DATA USEDDATA USED

ABSTRACTABSTRACT

OBJECTIVESOBJECTIVES

Vigorous testing of HN and RDT will be carried out for NYCMAImprovement to the models will be carried out to suite the NYCMA. This might include various parameters as realized from the results analysis.The use of 700mb wind fields as a steering current for convective storms will be studied.Automation of nowcasting will be developed with products made available to the public domain through internet

STUDY AREASTUDY AREA

The study area is located in Eastern United States, between latitudes 36º

N to 47º N, and longitudes 67º W to 82º W.

Two of the selected nowcasting algorithms: Hydro-Nowcaster (HN) and Rapid Developing Thunderstorm (RDT) have already been installed to be tested for nowcasting over the NYCMA.

The HN ModelThe HN Model:: The HN algorithm focuses on two primary components of nowcasting. These are:

1. Motions of rain cells by identifying cloud clusters bounded by isotherms of brightness temperature (BT) and dignosing their motions in a 100 x 100-pixel regions

2. Growth or Decay of the rain cells is based changes of characteristics of cloud cluster of one image to the next. The chnges considered are cloud cluster size, temperature of coldest pixel and average temperature of the cluster.

TheThe RDT Model:RDT Model: The RDT model can be split into 3 stages; 1. Detecton of Cloud System using an adaptative temperature threshold of

infrared image (GOES’ IR 10.8)2. Tracking of cloud system using an algorithm based on the geographical

overlaping of the cells.3. Discrimination of the convective systems among the tracked clouds by

identifying trajectories of the cloud systems using either lighting data or the IR characteristics of the cloud systems.

The output is the RDT product coded in BUFR format and stored in binary files and can be visualized as in the figure below.

NOWCASTING ALGORITHMSNOWCASTING ALGORITHMS

New York City Metropolitan Area (NYCMA) New York City Metropolitan Area (NYCMA) New York City Metropolitan Area (NYCMA) New York City Metropolitan Area (NYCMA)

HN was implemented for the storm developed on June 12th 2006

at 17:15 UTC. The GOES IR cloud information for this and

previous time at 17:02 UTC in addition to relative humidity (RH),

precipitable water (PW) and temperature (T), were used as input

of the HN model to nowcast the progression, growth/decay, and

intensity of the storm for the next 3 hours. The GOES IR images

used and the HN output are presented below.

National Oceanic and Atmospheric Administration (NOAA/ NESDIS) Cooperative Research Program (CoRP)3rd Annual Science Symposium, Fort Colins, Colorado, 15 – 16 August 2006

Left: METEOSAT infrared image of the 15/08/97 at 1800 UTC; Right: Detected “cells” with colors indicating the temperature threshold used to detect the corresponding cluster.Source: SAF-NWC-IOP-MFT-SCI-SUM-11_v1.0.doc

PRELIMINARY RESULTS:PRELIMINARY RESULTS:

METHODOLOGYMETHODOLOGY

1. Infrared (IR) cloud-top brightness temperature (BT) from GOES 10

satellite (Channel 4 [10.8m] wavelength), was used as input for the

both models. Information about other cloud properties such as relative

humidity, temperature, and precipitable water were also used for rainfall

estimation in conjunction with IR cloud information.

2. NEXRAD stage III and IV rainfall product and rain gauge observations

are used for evaluating the nowcasts.

Accurate forecasting of convective precipitation for time periods of

less than a few hours (Nowcasting) has always been a big challenge to

scientists and engineers. Nowcasting, up to 6 hours, in New York City

Metropolitan area (NYCMA) is a new challenge because the NYCMA is

the largest in the Nation and accurate reliable nowcasts of heavy

precipitation would have enormous economic and social value.

Over the years the performance of the quantitative precipitation

forecasts (QPF) using numerical weather prediction (NWP) models,

weather radar data, lightning detectors and satellite imagery as their

primary tool for detection of convective storms, have significantly

improved, despite some shortcomings on each system. NWP model QPF

continues to lag in skill during the first several hours after model

initialization, due largely to the “spin-up” problem of having to produce

dynamically consistent vertical motion fields. Satellites data have the

ability to overcome many of the limitations of NWP model and radar data.

Geostationary satellites are capable of providing information about cloud

properties at very high temporal resolution (15 minutes) on continuous

basis and therefore addressing many of the previous systems’

shortcomings.

Efforts in this study will be directed in trying several existing

nowcasting algorithms from NOAA-NESDIS, EUMETSAT, NSSL, and

NCAR for the NYCMA and modifying the suitable one for using satellite-

based cloud information.

Modifying an existing nowcasting algorithm for NYCMA to nowcast rainfall

at every 15 minutes up to 6 hours duration using satellite-based cloud

information.

Selected existing nowcasting models are:

Hydro-Nowcaster (HN) from NOAA-NESDIS,

the Rapidly Developing Thunderstorm (RDT) models from France,

the NSSL WDSSII Multiscale Storm Identification and Forecast

algorithm,

the Thunderstorm Identification, Tracking, Analysis, and Nowcasting

(TITAN) module of the NCAR Autonowcast (ANC) system

YellowYellow contour = newly detected systemYellowYellow line = the trajectory of the convective system.RedRed contour = the system is growingVioletViolet contour = the system is mature.BlueBlue contour = the system is decreasing.GreenGreen contour = the convective system in the previous satellite image.BlackBlack arrow = the expected move of the convective system

Visualization of the RDT ProductVisualization of the RDT Product superimposed on its IR.10.8 image superimposed on its IR.10.8 image

GOES IR, at 17:02 UTC GOES IR, at 17:15 UTC

Rainfall Nowcastes, at 18:15 UTC (after 1-hour) Rainfall Nowcastes, at 19:15 UTC (after 2-hours)

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Satellite-Based Nowcasting over the New York City Metropolitan AreaSatellite-Based Nowcasting over the New York City Metropolitan Area Bernard.Mhando & Nasim Nourozi, of Graduate Center of City University of New York

Dr. Shayesteh Mahani and Dr. Reza Khanbilvardi, Department of Civil Engineering, City College of New York at CUNY

Visualization of HN Results. The GOES image have been reproduced into rainfall The GOES image have been reproduced into rainfall images showing increasing intensity (color changes) and spatial scatering of the storm. images showing increasing intensity (color changes) and spatial scatering of the storm. This is compared to Stage III radar data for validation.This is compared to Stage III radar data for validation.

FUTURE WORKFUTURE WORK