Samaná – Report
Weather Station Data
Dominican Republic is a small island located within the Caribbean Basin that has recently been subjected to many environmental changes. According to Germanwatch 2013, this country has been ranked as the tenth most vulnerable country in the world for long term risk. In addition, detected regional warming will enhance extreme events over the Caribbean region.
The City College of New York (CCNY) has been collecting the accessible climate data, applying quality data criterion, analyzing climatology and extreme events, and mapping the watersheds that contain the following four municipalities: Santo Domingo National District, Santiago, San Pedro de Marcorís, and Samaná.
Weather station data were collected from ONAMET and the National Climate Data Center (NCDC) from NOAA. In Samaná province, one station provides useful information from ONAMET (see Figure 1). Data for Samaná can be download here.
The Caribbean region is characterized by a rainfall season with a bimodal nature, where the initial peak of this season, called early rainfall season (ERS), begins in May and it extends until July, with a brief dry period in July. The second half of the overall rainy season or late rainfall season (LRS) spans from August to November (see Figure 2). From November to March, the low rainfall season is called dry season (DS).
At local scale, the rainfall shape and intensity could be affected by local urbanization, deforestation, and terrain elevation as well as aerosol concentration in the atmosphere. Weather station data capture the local spatial variability and provide a good representation of human activity impact on local climate. In the province of Samaná, Dominican Republic, ground station data were collected from ONAMET to calculate climatology and time series for rainfall, and air temperature. Heat index is not calculated because this station does not provide relative humidity or dew point temperature data. The rainfall climatology calculated from ONAMET data depicts a bimodal pattern in similar way than the Caribbean region, with a mid-summer drought shifted toward June, and with a very intense rainfall activity in May (see Figure 3).
A near term rainfall time series was divided into early rainfall season and late rainfall season. During the early rainfall season, the rainfall show a tendency to increase with time at a rate of 6.36 mm per year, while in the late rainfall season a rainfall deficit tendency is detected with a rate of decrease of -3.3 mm per year (see Figure 4).
The air temperature climatology describe a unimodal pattern with a hotter atmosphere in July and August, reaching a peak temperature of 27.6oC (see Figure 5). Furthermore, a time series analysis indicates a clear decreasing tendency with a rate of change of -0.3oC per year (see Figure 6). In this weather station there is cooler environment tendency.
Lack of precipitation causes a complex reverse process of evaporation and slow depletion of soil moisture. In a brief period without rainfall, plants with deeper roots, such as bushes, trees and most field crops, will not suffer negative. When lack of precipitation is combined with exceptionally high temperatures, evaporation increase from the soil and plant transpiration, which launch a severe drought. Drought events could have negatively effects on the economy and population health. Farmers could lose their crops or spend more money on irrigation, Ranchers will spend more money on feed and water their livestock and the food will become more expensive. Low water flows and poor water quality could generate health problems as well as loss of human life. Economic loss and reduced incomes could incentive the anxiety or depression in the population.
The meteorological drought is defined as episodes with a very low rainfall activity. Precipitation is concentrated within a short period, followed by no precipitation for months. This lack of precipitation could lead to a deficit in soil moisture.
The standardized Precipitation Index (SPI) is a meteorological drought index used to monitor periods of anomalous dry events. To calculate SPI, a sliding windows technique is used, where the sliding window accumulate the rainfall according the selected time scale. A gamma distribution is fitted to the accumulated monthly rainfall and the cumulative distribution function is transformed to the standardized normal distribution. The z-scores is the SPI. This index characterize a severe drought when get values between -1.5 to -1.99, and extreme droughts when SPI is less than -2.0 (see Table 1).
Drought events in Dominican Republic
The CPC Merged Analysis of Precipitation data with a resolution of 2.5 degree was selected to calculate the SPI over the Dominican Republic. The closest coordinate to Dominican Republic corresponds to 18.25oN, 71.25oW, which is placed at Southeast of Dominican Republic and represent the mean value for the whole Dominican Republic Island.
Long term monthly SPI time series with a three month sliding window indicate a periodicity decrease of 60 months during the last years (2003 – 2014) but with intense drought events. In addition, in this monthly time series an extreme drought event were identified in Dominican Republic, in the month of June 1994 (see Figure 7).
Figure 7. Monthly drought index time series for the whole Dominican Republic.
At local scale, weather station rainfall data from Samaná – ONAMET was used to analyze drought events in order to detect climate variability at local scale. Samaná gage stations were taking into account to identify the intensification or weakening of extreme rainfall.
Long term trend of monthly drought index in Samaná shows periods of extreme drought events. Samaná has an extreme drought in October 2000, March 2009, among other drought events (see Figure 8). Furthermore, Samaná shows a small period with drought intensification from 2011 to 2014.
. Stull, Roland. 2000. Meteorology for scientists and engineers. Second. Belmont: Brooks/Cole Cengage Learning.
. NWS. 2014. The Heat Index Equation. May 28. Accessed July 1, 2015. http://www.wpc.ncep.noaa.gov/html/heatindex_equation.shtml.