ABSTRACT
On March 2, 2020, the first Coronavirus Disease (COVID-19) case was reported in Jakarta, Indonesia. One and a half months later (15/05/2020), the cumulative number of infection cases was 16,496, with a total of 1076 mortalities. This study investigates the possible role of weather in the early cases of COVID-19 in six selected cities in Indonesia. Daily temperature and relative humidity data from weather stations nearby in each city were collected from March 3 to April 30, 2020, corresponding with COVID-19 incidence. Correlation tests and regression analysis were performed to examine the association of those two data series. Moreover, we analyzed the distribution of COVID-19 referring the weather data to estimate the effective range of weather data supporting the COVID-19 incidence. Our result reveals that weather data is generally associated with COVID-19 incidence. The daily average temperature (T-ave) and relative humidity (RH) present significant positive and negative correlation with COVID-19 data, respectively. However, the correlation coefficients are weak, with the strongest correlations found at the 5-day lag, i.e., 0.37 (- 0.41) for T-ave (RH). The regression analysis consistently confirmed this relation. The distribution analysis reveals that most COVID-19 cases in Indonesia occurred in the daily temperature range of 25-31 °C and relative humidity of 74-92%. Our findings suggest that COVID-19 incidence in Indonesia has a weak association with weather conditions. Therefore, non-meteorological factors seem to play a more prominent role and should be given greater consideration in preventing the spread of COVID-19. Supplementary Information: The online version contains supplementary material available at 10.1007/s42398-021-00202-9.
ABSTRACT
Extreme rainfall accompanied by strong winds hit the province of Bengkulu in the western coastal area of Sumatera Island during September 19-20, 2017, causing floods and landslides in Seluma and Central Bengkulu district. This extreme rainfall was recorded by Bengkulu Meteorological Station about 257.0 mm day-1 using rain-gauge observation. The spatial distribution of extreme rainfall cannot be seen if only using a rain-gauge observation in this location. The spatial distribution of extreme rainfall is needed to identify the impact of rainfall on landslides in large areas. The study aims to (1) develop the reconstruction of the spatial distribution of extreme rainfall using weather radar and (2) investigate the trigger that caused extreme rainfall by analyzing the synoptic-scale tropical waves. Each weather radar datum is saved in a Constant Altitude Plan Position Indicator (CAPPI). To get rainfall information, the CAPPI must be derived from Quantitative Precipitation Estimation (QPE) values. In this paper, we derived CAPPI using a Marshall-Palmer reflectivity-rain rate relationship. The result shows that rainfall formed on September 20, 2017, 21.00 UTC with total daily rainfall ranged between 176 and 247 mm in both districts and the mean of total daily rainfall has exceeded the average of monthly rainfall. The analysis of tropical waves suggests that only Kelvin waves were active and served as a possible trigger factor while the Madden-Julian Oscillation (MJO) and Equatorial Rossby (ER) waves were inactive during this extreme rainfall.
ABSTRACT
Indonesian Maritime Continent has the second longest coastline in the world, but the characteristics of offshore rainfall and its relation to coastline type are not clearly understood. As a region with eighty percent being an ocean, knowledge of offshore rainfall is important to support activity over oceans. This study investigates the climatology of offshore rainfall based on TRMM 3B42 composite during 1998-2015 and its dynamical atmosphere which induces high rainfall intensity using WRF-ARW. The result shows that concave coastline drives the increasing rainfall over ocean with Cenderawasih Bay (widest concave coastline) having the highest rainfall offshore intensity (16.5 mm per day) over Indonesian Maritime Continent. Monthly peak offshore rainfall over concave coastline is related to direction of concave coastline and peak of diurnal cycle influenced by the shifting of low level convergence. Concave coastline facing the north has peak during northwesterly monsoonal flow (March), while concave coastline facing the east has peak during easterly monsoonal flow (July). Low level convergence zone shifts from inland during daytime to ocean during nighttime. Due to shape of concave coastline, land breeze strengthens low level convergence and supports merging rainfall over ocean during nighttime. Rainfall propagating from the area around inland to ocean is approximately 5.4 m/s over Cenderawasih Bay and 4.1 m/s over Tolo Bay. Merger rainfall and low level convergence are playing role in increasing offshore rainfall over concave coastline.
