Annual SAC Reviews (2015) [10pt] NUMERICAL ATMOSPHERE … · 2018-09-02 · Lateral Boundary...

Annual SAC Reviews (2015)

NUMERICAL ATMOSPHERE MODELLING

D. BALA SUBRAHAMANYAM

SPACE PHYSICSLABORATORY, V IKRAM SARABHAI SPACE CENTRE

THIRUVANANTHAPURAM - 695 022

http://spl.gov.in/

D. Bala Subrahamanyam (NAM) Annual SAC Reviews (July 2015) 22 July 2015 1 / 23

Annual SAC Reviews (July 2015) Scope of the Presentation

SCOPE OF THE PRESENTATION

Atmospheric Modelling Activities:OPERATIONAL AND RESEARCHMODE APPLICATIONS OF THENWP MODELS

Short-range Weather Predictions in support ofPSLV/GSLV Missions

Migration from the HRM to COSMO ModelComplete Automation of the COSMO Model Simulations

=====================================================

Rainfall Simulations through HRM and COSMOChallenging Tasks (Localized and Isolated Rainfall Events)

=====================================================

Current Status of Ongoing and New ActivitiesCoupling of the FLEXPART with COSMO Model

Large Eddy Simulations: Initiatives with the PALM Model

=====================================================


Annual SAC Reviews (July 2015) COSMO Simulations for PSLV/GSLV Missions

Weather Predictions for PSLV/GSLV Missions

COSMO Simulations in support of PSLV/GSLV Missions

SPL IS ONE OF THE PARTICIPATING INSTITUTIONS IN THE

“I NTER-CENTREWEATHER FORECASTINGEXPERT TEAM”CONSTITUTED BY SDSC, SHARFOR PSLV & GSLV

LAUNCHES SINCECHANDRAYAAN -1 MISSION.

SPL IS ALSO SUPPORTING THERLV-TD PROJECT THROUGH

DOL-WIND BIASING MEASUREMENT STRATEGY OVERSHARAND BAY OF BENGAL.

THIS YEAR, SUPPORT WAS EXTENDED TOPSLV-C26, C27,C28 AND GSLV-MK III (LVM3-X) M ISSIONS.

Mandate of the Expert Team:to forecast formation of low pressure systems in Bay of Bengal concerned to SHAR

clearance for start of countdown activities (T - 72 Hrs)

regular bulletins regarding thunderstorms over SHAR region from T - 5 days

analysis of NWP products from different global models with reference to SHAR






























Annual SAC Reviews (July 2015) Migration from the HRM to COSMO Model

MIGRATION FROM THE HRM TO COSMO MODEL

High-resolutional Regional Model (HRM)⇓

Consortium for Small-scale Modelling (COSMO)

BACKGROUND: GRIdded Binary (GRIB) Data Format

The first version (GRIB1) was introduced by WMO in 1985

This is a CBS (Commission for Basic Systems)/WMO Data Format

Used world-wide for the storage and exchange of weather products

GRIB1 Data Format: A Few Shortcomings and Disadvantages:

(i) Compression of GRIB1 Data (Was not advantageous)

(ii) No convention for missing data

(iii) No support for smaller time-steps

(iv) Inclusion of new products in the GRIB1 format (EnsembleForecast) ???



MIGRATION FROM THE HRM TO COSMO MODEL ...

High-resolutional Regional Model (HRM)⇓

Consortium for Small-scale Modelling (COSMO)

INTRODUCTION OF THE GRIB2 DATA FORMAT

In 2003, WMO introduced a NEW edition of GRIB, namely: GRIB2

The GRIB2 data format offered inclusion of infinite no. of newproducts

The GRIB2 data also offered excellent compressibility:

Compressibility of GRIB1 Data (TAR + GZ) = 50%∗

Compressibility of GRIB2 Data (TAR + GZ) = 88%∗

∗[Based on GME global model analyes data compression]

WITH THE CHANGING TRENDS WORLDWIDE, THE GERMAN WEATHER SERVICE (DWD)

ALSO ADOPTED THEGRIB2 FORMAT FOR THEIR GLOBAL MODELS(GME AND ICON).




GLOBAL SCENARIO: Grid-Resolution of Global Atmospheric Mo dels

Source: IPCC Fourth Assessment Report (2007)

WITH THE AVAILABILITY OF VERY FINE

RESOLUTION SPATIAL OBSERVATIONS,

TOGETHER WITH A DENSE IN-SITU

OBSERVATIONAL NETWORK, IN

CONJUNCTION WITH HIGH-PERFORMANCE

COMPUTING SYSTEMS, ALL THE THE

GENERAL CIRCULATION MODELS (GCMS)

ARE FORCED TO REFINE THEIR GRID

RESOLUTIONS.




Future Scenario in Atmospheric Modelling ???[PRESENTLY(2015), DWDIS PROVIDING THE GLOBAL DATA @ 0.20°RESOLUTION!!!]




Inevitable Migration from the HRM to COSMO Model

⇓

Migration of Global Models from GRIB1 to GRIB2 data format

Compatibility issues for HRM in handling the GRIB2 data

Migration from hydrostatic to non-hydrostatic models

A new version of HRM ??? (A temporary solution for few more years)

SINCE JUNE 2014, SPLHAS COMPLETELY MIGRATED FROM THEHRM TO COSMO

MODEL, AND NOW THE SHORT-RANGE WEATHER PREDICTIONS IN SUPPORT OF THE

PSLV/GSLVMISSIONS ARE CARRIED OUT THROUGHCOSMOMODEL SIMULATIONS.


Annual SAC Reviews (July 2015) Comparison of HRM and COSMO Models

COMPARISON OF HRM AND COSMO MODELS

HRM and COSMO Models: Brief Technical Details

HRM COSMO

Model Type Hydrostatic Non-Hydrostatic

Prediction ofw diagnostic approach direct approach

Grid-type Arakawa-C type Arakawa-C type

Vertical Grids Hybrid vertical coordinates Lorentz vertical grid staggering

Time Integration Split semi-implicit Second-order leapfrog HE-VI

Initial Conditions GME, ICON GME, ICON, ECMWF, COSMO

Lateral Boundary Conditions Davies (1976) Davies (1976)

Radiation Ritter and Geleyn (1992) Ritter and Geleyn (1992)

Convection Tiedtke (1989) OR Tiedtke (1989) ORBechtold (2001) Bechtold (2001)

Surface-Layer Processes Louis (1979) Louis (1979) ORTKE-Based Scheme

Vertical Diffusion (ABL) Mellor and Yamada (1974) Mellor and Yamada (1974) OR1-D TKE-Based Diagnostic Closure


Annual SAC Reviews (July 2015) Comparison of HRM and COSMO Models

COMPARISON OF HRM AND COSMO MODELS

Operational Mode Applications of the COSMO Model

THE NECESSITY IS MOTHER OFINVENTION

For a given spatial domain (15°x 15°x 60-verical layers), generation of+48 hrs forecast (@ 0.10 degree grid resolution), the HRM wasconsuming about 50 minutes on Parallel Computing Facility.

For a similar configuration, the COSMO model took about 3+ hrs.

In addition to the above mentioned timings, manual intervention forentering the appropriate dates, and proper time-stamping in the modeloutput also required adequate attention.

⇓

Automation of the COSMO Model Runs


Annual SAC Reviews (July 2015) Automation of the COSMO Model Runs

AUTOMATION OF THE COSMO MODEL RUNS

Automatic Scheduling of the COSMO-related Important Processes

Auto-shutdown and Auto-reboot at pre-assigned timings

Automatic file transfer of GME (ICON) model data from Surya server to SPL server

Unpacking the GME (ICON) data and identification of analysestime stamp

Generation of GME (ICON) to COSMO conversion control files

Generation of COSMO model runs control files

Self-execution of COSMO binaries

Generation of basic necessary plots with relevant time-stamps

Self-archival of the whole database in appropriate folder

⇓

DIRECTLY EXAMINE THE OUTPUT FIELDS IN PDF FORMATRoutine Forecast fields (based on 00 UTC) become ready by 0600UTC


Annual SAC Reviews (July 2015) Automation of the COSMO Model Runs

Automated COSMO Forecast Fields: A Typical Sample


Annual SAC Reviews (July 2015) Rainfall Simulations: Model vs. Observations

Rainfall Simulations from HRM and COSMO Models

Performance of HRM and COSMO Models on June 23, 2014A TYPICAL CASE STUDY ON “I SOLATED RAINFALL EVENTS OVERWESTERNCOAST OF INDIA”

Category : Rainfall (in mm)

No Rain : 0.0Very light Rain : 0.1 - 2.4Light Rain : 2.5 - 7.5Moderate Rain : 7.6 - 35.5Rather Heavy : 35.6 - 64.4Heavy Rain : 64.5 - 124.4Very Heavy Rain : 124.5 - 244.4Extremely Heavy Rain : > 244.5Exceptionally Heavy Rain : > 1200.0

Is HRM over-estimating ? Or COSMO under-estimating ? Or ????



Rainfall Simulations: Model Vs. Observations

Space-based Observations of Rainfall on 22-June-2014 (INSAT-3D SND)TOTAL PRECIPITABLE WATER VAPOUR (IN MM ) FOR 0600AND 1200 UTC

Image Courtesy: India Meteorology Department



Rainfall Simulations: Model Vs. Observations ...

Space-based Observations of Rainfall on 22-June-2014 (INSAT-3D SND)TOTAL PRECIPITABLE WATER VAPOUR (IN MM ) FOR 1800AND 0000 UTC (23-JUNE-2014)

Image Courtesy: India Meteorology Department




Space-based Observations of Rainfall on 23-June-2014 (INSAT-3D)DAILY ACCUMULATED RAINFALL (IN MM ) OBTAINED FROM INSAT-3D

Image Courtesy: INSAT Meteorological Data Processing System (IMDPS, MOSDAC)




Space-based Observations of Rainfall on 22-June-2014 (KALPANA-1)THREE-HOURLY ACCUMULATED RAINFALL (IN MM ) OBTAINED FROM KALPANA-1

Image Courtesy: http://www.mosdac.gov.in/




Space-based Observations of Rainfall on 22-June-2014 (KALPANA-1)THREE-HOURLY ACCUMULATED RAINFALL (IN MM ) OBTAINED FROM KALPANA-1

Image Courtesy: http://www.mosdac.gov.in/


Annual SAC Reviews (July 2015) COSMO Simulations during PSLV-C28 (DMC3) Mission

COSMO Simulations during PSLV-C28 (DMC3) Mission

ONE OF THE MOST CLASSICAL CASES OF “FALSETHUNDERSTORM” ALERT

DWR Images Courtesy: Chennai IMD




ONE OF THE MOST CLASSICAL CASES OF “FALSETHUNDERSTORM” ALERT

COSMO Alerts (48 h before; 40 h before; 18 h before)




Time-Series of Rainfall over SHAR (COSMO Model Simulations)




Important Inferences from the HRM and COSMO Simulations

HYPOTHESIS:

Similarity in the HRM and COSMO Model Runs [ (i) Initialised from the same GMEanalyses, and the lateral boundary conditions extracted from GME forecast fields; (ii)Similar model configurations were maintained for both the simulations. ]

EXAMINATION OF MODEL SIMULATIONS:

The INSAT-3D and KALPANA-1 observations clearly indicatedisolated rainfall(moderate) over the western coastline of the India, while the southern peninsularemained mostly dry. The HRM simulations had a tendency to create wide-spreadrainfall, whereas the COSMO could discriminate isolated spots of rainfall efficient zones.

SCIENTIFIC INFERENCES:

Despite the “Mass Flux Convection Parametrization Scheme”indicating favourableconditions for the light to moderate rainfall, the non-hydrostatic nature of COSMO (wbeing treated directly) allowed the discrimination of rainfall efficient zones from therainfall deficient zones.



“Some Ongoing Activities” & “New Initiatives”

Present Status of “Short-term” & “Long-term” Future Projec tions

COSMO Model Related Studies:

Ingestion of coastal ABL heights into COSMO modelRedefining the mixing length scale in ABL parametrization ofCOSMOTesting of new “Tropical” setup for rainfall simulations

Large Eddy Simulations:

Operationalisation of Parallelized Large Eddy Simulation(PALM) ModelFeasibility of COSMO Model runs for LES configuration

CO2 Fluxes over the Indian Region:

Installation of FLEXPART model and its operationalisationOffline coupling of the FLEXPART with COSMO Model


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Annual SAC Reviews (2015) [10pt] NUMERICAL ATMOSPHERE … · 2018-09-02 · Lateral Boundary...

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