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South Asian Regional Reanalysis (SARR). Ashish Routray National Centre for Medium Range Weather Forecasting (NCMRWF) Ministry of Earth Sciences Government of India. Motivation for South Asian Regional Reanalysis

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south asian regional reanalysis sarr

South Asian Regional Reanalysis (SARR)

Ashish Routray

National Centre for Medium Range Weather Forecasting (NCMRWF)

Ministry of Earth Sciences

Government of India

slide2

Motivation for South Asian Regional Reanalysis

Due to the direct societal impacts, interest in Regional Hydroclimate (precipitation, surface temperature, soil moisture, stream flow, drought indices, etc.) is intense and growing.

National Action Plan on Climate Change

Government of India

Prime Minister’s Council on Climate Change

3.8.2 ……. Regional data reanalysis projects should be encouraged. ……..

slide3

South Asian Regional Reanalysis (SARR)

A Collaborative Project between

Ministry of Earth Sciences,

Government of India

and

National Oceanic and Atmospheric Administration,

Department of Commerce,

United States of America

slide4

Specific SARR Goals

Refinement in methods of precipitation and radiances assimilation.

Conduct a 5-year pilot-phase reanalysis

(to test and optimize data stream organization and the geographic domain and assimilating model choices)

Develop high-resolution SST analysis for the Indian ocean from satellite and in-situ observations, including moorings, drifters and Argo floats

Design techniques for assimilation of aerosols

Generate a high spatio-temporal resolution (≤25 Km, ≤3 hours) climate data set for the 1979-2009 period over the South Asian land-ocean region.

slide5

Responsibilities of the Parties

NOAA agrees to:

Provide MoES full access to the archived observations used in the global reanalysis projects.

Provide technical help, training, and guidance in organization of data streams and in the implementation of the regional reanalysis model.

Provide training to MoES scientists in regional reanalysis techniques and procedures during 6-8 week annual visits to US institutions and NOAA laboratories.

Share the NCEP data processing and quality control procedures during reanalysis project with MoES scientists.

Support travel of NOAA and US university scientists to India in connection with SARR project activities.

slide6

MoES agrees to:

  • Provide NOAA full access to all historical and current meteorological observations as per requirement of the project over the Indian subcontinent and Indian Ocean, including those from Indian satellites.
  • Execute the South Asian Regional Reanalysis project through NCMRWF.
  • Provide full-time modeling scientists to develop, implement, and test numerical codes.
  • Provide 4-6 full time Ph.D. scientists to design, test, and implement various assimilation schemes in the numerical model.
  • Provide high-speed mainframe computer resources for execution of this computationally intensive project.
  • Provide storage devices and skilled manpower (data management specialists) to organize data streams, data archival, data dissemination, and webpage design and maintenance.
  • Provide continuous high-speed internet access to project scientists, including visiting ones.
  • Provide lodging and boarding for visiting US project scientists.
exchange visits
Exchange visits
  • NOAA will provide training to 2-3 MoES scientists in regional reanalysis techniques and procedures during 6-8 week annual visits to the University of Maryland and NOAA's National Centers for Environmental Prediction (NCEP).
  • NCEP will seek resources and assistance from NOAA's International Activities office in meeting its responsibilities.
  • NOAA and MoES scientists will meet yearly to discuss the project's progress, and to strategize on how to best accomplish the project goals.
  • NOAA and MoES will separately cover travel costs associated with exchange visits for their respective technical and scientific personnel.
slide8

Milestones

SARR IA signed in September 2008 in New Delhi

1st Annual Review by JEM held in October 2009 in New Delhi

Functional Group created at NCMRWF for SARR in November 2009

SARR Scoping Workshop held in New Delhi in February 2010

2nd Annual Review by JEM held in October 2010 in Washington DC

slide9

The SARR Project is being carried out with an objective that the SARR Products shall be useful for

Climate Diagnostics,

Climate Variability,

Climate Change,

Model Verification/Tuning

It is expected that

The SARR project will provide an Atmosphere-Land-Ocean surface state description where consistency between circulation and hydroclimate components is assured.

To achieve the goal, assimilation of rainfall, radiance, and aerosol observations in numerical weather prediction models shall be carried out

slide10

SARR Project Team at NCMRWF

Sarat C. KarProject Management

Ashish RoutrayAssimilation- Lead

Prashant Mali Modeling- Lead

Jaganabdhu Panda Modeling (worked for about 3 months and left in September 2010)

K. Sowjanya Assimilation (worked for about 1 year and left in September 2011)

Sapna Rana Diagnostics (worked for about 1 year and left in November 2011)

slide11

Domain chosen for SARR

Lat: 150S-450N (286 pts)

Lon: 400E-1200E (332 pts)

Res.: 25 km (pilot phase)

18 km (final SARR)

Cen-lat: 17.50N

Cen-lon: 80.00E

slide13

NCEP

SARR

OBSERVATION

DATA BANK

IMD

NCMRWF

Countries in

SARR domain

INCOIS

ISRO

Field

Experiments

slide14

DATA from FIELD EXPERIMENTS

Land Surface Processes Experiment (LASPEX)

C

T

C

Z

BOBMEX

ARMEX

PROWNM

C

B

STORM Programme

slide15

SARR Scoping Workshop

held in New Delhi, India (February 10-11, 2010)

9 scientists from USA and about 20 scientists from India participated.

Analysis method and the model as

well as domain of analysis finalized.

WRF model (3.1 version) and

WRF-3DVar shall be used to carry

out SARR Pilot phase.

The Workshop recommended an

implementation strategy for

success of the SARR project.

work plan at ncep
Work plan at NCEP
  • Training on methodology for assimilation of the radiance data (mainly the older period radiance data) using the GSI system so that a similar technique can be developed later for the WRF-3DVAR analysis system.
  • As part of the training, experiments using radiance data assimilation for Indian summer monsoon seasons (mainly for older period) using the NCEP GSI system and document impact assessment.
  • Familiarization with the available diagnosis package for monitoring and for calculation of statistics of the radiance data utilized in the assimilation cycle.
slide18

Analysis Scheme & Model for SARR Pilot Phase

WRF 3.1 and WRF-VAR (3.1) has been chosen for SARR Pilot phase experiments

Several modeling and assimilation experiments have been carried out using past data.

Most of the experiments are for July 1999 using NCEP & NCMRWF observation datasets

slide19

Challenging regions for obs. data

Sound

Av. Number of TEMP observation per day reaching particular height in July 1999

Average Number of Observations per day in July 1999

Blocks- 42 and 43

slide21

Mean RMSE of OBS-FG

Mean RMSE of OBS-ANA

SARR Test runs with NCEP & NCMRWF data

slide22

SARR Pilot Phase Experiments

(i) with various Physics Options

Dynamic Downscaling using WRF

(ii) with various Physics Options

Assimilation using WRF & WRF-VAR

Most of the experiments are for July 1999 using NCEP & NCMRWF observation datasets

slide23

SARR Pilot Phase Sensitivity Experiments

All Experiments were done for July 01- 31 1999.

With Assimilation- Cyclic, Four times a day (6-hourly)

No Assimilation- only Model run Four-times a day (6-hourly).

(Similar to downscaling experiments)

Precipitation in July 1999 CMAP, TRMM (3B42) and IMD Observed Rain

slide24

Precipitation from Global Reanalysis datasets for July 1999

As can be seen, the global reanalysis has failed to bring out details of rainfall distribution over India and higher rainfall amounts are placed at incorrect locations

slide26

SARR Pilot phase Sensitivity Experiments

No Assimilation

With Assimilation

slide27

It has been shown that

just downscaling of coarse resolution global reanalysis (No Assimilation runs) is not sufficient for accurate representation of the Indian monsoon hydroclimate.

When regional assimilation is carried out, such representation is improved.

slide28

SARR Pilot Phase Sensitivity Experiments

Experiments have been carried out using ISRO derived vegetation data instead of USGS climatological vegetation available with the WRF model.

Results indicate that hydroclimate representation over India is sensitive to such specifications.

slide29

Impact of Field phase Experiments- BOBMEX data

Bay of Bengal

Monsoon Experiment

(BOBMEX)

July-August 1999

slide30

Impact of Field phase Experiments- BOBMEX data

(00Z 12 August 1999)

Assim- Control

Assim- with BOBMEX

Difference

slide31

Parallel Assimilation from May 2001 to Sept 2001.

Need of Overlapping period

U at 850hPa

Pilot phase Assimilation with conventional data has been completed from 1999-2003.

Assimilation with Radiance data and conventional data is being carried out for the same period.

Parallel run period is also being extended.

T at 850hPa

slide33

SARR Production Runs

Five simultaneous Streams

  • Jan. 1979 - Dec. 1985 7 years
  • Apr. 1985 - Dec. 1991 7 years
  • Apr. 1991 - Dec. 1997 7 years
  • Apr. 1997 - Dec. 2003 7 years
  • Apr. 2003 - Dec. 2009 7 years

9-month overlap for each stream

Total 35 years of Reanalysis Computation

slide34

SARR Products

Archival and Distribution

Archival Format (Reanalysis):

IEEE (suitable for GrADS)

NetCDF

GRIB2

Archival Format (Observed data):

ASCII (GTS)

PrepBUFR

little-R

Original format of data

Archival online/nearline disk, Tapes

Available to Partner Organizations: Immediately

slide36

SARR – What next?

SARR -II

After the successful completion of SARR’s present project, We propose to carryout SARR-60

SARR-60 From 1950 to 2009 at 9 km resolution

Regional Ocean-Atmosphere coupling

- shall be the comprehensive dataset for

climate studies in South Asia.

numerical experiments

Numerical Experiments

The objective of the study is to evaluate the impact of the different back ground errors (Global and Regional) towards simulation of four Monsoon Depressions (MDs) over Indian region during SARR pilot phase period.

27-29 July 1999 (Case-1)

17-18 June 1999 (Case-2)

11-12 June 1999 (Case-3)

6-8 August 1999 (Case-4)

For this purpose three numerical experiments are carried with WRF-3DVAR as follows:

CNTL: Without data assimilation using NCEP re- analyses as IC and BC.

BG-3DV: Data assimilation using NCEP global Background Error (BE).

3) BR-3DV: Data assimilation using own calculated BE over SARR region.

The additional observations viz. SYNOP, SHIP, TEMP, BUOYS, PILOT, GEOMV, AIREP etc. are used to improve the model initial condition derived from coarse resolution large scale global analysis.

slide39

b)

a)

c)

Mean RMSE from BR-3DV and BG-3DV of O-A for a) U (m/s), b) V (m/s) and c) T (K).

slide40

BG-3DV ANA

NCEP ANA

BR-3DV ANA

OBS: 21.0/89.0

CNTL:21.8/89.8

BG-3DV:21.6/88.8

BR-3DV:20.8/89.5

Case-2

OBS:18.5/86.0

CNTL:18.5/87.0

BG-3DV:18.9/87.1

BR-3DV:19.2/86.5

BG-3DV ANA

BR-3DV ANA

NCEP ANA

Case-1

Model Initial time wind fields at 850 hPa and MSLP

slide41

Case-1

Case-2

slide42

Case-3

Case-4

slide43

Spatial RMSE (mm) and Correlation Co-efficient (CC) of rainfall over the area (Lat=150-250N; Lon=750-900E) for all cases.

slide47

Temperature (oC) at 850 hPa

GTS+Rad

GTS

Diff. (Rad-GTS)

slide48

Wind (m/s) at 850 hPa

GTS+Rad

GTS

Diff. (Rad-GTS)

slide49

GTS+Rad

GTS

Diff. (Rad-GTS)

Wind (m/s) at 500 hPa

slide51

Rainfall Climatology

These are accumulated 6-hrly Rainfall from the models used for Reanalysis. Every 6-hour, observed data are inserted into the data Assimilation systems, and analyses are carried out. Assumption is that models are good enough for at least 6 hour.

slide52

These studies show there are large uncertainties in the Global Reanalysis data over our Region.

Model Resolution? Data Quality/Quantity?

We need to carry out a Systematic Regional Reanalysis for our Region to have a consistent Hydro-climate dataset.

The Global reanalysis data are utilized for studying climate change and to develop several Application models.

Therefore, we should provide the users with a good quality data set for our Region.

slide53

a single u-wind observation 1 m/s

a single Temperature observation 10K

Global BE

Global BE

Reg. BE

Reg. BE

  • A large part of tropical forecast errors can be represented by equatorial waves.
  • These modes effectively reduce the mass/wind coupling at the equator.
  • Daley (1996) has noted that equatorial error covariance is weaker than higher latitude and similar to that obtained by equatorial beta plane theory.
  • By suppressing the erroneous tropical wind-height coupling, Daley did not find the covariance pattern to the south of central latitude in the tropical domain.
  • In our study, we find that for the BE statistics, the effect of a single wind observation is consistent with theoretically derived wind correlations for non-divergent flow.

Response of the Analysis Increments to