Efforts in Assimilation of Satellite data at NCMRWF

Efforts in Assimilation of Satellite
data at NCMRWF
V.S. Prasad
[email protected]
Introduction
• NCMRWF is the atmospheric modelling centre of MoES.
• Its one of the main objective is developing system for
data handling and assimilation for global meteorological
observations with special emphasise to Indian satellite
data.
• A brief description of this system with recent
development as example will be presented .
Building of data assimilation
system
– Observing system
– Data handling system
– Forecast model
– Computational resources
– understanding the available knowledge about
observations and statistics
– Human resources (?)
– Verification and monitoring system
Six Regional Associations of WMO:
Region
Area
1
Africa
2
Asia
3
South America
4
North & Central America
5
South-West Pacific
6
Europe
GTS
Efforts for getting Satellite
data sets
•
•
NCMRWF mad arrangements to
receive satellite radiance data
through various national and
international sources either
through direct link or ftp. The
different sources include
NOAA/NESDIS, KNMI, JMA,
EUMETCAST, SAC, NRSC,
ISSDC, IMD, etc
The list is increasing and recently
NPP-CrIS and ATM are also
added
Monthly Average Data Volume (MB/Day) in NCMRWF
May-2011 to May-2012
GTS + Radar
Radar
Data Volume (MB/Day)
14000.00
12000.00
10000.00
8000.00
6000.00
4000.00
2000.00
0.00
May-11
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Jan-12
Feb
Mar
Apr
Month
Satellite data download via FTP
Organisation
Jan 2011
July 2013
Vol/day
Near
Future
Vol/day
~ 12 GB
~ 20GB
EUMETCAST 0
~3GB
~ 20GB
ISRO
~500 mb
~ 1 GB
(last meeting)
As of now
GTS – 300mb (June2010) NESDIS
- 1.2 GB (Sep 2013)
Radar – 17GB
Vol/day
~500 MB
~500 mb
May
Started receiving and
assimilating NOAA
profilers (USA) through
GTS from Sept. 2012
Increase in profiler data by ~50%
Aircraft Observations
Since November,
2012 more aircraft
reports are being
received at
NCMRWF
Data pre-processing system for NCUM
Strategy for assimilating new data
• Operational data assimilation data requires:
–
–
–
–
–
–
–
Data available in real time in acceptable format
A stable data source
Quality control procedures to be defined
Bias correction and observational errors defined
An accurate forward model
Data monitoring
Evaluation and testing to ensure neutral/positive
impact
– All of the above are more important than assimilation
technique.
MeghaTropiques (MT)
• India and French jointly launched MT
satellite. It carries four instrumenst
• Saphir
• ScaRab
• Madras
• Rosa
• Assimilation of MT-Saphir is in final stages
• ScaRab will be used as a diagnostic tool
Saphir Charecterstics (developed by CNES)
Scan Type – Cross Track scanning at const. speed Incidence angle – Varaible
Along the swath , Scan angle ±42.96˚ , resolution 10 km ;no pixel per scan130
Channel Central Nominal
Frequencies (GHz)
S1
183.31±0.2
Channel
bandwidth MHz
200
S2
350
183.31±1.1
CH # 3 MHS
S3
183.31±2.8
500
S4
183.31±4.2
700
S5
183.31±6.8
1200
CH # 5 MHS
S6
183.31±11
2000 TMI CH
Cloud detection
Using Hong
et al 2005
Number and coverage of MT-ROSA Profiles
Absolute difference in refractivity between model first
guess and ROSSA data and standard deviation
( Based on 5012 profles)
0
Pressure (mb)
200
400
600
800
1000
-20
0
20
40
60
80
100
120
140
Refractivity (N units)
Absolute difference in Refractivity between
COSMIC & ROSSA and standard deviation (based
on 43 profiles)
Altitude (m)
15000
12000
9000
6000
3000
0
-20
0
20
40
60
Refractivity (N units)
80
100
120
Mean RMSE in Relative Humidity w.r.t. analysis over tropics (-30S to
30N) at different pressure levels simulated by OSSE (GPSRO) and
Control (T574)
200
mb
26
500 mb
26
24
24
22
22
20
T574
GPSRO
T574
GPSRO
18
RH
(%)
RH
(%)
20
18
16
16
14
14
12
day2
day3
day4
day5
Forecast
day
day1
850
mb
26
22
20
T574
GPSRO
18
16
14
12
10
day1
day2
day3
Forecast day
day2
day3
Forecast
day
24
RH (%)
day1
day4
day5
day4
day5
Mean RMSE in rainfall with IMD-NCMR merged data over Indian region
simulated by OSSE (GPSRO) and Control (T574)
(a)
8
7.8
7.6
Rain in
(mm)
7.4
GPSR
O T574
7.2
7
6.8
6.6
day1
day2
day3
Forecast
Day
day4
day5
Long wave Flux 00-06z 29Aug 2012
MT ScaRAB
NCMRWF
UM
Comparison of 10m wind Anal and Buoy observations
8-23 june 2011
Buoy locations
Correlation coeff. of
buoy measured wind
with model CNTL
analysis 10m wind
Correlation coeff. of
buoy measured wind
with model EXP
analysis 10m wind
23007 [88.99˚E, 8.02˚N]
0.73
0.75
0.1
0.63
0.03
0.88
0.72
0.68
0.95
0.9
53006 [80.51˚E, -12˚S]
0.61
0.61
14042 [54.99˚E,12.04˚S]
0.95
0.99
14043 [67.22˚E,12.19˚S]
0.92
0.92
14046 [55˚E, -16˚S]
0.72
0.86
23006 [89.59˚E, 3.98˚N]
23004 [89.85˚E, 0.03˚N]
14041 [55.08˚E, -7.93˚S]
53005 [80.46˚E, -8.01˚S]
RH contours
Wind speed shaded
Analysis and Forecast wind plots
Based on IC: 00UTC Of 14May2013
Oper – no oscat
Exp - with oscat
Conclusions
• NCMRWF making many attempts to get all
possible data from global met community.
• It became successful in assimilating
Oceansat-2 scatterometer, MT-Saphir
• Many other satellites such as GOES-E
&W, MTsat etc are successfully used in
Data assimilation system
• Efforts are on to use NPP data, METOP-B
etc.