Weather & Climate Modeling Activities at MoES Relevant to MAHASRI A.K. Bohra Ministry of Earth Sciences (MoES) National Centre for Medium Range Weather.

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Presentation transcript:

Weather & Climate Modeling Activities at MoES Relevant to MAHASRI A.K. Bohra Ministry of Earth Sciences (MoES) National Centre for Medium Range Weather Forecasting Government of India ______________________________________________________________________________________________________________________________________________ Presentation at MAHASRI Planning Meeting, January 2007, Tokyo, Japan

Ministry of Earth Sciences (MoES) in Government of India has been created recently by bringing all Departments/ Institutions related to Meteorology and Oceanography under one umbrella. Major Institutions for Weather & Climate in MoES are India Meteorological Department (IMD) National Centre for Medium Range Weather Forecasting (NCMRWF) Indian Institute of Tropical Meteorology (IITM) Indian National Centre for Ocean Information Services (INCOIS)

Weather & Climate in MoES IMD- Lead Institute for Meteorological Observations & Public Interface for Weather & Climate Information NCMRWF- Lead Institute for Modeling of Weather & Climate in all scales and for Global & Regional Data Assimilation (NCMWC) IITM- Lead Institute for Research & Process Studies INCOIS- Lead Institute for Ocean Observation, Modeling and Information

Seasonal Global Regional India ACZ DISTRICT Monthly WeeklyCumulative 5 Days LocationSpecific Scientists of the NCMRWF have developed (put together) a Real-Time Global Data Assimilation and Forecast System. The Analysis/Forecast System is regularly upgraded assimilating Research done at NCMRWF and also elsewhere. Scientists also carry out Research on Dynamical & Physical Processes in the Atmosphere to understand and model the Weather & Climate Variability NCMRWF is the only Organization in India where Real-Time Global Data Assimilation and Forecast Systems are Run every day NCMRWF’S Forecasts are available in all spatial scales and are in all timescales (from Day to Seasonal Scales)

Computing Resources at NCMRWF PARAM PADMA 64 Processors IBM P-5 based (0.5 TF) CRAY X1E 64 Processors Vector System (1 TF) CRAY SV1 24-Processors Vector System ( 28 GF) DEC-ALPHA Servers & Workstations SGI ORIGIN Servers & Workstations Procurement Process has begun to have further upgradation

Global Model & Data Assimilation System Data Assimilation at T170/L28 & T80/L18 Resolutions Global Model at T170/L28 & T80/L18 Resolutions (experiments with T254/L64, work related to T382 has begun) Ensemble Prediction at T80/L18 Resolution 8 Member Ensemble (Breed Vector )

Global Data Assimilation System Data Assimilation at T170/L28 & T80/L18 Resolutions (A 3-dimensional Variational Analysis Scheme) (Recently upgraded to T254L64) Issues addressed: Development of schemes to assimilate Satellite data (derived products) Assessment- Impact of New data on Analysis & Forecasts Assessment of Model Bias on Analysis Issue to be addressed: Assimilation of Direct Radiance 4-dimensional Variational Analysis

Land Surface Processes Experiment (LASPEX) NCMRWF is the only organization in India which validates Its model with data from Field Campaigns

Arabian Sea Monsoon Experiment (ARMEX) Major Objectives : Phase I -Offshore-Trough Phase II - Arabian sea Warm pool Period : Phase I : 15 June- 15 August 2002 Phase II : Nov to June 2003 Phase IIa : April-May 2005 ARMEX-Infrastructure deployed Land-based Platforms: RS/RW Network of IMD, Synoptic & Agromet Stations, Atmospheric Fluxes (Towers), AWS, Slow-rising balloons, Wind Profilers Ocean-based Platforms: Ships, Buoys, CTD, XBT, LADCP Moorings, AWS, Slow-rising balloons, Atmospheric Fluxes, Radiation, Underwater Radiation Profiles, Chemistry & Aerosols, Other Platforms Aircrafts, Satellites

Impact of ARMEX observations (active monsoon case) Strengthening of LLJ and monsoon low in ARMEX analysis Armex expControl NCMRWF carries out Reanalysis with special data from Field Campaigns. Also functions as ARMEX Data Centre.

Weather and Climate in the Tropics CONVECTION Dictated by Mesoscale in Nature Intense Convection Processes Leading To SEVERE THUNDERSTORMS & TORNADOES ESSENTIALLY REQUIRES MESO-NETWORK STATIONS Organizes Tropical Synoptic systems; ITCZ, Monsoons and TCs Source:PSRAO

Severe Thunderstorms – Observations & Regional Modeling (STORM) Programme Science Plan To understand the genesis, development and propagation of severe thunderstorms over eastern and north-eastern India. To enhance the knowledge of dynamical and thermo-dynamical structure and the role of micro-physical processes on intensification of these severe storms. To study the behaviors of atmospheric electrification during intensification of these storms and their interaction with cloud microphysical processes. Development/ customization of mesoscale prediction systems with improved forecast skill for prediction of these severe thunderstorms. NCMRWF is a key Partner in STORM Program Source:PSRAO

Synoptic- and Meso-scale Domains of STORM during Pilot Experimental Design 14 April- 31 May 2006 Main Field Experiments ( )

Continental Tropical Convergence Zone (CTCZ) under ICRP during Major Components Boundary Layer Processes Land Surface Processes Hydrological Processes at the River basin scale Cloud-Aerosol Interactive Processes Convection – Direct and Indirect Effects on the Energy and Water cycles Regional and Meso-scale Modeling NCMRWF shall assimilate all data and carry out Modeling works Relevant to CTCZ Source:PSRAO

PRWONAM Observational Programme Meso-Net Experimental Test Region SHAR-KALPAKKAM-BANGALORE B E Bangalore SHAR Kalpakkam Gadanki Chennai Synoptic-Regional- Mesoscale Interactons D C Green Boxes: Mesoscale Black Box : Regional Pilot phase Field Expt: May 2006 October 2006 Main Phase Field Expt: May 2007 NCMRWF- Products of Analysis- Forecast System for Indian region from Global/Meso-scale systems. Satellite derived water vapour channel winds from Meteosat.

Applications in Water Resources SNOWMOD Observed streamflow Simulated streamflow NCMRWF 5 Days Forecast TX, TN, RAIN SNOW COVER AREA BBMB Observed Data TX, TN, RAIN DIS Forecasted streamflow compare Issues to be addressed: Accuracy of meteorological forecasting Delay in data communication Information on snow covered area

NCMRWF OBS-GUESS RMSE for DEC HEIGHT during change to Sippican 850 hPa 500 hPa 200 hPa 100 hPa Delhi 0000UTC

Mesoscale Model & Data Assimilation System Mesoscale Data Assimilation over India - WRF Mesoscale Models Indian Several Domains over India MM5 WRF ETA RSM These Models are run using Initial and Boundary Conditions from NCMRWF Global Models

Very High Resolution Forecast (For prediction of Localized Weather Events) MM5 10 km Rainfall Forecast for Central Himalaya MM5 10 km Rainfall Forecast for West Bengal & Adj. areas

NOAH LSM Experimental runs were made for May 2006 at 1x1 global grid. Enhanced soil moisture across west coast and northeast India with the onset of Indian monsoon on 26 th May 2006 Residue in the simulation of water balance is reasonably low.

Climate Prediction Program of NCMRWF First-time in India: Monsoon Simulation: MONEG Seasonal Simulation using Global Model Real-time Monthly Prediction for Monsoon Long-term Simulations AMIP-type Sensitivity Studies (Seasonal) Aerosol & Climate (Simulation Studies) Real-time Monitoring & Prediction of MJO/ISO Impact of Solar Variability on Climate Simulations Regional Climate Modeling (Dynamic Downscaling) Atmospheric Chemistry and Climate Climate and Crop Yield

Climate Prediction Program of NCMRWF  A new perspective of Continuum of Prediction: blurring distinction between Shorter-term and Longer-term climate predictions.  An Initial-value problem. Knowledge of the current state of Atmosphere, Oceans, Cryosphere, and Land Surface  Climate Models: with the highest possible Resolutions  Ability to relate the Structure, Parametrizations and Performance of models  Practical approach  Unified: Models aimed at different time-scales and phenomena may have large commonality but place emphasis on different aspects of the system.  Models to include Atmospheric Chemistry, Carbon Cycle, evolving Vegetation, etc.  Theoretical basis of Predictability: what Predictions and what Techniques to attempt

SeaPrAS IN-GLM1 Model has been integrated for using Initial conditions from April each year with Observed SST, & Climatological SST. Integrations of other versions of the model are in progress Model Climate compared to Observation ( ) Seasonal Predictions- Modeling Monsoon Variability

Inter-member Spread is quite large- Possibility of making Probabilistic Predictions? Current Skill Level Worldwide for Precipitation Prediction is too Low SeaPrAS

NCMRWF Agro-Advisory Service Network- for 127 Zones Existing- 107 Zones

IMD under the MoES is having a massive Modernization Plan Of its Observing Network

Data Centre Proposal NCMRWF LAN INTERNET Application Servers (MARS) Workstations Servers Ingest Servers Consoles DB Servers Tape Library Storage Archive Web Servers(LAS) HW Firewall Core Switch Firewalls Load Balancer Routers Separate LAN for Archiving Tape Library

NCMRWF proposes to actively participate in the MAHASRI Program NCMRWF shall carry out near Real-time Assimilation to Include Data from MAHASRI (if agreed to by MAHASRI) NCMRWF shall carry out Model simulations to understand the processes of Aerosol Impacts The Centre shall participate in the Modeling of the Ocean- Atmosphere Coupling and Intra-Seasonal Variability Preliminary proposal on Regional Reanalysis (Indian? South Asian?) is being discussed at NCMRWF. (to study hydro-climatic variability, especially during monsoon)

The Centre is carrying out Systematic Hindcast Experiments to clarify predictability of the monsoon. The results of the study Can support the activities of MAHASRI NCMRWF is in the process of implementing a Multi_Model Ensemble Seasonal Prediction System. The Centre shall join the efforts made through MAHASRI. NCMRWF has a plan to implement Web based Data Service and a Data Centre for NWP products. IMD has an ambitious Modernization Plan for its Observing Systems. These data can be made available through GTS or Processed data through NCMRWF