Precipitating Clouds from Cloud Physical Properties 
(NWC/GEO PC-Ph,v2018)

 

Table of contents

1. Goal of PC-Ph product  
2. PC-Ph algorithm description  
3. List of inputs for PC-Ph  
4. Description of PC-Ph outputs 
5. Example of PC-Ph visualisation 
 

Access to "Algorithm Theoretical Basis Document for the Precipitation Product Processors of the NWC/GEO" for a more detailed description of the algorithm.

 

1. Goal of PC-Ph product

PC-Ph product, developed within the NWC SAF context, is a Nowcasting tool that provides estimation on the probability of precipitation (PoP) occurrence during the whole day.
PoP is defined as the instantaneous probability that a rain rate greater than or equal to 0.2 mm/h occurs at the pixel level.

 

2. PC-Ph algorithm description

Day time

The PoP estimation is done using information on the cloud top microphysical properties, Effective Radius (Reff) and Cloud Optical Thickness (COT). 
The microphysical properties are computed within the NWC/GEO CMIC product for daytime, so it is necessary to run CMIC product previous to run PC-Ph. 
Using Reff and COT the Cloud Water Path (CWP) is computed. CWP means Liquid Water Path for water clouds and Ice Water Path of ice clouds. This parameter is computed using the following equation:

For the retrieval of the probability of precipitation, the Cloud Water Path (CWP) is used. The following relation between CWP and PoP has been obtained in order to assign a PoP to each satellite pixel:

 

 

Where PoP is the Probability of Precipitation occurrence (%) and CWP is the Cloud Water Path (gm-2). 

Since the parameters used by this algorithm have a high dependence on illumination conditions, a study has been carried out in this sense. This study concluded that illumination conditions don't affect the quality of PC-Ph product. 
For a better PoP area location a parallax correction can be applied to this product. This option is chosen by the user through the product model configuration file and it is applied by default. When the Parallax Correction is working, a spatial shift is applied to every pixel with PoP greater than 0%.

Night time

The PoP estimation is computed whenever the CMIC phase is defined. A nonlinear regression, the Kernel Ridge Regression (KRR), is applied to establish a relationship between SEVIRI brightness temperatures and rainfall intensities.

Transition between day to night algorithm is produced whenever the solar zenith angle is greater than 70º. It is also possible to configure the product to only use the night algorithm by setting the sun zenith angle threshold to 0. This would avoid discontinuities in the product at the day/night transition on the cost of degrading performance during day time.

 

3. List of inputs for PC-Ph 

NWC/GEO CMIC microphysical parameters

  • CMIC Phase, COT and Reff parameters are mandatory inputs to PC-Ph day algorithm.
  • CMIC Phase is mandatory input to compute the PC-Ph night algorithm 

Satellite imagery

IR10.8 SEVIRI brightness temperature at full IR spatial resolution is a mandatory input to compute Parallax Correction.

IR10.8 and WV6.2 are mandatory inputs to compute the PC-Ph night algorithm. 

Numerical model

Temperature at 1000, 925, 850, 700, 500, 400, 300, 250 and 200 hPa
Geopotential at 1000, 925, 850, 700, 500, 400, 300, 250 and 200 hPa
 

This information is used by default for parallax correction. In case of lack of NWP parameters parallax correction will be run using a climatological profile.

Ancillary data sets

Climatological profile is necessary as a back up for Parallax correction in case NWP is not available. This information is included in the software package and is located in the $SAFNWC/import/Aux_data directory

Model configuration file for PPh

PPh model configuration file contains configurable system parameters in the generation process of both PC-Ph and CRR-Ph products. The PC-Ph product related parameters refers to ancillary datasets, numerical model data and parallax correction. The complete list of these parameters and the explanation of the most useful ones are available in the "User Manual for the Precipitation Product Processors of the NWC/GEO".

 

4. Description of the main PC-Ph output

PC-Ph product is coded in NetCDF format and its content is the following:

  • pcph output provides an estimation of the probability of precipitation from 0% to 100% of probability.
  • pcph_status_flag provides information on the data availability, whether parallax correction has been applied and holes due to parallax correction for each pixel:

 

DAY ALGORITHM

GEO-CMIC-INPUT PHASE

PHASE INPUT CLASS

COT OR REFF FROM CMIC

PC-PH OUTPUT

Liquid

1

NO DATA

NO DATA

DATA AVAILABLE

pcph(%)=scale_factor * counts + add_offset

Ice 

2

NO DATA

NO DATA

DATA AVAILABLE

pcph(%)=scale_factor * counts + add_offset

Mixed

3

NO DATA

NO DATA

DATA AVAILABLE

pcph(%)=scale_factor * counts + add_offset

Cloud-free

4

NOT APPLICABLE

0

Undefined

5

NOT APPLICABLE

NO DATA

No data or corrupted data

FillValue

NOT APPLICABLE

NO DATA

 

NIGHT ALGORITHM

GEO-CMIC-INPUT PHASE

PHASE INPUT CLASS

PC-PH OUTPUT

Liquid

1

pcph(%)=scale_factor * counts + add_offset

Ice 

2

pcph(%)=scale_factor * counts + add_offset

Mixed

3

pcph(%)=scale_factor * counts + add_offset

Cloud-free

4

0

Undefined

5

NO DATA

No data or corrupted data

FillValue

NO DATA

 

where:

  scale_factor        = 1.0

  add_offset           = 0.0

 

Data Availability:

Bit 0:            Reff or COT not computed (out of cloud, night time or undefined phase)

Bit 1:            Phase not computed or undefined

Bit 2:            IR band missing (used in parallax correction)

Applied Correction:

Bit 3:            Parallax correction applied

Other information

Bit 4:             pc_intensity was a hole because of the parallax correction, and then was filled by the median filter

 

5. Example of PC-Ph visualisation

Below threre are shown two images corresponding to PC-Ph probability of precipitation output. It has been obtained at full resolution and parallax correction have been applied.

Figure 1: PC-Ph probability of precipitation for 10th May 2016 at 12:00 UTC over Sapin,day algortihm

 

                               Figure 2: PC-Ph probability of precipitation for 10th February 2019 at 21:00 UTC over Europe, night algorithm

References

  • Pilewskie, P. and Twomey, S., 1987. Discrimination of ice from water in clouds by optical remote sensing. Atmos. Res., 21:113-122
  • Rosenfeld, D., and G. Gutman, 1994. Retrieving microphysical properties near the tops of potential rain clouds by multispectral analysis of AVHRR data, Atmos. Res., 34, 259-283, doi:10.1016/0169-8095(94)90096-5.
  • Roebeling, R.A., A.J. Feijt and P. Stammes, Cloud property retrievals for climate monitoring: implications of differences between SEVIRI on METEOSAT-8 and AVHRR on NOAA-17 J. Geophys. Res., 2006, 111, 20210, doi:10.1029/2005JD006990.
  • Roebeling, R.A. and I. Holleman, 2009. SEVIRI rainfall retrieval and validation using weather radar observations. J. Geophys.Res., D2120, 114.
  • Daniel Rosenfeld, William L. Woodley, Amit Lerner, Guy Kelman, Daniel T. Lindsey, 2008. Satellite detection of severe convective storms by their retrieved vertical profiles of cloud particle effective radius and thermodynamic phase. J. Geophys. Res. D4, 113.- Gutierrez, J. M. and Aguado, F.: Quality image for the Spanish Radar National Composite, Proceedings of ERAD 2006, 318-320.
  • Algorithm Theoretical Basis Document for "Precipitation products from Cloud Physical Properties" (NWC-CDOP2-GEO-AEMET-SCI-ATBDPrecipitation_v2.1), v2018
  • Product User Manual for "Precipitation products from Cloud Physical Properties" ( NWC-CDOP3-GEO-AEMET-SCI-UM-Precipitation_v1.0 ), v2018
  • Validation Report for "Precipitation products from Cloud Physical Properties" (PC-Ph v2.1 & CRR-Ph v2.1), v2018

 

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