Water Cycle

The hydrological cycle drives the water availability in the watershed as well as groundwater recharge. Although rainfall data is loss by infiltration, evaporation and retention, large amount of water is turned into surface and sub-surface runoff to recharge the river network in the watershed. Furthermore, infiltration and percolation could return to the cycle providing the river base flow. In the water cycle, evaporation from the surface ocean is one of the main factors. Some water in the oceans evaporates into the air, and the rising air takes the vapor toward the upper atmosphere. The water vapor content in the atmosphere is then advected towards the land mass, where cooler temperatures cause it to condense into clouds (see Figure 1). Later, cloud particles collide, grow, and fall out of the sky as precipitation.

Regional warming with higher sea surface temperature (SST) could intensify the ocean surface evaporation, increasing the water content in the atmosphere. Too high SST along with changes in the wind patterns in the upper and lower atmosphere, changes in the high pressure system frequency and location could lead to drought events instead of heavy rainfall in the Caribbean region. In this way, the entire hydrological cycle could be affected and the water availability in the watersheds.

Figure 1. Hydrological water cycle.
Figure 1. Hydrological water cycle.

Drought Definition

Heavy and prolonged rain saturate the soil, creates runoff that accumulates in lower areas, causing flash floods, economic loss and in some cases loss of life. On the opposite side, lack of precipitation causes a complex reverse process of evaporation and slow depletion of soil moisture. The time without rainfall plays a crucial role in the drought evolution. In a brief period without rainfall, plants with deeper roots, such as bushes, trees and most field crops, will not suffer negative effects because they can draw moisture from deeper levels of the soil. When lack of precipitation is combined with exceptionally high temperatures, evaporation increase from the soil and plant transpiration, which in combination with a prolonged dry period can 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.

There is not a unique definition for the drought because this phenomenon is identified by its impact over different systems (agriculture, water resource, ecosystems, etc.). According with the environments, a drought could be defined as:

Meteorological drought: very low rainfall episodes. 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.

Hydrological drought: shortfalls in surface water and groundwater on whole watersheds. Water resources become depleted and rivers and reservoirs drop to lower than normal levels. There is a lag between the rainfall decrease and the streamflow reduction.


Drought Index

The standardized Precipitation Index (SPI) is meteorological drought index defined to monitor drought at a given time scale and rainfall station. This index also can be used to monitor periods of anomalous wet 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.

Drought index can be used to identify the beginning and the end of a drought event. A drought event start when the index take values below a given threshold, and end when again is about this threshold. The SPI 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).

Table 1. SPI classification.
Table 1. SPI classification.

There are relevant parameters to assess droughts (see Figure 2), such as:

Duration: time period where the index is blow the selected threshold.

Intensity: mean value of indexes below the threshold.

Magnitude: multiplication of duration and intensity, which means shortfalls accumulation below the selected threshold.

Drought area extension: drought event extend beyond one weather station.

Figure 2. Drought definition
Figure 2. Drought definition

Drought Time Scale

1-month  SPI: it is considered to be a more accurate representation of monthly precipitation for a given location because the long-term precipitation is fitted to a probability distribution.

3-month SPI: reflects short/medium moisture condition and provides a seasonal estimation of rainfall. In agriculture gives an indication of Soil Moisture condition at the growing season.

6-month SPI: indicates medium-term trends in precipitation. A 6-month SPI may also begin to be associated with anomalous streamflows and reservoir levels.

12-month SPI: associated with streamflows, reservoir levels, and even groundwater levels.


IPCC Scenarios

Accelerated increase of greenhouse gases (GHGs) and dramatic climate changes are influenced by anthropogenic activity, and according with this tendency, the IPCC conducted a study of technical, scientific and socioeconomic information to determine the risk of climate changes generated by human activity [1]. The IPCC issued new scenarios in 2011, called Representative Concentration Pathways (RCPs). These new scenarios not only provides projections of GHG concentration in the, but also the pathway required over time to reach specific radiative forcing outcome.

Four main scenarios were developed, RCP2.6 which considers GHGs emissions start decreasing after the first decade since 2013 and in 60 years to reduce almost to zero emission. This scenarios is considered unlikely to exceed in 2oC the earth temperature since pre-industrial time at the end of 21st century. In consequence, RCP2.6 is assuming an aggressive mitigation strategy [2]. RCP4.5 scenario is considered as a medium-low scenario. Because this scenario take into account some actions to control emissions, it is considered as a stabilization scenario. The target in this scenario is to stabilize the radiative forcing at 4.5 W/m2 in the year 2100. To reach this target, this scenario consider lower emissions technologies, intense use of carbon capture technology, geological store technology, and apply emission price to land use emissions to extend forest land areas from the present day [2,3].  RCP6.0 is a medium-high scenario and also considered as a stabilization scenario. In this scenario, CO2 emissions will continue increasing until 2080 and at the end of the 21st century concentration will be around 25% higher than RCP4.5 [2]. RCP8.5 is considered as a ‘business-as-usual’ approach, which combines high population and relative slow income growth. In addition, this scenario specifies a low rate of technology changes and energy improvements. Consequently, RCP8.5 is the pathway with highest GHG emissions in absence of climate change policies. In this scenario, CO2 concentration at the end of the 21st century will be three to four times higher than pre-industrial concentration in the atmosphere [2, 4]. In these scenarios, the RCP4.5 is more likely not exceed 2oC, while RCP8.5 is likely not exceed 4oC at the end of the 21st century. According with the RCP8.5 and RCP6.0 scenarios a more acidic oceans and global sea level rise between half to one meter are expected. In addition, more heat waves and changes in rainfall patterns should be expected (see Figure 3).

Figure 3. Four potential radiative pathways depending of policies governments adopted to cut emissions [10].
Figure 3. Four potential radiative pathways depending of policies governments adopted to cut emissions [10].

General Circulation Models

The fifth phase of the Coupled Model Intercomparison Project (CMPI5) provides large set of climate simulation using general circulation models to produce trustworthy multi model dataset along the 21st century. These GCMs provides near-term (10-30 years), and long term simulations (century scale), where long-term simulation projects the climate response to a changing atmospheric composition and land cover [5, 6]. Four GCMs were selected for this study; these models are the Community Climate System Model version 4 (CCSM4), the Community Earth System Model, version 1 (CESM1)–Biogeochemistry (CESM1-BGC), the CESM1 – Community Atmospheric Model version 5 (CESM1-CAM5), and the CESM1 – Whole Atmosphere Community Climate Model (CESM1-WACCM). These models have a uniform resolution of 0.94 degree in latitude and 1.25 degree in longitude and 26 vertical layers [7, 8, 9, 10]. Furthermore, CCSM4 has the capability to simulate a more realistic El Niño–Southern Oscillation, as well as the Madden–Julian oscillation [7, 11]. The GCMs are composed by four components, an atmospheric model, a land model, a sea ice model, and an ocean model. A flux coupler allow to exchange mass and energy fluxes between these components (see Figure 4). Data for General Circulation Models can be download here.

A mean multi-model ensemble will be used to account modeling uncertainties, taking the average of the climate variation simulated by every GCMs. RCP4.5 and RCP8.5 scenarios were selected to analyze long-term time series.

Figure 4. General Circulation Model components.
Figure 4. General Circulation Model components.

Caribbean Drought Projection

SPI was calculated for every GCMs over the Caribbean region, and from 2007 to 2099 under the RCP4.5 and RCP8.5 scenarios. A mean multi-model ensemble was applied to account the uncertainty in the climate modeling. Furthermore, this drought index was averaged across the Caribbean to identify the region tendency of rainfall shortfall. This average tends to provide low SPI values, but the tendency remains and it will indicate a wetter or drier atmosphere in the future.

The Caribbean region under the RCP4.5 scenario tends to intensify the drought in the future with a trend of -0.0032 per year (see Figure 5). According with the scenario RCP8.5, a more intense regional warming leads to a more intense drought in the region, where the SPI index decrease at a rate of change of -0.0096 per year (see Figure 6).

Figure 5. Mean multi-model ensemble for SPI long term trend from 2007 to 2100, RCP4.5.
Figure 5. Mean multi-model ensemble for SPI long term trend from 2007 to 2100, RCP4.5.
Figure 6. Mean multi-model ensemble for SPI long term trend from 2007 to 2100, RCP8.5.
Figure 6. Mean multi-model ensemble for SPI long term trend from 2007 to 2100, RCP8.5.

The 21st century was divided in four climate periods: 2020-2039, 2040-2059, 2060-2079, and 2080-2099. In the RCP4.5 scenario, the maximum number of drought events in the region is centered in the period 2060-2079, obtaining 15 droughts in 20 years (see Figure 7). From 2040 to 2099, the number of drought events remains almost constant. In the RCP8.5 scenario, the drought events increase fast, getting the maximum number of events in the last two decades (2080-2099). In this scenario and in the last two decades, there are more than 20 events per two decades (see Figure 8).

Figure 7. Number of drought events along the 21st century under the RCP4.5 scenario.
Figure 7. Number of drought events along the 21st century under the RCP4.5 scenario.
Figure 8. Number of drought events along the 21st century under the RCP8.5 scenario.
Figure 8. Number of drought events along the 21st century under the RCP8.5 scenario.

A SPI frequency analysis indicate that the RCP4.5 scenario depicts a probability of 60% to develop drought events in the Caribbean region (see Figure 9), while the scenario RCP8.5 describes  a probability of 55% to get drought events in this region (see Figure 10).

Figure 9. Relative and cumulative distribution for SPI under the RCP4.5 scenario.
Figure 9. Relative and cumulative distribution for SPI under the RCP4.5 scenario.
Figure 10. Relative and cumulative distribution for SPI under the RCP8.5  scenario.
Figure 10. Relative and cumulative distribution for SPI under the RCP8.5 scenario.


The Caribbean region shows a drought intensification in the future. The RCP4.5 scenario tends to intensify the droughts, but the scenario RCP8.5 accelerate the process with a SPI rate of change of -0.0096 per year. Although the scenario RCP8.5 increase very fast the number of drought events in the future, the scenario RCP4.5 possess the higher probability to develop drought events.



[1]. IPCC, 2000, Emissions scenarios: summary for policymakers, Intergovernmental Panel on Climate Change.

[2]. Symon, C., 2013, Climate change: Action, trends and implications for business, European Climate Foundation.

[3]. Thomson, A., Calvin, K., Smith, S., Kyle, G. P., Volke, A., Patel, P., Delgado-Arias, S., Bond-Lamberty, B., Wise, M., Clarke, L., and Edmonds, J., 2011, “RCP4.5: a pathway for stabilization of radiative forcing by 2100,” Clim. Change, 109, pp. 77–94.

[4]. Riahi, K., Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G., Kindermann, G., Nakicenovic, N., and Rafaj, P., 2011, “RCP 8.5—A scenario of comparatively high greenhouse gas emissions,” Clim. Change, 109, pp. 33–57.

[5]. Meehl G, Goddard L, Murphy J, et al (2009) Decadal prediction, can it be skillful? BAMS 1467–1485.

[6]. Taylor K, Stouffer R, Meehl G (2012) An overview of CMIP5 and the experiment design. BAMS 485–498.

[7]. Gent P, Danabasoglu G, Donner L, et al (2011) The community climate system model version 4. J Clim 24:4973–4991.

[8]. Gettelman A, Kay J (2011) The evolution of climate sensitivity and climate feedbacks in the community atmosphere model. J Clim 25:1453–1469.

[9]. Danabasoglu G, Bates S, Briegleb B (2012) The CCSM4 Ocean component. J Clim 25:1361–1389.

[10]. Holland M, Bailey D, Briegleb B, et al (2012) Improved sea ice shortwave radiation physics in CCSM4: The impact of melt ponds and aerosols on Arctic Sea ice. J Clim 25:1413–1430.

[11]. Subramanian C, Jochum M, Miller A, et al (2011) The Madden–Julian oscillation in CCSM4. J Clim 24:6261–6282.

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