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Upper Progo watershed is one of the important agricultural areas in Temanggung Regency, Central Java. This research used the data obtained from Landsat 8 imagery to analyze the agricultural drought risk in the watershed. The hazard was analyzed using multi-temporal data every 16 days (to the Landsat 8’s temporal resolution) during the drought; from May to September 2015 combining the Landsat 8 imagery and the land’s physical condition. An agricultural drought hazard map was then created by summing the hazard class score in every recording time with overlay method. The crop’s vulnerability analyzed using NDVI difference, which indicates the crop’s ability to survive in dry conditions. The crop’s vulnerability was also analyzed every 16 days. A vulnerability map was then created by summing the vulnerability class of every recording time. The assessment of the drought risk was done by multiplying the hazard and the vulnerability scores. The result shows the high and very high classes of agricultural drought risk were located on the west research area which had a high class of hazard and vulnerability. Meanwhile, the moderate, low, and very low classes of agricultural risk were distributed evenly in the center and east area.

Sangiran Site is dominated by rainfed field. Climate parameters, especially rain intensity affects crop patterns. Farmers strongly depend on rain intensity to support productivity thus they need climate-based crop patterns. Sangiran Site is prone to drought hazard since the region has a limited access to groundwater, which is henced by deep well in the region. Drought becomes the main threat to agriculture within Sangiran. This study aims to analyse meteorological drought and crop pattern determination using the SPI and the Oldeman classification respectively. Rainfall data is derived from multi temporal CHIRPS data. A monthly time series with thirty consecutive years (1988–2017) was used to calculate the annual SPI. The annual SPI help to determine crop patterns which is suitable for the region. The results of the study show that angiran Site has monsoonal rainfall with one peak of dry season, and one peak of wet season. Rainfed field is at the highest risk when drought lasts for above four months. Climate based crop patterns with the Oldeman classification indicate that Sangiran Site is classified into type C2 which is adequate for two times palawija crops and one time paddy crops.

Predicted increasing climate variability and change in the future by the Intergovernmental Panel of Climate Change have significant impact towards agricultural sector in Indonesia.Local farm commodities in Indonesia, such as tobacco, are very sensitive to changing climate. This study aims to measure tobacco farmers perspective towards increasing climate riskin Indonesia. Tobacco plantationarea in Temanggung District is selected as a case study since it is well known for its tobacco production, particularly for cigarette.Focus Group Discussion (FGD) towards local tobacco farmers has been conducted to identify how the weather and climate affect the farmer activity, as well as the climate risk due to increasing unpredictability of weather and climate. The result shows that in farmers perspective, it becomes more difficult to manage the farmlands. For the case of tobacco, excessive rainfalls orinsufficient rainfall could cause crop failure. As a result, the tobacco productivity is not as large compared to the past. The farmers also have lower income compared to the past5 years due to lower tobacco quality and quantity.

Madden-Jullian Oscillation (MJO) has a strong influence towards rainfall over The Maritime Continent (MC). Due to possible impacts towards extreme precipitation in this area, a study is required to determine the influence of those processes. This research aims to investigate the influence of MJO on extreme precipitations over Indonesian Maritime Continent. To investigate the influence of those three processes, satellite precipitation data from The Tropical Rainfall Measuring Mission (TRMM) 3B42 product and Real time multivariate MJO (RMM) Index are used. Several extreme indices are calculated to identify magnitude of the extremes by calculating the area coverage of a specific precipitation threshold in each climate zone. Principal component analysis (PCA) is implemented to these indices to reduce large number of data into smaller number of information. Correlation analysis is implemented to the PCA and then matched to the MJO index to identify degree of influence of each process. Comparison of winds and mean sea level pressure data during each phenomenon is conducted to identify the key elements that control the generation of extreme precipitation. The result indicates extreme rain events in Indonesia could be triggered by the MJO, particularly during phase 4-6.

Even though climate change has a multisectoral impact on the agricultural country Indonesia, farming sector experiences the most significant adversity. The concomitant climate uncertainty potentially harms in particular traditional farmers. Current technology is now able to predict weather and climate conditions, and as such, it is useful for farmers as an input to their decision-making process in farmland management. This paper explains the design of a mobile application created by researchers to present information on seasonal weather prediction that fits adaptation measures in the agricultural sector to climate variability. The product can help to enhance the adaptation capacity of communities to erratic climate, particularly farmers and the Office of Agriculture in Temanggung District. Also, the application is expected to provide recommendations for both parties to be able to reduce crop failure and subsequent loss due to climate variability and increase the resilience of farmers to climate change impact, especially the persistent increase and decrease in rainfall each in the rainy and dry season.