TRMM 3 B 43 RAIN DATA INFORMATION IN DETERMINING LONG WET AND DRY PERIODS IN FARMING BUSINESS IN MOONSON AREA

Based on the observation towards climate station in several agriculture production centers, there is an increase temperature. Temperature rise due to greenhouse effect is very clearly visible, e.g., in Banjarbaru Indonesian Agency of Meteorological, Climatology, and Geophysics (BMKG), misal di stasiun BMKG Banjarbaru, Banjarmasin Sei Tabuk Special Farm Meteorology Station (SMPK), and South Kalimantan Kotabaru BMKG. This temperature rise impacted to plant’s respiration increase that led to the reduction of photosynthesis result. Adaptation strategy with plants water balance analysis to determine the correct planting time and surplus period and water deficit, in various growth phases, is one of water permanent strategic measures to know water suffiency in the field. Material used in this research is TRMM from 3B43 type in the form of grid with monthly temporal resolution and spatial resolution 0.25 x 0.25 with data from 1998 – 2015 period. Data format in the form of binary from ftp://disc2.nascom.nasa.gov/data/TRMM/Gridded/3B43_V7. Reanalysis surface temperature data is grid data from European Centre for Medium-Range Weather Forecasts (ECMWF) from 1998 -2015 period in netcdf format. Water balance analysis used Thornthwaite and Mather (1957) method. Water balance analysis shown groundwater in sufficient category (>60%) happens during November – July period, meanwhile water surplus happens during December – June period. Whereas during August – October period is in less period (<40%). This information can be used in the formulation of one season planting pattern both in wet or dry field.

Since 1980s, it is predicted that the global warming has become reality, like what happened to several research results related directly with global and local climate change or climate aberrations.Based on the observation towards severa climate stations in several agriculture centers, it shows that there is temperature rise.Temperature rise due to greenhouse effect is very clearly visible, e.g., in Banjarbaru BMKG, Banjarmasin Sei Tabuk SMPK, and South Kalimantan Kotabaru BMKG.This temperature rise resulted in the increase of plant's respiration that led to photosynthesis result reduction.
Yonny et al. (1999) who stated that the most important impact of climate change is not in gradual warming but instead in the occurance of extreme, e.g., long drought, thunder storm, flood, or landslide with rising frequency and magnitude.The meteorology researchers in CNRM believe that the rising rainfall quantity is the impact of temperature rise that will trigger water loss in the form of evaporation.
Anticipative measure towards climate change and its impact, analysis towards climate parameter in various observation scales must be improved, especially the one related with the ability of weather forecast.The ability upgrade for accourate weather forecast can be conducted up to the poured water volume and avalaibility and storing in ground for certain length of countable time.Therefore correct planting time can be predicted to anticipate extreme climate change, and able to give information or early warning to farmer communities on drought and flood.If rain characteristics or rainfall in certain place in the future is unknown, then the conducted analysis can only be rain evaluation.
Technology development in remote sensing, e.g., satellite and radar, rainfall measuring conducted by that technology until enabling it for rainfall observation in large areas even area that unreachable by conventional equipment.The advantages of remote sensing should be utilized further to learn weather and climate in an area for the interest of water resource management and it's utilization for society welfare (Syaifullah, 2014).Especially for tropical area, at the moment there is remote sensing equipment that able to conduct rainfall measurement mission in tropical area by Tropical Rainfall Measurement Mission (TRMM) satellite.TRRM satellite can measure rainfall intensity from three hours, daily, to monthly scale.
Climate information is highly needed in disaster mitigation as a reference in policy making.Climate information advantages in agriculture are the avalaibility of ground water for plants.Based on the capability to conduct climate analysis both in macro or micro scale able to generate product that can be used to support prospective farming and highly competitive farming, e.g., through plants water balance analysis to determine the correct planting time and water surplus and deficit period in various growth phase.
Based on the explained background, the formulation of the research problem is how to utilize TRMM satellite for agroclimate zonation based on water balance analysis?The scope of problem are (1) Research study area is South Kalimantan, (2) TRMM Satellite data used is TRMM 3b43 data which is monthly rainfall estimation data with spatial resolution 0.25 x 0.25 degree, and (3) foeld water balance calculation based on Thornthwaite and Mather method.Field Capacity Value (KL) and Permanent Wilting Point (TLP) based on field water balance technical guide from BMKG.This research purpose is to make agroclimate zonation based on field water balance based on TRMM satellite data in South Kalimantan.

METHODS OF RESEARCH
This research is conducted in South Kalimantan Province which is located between 1°20' S -4°10' S and 114°19'E -116°33'E.The research is conducted in six months from March to August 2016.For research location and rain observation post in South Kalimantan can be viewed in detail in Graphic   Where: KAT= ground water level; TLP = permanent wilting point; KL = field capacity and avalaible water.What categorized into three parts are:  Lack, if ground water avalaibility < 40%;  Medium, if ground water avalaibility 40% -60%;  Sufficient, if ground water avalaibility > 60%.
A month experience rainy season rainfall ratio (CH) and ETp of related month has value > 0.75.Dry season happen when the ratio of Deficit (D) and ETp of related month has value > 0.5, meanwhile if the ratio is between 0 -0.5 then it is called transition season or time.
This research procedure flow is presented in Graphic 2.
TRRM satellite monthly data and surface rainfall data series (r) correlation value has good correlation between 0.73 -0.86 with sample overall correlation average value as much as 0.78.Calcullation Result of correlation value and TRRM satellite rainfall and surface rainfall pattern comparison shows that TRMM highly capable to be used as surface rainfall data which is indicated by strong correlation value.r Value in calculation result table can also be viewed in the following graphic: Graphic 3 -TRRM Satellite Data Series and Sei Tabuk SMPK Surface Rainfall Graphic South Kalimantan Area Water Balance Analysis.Based on TRRM 3B43 satellite data and reanalysis temperature data on every set grid spot analysis and field water balance calculation as illustrated by Graphic 4 is conducted.The graphic shows water surplus and deficit grid spot 92 (Sei Tabuk, Banjar Regency 3.33 ºS and 114.68 ºE).Water surplus period happen during five months, i.e., December to April, meanwhile water deficit period happen during six months, i.e., May to September.Since November CH > ETP but water surplus or deficit condition is the same with 0 (zero), this shows that rain water surplus condition is utilized to fill groundwater avalaibility through infiltration and the rest of it released in the surface.Water surplus condition happened if ground water condition has become saturated or reached field capacity.Water surplus period can be optimized for rain fed agriculture and stock water storage in the form of irrigation making or retention basin building for dry season period.In wet field, last month surplus, April started rice seedlings plantation in the field (transplanting).
Field Water Balance in December, January, and February (DJF).Ground water avalaibility level analysis in South Kalimantan in December, January, and February, shows

Graphic 1 -
Research location and rain post in South Kalimantan Research Procedure.The stages in this research are: 1. Determining Input Data.Main data used is monthly rain data from TRMM satellite type 3B43 1998 -2015 data period in the form of grid with spatial 0.25 ° x 0.25 °. /disc2.nascom.nasa.gov/data/TRMM/Gridded/3B43_V7.Supporting data in the form of monthly surface rainfall data 1998 -2015 period from BMKG observation spot in South Kalimantan for TRMM data validation.Monthly surface temperature data from ECMWF reanalysis data in netcdf format 1998 -2015 periods.2. TRMM Satellite Data Extraction.Binary format of TRMM Satellite Data extracted to certain grid (research domain area) by using GRADS software.Next data binary converted into numerical data with Matlab software.Data from conversion result compiled as monthly data serios from 1998 to 2015. 3. TRRM Satellite Rainfall Data and Surface Rainfall Data Validation.TRRM rainfall data and surface rainfall data validation applied correlation analysis (r).Correlation coefficient calculated by using equation (Wilks, 1995):
coefficient between TRMM satellite data with surface observation