BMKG Drought monitoring and mapping in Indonesia under current and future climate conditions Mamenun1, Ronald Vernimmen2 mamenun@bmkg.go.id , mamenun@gmail.com ronald.vernimmen@deltares.nl 1 Meteorological Climatological and Geophysiscal Agency of Indonesia (BMKG) Jl. Angkasa I No. 2 , Jakarta 10720 Indonesia 2 Deltares, P.O.Box 177. 2600 MH, Delft, the Netherlands International workshop on the Digitation of Historical Climate Data, the new SACA&D Database and Climate Analysis in the Asian Region, Citeko 2-5 April 2012

Outline Background Joint Cooperation Program (JCP) Drought Monitoring & Mapping a. Using ground stations b. Using sattellite observations Validation TRMM satellite data withground stations Monthly average Monthly deficit precipitation Next steps Agroclimatic mapping Drought occurance in the future Summary BMKG

Background

Joint Cooperation Programme 21 april 2017 Joint Cooperation Programme Joint Cooperation Program BMKG PusAir KNMI Deltares Component A; General Institutional Development Component B; Collborative Development of Customized and Standardized IWRM tools and Approaches Component C; Supporting the Development of Consistent Datasets Component D; Operational Management Support: Drought and Flood Monitoring and Warning BMKG

Joint Cooperation Programme 21 april 2017 Joint Cooperation Programme JCP Framework BMKG

Building DEWMS Indonesia 21 april 2017 Building DEWMS Indonesia System based on Delft-OMS = Delft-FEWS Open Shell Forecasting System System for operational forecasting (resilience !) Fully configurable by users (Open Interface to models and data) Platform for operational research (Short cycle from research to operations) Java, PostgreSQL/Oracle, Jboss, XML Operating system independent, very scalable Toolbox for development of forecasting systems Highly modular structure – independent modules provide functionality Rapid implementation, scalable & flexible Automatic / manual & stand alone http://publicwiki.deltares.nl/display/FEWSDOC/Home BMKG

Building DEWMS Indonesia 21 april 2017 Building DEWMS Indonesia Concept Delft-OMS import validation transformation / interpolation data hierarchy general adapter export / report administration (data, forecasts) viewing (data, forecasts) archiving … data feeds PI import models export & dessimination BMKG

Building DEWMS Indonesia 21 april 2017 Building DEWMS Indonesia BMKG BMKG

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping A. Using Ground Stations As a pilot, for the Pemali Comal catchment in Central Java, manual ground measurements of rainfall serve as input for calculation of the Standardized Precipitation Index (SPI). BMKG

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping A key feature of the SPI is the flexibility to measure drought at different time scales. Short term droughts of 1 month (SPI-01) defined by specific regional climatology; Agricultural important droughts over 3 to 6 months (SPI-03, SPI-06) resulting in deficits in soil moisture; Longer term droughts (months to years) have impact on surface and groundwater supplies. The severity of a drought can be compared to the average condition for a particular station or region. Values range from 2.00 and above (extremely wet) to -2.00 and less (extremely dry) with near normal conditions ranging from 0.99 to -0.99. SPI value; Drought Category; 2.00 and above Extremely wet 1.50 to 1.99 Very wet 1.00 to 1.49 Moderately wet -0.99 to 0.99 Near Normal -1.00 to -1.49 Moderately dry -1.50 to -1.99 Severely dry -2.00 and less Extremely dry BMKG

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Timeseries for individual stations are calculated BMKG

Drought monitoring & mapping SPI-1 SPI-3 SPI-6 SPI-12 BMKG (April 2007)

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping B. Using Satellite Observations Validation of TRMM 3B42RT (TMPA) satellite data with ground stations on monthly basis Location Rain gauge TRMM Grid Cell Jakarta 10 3 Bogor 4 Bandung 13 Banjarbaru 15 6 East Java Lampung 5 BMKG Source : *Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia, Hydrol. Earth Syst. Sci., 16, 133-146, doi:10.5194/hess-16-133-2012, 2012.

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Correction Factor: TRMMCorr= 3.20 TRMM 0.79 Validation Region Ground Stations TMPA TMPA bias corr P Avg.diff Rel. bias RMSE R2 Jakarta 2010 1865 -145 -7.2 83.8 0.84 1918 -92 -4.6 78.2 Bogor 3056 2944 -112 -3.7 94.9 0.83 2845 -211 -6.9 79.8 Bandung 1723 1936 213 12.3 85.8 1965 242 14.0 71.6 0.86 East Java 2106 1835 -271 -12.8 56.0 0.95 1819 -287 -13.6 49.3 0.96 Banjar Baru 2208 2217 9 0.4 59.6 2303 95 4.3 0.85 Lampung 1946 2191 244 12.6 0.89 2200 254 13.1 63.6 0.90 Annual ground station and TMPA 3B42RT comparison before and after bias correction of TMPA 3B42RT precipitation estimates over the period 2003–2008. BMKG Source : *Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia, Hydrol. Earth Syst. Sci., 16, 133-146, doi:10.5194/hess-16-133-2012, 2012.

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Validation Region Ground Stations TMPA TMPA bias corr P Avg.diff Rel. bias RMSE R2 Jakarta 319 276 -43 -13.5 50.5 0.62 340 21 6.6 51.2 0.65 Bogor 715 539 -176 -24.6 72.9 0.78 604 -111 -15.5 64.1 0.79 Bandung 286 204 -82 -28.7 33.9 0.87 265 -21 -7.3 29.7 East Java 166 75 -91 -55.1 31.8 0.91 114 -52 -31.3 23.6 0.92 Banjar Baru 462 467 5 1.0 36.0 0.85 551 89 19.3 40.2 Lampung 367 255 -121 -30.3 39.9 0.71 336 -8.4 32.2 0.77 Dry season (June–October) ground station and TMPA 3B42RT comparison before and after bias correction of TMPA 3B42RT precipitation estimates over the period 2003–2008. BMKG Source : *Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia, Hydrol. Earth Syst. Sci., 16, 133-146, doi:10.5194/hess-16-133-2012, 2012.

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Validation result BMKG Source : *Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia, Hydrol. Earth Syst. Sci., 16, 133-146, doi:10.5194/hess-16-133-2012, 2012.

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Validation result BMKG

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping TRMM satellite data are used for improved rainfall monitoring and assessing the current drought status. BMKG TRMM 3B42RT satellite precipitation (in mm) over Indonesia on 28 March 2012 19:00 WIB.

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping TRMM 3B42RT satellite precipitation aggregated to monthly totals are bias corrected using the method described in Vernimmen et al. 2012*, based on validation of TRMM 3B42RT with ground stations. BMKG Bias corrected TRMM 3B42RT satellite precipitation (in mm) over Indonesia in March 2012. *Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., and van Dijk, A. I. J. M.: Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia, Hydrol. Earth Syst. Sci., 16, 133-146, doi:10.5194/hess-16-133-2012, 2012.

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Climatology (monthly average) from corrected TRMM3B42RT Monthly average on March 2012. BMKG

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Climatology of corrected monthly TRMM 3B42RT is used to calculate ‘Sifat Hujan’ (monthly rainfall compared to long-term average). BMKG ‘Sifat Hujan’ March 2012. Yellow is normal conditions, orange is drier while green is wetter compared to long-term average

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Monthly precipitation deficit is calculated. For evaporation, currently the CGIAR-PET* monthly dataset multiplied with a fixed crop factor of 0.8 is used. Global CGIAR-PET is a modelled dataset (1 km resolution) using data available from WorldClim Global Climate Data over the period 1950-2000. BMKG Precipitation deficit in March 2012. The precipitation deficit needs to be linked to drought indicators for different agricultural crops *http://www.cgiar-csi.org/data/item/51-global-aridity-and-pet-database

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Deficit precipitation on watershed basin (DAS) for java location BMKG March 2012 *http://www.cgiar-csi.org/data/item/51-global-aridity-and-pet-database

Drought monitoring & mapping 21 april 2017 Drought monitoring & mapping Next Steps : Using the TRMM 3B42RT satellite precipitation the following will also be implemented (in progress): Onset of dry season, defined as 3 consecutive decadal (10-day) periods with precipitation < 50 mm Similarly, onset of the wet season 3. SPI 4. Peat fire forecasting (through running a peatland water budget model; ground water table depth is a better indicator for fire risk then precipitation alone) Other suggestions? ECMWF Seasonal Forecast data will be utilized in the near future as well. BMKG

Agroclimatic mapping using satellite observations Oldeman agroclimatic maps for Indonesia based on corrected monthly TRMM satellite precipitation. Classification based on number of wet and dry months in a year. Wet month = long term average > 200 mm Dry month = long term average < 100 mm Historical maps (1980’s) based on ground stations measurements and used by ‘Pertanian’ (Ministry of Agriculture) Oldeman, L. R., Las, I., and Darwis, S. N.: An agroclimatic map of Sumatra, Contributions, Central Research Institute for Agriculture, Bogor, No. 52, 35 pp., 1979. Oldeman, L. R., Las, I., and Muladi: The agroclimatic maps of Kalimantan, Maluku, Irian Jaya and Bali, West and East Nusa Tenggara, Contributions, Central Research Institute for Agriculture, Bogor, No. 60, 32 pp., 1980. BMKG

Oldeman classification 5 main zones A has more than 9 consecutive wet months. Wetland rice can be cultivated any time of the year. B has 7-9 consecutive wet months. Two wetland rice crops can be cultivated during this period. C has 5-6 consecutive wet months. Two rice crops can be cultivated only, if the first rice crop is planted (or sown) as a dry land crop (so-called gogorancah system). D has 3-4 consecutive wet months. Only one wetland rice crop is generally possible. E has less than 3 consecutive wet months. Without additional water from irrigation, wetland rice is not recommended. BMKG

Oldeman classification These 5 main zones are subdivided based on length of dry season 1 less than 2 dry months. No restrictions are expected with regard to available water. 2 2-3 dry months. Careful planning is needed to grow crops throughout the year. 3 4-6 dry months. A fallow period is part of the rotation system because of water constraints. 4 7-9 dry months. Only one crop can successfully be cultivated. The remainder of the year is too dry. 5 more than 9 consecutive dry months. Areas in this subzone are generally not suitable for any cultivation of arable crops. BMKG

Oldeman map Indonesia Oldeman agroclimatic map based on bias corrected monthly TRMM 3B42RT (left) compared to historical map (right) for Kalimantan BMKG

Oldeman map Indonesia BMKG

Schmidt-Ferguson Climatic map Similarly, the Schmidt-Ferguson (1951) climatic map is generated. Different definition of dry and wet month! dry: < 60 mm (whereas Oldeman < 100 mm) wet: > 100 mm (whereas Oldeman > 200 mm) BMKG

Drought occurrence in the future Precipitation datasets from different Global Circulation Models (GCMs) under different IPCC scenario’s will be processed using Delft-OMS and will be used to generate precipitation change, drought occurance, Oldeman maps, etc. These maps will help create an understanding of future drought vulnerabilities (which areas in Indonesia are vulnerable to climate change?) and will prepare for climate proofing of agricultural and water supply systems. The following GCM’s will be considered: Model Institute Country Acronym BCM2.0 Bjerknes Centre for Climate Research Norway BCCR CGCM3.1 Canadian Centre for Climate modelling and Analysis Canada CCCMA CGCM2.3.2 Meteorological Research Institute Japan CGCM CSIRO-Mk3.0 Commonwealth Scientific and Industrial Research Organisation Australia CSIRO ECHAM5 Max Planck Institute Germany ECHAM ECHO-G Freie Universität Berlin Berlin ECHO GFDLCM 2.0 Geophysical Fluid Dynamics Centre USA GFDL GISS ER Goddard institute for Space Studies GISS IPSL CM4 Institute Pierre Simon Laplace France IPSL MIROC3.2 Center of Climate System Research MIROC NCAR PCMI National Center for Atmospheric Research NCAR HadGEM2 Met Office’s Hadley Centre for Climate Prediction UK HADGEM BMKG

Summary Drought monitoring and mapping both using ground stations and validated sattellite observation has been made as part of the development of Drought Early Warning and Mapping System The average monthly and characteristic of climatology (sifat hujan), deficit rainfall in Indonesia and java’s watershed basin is calculated based on the corrected satellite data The correction sattellite data will be applied on calculating SPI index, decadal precipitation for wet and dry onset, peat fire forecasting, and climate type ECMWF Seasonal Forecast data will be utilized in the near future as well. The climate scenario will be applied to project the drought occurance in the future BMKG

21 april 2017 Thank You BMKG