Monthly Rainfall Research Articles

Konsistensi Sistem Prakiraan Iklim Musiman Menggunakan Indikator ENSO di Daerah Tipe Iklim D3 dan D4 Kabupaten Lombok Tengah

The purpose of this study was to determine the consistency of seasonal climate forecasts using the ENSO phenomenon. The ENSO indicator categorized with El Nini, Neutral and La Nina were coorelated to rainfall categorized with Below Normal, normal and above normal. The research was carried out in the D3 dan D4 type of climate in ccentral Lombok regency. The method used in this research is descriptive method, which is a method aimed at solving problems by collecting data, compiling, analyzing, interpreting data, and drawing conclusions. This research was conducted in Central Lombok in climate types D3 and D4 covering the areas of Kopang, Mantang, Praya, Puyung, Pringgarata, Penujak, Mujur, Pujut, and Janapria. Using monthly rainfall data for ± 50 years from 1970-2019. Rainfall data were taken at Kopang, Mantang, Praya, Puyung, Pringgarata stations for type D3 and Penujak, Mujur, Pujut, and Janapriafor type D4. SOI data can be accessed at http://www.bom.gov.au/climate/current/soi2.shtml. The results showed that from 1970-2019 (50 years) there was a consistent value in all areas that were predicted, namely above 50% and inconsistency below 50%. Consistency describes how accurate the results of the forecast are. If the percentage of the consistency value is above 50%, it means that it is better to predict using the forecasting method by looking for consistency than using the average. Therefore, if you use a forecasting system, if an El Nino phenomenon occurs there will be a shortage of water, you can adjust the planting time, prepare irrigation water first, reduce the planting area, and delay the planting time first.Keywords: Climate Variations, SOI, Rainfall, Climate D3 and D4

Climate-related variables may not improve monthly scale rainfall predictions by artificial neural networks for the metropolitan region of Belo Horizonte, Brazil

Artificial neural networks (ANNs) may experience problems due to insufficient or uninformative predictors, and these problems are common for complex predictions such as those for rainfall. However, some studies point to the use of climate variables and anomalies as predictors to make the forecast more accurate. This research aimed to predict the monthly rainfall, one month in advance, in four municipalities of the metropolitan region of Belo Horizonte using an ANN trained with different climate variables; additionally, it aimed to indicate the suitability of such variables as inputs to these models. The models were developed using the MATLAB® software Version R2011a using the NNTOOL toolbox. The ANNs were trained by the multilayer perceptron architecture and the feedforward and backpropagation algorithm using two combinations of input data, with two and six variables, and one combination of input data with the three most correlated variables to observed rainfall from 1970 to 1999 to predict the rainfall from 2000 to 2009. The climate variable most correlated with the rainfall of the following month was the average compensated temperature. Even when using the variables most correlated with precipitation as predictors (0.66 ≤ nt index ≤ 1.26), there was no notable improvement in the predictive capacity of the models when compared to those that did not use climate variables as predictors (0.55 ≤ nt index ≤ 0.80).
 Keywords: artificial intelligence, ENSO, hydrological modelling.

Golden-bellied mangabeys (Cercocebus chrysogaster) exhibit a larger home range and longer travel distances than those of bonobos (Pan paniscus) at LuiKotale, Democratic Republic of the Congo.

Primate ranging behavior is associated with numerous social and ecological correlates. Interspecific comparisons of ranging behavior can therefore provide insight into the socio-ecological conditions that characterize a species' niche within its community. We provide the first description of ranging behavior in golden-bellied mangabeys (Cercocebus chrysogaster), using sympatric bonobos (Pan paniscus) as a comparison. Over 6 months, we recorded GPS tracks at 1- and 5-min intervals from one habituated golden-bellied mangabey group and two habituated bonobo communities at LuiKotale, central Democratic Republic of the Congo. We compared estimates of home range size, time spent at different elevations, and hourly travel distances between species. We modeled daily travel distances against total monthly rainfall to investigate seasonal variation in daily ranging. The golden-bellied mangabey home range was similarly sized or larger than each of the two bonobo communities at LuiKotale across estimation methods. Mangabeys visited more of their range per day and spent more time in terra firma forest and less time in swamps than bonobos. Mangabeys traveled significantly farther per day and during midday hours than bonobos, but travel distances did not relate to monthly rainfall in either species. Golden-bellied mangabeys exhibited wide daily ranging behavior that more closely resembled that of sympatric bonobos than other Cercocebus species. Large homes ranges in mangabeys are likely influenced by food availability in terra firma forest, especially as groups appear to travel long distances between fruit trees and terrestrial food patches. Maximizing daytime activity may help mangabeys avoid competition from heterospecifics and indicates temporal niche partitioning in this primate community.

The Effects of Monthly Rainfall and Temperature on Flowering and Fruiting Intensities Vary within and among Selected Woody Species in Northwestern Ethiopia

The phenological responses of plants to climatic variables are critical for conservation planning; however, it is less understood in an Afrotropical context. Here, we observed how flowering and fruiting phenophases of seven indigenous plant species are related to monthly rainfall and temperature for 24 months in Ethiopia. We employed linear and non-linear models to test the effects on flowering and fruiting intensity. The results of the linear model showed that flowering intensity decreased with increasing monthly temperature for Maytenus arbutifolia, Prunus africana, and Solanecio gigas, but increased for Bersama abyssinica, and decreased with increasing monthly rainfall for Maytenus arbutifolia. The results of the non-linear model indicated that the flowering intensity of Brucea antidysenterica, Dombeya torrida and Rosa abyssinica decreased, leveled off and increased with increasing monthly temperature. Moreover, the fruiting intensity of Brucea antidysenterica and Rosa abyssinica decreased with increasing monthly rainfall, but increased for Bersama abyssinica; The fruiting intensity increased with increasing monthly temperature for Brucea antidysenterica and Rosa abyssinica. Altogether, the effects of climatic variables not only vary among the species, but also among the phenophases of a plant species. Hence, considering these varied effects in forest conservation schemes is critical, especially during the epoch of this continuing climate change.

A Dynamic Stochastic Integrated Climate–Economic Spatiotemporal Model for Agricultural Insurance Products

We propose a new methodology for area yield distribution modeling. We explore a variety of new hybrid data emulators for spatialtemporal statistical modeling of agricultural crop yields. The regression models explored leverage from a combination of model-generated and observed features incorporating climate/weather variables relating to temperature and precipitation over space and time and agricultural variables for farms such as crop allocations, crop types, land use, and crop rotation. This provides the modeling framework to achieve a hierarchical decomposition of the yield distribution at multiple spatial scales over time, allowing us to study both county- and individual farm-level information with suitably selected weighting functions that take into account farm size and crop type. A core component of our model framework is the climate model component that involves a spatialtemporal local approximate seasonal autoregressive integrated moving average Gaussian process (La-SARIMA-GP) model that is suitable for accurately studying local monthly temperatures and rainfalls. Upon construction of the crop yield model, we demonstrate that for practitioners, there is a clear incentive to consider such a model because it accommodates apportioning of the county yield information to the farms level. This is of significance for both individual and index-based agricultural crop insurance product design and for farm risk management. We demonstrate an application of our model in the insurance context of crop insurance risk pooling and insurance policy rating where we investigate the impact of different temporal and spatial interpolation methods on insurance loss ratios using a rating game.

Micro scale level rainfall trend analysis at Madhira, Khammam district of Telangana

Rainfall is an important factor for agriculture in India as nearly 60 per cent net arable land lacks irrigation and water availability determines the yield of pulses, rice, wheat and sugarcane. The variation of rainfall was one of the major concerns under present climatic situation challenging the farmers to obtain optimum farm production and maintain employment. Therefore, trend analysis was examined for long-term trends from 1975-2021 for rainfall at micro scale level of Madhira in Telangana state. In this study, average monthly and seasonal rainfall, coefficient of variation (CV) was ranging from 43.91 to 300.56 per cent and 27.44 to 171.87 per cent, respectively. The annual value of kurtosis and skewness were -0.39 and 0.47 which resembles light tailed to normal distribution and positively skewed resembling right to the mean. During monsoon, post monsoon and annual rainfall trends were showing non-significantly deceasing trend while winter and post monsoon showed non-significantly increasing trends but, as per Spearman's Rho (non parametric) tests significant increasing trend for winter season. Overall, the four decades of observations showed that there is alternate increasing and decreasing trend at Madhira for monsoon season. The post-monsoon season four decades showed negative departures and annual rainfall was mostly dominated by monsoon, a similar pattern was observed in it also.

A study on the Relationship between the rainy season and Dengue outbreak in the Colombo District of Sri Lanka

Introduction – Dengue is a mosquito-borne viral disease considered a global health problem. It is considered one of the major health concerns in Sri Lanka because of being a tropical country. Even though dengue cases are being reported throughout the year, there are some significant differences between incident rates in some months. The highest incident rate is usually reported from the western province. Aim – This study aims to understand the relationship between dengue incidences and monsoon seasons in the Colombo District of Sri Lanka, and the effect of the rainy season on spreading the disease. The results of this study are expected to be helpful in the implementation of new dengue prevention methods and in strengthening the existing preventive methods. Study Design – The study is a statistical analysis using SPSS – 16 version. Graphical analysis is carried out between monthly rainfall and dengue incidences in the Colombo District of Sri Lanka from January 1st of, 2010, till December 31st of, 2019. Methodology – The number of reported dengue cases in the Colombo district during the mentioned ten-year period is obtained from the Bureau of Health Information, Colombo municipal council. Those obtained data are analyzed using bivalent graphs opposite the months and rainfalls of the relevant months. The discussion will be based on the results of the graphs.

THỬ NGHIỆM ĐÁNH GIÁ XU THẾ BIẾN ĐỔI LƯỢNG MƯA TẠI TỈNH BÌNH ĐỊNH BẰNG PHƯƠNG PHÁP KIỂM ĐỊNH MANN-KENDALL VÀ XU THẾ THEIL-SEN

The paper aims to assess the changing trend of monthly rainfall and minimum monthly rainfall in Binh Dinh province by the Mann-Kendall test method and the Theil-Sen trend in the period 1981 - 2919. The results show that: With a statistical significance of 5%, rainfall tends to increase in January at Hoai Nhon and Binh Tuong stations with an increase of 1.2 - 1.3 mm\year and tends to increase in August at An Nhon station with an increase of 1.7 mm\year but tends to decrease in June at Quy Nhon station with a decrease of 1.6 mm\year. The total rainfall in the minimum months (from January to April) tends to increase at Hoai Nhon and Quy Nhon stations with an increase of 2.3 - 2.5 mm\year. Monthly rainfall and total monthly rainfall at the remaining stations do not satisfy the condition P-value ≤ 0.05, therefore, hypothesis H0 is accepted as a trendless series.

Hydrogeochemical characterization of the alluvial aquifer of Catania Plain, Sicily (South Italy)

A hydrogeochemical study was carried out on the shallow Catania Plain alluvial aquifer, in eastern Sicily to reconstruct its hydrogeological structure, the meteoric recharge and to assess the influence of human activities on groundwater. To characterize the geochemistry of the shallow aquifer, two sampling campaigns were carried out, August–October 2004 and April–May 2005 in 47 sites distributed throughout the plain. The samples were collected and analyzed for physical–chemical parameters and major ions, as well as stable isotopes (δ18O and δ2H). Alluvial deposits with heterogeneous grain sizes constitute the aquifer. Varying conditions of vertical and horizontal permeability lead to the presence of a multilayered aquifer with different conditions of confinement and partial interconnection among layers. The sampled waters were separated into four groups of different compositions due to the water–rock interaction with the different lithologies present in and around the study area. Maps of electrical conductivity and sulfate show a systematic control of land use, in correspondence with the biggest farms. High sulfate concentration is due to both the natural interaction between local meteoric waters and Etna’s plume and the mixing with groundwater coming from the area where evaporitic rocks of the Gessoso Solfifera formation are present. In addition, anthropogenic contamination cannot be ruled out. A rain gauge network, consisting of 3 sites located at different altitudes, was installed to collect rain waters to determine isotopic data (δ2H and δ18O) and to measure the monthly rainfall amount. Based on the isotopic composition of sampled waters, it has been established that beyond the direct meteoric recharge, the recharging areas are in the North (Mt. Etna) and the South (Hyblean Plateau).

Penggunaan Korelasi Spearman Untuk Menguji Hubungan Suhu Dan Besarnya Curah Hujan Bulanan di Kota Padang

Rain is one of the important hydrological components. Factors that affect the amount of rainfall in an area are temperature, air humidity, air pressure and wind direction. Previous research stated that there is a strong relationship between temperature and the amount of rainfall. This research was conducted to find out how strong the relationship between the amount of monthly rainfall that occurs in Padang City and the average temperature that occurs in each month for the last 30 years. The research method used is to use quantitative methods using descriptive statistics and non-parametric (spearman correlation test). The selection of the Spearman correlation test was carried out based on the results of the data normality test using the One Sample Anderson-Darling, Ryan-Joiner and Kolmogorov-Smirnov method. Data on temperature and rainfall for the city of Padang are not normal even though they have been normalized using the Box-Cox tranformation method. Spearmen's correlation test shows that there is no significant relationship between the amount of rainfall and temperature with a correlation level of only 9% with a P-Value of 0.087 > 0.05 or 0.001. Further research is needed to find out how strong other factors such as air pressure, humidity and wind direction are on the amount of rainfall in the city of Padang.

Assessment and monitoring of meteorological and hydrological drought in semiarid regions: The Wadi Ouahrane basin case study (Algeria)

The aim of this study is to use the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI) to investigate meteorological and hydrological drought in the Wadi Ouahrane basin of north Algeria. Indeed, in recent years, the Wadi Ouahrane basin has suffered from persistent and recurrent meteorological and hydrological droughts, which caused large economic losses and extreme difficulties for the local population, resulting in widespread out-migration and poverty throughout the country. In order to evaluate the SPI, 6 monthly rainfall series for the period 1972–2018 have been considered. Moreover, with the aim to evaluate the SRI, monthly runoff data from 1972 to 2018 were also collected in one station. Both the SPI and the SRI have been evaluated at 1-, 3-, 6-, 9-, 12- and 24-month timescales. Although a similar percentage of positive and negative values of both the indices has been detected for the different timescales, the temporal distribution of these values allowed us to identify the periods characterized by severe or extreme drought conditions such as 1982, the end of 1983, 1987–1990, 1992–1995 and, recently, 2014–2016. Finally, in order to detect drought temporal evolution in the period 1972–2018, the SPI and SRI series at the different multi-times scales were tested for trends through the Theil-Sen estimator (SS), the Mann–Kendall test (MK), the Modified Mann–Kendall test (MMK) and the Innovative Trend Method (ITA). As a result, although the SS evidenced negative values, the MK test did not show significant trends thus indicating stable drought conditions.

Adapting rainfall bias-corrections to improve hydrological simulations generated from climate model forcings

Global circulation models (GCMs) provide important insights into future climate change. Bias-correction of downscaled GCM output is integral to any hydrological investigations of climate change due to discrepancies between the statistics of downscaled GCM simulations and observations. Many bias-correction techniques have been developed to support hydrological applications. However, there have been few comparisons of the sensitivity of hydrological simulations to different bias-correction assumptions. This paper investigates the importance of two common assumptions: (i) simultaneously correcting bias at multiple time scales, and (ii) explicitly handling rainfall autocorrelation; in quantile mapping of downscaled GCM rainfall data for hydrological simulation. Four quantile mapping methods are applied to correct bias in dynamically downscaled reanalysis and historical GCM simulations of rainfall for 11 catchments in south-eastern Australia and the performance of bias-corrected rainfall and streamflow simulations is evaluated.All quantile mapping methods investigated can effectively eliminate bias in monthly and annual rainfall totals. Quantile mapping methods that consider differences in the temporal dependence (autocorrelation) structure of downscaled GCM and observed rainfall are most effective in reducing bias in rainfall sequencing statistics, such as probability of consecutive wet or dry days. Streamflow simulations of mean and high streamflow percentiles are underestimated when generated using rainfall that is corrected using quantile mapping methods that do not consider differences in the temporal dependence structure of downscaled GCM and observed rainfall. Future hydrological investigations of climate change should therefore adopt methods that explicitly consider the temporal dependence structures of downscaled GCM and observed rainfall.

Statistical Analysis of Rainfall Distribution in Biratnagar, Nepal: A case study

Rainfall is a key component in the construction of many engineering projects, including canals, bridges, culverts, and road drainage systems. The primary goal of this study is to ascertain the annual, monthly and seasonal fluctuations in rainfall in Biratnagar, Nepal over a period of 10 years (2010-2019). The mean, standard deviation, coefficient of variation, skewness, kurtosis, Precipitation Concentration Index (PCI), normal rainfall along with Mann-Kendall test were calculated to check the rainfall variations. The annual data showed the biggest varieties in rainfall, with an average annual rainfall of 1542.43 mm during a ten years period. Furthermore, an erratic monthly rainfall pattern was found by the non-parametric Mann-Kendall test. However, the test value for each month was non-significant at the 5% level of significance. We also found that the rainfall is least in the winter and most during monsoon season. Based on these calculations, It is seen that the pattern of rainfall is inconsistent or unpredictable. However, present study will aid in the understanding of rainfall variations and trends, assisting in the management of water resources, ecosystems, irrigation, sustainable agricultural planning, engineering structural design, and other areas.

Rainfall data adjustment to Volta Redonda macro-region

Most Brazilian cities do not have a proper water and soil management system due to lack of planning in this sector and of an easy-consultation local-hydrological bibliography capable of reinforcing the future creation of a hydrological modeling. Volta Redonda macro-region's case can be added to this statistics, since it accounts for several natural hazards linked to floods and inundations in some specific locations. The aims of the present study are to descriptively analyze monthly rainfall data generated by CEMADEN's rainfall gauges and to assess whether monthly rainfall in the region adapts well to probability Gamma Distribution plots. Rainfall data from four points in Volta Redonda, Barra Mansa and Pinheiral cities, recorded for 48 months, and provided by CEMADEN, were used in the study. Gamma Distribution was adjusted to monthly rainfall data. In conclusion, the probability of having a given monthly rainfall value lower than, or equal to, that recorded for the Pinheiral – Volta Redonda – Barra Mansa conurbation area can be estimated through Gamma Distribution. Values recorded for shape (γ) and scale (β) parameters of Volta Redonda macro-region's municipalities were 1.59 and 79.30, on average, respectively.

How does increasing temperature affect the sub-annual distribution of monthly rainfall?

This paper investigates the relationship between temperature and sub-annual rainfall patterns using long-term monthly rainfall and temperature data from 1920 to 2018 in Australia. A parameter (τ) is used to measure the evenness of temporal rainfall distribution within each year, with τ = 0 indicating a uniform pattern. The study examines the relationship between τ and temperature for each year, considering whether it was warmer or cooler than average across five climate zones (CZs) in Australia, including tropical, arid, and three temperate climate classes. This study discovered a considerable association between annual maximum temperature and the distribution of monthly rainfall, with high temperatures resulting in greater variation (as represented by larger τ values) in the sub-annual distribution of monthly rainfall throughout all CZs, particularly in arid regions with τ values ranging from 0.27 to 0.52. In contrast, regions with temperate climates without dry seasons had a lower and narrower range of τ, from 0.15 to 0.26. This variability in rainfall distribution makes managing water resources more challenging in arid regions in Australia.

Influence of seasonal climate and water table management on corn yield and nitrous oxide emissions

Compared to regular tile drainage (FD), controlled drainage systems with sub-irrigation (CDS) can increase crop yield but could potentially heighten the production and subsequent emission of nitrous oxide (N2O). Accounting for growing season rainfall categorized under wet, dry and normal, the long-term effects of CDS on crop yield and nitrous oxide (N2O) emissions were investigated at a commercial corn farm in southwestern Quebec. Based on yield data collected over 12 years at the study site, CDS improved grain yield compared to regular tile drainage (FD), depending on the quantity and temporal distribution of rainfall during the growing season. On average, CDS positively affected grain yield by 17.7% and 3.4% in dry and normal years, but reduced yield by 25% in a wet year. The lower yield under CDS was particularly observed when excessive monthly rainfall (230 mm) occurred during the crop’s vegetative period. In three of six years, N2O fluxes under CDS treatments were greater by 49% than those under FD but 45% lower in the remaining years, implying that – notwithstanding the quantity of growing season rainfall – CDS does not necessarily always produce greater fluxes than FD. N2O fluxes coincided more with fertilizer application, particularly when associated with a rainfall event. Given that CDS tends to increase crop yield and does not heighten N2O emissions, it remains a beneficial management practice to be adopted in subsurface drained croplands, where appropriate.

Evaluasi Kapasitas Saluran Drainase Sekunder di Jalan Kapten Pattimura Telanaipura Kota Jambi Menggunakan Software Hec-Ras

One of the areas in Jambi City that experience drainage system problems are the Telanaipura area, precisely on Jalan Kapten Pattimura. The area around the research site is a densely populated area and there are several shopping centers, restaurants, and a fairly high road user. When there is a large rain or rain for a long enough time, this area is often flooded with water as high as 0.2 - 0.8 meters which can cause quite a lot of losses for local residents and also for business owners in the area. From this, it can be said that the drainage channel at this location is less than optimal for collecting and draining rainwater discharge. In this case, it is necessary to conduct a study of hydrological analysis and hydraulics analysis of the drainage channel which is useful in helping to solve the problems that occur. This study used hydrological data in the form of monthly rainfall for the past 10 years and the geometry of secondary drainage channels on Jalan Kapten Pattimura Telanaipura. The method used in this study is in the form of hydrological analysis with the maximum rainfall method, gumbel, and calculation of plan discharge with a rational method. This Hydraulic analysis carried out uses the help of the HEC-RAS program to simulate the discharge of water flow in the drainage. Based on the results of the analysis, it can be concluded that the secondary drainage channel of Jalan Kapten Pattimura, Telanaipura District, Jambi City, cannot accommodate the flow discharge of the plan for periods 2, 5, and 10 years. This is due to sedimentation, high rainfall, suboptimal drainage channels in accommodating flow discharge, and the presence of piles of garbage. The solution to this problem is to deepen the dimensions of the drainage channel by 40–135 cm deep.

Basin Runoff Responses to Climate Change Using a Rainfall-Runoff Hydrological Model in Southeast Australia

The effects of climate change have been observed in the Murrumbidgee River basin, which is one of the main river basins in the southeast region of Australia. The study area is the largest and most important agricultural production area within the Murray Darling Basin (MDB). It produces more than AUD 1.9 billion of agricultural products annually and accounts for about 46% of Australia’s total agricultural production. Since Australia’s economy largely depends on its natural resources, climate change adversely impacts the economy in various ways. According to the Intergovernmental Panel on Climate Change’s fifth assessment report (IPCC, AR5), the adaptive capacity and adaptation processes have increased in Australia. The country has implemented policies and management changes in both rural and urban water systems to adapt to future drought, unexpected floods, and other climatic changes. In this study, future catchment runoff has been estimated using the hydrological model, Simplified Hydrolog (SIMHYD), which is integrated with data from three different General Circulation Models (GCMs) and future emission scenarios. Two different representative concentration pathway (RCP) emission scenarios, RCP 4.5 and RCP 8.5, have been used to obtain downscaled future precipitation and evapotranspiration data for the period of 2016 to 2100. Modeling results from the two emission scenarios showed an anticipated warmer and drier climate for the Murrumbidgee River catchment. Runoff in the Murrumbidgee catchment is affected by various dams and weirs, which yields positive results in runoff even when the monthly rainfall trend decreases. The overall runoff simulation result indicated that the impact of climate change is short and intense. The result of the Simplified Hydrolog (SIMHYD) modeling tool used in this study under the RCP 4.5 scenario for the period 2016 to 2045 indicates a significant future impact from climate change on the volumes of runoff in the Murrumbidgee River catchment. For the same period, the climate change prediction showed a decrease in total annual rainfall within the range of 2% to 62%. This reduction in rainfall is projected to decrease river runoff in the upper catchments (e.g., Tharwa, and Yass) by 17% to 58% over the projected periods. However, the runoff trends in the lower sub-catchments (e.g., Borambola) have increased by 137% to 87% under RCP 4.5 and RCP 8.5, respectively. This increasing potential runoff trend in the lower Murrumbidgee catchments gives an indication to build irrigation dams for dry season irrigation management.

A Review of the use of Web-based Climate Information Systems for Agriculture Purposes

<p>The development of information system technology is needed in facing current and future agricultural challenges. An integrated agricultural information system is needed based on climate information system technology in answering this challenge. The Indonesian Agency for Agricultural Research and Development Ministry of Agriculture has developed a web-based Indonesia Integrated Cropping Calendar Information System (ICCIS). The ICCIS provides information for users in preparing planting plans. Likewise, Jaxa's Satellite-based Monitoring Network system (JASMIN-JAXA) web application that uses a satellite database covers all provinces in South Asia, Southeast Asia, and East Asia. This paper aims to review the use of web-based climate information systems in the ICCIS and the JASMIN-JAXA web-based application. Integrated climate information system in ICCIS, among others: flood estimation, drought and crop pests, prediction dry season and rainy season, district-level monthly rainfall prediction map. While JASMIN is a map (rainfall, drought index, soil moisture, groundwater index, solar radiation, surface temperature, and vegetation index) with time series and data sources. Both are able to monitor climate developments for agricultural purposes, dynamic, and growing. The importance of updating and verifying data in accordance with field conditions and equipment maintenance in the system is to be continuously improved to get benefits and accuracy of results in accordance with the interests of agriculture.<strong></strong></p>

Analisis Sebaran Suhu Permukaan Laut dan Kaitannya dengan Curah Hujan di Kepulauan Mentawai

The Mentawai Islands are directly connected to the Indian Ocean and are located on the equator, making the Mentawai Islands region influenced by the characteristics of the sea surface temperature of the Indian Ocean. This location causes the area to have a hot and humid climate and high rainfall. This study aims to determine the distribution of sea surface temperature, average rainfall, and the relationship between sea surface temperature and rainfall in the Mentawai Islands for 10 years (2012-2021). The method used in this study is a survey method, namely direct observation at the research site. The results of this study indicate that the sea surface temperature in the study area in the wet month (October - March) ranges from 29.05 oC - 29.68 oC. The sea surface temperature in the dry months (April – September) ranges from 30.23 oC – 28.95 oC. The maximum rainfall in the Mentawai Islands Regency occurs in November with an average rainfall of 386 mm while the minimum rainfall occurs in June with an average rainfall of 127 mm. The results of the correlation analysis of sea surface temperature with rainfall in the wet month showed a positive correlation. While in the dry month there is a negative correlation.