Seasonal variability of Indonesian rainfall in ECHAM4 simulations and in the reanalyses: The role of ENSO

A study on the skill of the atmospheric general circulation model ECHAM version 4 and two reanalyses in simulating the Indonesian rainfall is presented with comparisons to 30 years of rain gauge data. The reanalyses are those performed by the European Centre for Medium-Range Weather Forecasts and of the National Centers for Environmental Predic- tion jointly with National Center for Atmospheric Research. This study investigates the skill of the reanalyses and ECHAM4 with regard to regional, annual and interannual variability of rainfall and its responses to El Ni˜ no-Southern Oscillation (ENSO) events. The study is conducted at two resolutions, T42 and T106. A new regionalization method called the double correlation method is introduced. With this method, the Maritime Continent is divided into three climate regions, the south mon- soonal, the northwest semi-monsoonal and the Molucca anti-monsoonal region. Except over Molucca, the reanalyses and ECHAM4 simulate these annual rainfall patterns quite well. The three regions are used to study the variability of Indonesian rainfall and to mea- sure the skills of the reanalyses and ECHAM4. The skill of rainfall simulations in Indonesia depends on the region, month and season, and the distribution of land and sea. Higher sim- ulation skills are confined to years with ENSO events. Except for the region of northwest Indonesia, the rainfall from June (Molucca) and July (south Indonesia) to November is in- fluenced by ENSO, and it is more sensitive to El Ni˜ no than La Ni˜ na events. The observations show that the Moluccan region is more sensitive to ENSO, receives a longer ENSO impact and receives the earliest ENSO impact in June. The ENSO impact will diminish in Decem- ber. It is found that the reanalyses and the climate model simulate the seasonal variability better than the monthly one. The seasonal skill is the highest in June/July/August, followed by September/October/November, December/January/February and March/April/May. The correlations usually break down in April (for monthly analysis) or in spring (for seasonal analysis). In general the performance of ECHAM4 is poor, but in ENSO sensitive regions and during ENSO events, it is comparable to the reanalyses. The introduction of a higher resolution land-sea mask improves the model performance. Besides rainfall variability, signatures of the ENSO impact, the spring correlation breakdown and annual cycles are better represented by the higher resolution model

Variasi Spasial Dan Temporal Hujan Konvektif Di Pulau Jawa Berdasarkan Citra Satelit(spatial and Temporal Variation of Convective Rain in Java Island Based on Citra Images)

Convective rain is one of precipitation types that usually occur in Indonesia, result by convective process. This convective rain brings heavy rainfall in short period and could reach a higher intensity than common monsoon rain. Convective process may have a variation with time and location. This research have determined spatial and temporal variation of convective rain in Java island by using the black body temperature (TBB) gradient method based on the GMS-6 (MTSAT-1R) images. As a result, the seasonal convective rain generally occurred in similar period i.e. in the morning from 07.00 to 11.00 LT (local time) and in the evening from 18.00 LT until 05.00 LT. The maximum event occurred from 18.00 LT until mid night. There were different locations between the seasonal convective event. In the seasonal convective rain, there were two spatial patterns. In wet season (DJF) and transitional season from wet to dry (MAM) convective rain spread from east to west Java. While in dry season (JJA) and transitional season from dry to wet (SON), convective rain mostly occurred only in west Java

ANALISIS KORELASI CURAH HUJAN DAN SUHU PERMUKAAN LAUT WILAYAH INDONESIA, SERTA IMPLIKASINYA UNTUK PRAKIRAAN CURAH HUJAN (STUDI KASUS KABUPATEN CILACAP) (CORRELATION ANALYSIS OF RAINFALL AND INDONESIA SEA SURFACE TEMPERATURE, AND ITS ...

Significant decrease in rainfall caused extreme climate has significant impact on agriculture sector, especialy food crops production. It is one of reason and push developing of rainfall prediction models as anticipate from extreme climate events. Rainfall prediction models develop base on time series data, and then it has been included anomaly aspect, like rainfall prediction model with Kalman filtering method. One of global parameter that has been used as climate anomaly indicator is sea surface temperature. Some of research indicate, there are relationship between sea surface temperature and rainfall. Relationship between Indonesian rainfall and global sea surface temperature has been known, but its relationship with Indonesian’s sea surface temperature not know yet, especialy for rainfall in smaller area like district. So, therefore the research about relationship between rainfall in distric area and Indonesian’s sea surface temperature and it application for rainfall prediction is needed. Based on Indonesian’s sea surface temperature time series data Januari 1982 until Mei 2006 show there are zona of Indonesian’s sea surface temperature (with temperature more than 27,6 0C) dominan in Januari-Mei and moved with specific pattern. Highest value of spasial correlation beetwen Cilacap’s rainfall and Indonesian’s sea surface temperature is 0,30 until 0,50 with different zona of Indonesian’s sea surface temperature. Highest positive correlation happened in March and July. Negative correlation is -0,30 until -0,70 with highest negative correlation in May and June. Model validation resulted correlation coeffcient 85,73%, fits model 20,74%, r2 73,49%, RMSE 20,5% and standart deviation 37,96. Rainfall prediction Januari-Desember 2007 period indicated rainfall pattern is near same with average rainfall pattern, rainfall less than 100/month. The result of this research indicate Indonesian’s sea surface temperature can be used as indicator rainfall condition in distric area, that means rainfall in district area can be predicted based on Indonesian’s sea surface temperature in zona with highest correlation in every month.------------------------------------------------------------------Penurunan curah hujan yang cukup signifikan akibat iklim ekstrim telah membawa dampak yang cukup signifikan pula pada sektor pertanian, terutama produksi tanaman pangan. Hal ini menjadi salah satu alasan yang mendorong semakin berkembangnya model-model prakiraan hujan sebagai upaya antipasi terhadap kejadian iklim ekstrim. Model prakiraan hujan yang pada awalnya hanya berbasis pada data time series, kini telah berkembang dengan memperhitungkan aspek anomali iklim, seperti model prakiraan hujan dengan metode filter Kalman. Salah satu indikator global yang dapat digunakan sebagai indikator anomali iklim adalah suhu permukaan laut. Dari berbagai hasil penelitian diketahui bahwa suhu permukaan laut ini memiliki keterkaitan dengan kejadian curah hujan. Hubungan curah hujan Indonesia dengan suhu permukaan laut global sudah banyak diketahui, tetapi keterkaitannya dengan suhu permukaan laut wilayah Indonesia belum banyak mendapat perhatian, terutama untuk curah hujan pada cakupan yang lebih sempit seperti kabupaten. Oleh karena itu perlu dilakukan penelitian yang mengkaji hubungan kedua parameter tersebut serta mengaplikasikannya untuk prakiraan curah hujan pada wilayah Kabupaten. Hasil penelitian berdasarkan data suhu permukaan laut wilayah Indonesia rata-rata Januari 1982 hingga Mei 2006 menunjukkan zona dengan suhu lebih dari 27,6 0C yang dominan pada bulan Januari-Mei dan bergerak dengan pola yang cukup jelas. Korelasi spasial antara curah hujan kabupaten Cilacap dengan SPL wilayah Indonesia rata-rata bulan Januari-Desember menunjukkan korelasi positip tertinggi antara 0,30 hingga 0,50 dengan zona SPL yang beragam. Korelasi tertinggi terjadi pada bulan Maret dan Juli. Sedangkan korelasi negatip berkisar antara -0,30 hingga -0,70 dengan korelasi negatip tertinggi pada bulan Mei dan Juni. Validasi model prakiraan hujan menghasilkan nilai koefisien korelasi 85,73%, fits model 20,74%, r2 sebesar 73,49%, RMSE 20,5% dan standar deviasi 37,96. Hasil prakiraan hujan bulanan periode Januari-Desember 2007 mengindikasikan pola curah hujan yang tidak jauh berbeda dengan rata-rata selama 19 tahun (1988-2006) dengan jeluk hujan kurang dari 100 mm/bulan. Hasil penelitian mengindikasikan bahwa SPL wilayah Indonesia dapat digunakan sebagai indikator untuk menunjukkan kondisi curah hujan di suatu wilayah (kabupaten), artinya curah hujan dapat diprediksi berdasarkan perubahan SPL pada zona-zona dengan korelasi yang tertinggi pada setiap bulannya

Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia

The accuracy of three satellite rainfall products (TMPA 3B42RT, CMORPH and PERSIANN) was investigated through comparison with grid cell average ground station rainfall data in Indonesia, with a focus on their ability to detect patterns of low rainfall that may lead to drought conditions. Each of the three products underestimated rainfall in dry season months. The CMORPH and PERSIANN data differed most from ground station data and were also very different from the TMPA 3B42RT data. It proved possible to improve TMPA 3B42RT estimates by applying a single empirical bias correction equation that was uniform in space and time. For the six regions investigated, this reduced the root mean square error for estimates of dry season rainfall totals by a mean 9% (from 44 to 40 mm) and for annual totals by 14% (from 77 to 66 mm). The resulting errors represent 10% and 3% of mean dry season and annual rainfall, respectively. The accuracy of these bias corrected TMPA 3B42RT data is considered adequate for use in real-time drought monitoring in Indonesia. Compared to drought monitoring with only ground stations, this use of satellite-based rainfall estimates offers important advantages in terms of accuracy, spatial coverage, timeliness and cost efficiency

THE DAILY RAINFALL STATISTICAL SHIFT DURING THE HALF CENTURY OVER THE BRANTAS CATCHMENT, EAST JAVA(STATISTIK PERUBAHAN CURAH HUJAN HARIAN SELAMA SETENGAH ABAD DI DAERAH TANGKAPAN BRANTAS, JAWA TIMUR)

A study of long term shift of the daily rainfall over the Brantas catchment East Java was done. Such a study is relatively new for the country due to lack of good quality data and sparsely distributed data all over the region. With a good quality long-term daily rainfall data over the Brantas catchment, we could detect a statistical shift of amount of rainy days, shift between periods and frequency trend changes from weekly, monthly, three-monthly and annually. The study utilized several methods including the probability density function distribution shift, Mann Kendall non parametric trend test and the wavelet analyses. The shift of low amount rainfall occurs from the dry to the wet season. We found distinct influences of orography and ENSO years in our trend tests. Additionally, the result of the Mann Kendall test show that the trend of rainy days increase during the wet season and the second transition period, while decrease during the dry season and first transitional period. Meanwhile the El Nino and La Nina have significant influence toward the dry season and the second transitional period

Aplikasi Metode Curve Number Untuk Mempresentasikan Hubungan Curah Hujan Dan Aliran Permukaan Di DAS Ciliwung Hulu – Jawa Barat

Run off (surface flow) is one of the most important hydrological variable in supporting the activities of water resources development. A reliable prediction method to calculate the amount and rate of runoff from the land surface caused by the rain that falls in a watershed that is not equipped with measuring devices (un gauge watershed) is a verydifficult job and requires a lot of time. The research was conducted in the watershed Ciliwung Hulu, which is an important area in relation to the incidence of flooding in Jakarta. Curve Number (CN) method can be used to predict the amount of runoff from a watershed. This model required input of rainfall; land cover maps; soil type maps,and topography. The maps are processed using Arc View software, so we get the value of CN. In this study, we used of rainfall and discharge data 2007-2009. Based on the analysis of calculation, known that amount of surface flow approaching 50% of rainfall depth. This condition indicates that the Ciliwung Hulu watershed conditions were not ableand proper to absorb of rainfall. The correlation between the results of run-off prediction models using CN with run-off observation was quite good. This indicated that the Curve Number method could be able to represent the relationship of rainfall with surface flow (run off) and also to predict runof

Analisis Pembangunan Rendah Karbon Studi Kasus Propinsi Lampung

The increasing trend of CO2 emission globally, has been creating climate change in some areas in the world. The impact of climate change could cause disaster for human life such as drought and flood, health deseases, etc. Currently many programs and schemes are introduced to reduce CO2 emission. The low carbon development is one of those programs which is the economic development has to take into acount the CO2 emission reduction. This study found 90 % of the CO2 emision came from forestry sector, especially deforestation and fires. The recent CO2 emission was 70,3 MtCO2e in 2005 and estimated 79 MtCO2e in 2020, then finally will be 93,5 MtCO2e. Therefore mitigation actions should be focused on the forestry sector, these are reforestation & afforestation, REDD, mangrove rehabilitation, agroforestry development, and fire protection. These action programs potentially could reduce the CO2 emission as high as 76,8% in 2030

The changing face of major trauma in the UK

Aim Major trauma (MT) has traditionally been viewed as a disease of young men caused by high-energy transfer mechanisms of injury, which has been reflected in the configuration of MT services. With ageing populations in Western societies, it is anticipated that the elderly will comprise an increasing proportion of the MT workload. The aim of this study was to describe changes in the demographics of MT in a developed Western health system over the last 20 years. Methods The Trauma Audit Research Network (TARN) database was interrogated to identify all cases of MT (injury severity score >15) between 1990 and the end of 2013. Age at presentation, gender, mechanism of injury and use of CT were recorded. For convenience, cases were categorised by age groups of 25 years and by common mechanisms of injury. Longitudinal changes each year were recorded. Results Profound changes in the demographics of recorded MT were observed. In 1990, the mean age of MT patients within the TARN database was 36.1, the largest age group suffering MT was 0–24 years (39.3%), the most common causative mechanism was road traffic collision (59.1%), 72.7% were male and 33.6% underwent CT. By 2013, mean age had increased to 53.8 years, the single largest age group was 25–50 years (27.1%), closely followed by those >75 years (26.9%), the most common mechanism was low falls (39.1%), 68.3% were male and 86.8% underwent CT. Conclusions This study suggests that the MT population identified in the UK is becoming more elderly, and the predominant mechanism that precipitates MT is a fall from <2 m. Significant improvements in outcomes from MT may be expected if services targeting the specific needs of the elderly are developed within MT centres