An analytical study was conducted to assess the long‐term influence, role, and impacts of El Niño‐Southern Oscillation (ENSO) on Puerto Rico's precipitation patterns and significant moisture deficits (droughts). Detection and attribution was addressed by evaluating local rainfall measures and ENSO‐related data to (1) detect ENSO signals and patterns, (2) quantify the magnitude of any impacts, and (3) determine if ENSO may be an important factor for local prediction of future droughts. Data were evaluated at different time periods and two spatial scales (island‐wide and internal climate regions of Puerto Rico). Although a signal was detected, it was weak, in both directions, varied regionally, and has inconsequential impacts. No evidence was found for a major control by ENSO over local monthly, seasonal, and yearly rainfall for any climate regions on the island. These results indicate that ENSO is not a main factor causing droughts in Puerto Rico for the study period and thus should not be a factor in predicting the potential for local dry periods or large precipitation deficits in the future. Any presumed teleconnections between Puerto Rico's dry periods and ENSO are not based on current climatological evidence. Thus, local drought prediction efforts should be focused on finding major causes of local rainfall variation other than ENSO.

Abstract:Water is critical for sustaining natural and managed ecosystems, and precipitation is a key component in the water cycle. To understand controls on long-term changes in precipitation for scientific and environmental management applications it is necessary to examine whether local land use and land cover change (LULCC) has played a significant role in changing historical precipitation patterns and trends. For the small tropical island of Puerto Rico, where maritime climate is dominant, we used long-term precipitation and land use and land cover data to assess whether there were any detectable impacts of LULCC on monthly and yearly precipitation patterns and trends over the past century. Particular focus was given to detecting impacts from the urban landscape on mesoscale climates across Puerto Rico. We found no statistical evidence for significant differences between average monthly precipitation in urban and non-urban areas directly from surface stations, but, after subdividing by Holdridge Ecological Life Zones (HELZs) in a GIS, there were statistically significant differences (α = 0.05) in yearly average total precipitation between urban and non-urban areas in most HELZs. Precipitation in Puerto Rico has been decreasing over the past century as a result of a decrease in precipitation during periods (months or years) of low rain. However, precipitation trends at particular stations contradict synoptic-scale long-term trends, which suggests that local land use/land cover effects are driving precipitation variability at local scales. OPEN ACCESSClimate 2014, 2 48

Previous studies of the influences of land use/land cover changes (LULCC) on the climate of continental areas have provided a basis for our current understanding of LULCC impacts. However, continental climates may not provide complete explanations or answer specific scientific questions for other regions, such as small tropical-maritime dominated islands. Here we present a detailed analysis of temperature change over the past century for the tropical island of Puerto Rico, using an approach that accounts for internal climate variability and spatial resolution issues and assesses the degree to which some of this change might be related to urban development. Long-term weather data, digital maps, geographic information systems (GIS) and statistical analysis were used to detect and assess differences between urban and non-urban temperature records. Strong evidence of a relationship linking temperature magnitudes to local urban development was detected, and the analysis suggests that urbanization has increased minimum, maximum and average temperatures by 0.5 ∘ C in the warmest regions to 2 ∘ C in the coolest regions. The results also show that the magnitude of temperature impacts depends on the contextual ecology or environment where the development has occurred. Temperature differences between urban and non-urban areas are higher in colder and wetter microclimates than in dryer warmer ones, and were less pronounced for minimum temperature than for maximum temperature. However, because the levels of impacts are based on data that had some prior adjustment intended to control for urban signals, they represent minimum estimates of the impacts of land use on temperature in Puerto Rico.

The selection of statistical methods to evaluate data depends on study questions and characteristics of available data. In climate science, some methods are more popularly used than others; however, the use of applicable alternative methods does not invalidate study findings. Regardless of limitations, some methods like Pearson ordinary correlation are widely used in all sciences including climate and by scientists at government agencies like NOAA and the USGS. In addition, the use of the robust Student’s t test is valid for near-Gaussian distributions with high sample numbers, since it is resistant to data distribution inconsistencies. We wish to put in context the citation about our article and clarify the methods and justification for using them and to educate readers about the use of some conventional statistical tools and tests.