precipitation top heights estimation in convective systems

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F. J. Tapiador, R. Moreno and Z. S. Haddad Precipitation top heights estimation UCLM - JPL Precipitation top heights estimation in convective systems Francisco J. Tapiador, Ra´ ul Moreno and Ziad S. Haddad University of Castilla-La Mancha / Jet Propulsion Laboratory October 2018 Motivation The absence of systematic estimates of vertical trans- port of water by convective systems is one of the main causes of uncertainties: I Weather forecasting I Climate-scale analysis I Prediction of global circulation Objective Develop a systematic method for quantitatively esti- mating the maximum height of precipitation in convec- tive systems using brightness temperatures b . Available orbital instruments Radar + Water content vertical profile - Narrow swatch - Revisit time > 3 days Millimeter Wave radiometers + Wide swath + Revisit time 80 min - Absence of vertical profile (but features can be infered) IR instruments + Extra wide swath + No Revisit time -- Non sensitive for precitation Source: IR images of Tropical Cyclone Winston obtained from http://eumetsat.int Near-simultaneous coincidences Radar-radiometer pair of coincidences searched in millions of records, between Dual-Frequency Precipitation Radar (DPR) and each of the following instruments: I GPM Microwave Imager - GMI I SAPHIR humidity sounder I Advanced Technology Microwave sounder - ATMS I Special Sensor Microwave Imager/Sounder - SSMIS As a result, a training database and a testing database were built from the intersections obtained. Precipitation detection I Binary detection is performed using Linear Discriminant Analysis (LDA). I This method classifies b between precipitation P and dry D . I We used the training database to obtain a LDA discriminant x and its threshold v thr . ρ(b )= ( P if v (b ) > v thr D otherwise v (b )= x · b Precipitation estimation I Water height is estimated from b measurements classified as P , or b p . I Lookup tables are indexed based on the Principal Components (PC) of b p . I We used the training database to build lookup tables for every radiometer where every cell is addressable by the PC of their b p values, containing the estimated height: L (PC 1 (b p ), PC 2 (b p ), ..., PC i (b p )) E {h max } Estimation maps We used the L tables to get estimation maps of the maximum height of precipitation of the Tropical Cyclone Winston, just from b measurements: I Chosen case: 22 February 2016 I Tropical Cyclone Winston I Minimum water content for detection = 0.05g /m 3 . DPR GMI SAPHIR ATMS SSMIS

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Page 1: Precipitation top heights estimation in convective systems

F. J. Tapiador, R. Moreno and Z. S. Haddad Precipitation top heights estimation UCLM - JPL

Precipitation top heights estimation in convective systemsFrancisco J. Tapiador, Raul Moreno and Ziad S. Haddad

University of Castilla-La Mancha / Jet Propulsion Laboratory

October 2018

Motivation

The absence of systematic estimates of vertical trans-port of water by convective systems is one of the maincauses of uncertainties:

I Weather forecastingI Climate-scale analysisI Prediction of global circulation

Objective

Develop a systematic method for quantitatively esti-mating the maximum height of precipitation in convec-tive systems using brightness temperatures b.

Available orbital instrumentsRadar

+ Water content vertical profile− Narrow swatch− Revisit time > 3 days

Millimeter Wave radiometers

+ Wide swath+ Revisit time ≈ 80 min− Absence of vertical profile (but features can be infered)

IR instruments

+ Extra wide swath+ No Revisit time−− Non sensitive for precitation

Source: IR images of Tropical Cyclone Winston obtained from http://eumetsat.int

Near-simultaneous coincidences

Radar-radiometer pair of coincidences searched in millions of records,between Dual-Frequency Precipitation Radar (DPR) and each of thefollowing instruments:

I GPM Microwave Imager - GMII SAPHIR humidity sounderI Advanced Technology Microwave sounder - ATMSI Special Sensor Microwave Imager/Sounder - SSMIS

As a result, a training database and a testing database were built fromthe intersections obtained.

Precipitation detection

I Binary detection is performed using Linear DiscriminantAnalysis (LDA).

I This method classifies b between precipitation P and dry D.I We used the training database to obtain a LDA discriminant x

and its threshold vthr .

ρ(b) =

{P if v(b) > vthr

D otherwisev(b) = x · b

Precipitation estimation

I Water height is estimated from b measurements classified asP, or bp.

I Lookup tables are indexed based on the PrincipalComponents (PC) of bp.

I We used the training database to build lookup tables for everyradiometer where every cell is addressable by the PC of theirbp values, containing the estimated height:

L (PC1(bp),PC2(bp), ...,PCi(bp))← E {hmax}

Estimation mapsWe used the L tables to get estimation maps of themaximum height of precipitation of the TropicalCyclone Winston, just from b measurements:

I Chosen case: 22 February 2016I Tropical Cyclone WinstonI Minimum water content for detection

= 0.05g/m3.DPR

GMI SAPHIR

ATMS SSMIS

Tapiador
Sticky Note
Ponte tú primero en el póster
Tapiador
Sticky Note
uncertainties in:
Tapiador
Sticky Note
cita el paper de Ziad