Transcript Accumulated Precipitation Product HSAF Code: PR

Operational estimation of
accumulated precipitation using
satellite observation by Eumetsat
H-SAF
Attilio Di Diodato
National Centre for Aeronautical
Meteorology and Climatology (CNMCA)
Italy
A lot of activities have been running at Centro Nazionale di Meteorologia e
Climatologia Aeronautica (C.N.M.C.A.), the Air Force National Weather
Centre, to reach the EUMETSAT H-SAF final target: development of
algorithms, validation of results, implementation of operative procedure to
supply the service and to monitor the service performances. The H-SAF
precipitation products generating system is designed with high efficiency,
redundancy in machine and data link, easy to control by H24 human operator
system.
Italian Air Force - Meteorological Service has made many efforts to rapidly
improve satellite receiving system, computing power, licensed software,
engineering know-how, consuming nearly nothing of H-SAF budget.
List of H-SAF precipitation products and indication of the Units responsible of algorithm development.
Code
Acronym
Product name
Responsible for
development
H-01
PR-OBS-1
Precipitation rate at ground by MW conical scanners
I.S.A.C.-C.N.R. ITALY
H-02
PR-OBS-2
Precipitation rate at ground by MW cross-track scanners
I.S.A.C.-C.N.R. ITALY
H-03
PR-OBS-3
Precipitation rate at ground by GEO/IR supported by LEO/MW
I.S.A.C.-C.N.R. ITALY
H-04
PR-OBS-4
Precipitation rate at ground by LEO/MW supported by GEO/IR
I.S.A.C.-C.N.R. ITALY
H-05
PR-OBS-5
Accumulated precipitation at ground by MW+IR and MW only
C.N.M.C.A. ITALY
H-06
PR-ASS-1
Accumulated precipitation at ground computed by a NWP
C.N.M.C.A. ITALY
PR-ASS-1 (COSMO-ME domain)
HSAF domain
Super-Computing
Next implementation of cluster HP with 128 compute nodes each
forth-processor Intel Xeon will allow to cover the whole HSAF area
with NWP COSMO ME.
computing capabilities
more than 13,5 TFlops.
Basic considerations on
time sampling error structure
A preliminary study on precipitation time series recorded
by a network of 76 automatic stations (perfect
sampling time step: 15 minutes) showed the following
results:
24-h cumulated
3-h cumulated
Bias
STD
Bias
STD
3h
-1.53%
142%
-0.84%
167%
1h
-3.70%
66%
-5.1%
74%
30 min
0.54%
37%
-2.98%
43%
Sampling
periods
Basic considerations (2)
This time structure of precipitation field implies that
instantaneous sampling like that obtained by satellite remote
sensing requires accomplishing short time scanning.
H03 PR-OBS-3 Precipitation rate at ground by GEO/IR supported by LEO/MW
Integration of instantaneous
precipitation
Aim: to obtain a value of accumulated precipitation (RS_acc )
starting from satellite estimation of instantaneous
precipitation.
RS_acc=∫T RS (t) dt
The evaluation of the accumulated precipitation achieved
by the integration of any interpolation function (linear,
cubic, spline, etc..) is very similar.
Integration of instantaneous
precipitation
Assumption: rain rate does not change
during the 15 minutes intervals.
The accumulated precipitation for each time
step is obtained with the rain rate value
multiplied by the same time step.
Total accumulated precipitation in 3, 6, 12
and 24 hours is a sum up of each
contribution.
Quality Control
Search of outliers every 15 minutes and on
the differents accumulation periods, using
climatological data (different thresholds by
season and geographic position) got from
“Climate Atlas of Europe” led by Meteo France
inside the project ECSN (European Climate
Support Network) of EUMETNET.
PR-OBS 5 Version 1
The algorithm runs on the operational chain at
CNMCA;
The products are available about
minutes after the synoptic hours;
fifteen
If an input file is missing the algorithm cuts the
value of the previous file.
PR-OBS 5 Version 1
The final result contains not negligible
random and bias error due to the indirect
nature of the relationship between the
observation and the precipitation, the
inadequate sampling and algorithm
imperfections.
PR-OBS 5 Version 1
Use of N-SAF
cloud mask
Case study 23 July 2008
Case study 23 July 2008
Case study
23 July 2008
Version2: Use of rain gauge data
Ground measurements
points (only synoptic
stations on GTS network)
are used for the
intercalibration between
satellite estimations and real
measurements due to
timeliness and cal/val aims.
Use of rain gauge data
We have to consider that rain gauge measurements are not perfect,
but they are affected by some bias error, due to:
- Trace precipitation
- Wetting loss
- Evaporation loss
- Wind-induced error
Pc=K(Pg + ΔPw + ΔPe) + ΔPt
For operational aims only wind-induced error has taken in account
Pc=K * Pg
where
K = 1/ CR
with CR= catch ratio
Use of rain gauge data
CR= exp(-0.041* vg)
Where vg = wind speed (m/s) at gauge height.
Logarithmic wind reduction equation (Garrat 1992) is used to convert
the measured wind speed at certain height to the wind speed at
gauge height.
vg = vH * log(h/ Z0)/log(H/ Z0)
where:
• h = Height of the gauge orifice (m)
• H = Height of the wind speed measurement (m) (usually 10 m for
the stations comply with WMO standards)
• Z0 = Roughness length (m) (usually taken as 0.03m)
• vH = Wind speed measured at height H
Increments computation
• At all rain gauge points the
•
difference between ground
measurements and satellite
estimated precipitation is
calculated.
The values of satellite
estimations on the rain
gauge points are obtained
by interpolation techiques
Version 2: spatial interpolation
Use of Kriging method to interpolate the increments
Distribution of differences over the gridded HSAF area is
prepared by using standard kriging method.
Version 2: final result
In each satellite grid point the final
product is the sum of satellite
precipitation estimation and the
increment.
Version 2: case study
final result
Problems
This method reduces the bias error introduced basically
from IR observations by geostationary satellite, but we
have other problems:
• Ground data are not available over sea areas;
• Observation network density is poor over some regions;
• Precipitation information inside synop messages are
•
presents only every 6 hours;
We don’t take in account the orography;
Future developments
To use the QPF by numerical model COSMO - ME as background
field (OI).
Model resolution: 7 Km
2 Runs per day (00 and 12 UTC)
Output every 3 hours.
Future developments
To improve the output of H03 algorithm
(istantaneous precipitation), for example
through a clouds discrimination.
NEFODINA: a product to discriminate
convective clouds
An application for automatic detection
of convective phenomena (NEFODINA)
running operationally at Italian Met
Service, which make use of three
SEVIRI Channels (6, 7 and 10 )
Algorithms have been upgraded and
improved with the contribution of the
former Eumetsat fellowship (2003-2005,
Dr. Puca) .
Early detection of convective clusters
and active Nuclei identification.
Nowcasting of active nuclei evolving
phase.
Running operationally over Mediterranean area.
Under testing over full disk