Bioclimatology

Crop production in the tropics is subject to considerable climate variability caused by the El Niño-Southern Oscillation (ENSO) phenomenon. In Southeast Asia, El Niño causes comparatively dry conditions leading to substantial declines of crop yields with severe consequences for the welfare of local farm households. Using an interdisciplinary modelling approach that combines regression analysis with linear programming (LP) and stochastic simulation and integrates climatic and hydrologic modelling results, the objective of this paper is to assess the impact of El Niño on agricultural incomes of different types of smallholder farmers in Central Sulawesi, Indonesia, and to identify suitable crop management strategies to mitigate the income depressions. We identify five farm classes by cluster analysis. Our LP-model maximizes their cash balance at the end of the period most severely affected by El Niño. Main activities are the cultivation of rice, maize, and cocoa; including water supply as an input factor, external Cobb-Douglas production functions generate output according to level of production intensity and predicted weather patterns. Stochastic simulation accounts for variations in crop yields due to factors not captured by the production functions. Iterative model runs produce probability distributions of the model outcomes for each household class, whereby the downside risk of failing to achieve a specified minimum level of income is particularly insightful. The results can contribute to the formulation of enhanced development policies by illustrating that drought-related crop management recommendations must be tailored to farm households according to their location, farming system, and resource endowment.

The regional climate model REMO has been applied to study rainfall variability in South Sulawesi, Indonesia by comparing model data with observations. During the period 1979 -1993 data correlation was 0.82. A high correlation (more than 0.90) was obtained during El Niño year 1987. At the La Nina year 1988/1989, the results of the REMO simulation under estimates the observation data. The pattern of rainfall variability related to ENSO phenomena was similar to observations. Rainfall during El Niño year is lower than average while it is higher than average during the La Nina year. The simulated and measured lower rainfall as an impact of El Niño and the higher rainfall as an impact of La Nina occur during dry season, whereas the rainfall during the wet season is not altered significantly.

Conversions of natural ecosystems, e.g., from rain forests to managed plantations, result in significant changes in the hydrological cycle including periodic water scarcity. In Indonesia, large areas of forest were lost and extensive oil palm plantations were established over the last decades. We conducted a combined social and environmental study in a region of recent land-use change, the Jambi Province on Sumatra. The objective was to derive complementary lines of arguments to provide balanced insights into environmental perceptions and eco-hydrological processes accompanying land-use change. Interviews with villagers highlighted concerns regarding decreasing water levels in wells during dry periods and increasing fluctuations in stream flow between rainy and dry periods. Periodic water scarcity was found to severely impact livelihoods, which increased social polarization. Sap flux measurements on forest trees and oil palms indicate that oil palm plantations use as much water as forests for transpiration. Eddy covariance analyses of evapotranspiration over oil palm point to substantial additional sources of evaporation in oil palm plantations such as the soil and epiphytes. Stream base flow from a catchment dominated by oil palms was lower than from a catchment dominated by rubber plantations; both showed high peaks after rainfall. An estimate of erosion indicated approximately 30 cm of topsoil loss after forest conversion to both oil palm and rubber plantations. Analyses of climatic variables over the last 20 years and of a standardized precipitation evapotranspiration index for the last century suggested that droughts are recurrent in the area, but have not increased in frequency or intensity. Consequently, we assume that conversions of rain forest ecosystems to oil palm plantations lead to a redistribution of precipitated water by runoff, which leads to the reported periodic water scarcity. Our combined social and environmental approach points to significant and thus far neglected eco-hydrological consequences of oil palm expansion.

Membandingkan data curah hujan bulanan antara hasil pengamatan di permukaan (OBS) dengan data dari pengukuran melalui satelit TRMM dan hasil keluaran model permukaan NOAH telah dilakukan terhadap beberapa lokasi yaitu Medan, Indramayu, Karang Ploso dan Makassar. Data yang dibandingkan adalah curah hujan bulanan dari periode 1998 sampai 2007. Hasil perbandingan ini menunjukan bahwa curah hujan yang diukur melalui satelit maupun hasil keluaran model NOAH memperlihatkan pola curah hujan bulanan yang sesuai dengan pengamatan di permukaan. Namun besarannya setiap lokasi yang dianalisa menunjukan adanya variasi perbedaan curah hujan bulanan. Hal ini terlihat melalui korelasi dari ketiga data set tersebut yang tertingi adalah curah hujan observasi dengan satelit TRMM dilokasi Hasanuddin (Makassar), Karang Ploso dan Medan. Di Indramayu korelasi tertinggi adalah antara data model NOAH dengan TRMM. Di Stasiun Hasanuddin, korelasi tinggi selain pasangan data observasi-TRMM juga pada pasangan data model NOAH dengan observasi. Memperhatikan besarnya korelasi, yaitu antara 0.7-0.9 data curah hujan dari TRMM berpotensi untuk digunakan mengisi data-data pengamatan di darat yang kosong baik secara temporal untuk series data suatu lokasi, maupun mengisi kekosongan spasial untuk suatu wilayah yang kurang memiliki kerapatan pengamatan curah hujan di permukaan.

Simulations of the Indonesian rainfall variability using the Max Planck Institute regional climate model REMO have been performed using three different lateral boundary forcings: Reanalyses from the European Centre for Medium-Range Weather Forecasts (ERA15), the National Centers for Environmental Prediction and National Center for Atmospheric Research (NRA) as well as from ECHAM4 climate model simulation. The result of those simulations are compared to station data. REMO simulations were performed at 0.5°horizontal resolution for the whole archipelago and at 1/6°for Sulawesi Island. In general the REMO model, reproduces the spatial pattern of monthly and seasonal rainfall well over land, but overestimates the rainfall over sea. Superiority of REMO performance over land is due to a high-resolution orography, while over sea, REMO suffers from erroneously low surface fluxes. REMO reproduces variability during El Nin˜o-Southern Oscillations years well but fails to show a good (wet and dry) monsoon contrast. Despite strong influences of the lateral boundary fields, REMO shows a realistic improvement of a local phenomenon over Molucca. Significant improvement for the step from the relatively high global 1.125°to 0.5°resolution is noticeable, but not from 0.5°into 1/6°. The REMO simulation driven by ERA15 has the best quality, followed by NRA and ECHAM4 driven simulations. The quality of ERA15 is the main factor determining the quality of REMO simulations. A predictability study shows small internal variability among ensemble members. However, there are systematic intrinsic climatological errors as shown in the predictability analysis. These intrinsic errors have monthly, seasonal and regional dependencies and the one over Java is significantly large. The intrinsic error study suggests the presence of the spring predictability barrier and a high level of predictability in summer.

This study has analyzed a rainfall estimation using a modified convective stratiform technique (CSTm). Unlike the original convective stratiform technique (CST), which only utilizes infrared (IR) data, CSTm applies not only IR data but also passive microwave (PMW) data. Two major modifications contained in CSTm are: (1) the application of a variability index (VI) method that uses PMW data to perform convective and stratiform separation, and (2) the ability to determine the average extensive coverage of the new areas of each pixel point as a result of the utilization of the PMW data. In this study, rainfall estimation was conducted for 23 points spread over four major islands in Indonesia. The estimation was performed based only on IR and PMW data obtained from coincident observations. For verification, the estimation results were compared with real observations. The main verification action conducted in this study used multi-category contingency tables for 4 categories and this action was supported by the root mean square error (RMSE) method. The verification results of the hourly estimation conducted for 4 days in early November 2011 showed that CSTm can effectively improve the performance quality of CST.

Model iklim regional RegCM4 telah digunakan untuk mempelajari dampak perubahan penggunaan lahan (land use) terhadap variabilitas komponen fluks radiasi dan pameter permukaan. Data penggunaan lahan tahun 2000 dan tahun 2010 digunakan sebagai data permukaan untuk kondisi batas (boundary condition) model. Dua jenis simulasi dijalankan untuk menunjukkan pengaruh perubahan penggunaan lahan pada dua periode tersebut. Simulasi pertama adalah kondisi awal atmosfer tahun 2010 disimulasikan dengan data penggunaan lahan tahun 2010 sebagai kondisi penggunaan lahan terkini, dan simulasi kedua adalah kondisi atmosfer tahun 2010 yang menggunakan data penggunaan lahan tahun 2000. Perbedaan nilai parameter komponen fluks radiasi dan permukaan antara dua simulasi tersebut menunjukkan pengaruh perubahan penggunaan lahan. Hasil perbandingan parameter seperti kandungan air dan suhu tanah menunjukkan adanya pengaruh perubahan jenis penggunaan lahan. Lahan akibat deforestasi yang sudah banyak terbuka seperti pada kondisi tahun 2010 telah mengakibatkan radiasi matahari banyak diserap permukaan dan dirubah menjadi radiasi gelombang panjang yang memanaskan permukaan. Hal ini ditunjukkan dengan tingginya suhu tanah maksimum dan rendahnya kandungan air tanah pada kondisi penggunaan lahan tahun 2010.

Pemilihan prediktor terbaik untuk curah hujan di 15 pos pengamatan di Indramayu telah dilakukan menggunakan metode statistical downscaling. Teknik Singular Value Decomposition (SVD) yang diaplikasikan pada metode ini menggunakan data curah hujan bulanan dari GPCP dan CMAP, serta data tekanan udara, precipitable water, tekanan udara permukaan laut, suhu, dan komponen angin zonal luaran NCEP/NCAR reanalisis sebagai input. Dari metode ini diperoleh hasil bahwa angin zonal adalah prediktor terbaik untuk memprediksi rata-rata curah hujan bulanan di 15 pos pengamatan di Indramayu. Selanjutnya, digunakan data input NCEP/NCAR reanalisis yang telah di-downscale menggunakan CCAM (dynamical downscaling) resolusi ~60 km untuk wilayah Indonesia. Kombinasi dua metode ini (dynamical dan statistical downscaling) terbukti mampu meningkatkan akurasi prediksi curah hujan bulanan dan menurunkan nilai RMSEP di 15 pos pengamatan tersebut.

Tropical lowland rainforests are increasingly threatened by the expansion of agriculture and the extraction of natural resources. In Jambi Province, Indonesia, the interdisciplinary EFForTS project focuses on the ecological and socio-economic dimensions of rainforest conversion to jungle rubber agroforests and monoculture plantations of rubber and oil palm. Our data confirm that rainforest transformation and land use intensification lead to substantial losses in biodiversity and related ecosystem functions, such as decreased above- and below-ground carbon stocks. Owing to rapid step-wise transformation from forests to agroforests to monoculture plantations and renewal of each plantation type every few decades, the converted land use systems are continuously dynamic, thus hampering the adaptation of animal and plant communities. On the other hand, agricultural rainforest transformation systems provide increased income and access to education, especially for migrant smallholders. Jung...

The regional climate model REMO has been applied to study rainfall variability in South Sulawesi, Indonesia by comparing model data with observations. During the period 1979-1993 data correlation was 0.82. A high correlation (more than 0.90) was obtained during El Niño year 1987. At the La Nina year 1988/1989, the results of the REMO simulation under estimates the observation data. The pattern of rainfall variability related to ENSO phenomena was similar to observations. Rainfall during El Niño year is lower than average while it is higher than average during the La Nina year. The simulated and measured lower rainfall as an impact of El Niño and the higher rainfall as an impact of La Nina occur during dry season, whereas the rainfall during the wet season is not altered significantly.

Extreme rainfall zone is needed to determine of vulnerable areas. Unfortunately there is no any study about it until now. The existing zone is only limited to the average rainfall so it is not suitable for extreme rainfall. This study aims to establish the zone of extreme rainfall, especially in West Java. The distribution used is Generalized Extreme Value (GEV) distribution. Zones were built based on the extreme spatial parameter estimation using copula. The zone boundaries were based on contour plot of location parameter estimation using regression splines, thin plate spline and kriging. Spline regression and thin plate spline resulted 19 zones, while kriging resulted 20 zones. Extreme rainfall zones using thin plate spline were the best terms of grouping and image smoothness.

Tropical peatlands in Indonesia have been disturbed over decades and are a source of carbon dioxide (CO) into the atmosphere by peat respiration and peatland fire. With a portable solar spectrometer, we have performed measurements of column-averaged CO dry-air molar mixing ratios, XCO, in Palangka Raya, Indonesia, and quantify the emission dynamics of the peatland with use of the data for weather, fire hotspot, ground water table, local airport operation visibility and weather radar images. Total emission of CO from surface and underground peat fires as well as from peatland ecosystem is evaluated by day-to-day variability of XCO. We found that the peatland fire and the net ecosystem CO exchange contributed with the same order of magnitude to the CO emission during the non-El Niño Southern Oscillation year of July 2014-August 2015.

Deforestation and draining of the peatlands in equatorial SE Asia has greatly increased their flammability, and in September-October 2015 a strong El Niño-related drought led to further drying and to widespread burning across parts of Indonesia, primarily on Kalimantan and Sumatra. These fires resulted in some of the worst sustained outdoor air pollution ever recorded, with atmospheric particulate matter (PM) concentrations exceeding those considered "extremely hazardous to health" by up to an order of magnitude. Here we report unique in situ air quality data and tropical peatland fire emissions factors (EFs) for key carbonaceous trace gases (CO 2 , CH 4 and CO) and PM 2.5 and black carbon (BC) particulates, based on measurements conducted on Kalimantan at the height of the 2015 fires, both at locations of "pure" sub-surface peat burning and spreading vegetation fires atop burning peat. PM 2.5 are the most significant smoke constituent in terms of human health impacts, and we find in situ PM 2.5 emissions factors for pure peat burning to be 17.8 to 22.3 g•kg −1 , and for spreading vegetation fires atop burning peat 44 to 61 g•kg −1 , both far higher than past laboratory burning of tropical peat has suggested. The latter are some of the highest PM 2.5 emissions factors measured worldwide. Using our peatland CO 2 , CH 4 and CO emissions factors (1779 ± 55 g•kg −1 , 238 ± 36 g•kg −1 , and 7.8 ± 2.3 g•kg −1 respectively) alongside in situ measured peat carbon content (610 ± 47 g-C•kg −1) we provide a new 358 Tg (± 30%) fuel consumption estimate for the 2015 Indonesian fires, which is less than that provided by the GFEDv4.1s and GFASv1.2 global fire emissions inventories by 23% and 34% respectively, and which due to our lower EF CH4 produces far less (~3×) methane. However, our mean in situ derived EF PM2.5 for these extreme tropical peatland fires (28 ± 6 g•kg −1) is far higher than current emissions inventories assume, resulting in our total

The extremogram is a method for measuring extreme events dependence in stationary time series, which can be view analog as the autocorrelation function (ACF) of extreme value. This study aims to measure the time dependency of extreme rainfall in West Java using extremogram, and to observe the pattern of time dependencies of extreme rainfall between stations and see the relationship based on distance using cross-extremogram. The data used is monthly rainfall from 30 BMKG rain observation stations with period from 1981 to 2012. In general, the extremogram plot shows that extreme rainfall in West Java has a periodic pattern except for zone 14 and 18. As seen from the peaks of maximum values for monthly rainfall in extremogram, extreme rainfall occurring over a certain period of time, especially in November, December, and January. The periodic pattern is illustrated by the recurrent extremogram peak values for lag-11, lag-12, and lag-13. The plot between the crossextremogram and the distance shows the further distance between the rain stations, the value of extreme rainfall dependency gives a smaller correlation value.

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APN Science Bulletin 8 (1) www.apn-gcr.org/bulletin Future changes in annual precipitation extremes over Southeast Asia under global warming of 2°C This article provides detailed information on projected changes in annual precipitation extremes over Southeast Asia under global warming of 2°C based on the multi-model simulations of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment Southeast Asia (SEACLID/CORDEX-SEA). Four indices of extreme precipitation are considered: annual total precipitation (PRCPTOT), consecutive dry days (CDD), frequency of rainfall exceeding 50 mm day-1 (R50mm), and intensity of extreme precipitation (RX1day). The ensemble mean of 10 simulations showed reasonable performance in simulating observed characteristics of extreme precipitation during the historical period of 1986-2005. The year 2041 was taken as the year when global mean temperature reaches 2°C above pre-industrial levels under unmitigated climate change scenario based on Karmalkar and Bradley (2017). Results indicate that the most prominent changes during the period of 2031-2051 were largely significant. Robust increases in CDD imply impending drier conditions over Indonesia, while increases in RX1day suggest more intense rainfall events over most of Indochina under 2°C global warming scenario. Furthermore, northern Myanmar is projected to experience increases in CDD, R50mm and RX1day, suggesting that the area may face more serious repercussions than other areas in Southeast Asia.

Drought is becoming one of the most important issues for government and policy makers. National food security highly concerned, especially when drought occurred in food production center areas. Climate variability, especially in South Sulawesi as one of the primary national rice production centers is influenced by global climate phenomena such as El Niño Southern Oscillation or ENSO. This phenomenon can lead to drought occurrences. Monitoring of drought potential occurrences in near real-time manner becomes a primary key element to anticipate the drought impact. This study was conducted to determine potential occurrences and the evolution of drought that occurred as a result of the 2015 El Niño event using the Vegetation Health Index (VHI) from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellite products. Composites analysis was performed using weekly Smoothed and Normalized Difference Vegetation Index (or smoothed ND...

The glaciers near Puncak Jaya in Papua, Indonesia, the highest peak between the Himalayas and the Andes, are the last remaining tropical glaciers in the West Pacific Warm Pool (WPWP). Here, we report the recent, rapid retreat of the glaciers near Puncak Jaya by quantifying the loss of ice coverage and reduction of ice thickness over the last 8 y. Photographs and measurements of a 30-m accumulation stake anchored to bedrock on the summit of one of these glaciers document a rapid pace in the loss of ice cover and a ∼5.4-fold increase in the thinning rate, which was augmented by the strong 2015–2016 El Niño. At the current rate of ice loss, these glaciers will likely disappear within the next decade. To further understand the mechanisms driving the observed retreat of these glaciers, 2 ∼32-m-long ice cores to bedrock recovered in mid-2010 are used to reconstruct the tropical Pacific climate variability over approximately the past half-century on a quasi-interannual timescale. The ice c...