuru Iwanami
Background areal rain-rate estimators
139 2. ° 139 4. ° 139 6. ° 139 8. °35°
35.2°
35.4°
35.6°
35.8°
36°
LONGITUDE
LA
TIT
UD
E
Tokyo Bay
Tokyo
Kanagawa
Prefecture
Ebina Radar
37°
50 km50 km
Hayabuchi
-55°
-500
0
500
1000
1500
2000
Kisarazu Radar
Elevation [m]
139 53. ° 139 55. ° 139 57. ° RR [mm/hr]35.54°
35.55°
35.56°
35.57°
35.58°
35.59°
35.60°
0
10
20
30
40
50
60
LONGITUDE
LA
TIT
UD
E
37°35°
39°
33°31°
41°
Ebina Radar
Kisarazu Radar
r)( 12 r
1°
)( 22 r
)( 32 r )( 42 r
)( 41 r
)( 31 r)( 21 r
)( 11 rこの範囲でφDP が一
定であると仮定
r1、r2 はθに応じて
変化する r1,r2 changes
with
dp is constant
→ 3.96 10 , 0.551 → 4.26 10 , 0.644
(1) Z-R method
(2) KDP-R method
(3) DP-AR-Ryzhkov method
(4) DP-AR-Bringi method
0 1 2 3 4 5 60102030405060708090
100
R=23.4･KDP (0.1～0.5)R=20.4･KDP (0.5～1.0)
R=18.1･KDP (1.0～2.0)
R=14.7･KDP (2.0～7.0)
KDP [deg/km]
Rai
n ra
te [m
m/h
] R=18.9･KDP0.856
R=c･KDP
(5) Composite DP-AR method ( DP-AR-NIED)
DPARRyzhkov DPARBringi
(6) MKDP–R method ( )
Since National Research Institute for Earth Science andDisaster Prevention (NIED) deployed the first dual-polarization X-band radar around the Tokyometropolitan area in 2000, a widespread use of dual-polarization X-band radars has gained significantmomentum in Japan.Rainfall estimators using polarimetric parameters fromX-band radar have been proved to be in the bestharmony with rain gauge measurements without anycorrections from surface observations.Most of the common used hydrological models still relyon rain gauges and are usually based on theassumption of uniform rainfall over the catchment.What is the best rainfall estimating method in thecatchment areas for X-band radars? Can radar derivedrainfall take the place of traditional gauges be used inhydrological models?
XRAIN 38 Radars up to 2013
Objectiveresults verification
139.52 139.54 139.56LONGITUDE
35.54
35.55
35.56
35.57
35.58
35.59
0 5 10 20 30 40 50 60
LATI
TUD
E
[mm/hr]
139.52 139.54 139.56LONGITUDE
35.54
35.55
35.56
35.57
35.58
35.59
0 5 10 20 30 40 50 60
LATI
TUD
E
[mm/hr]
139.52 139.54 139.56LONGITUDE
35.54
35.55
35.56
35.57
35.58
35.59
0 5 10 20 30 40 50 60
LATI
TUD
E
[mm/hr]
139.52 139.54 139.56LONGITUDE
35.54
35.55
35.56
35.57
35.58
35.59
0 5 10 20 30 40 50 60
LATI
TUD
E
[mm/hr]
Estimate the areal rainfallrate using dual-polarization X-band radar and compare thederived results against a highdensity rain gauge networkof 30 rain gauges within thearea of 20 km2 around a verysmall river basin in Japan.
experiment areaHayabuchi river basin
Flow along Yokoama city Merge into Tsurumi river
and flow into Tokyo Bay Length : about 13.7 km Max. width: about 20 m Many water parks along
the Hayabuchi river Typical city river prone to
flash flood
Rain gauges 12 rain gauges in the
Hayabuchi river basin, 18outside
11 rain gauges between36 – 38 azimuth anglesof Ebina Radar
Figure1. Location of experiment area , rain gauges, and radars used in this study
Figure2.PPI images ofEbina Radar* Volume scan covers 12 elevations within 5 minutes.*KDP (NIEDstable) isestimated usingthe iterative filterand local linearregression.
conclusion and future workMean areal rain-rate estimators using differential propagation phase shift return the best harmony to Thiessen (gauge) – derived rainfall rates.Mean areal rain-rate estimators using reflectivity tends to underestimate rainfall rate, while classic KDP gives negative values because thedifferential propagation phase is contaminated by noise sometimes .Although MKDP (estimated using variational method) avoids the negative KDP values, the computation cost is heavy.Introduce mean areal rain-rate estimators into hydrological models to forecast real time flash flood is our future work.
:05 00 :07 00 :09 00
AVER
AGERRPER5MIN
0
10
20
30
40
50RainGaugeRefKdpPdp Ryzhkov_Pdp Bringi_Pdp NIED_MKdp
:15 00 :16 00 :07 00 :08 00 :18 00 :19 00
AVERAGERRPE
R5MIN
0
10
20
30
40
50[mm/hr]
LOCAL TIME (UTC+9)LOCAL TIME (UTC+9)LOCAL TIME (UTC+9)LOCAL TIME (UTC+9)
RAINFA
LLAM
OUNT
0
5
10
15
20
25
30RainGaugeRefKdpPdp Ryzhkov_Pdp Bringi_Pdp NIED_MKdp
RAINFA
LLAMOUNT
0
10
20
30
40
50
60
[mm]
CASE04 - 2011.07.30CASE03 - 2011.07.19CASE02 - 2011.06.30CASE01 - 2011.06.11:05 00 :07 00 :09 00 :15 00 :16 00 :07 00 :08 00 :18 00 :19 00
Case studies were carried out forthe verification of 6 areal rainfallrate estimators4 rainfall events occurred in 2011summer season, which included 1stratiform rainfall (CASE01) and 3convective rainfalls (CASE02 - 04)Radar ray-based verification, andbasin-based verification areconducted respectivelyBasin-based verificationresult is shown in this posterAreal rainfall rate for raingauges was obtained byapplying Thiessen algorismResults are noise in the caseof stratiform case comparedwith convective casesOnly DP estimators producedtime-continuous results,missing data occurs whileusing other parameters
Figures on the right Upper panels : distributions of rain rate at a
sample time for each case Middle panels : basin averaged areal rainfall
rates with respect to time for each case Bottom panels : basin-based rainfall amounts
with respect to time for each case
Rainfall amount
Rainfall rate
DPestimators
One no data periodWhen using other estimators
DP gives negative values
DP do over estimate
do under estimate
