Utilisation of MT-Satellite observations at NCMRWF : Plan & prospects A.K. Bohra, M. Das Gupta, John P. Geogre, R. Ashrit & A.K. Mitra National Centre for Medium Range Weather Forecasting NOIDA, India

Objectives of NCMRWF  Development of operational Global and regional scale NWP models for forecasting weather in medium range(3-10 days) time scale taking full advantage of existing and concurrent developments in this field  To inform and guide the farmers in advance to undertake various farming activities based on the expected weather  Research on various aspects of NWP A near real time numerical weather prediction (NWP) suite is being run operationally at NCMRWF since 1st June 1994 to issue medium range weather forecasts over Indian subcontinent

NWP NWP Models at NCMRWF Global Models T-80 [ 150 km x 150km resolution] T-170 [ 75kmx75km resolution] Meso-scale Models MM5 [Nested 90, 30, 10 km resolution] Eta [ 48km resolution] RSM [50km] Ocean Wave Model WAVEWATCH-III at 1 deg.for global ocean

Forecast to different Sectors NCMRWF Forecast Agriculture Adventure Tourism Power Water Resources Armed Forces Shipping & Fisheries Space

To make a accurate forecast it is important to know the current weather Global observations are continuously downloaded through GTS and ftp access and fed into the assimilation system about 10 6 observations are processed in each assimilation cycle Global Satellite Obsn. Global Aircraft Obsn.

DATA PROCESSING & QUALITY CONTROL DATA RECEPTION & DECODING at NCMRWF(1/2 hrly) RTH NEW DELHI FTP Satellite Data MSMR, SSMI etc. Ships & Buoys Surface observations AircraftRS/RW Satellite data Pilot Balloon PREVIOUS (6HR.) ANALYSIS ANALYSIS SURFACE BOUNDARY CONDITIONS DATA PROCESSING AND QUALITY CONTROL PREVIOUS (6 HOURS) ANALYSIS SSI ANALYSIS T80 GLOBAL SPECTRAL FORECAST MODEL SURFACE BOUNDARY CONDITIONS MEDIUM RANGE WEATHER FORECAST BASED ON 00 UTC ANALYSIS GTS DATA Global Data assimilation System (GDAS) operational at NCMWRF 6-hrly intermittent 3D-VAR analysis (SSI) conventional and satellite obsn. Repeated four times a day 00,06,12 & 18 UTC Satellite data assimilated at NCMRWF Classical CMVs from GOES, METEOSAT,GMS and Kalpana High resolution winds from METEOSAT-5(63ºE) ATOVS (120km) temperature and total precipitable water(TPW) (500km TOVS) SSM/I, (MSMR) wind speed QSCAT, (ERS-2) winds

Satellite data utilisation in data assimilation – forecast system Some of the recent studies carried out at NCMRWF Impact of satellite derived temperature profile data on medium range forecasts (TOVS NOAA-12/14 coarse resolution km) ’Global Ocean Atmosphere Systems, 1998’ TOVS temperature profile data at its full resolution ( With IMD / HRPT -85 Km ) Meteorology & Atmos. Physics, 1999’ Improve the quality of INSAT derived CMVs Height re- assignment by employing guess fields from global forecast model ( With IMD ) ‘Meteorology & Atmos. Physics, 2002’ The divergent part of the wind was improved by using INSAT OLR information as input in analysis system( with IITM ) ‘Meteorology & Atmospheric Physics, 1997’ Derive synthetic moisture profiles from INSAT IR data JMA and BMRC type technique ‘Int. J of Remote Sensing, 2002’ / ‘Atmosfera, 2001’

Assimilation of MSMR data in NCMRWF global data assimilation system (with IIT-D), Meteorology and Atmospheric Physics, 2002 Impact of ATOVS temperature and moisture profiles, Mausam, 2003 Impact of ERS-2 scatterometer winds ‘Mausam, 2002 Impact of High Density Atmospheric Motion Vectors, 6 th International Winds Workshop, 2002 Analyses of Orissa Super Cyclone using TRMM (TMI), DMSP (SSM/I) and OceanSat-I (MSMR) Derived Data, The Global Atmosphere and Ocean System, 2003 Observed daily large-scale rainfall patterns during BOBMEX-99, Earth & Planetary Science, 2003 Daily Rainfall for Indian Monsoon Region from Merged satellite and Rain-Guage Values: Large-Scale Analysis from Real Time data, Journal of Hydrometeorology, 2003

Impact studies with SSM/I and MSMR wind speed & TPW

Impact of SSM/I wind speed and TPW

Comparison of SSM/I and MSMR wind speed with Buoy obsn.

Experiments with TRMM/TMI Data Orissa Super Cyclone – October 1999 TPWC, Wind Speed from:- TMI / TRMM SSM/I MSMR METEOSAT - 5

20 – 31 Oct 1999 / TPWC & Wind Exp1: TRMM 25 km Exp2: TRMM averaged to 75 km Exp3: SSM/I averaged to 75 km EXP4: MSMR 75 km Best simulated track is from the analyses with TRMM (25 km) and METEOSAT-5 (not shown) However, forecast quality was still poor even in T170 version and with 25 km TRMM data Vertical structure is important; ATOVS type data might improve Simulated track of super-cyclone based on 00UTC 24 Oct 2005

Experiments with ATOVS (NOAA 15 &16) temperate and moisture (global model)

Temperature at 850 hPa NOAA 15 & 16 00UTC 29 Sept 2001

Specific Humidity at 850 hPa NOAA 15 & 16 00UTC 29 Sept 2001

TPWC (mm) NOAA 15&16 00UTC TPWC (mm) SSM/I 00UTC SSM/I obsn. more moist over Tropics

(mm) as expected analyses with SSM/I are more moist than analyses with ATOVS

SSM/I - more rainfall over Ocean ATOVS - rainfall reduced over Ocean more over Indian land with ATOVS with SSM/I OBS D1-FCST Total rainfall Sept. 2001

Experiments with ATOVS (NOAA 15 &16) temperate and moisture (Mesoscale model MM5 3DVAR)

without ATOVSwith ATOVS Analyses of a monsoon low with & without ATOVS (temp. & moisture) 850 hPa height & wind 00UTC 27 th, 28 th & 29 th July 2004 In analyses with ATOVS, low is better organized, with centre of circulation coinciding with contour low

without ATOVSwith ATOVS 24hr., 48hr. 72 hr. prediction based on 00UTC 26 th July 2004 with & without ATOVS (temp. & moisture) 850 hPa height & wind system is predicted more intense, in with ATOVS run

Validation of radiative fluxes

Validation of Net Radiatve Fluxes using LASPEX data set over Anand Summer Monsoon Post-MonsoonWinter T80 simulation of net radiative fluxes matches well with observation in clear sky condition

Recent Heavy Rainfall Episode over West Coast of India

With NCMRWF analysis With UKMO analysis Unprecedented Heavy Rainfall(~95cm) over Mumbai on 26 th July 2005, very localized event over a region 20-30kms NCMRWF’s operational models could not predict such high rainfall with initial condition from its 3D-VAR assimilation system (without radiance) Same event is better simulated with initial condition generated by 4DVAR (with radinace) assimliatiion (obtained from UKMO)

Studies related with different physical parameterization schemes conducted at NCMRWF  Convection : KUO/RAS/SAS  PBL : Local / Non-Local closure  Radiation: GFDL / Harshavardhan

Satellite – rain gauge merged rainfall analysis (real time product for model validation)

Satellite – rain gauge merged product (NCMRWF) CMAP (XIE-ARKIN) Rainfall Total rainfall Sept 2001 heavy rainfall over peninsular India and over Nepal and adjoining NE India is captured better in NCMRWF product

Comparison of Analysed rainfall amount June 2001 Northern part of west coast Southern part of west coast East coast & north BOB Central India & monsoon trough reg. Rainfall in cm (OBS)

Future Scenario Developments of NWP models (global) – trends Increased horizontal and vertical resolution Horizontal resolution: 8-15 km (2015), 3-5 km (2025) Vertical resolution: Boundary layer: 70m (2015), 40m (2025) Free atmosphere: 300m (2015), 200m (2025) Stratosphere: 500m (2015), 200m (2025) Global NWP is likely to cover FC+24 onwards Similar to what meso-scale models are now  An accurate description of the hydrological cycle is vital for short/medium range forecasting (NWP models)

Megha-tropique satellite is proposed to carry three scientific instruments: Multi-frequency Microwave Scanning Radiometer, MADRAS rain above the oceans & surface winds, integrated water vapour content, liquid water in clouds, convective rain Multi-channel Microwave Instrument, SAPHIR vertical humidity profile in the atmosphere Multi-channel instrument, SCARAB earth's radiation budget Expected observations from Megha-tropique satellite

Possible Use of Megha-Tropiques data at NCMRWF  Input to the NWP models  Model validation 1. Input to the NCMRWF assimilation- forecast system:- Ocean surface wind, integrated water vapor and rain (MADRAS) Water vapor profiles in the cloud free troposphere (SAPHIR). Use of these parameters in assimilation system may improve the distribution of the water vapor over the tropical oceans in analysis, which may ultimately improve the convection and other precipitation processes in the model.

Cloud liquid water and ice (MADRAS) can be used an input to the model, which may improve the computation of cloud optical properties (input to the radiation scheme) in the model and hence the radiation fluxes and heating/cooling rates. 2. Model validation Shortwave and Longwave radiation (ScaRaB) measurements are useful for the validation of the radiation scheme over the tropical areas. The radiative fluxes observation in this mission is a valuable data to validate the model generated cloud radiative forcing. Deep convection areas, cloud liquid water, precipitation, cloud top ice, anvil areas and humidity profiles (SAPHIR, MADRAS) useful for the validation of the parameterization of convection and other precipitation processes in the model

Proposed studies using observations from Megha-Tropiques satellite

(1) Data Assimilation  direct radiance assimilation  assimilation of surface wind, TPW  rainfall assimilation (nudging / 4DVAR)  observing system experiments

(2)Convection-Radiation Study  initiation and life cycle of convective systems over the Asian Monsoon Region has to be studied using Mesoscale/Cloud Resolving Model (MCRM) and data from Megha-Tropiques  preparation of cloud climatology for Asian Monsoon Regime  ScaRab radiation data will be used for comparing and ultimately improving radiation budget of numerical models

(3)Large scale & intra-seasonal monsoon variability  Hadley Walker circulations, Water vapour transport  Feedbacks on radiation  Madden-Julian oscillations  Onset, break and variations of monsoons  Ocean-Atmosphere interactions

(4) Local retrieval  retrieval through RT models using MW & SCARAB  Use NCMRWF’s meso-scale NWP outputs  Improved temp., mositure and rainfall

(5) Rainfall analysis  calibration of IR rainfall with MW rainfall  technique for blending of rainfall data from Megha-Tropiques, TRMM, SSM/I and other geo-stationary satellite to  generation of grided rainfall dataset at different required (synoptic and meso scales) resolution