In this study, we document the air temperature and precipitation changes between present-day conditions and those projected for the period 2041-2070 in the state of Rio de Janeiro (Brazil) by means of Eta driven by HadCM3 climate model output, considering the variation among its four ensemble members. The main purpose is to support studies of vulnerability and adaptation policy to climate change. In relation to future projections of temperature extremes, the model indicates an increase in average minimum (maximum) temperature of between +1.1°C and +1.4°C (+1.0°C and +1.5°C) in the state by 2070, and it could reach maximum values of between +2.0°C and +3.5°C (+2.5°C and +4.5°C). The model projections also indicate that cold nights and days will be much less frequent in Rio de Janeiro by 2070, while there will be significant increases in warm nights and days. With respect to annual total rainfall, the Northern Region of Rio de Janeiro displays the greatest variation among members, indicating changes ranging from a decrease of -350 mm to an increase of +300 mm during the 21st century. The southern portion of the state has the largest increase in annual total rainfall occurring due to heavy rains, ranging from +50 to +300 mm in the period 2041-2070. Consecutive dry days will increase, which indicates poorly time distributed rainfall, with increased rainfall concentrated over shorter time periods.
Climatic variations in a given region, whether natural or anthropogenic, can lead to various environmental impacts such as elevation or reduction in mean sea level, an increase or decrease in frequency of occurrence and intensity of droughts, heavy rains, heat waves and transient systems (cyclones, frontal systems and others). The knowledge of future climate change contributes to the establishment of mitigation measures, since such impacts have consequences for areas of human concern such as agriculture, health, urban planning, and water resources, among others.
Periodic reports from the Intergovernmental Panel on Climate Change (IPCC) about the causes, impacts and measures for mitigating global climate change serve as a standard reference on this subject for the entire scientific community and for governments and industries worldwide. The Fifth Assessment Report (AR5) of the IPCC [
The state of Rio de Janeiro’s climate exhibit high variability as a result of its quite complex terrain, with hills, mountains, valleys, variety of vegetation, and lowland areas and bays, as well as the proximity to the Atlantic Ocean. In the climatological fields of the spatial distribution of air temperature and precipitation highlight the strong presence of the Paraíba Valley and of the Mountainous Region, even as the coast. In addition, the state has the highest population density in Brazil [
To develop projections of future climate change, numerical general circulation models of the earth system are used. However, since global models need to cover a broad area, they are not able to represent many sub-grid scale feedback processes controlled by local features, such as high resolution of topography, land-sea boundaries, vegetation and others. Therefore, projections of future regional climate change obtained from regional models nested within global models have been used by many different research groups. At the National Institute for Space Research (INPE), the regional Eta model [
The objective of this work is to support studies of vulnerability and adaptation to climate change scenarios in Rio de Janeiro State. In order to achieve this goal, we conducted investigations using future projections (2041- 2070) of indicators of climatic extremes in the state, using the regional climate model Eta-HadCM3, and consi- dering the variations among its four members (Cntrl, High, Mid and Low), as described in [
In this study, simulations of future generated by INPE’s 40 km regional Eta climate model nested in the HadCM3 (Coupled Atmospheric-Ocean General Circulation Model) of the Hadley Center are used. Information about this model is summarized below and can be found in greater detail in [
The boundary conditions for the regional Eta model are provided by the control member and three other members of the HadCM3 model [
Experiments with ensemble members provide the means by which the uncertainty in climate change projections can be partially explored. The ensemble of the HadCM3 model uses an approach in which the structure of a simple model is used with perturbations introduced into the physical parameterization schemes. This perturbed physics ensemble (PPE) is very expensive in computational terms, but is a method for systematic examination of the uncertainties in the different components of the model. This is done by first identifying the model parameters that are uncertain as well as important for the model response, and thus it becomes feasible to use an ensemble of several members to explore the implications of these uncertain parameters [
The regional climate is simulated using the regional Eta model [
This model has been used in studies of seasonal forecasts for South America [
The Eta model uses the Betts-Miller scheme [
Some modifications were made to the Eta model to adapt it to the climate change runs through the use of sea surface temperature (SST) derived from the monthly average of the HadCM3 model. The SST model updates daily by linear interpolation. The main change in the Eta model is the 360-day calendar, which was necessary in order to use the boundary conditions from HadCM3. The inclusion of a CO2 increase in the Eta model was made possible by updating the indices of absorption and transmissivity every 5 years. Changes in the original code of the Eta model were made so that the CO2 concentration could vary according to the scenarios used. At decadal time scales, linear interpolation was developed to avoid sudden jumps in the annual values generated for the amount of CO2.
As described in Section 2.1.1, the PPE’s from the HadCM3 model with atmospheric forcing from the A1B greenhouse scenario consists of the standard model plus 16 ensemble members, each with a different climate sensitivity. It is expected that the large variation in the response of global temperature by the end of the 21st century also produces a wide variation in the response of the temperature of the regional climate through a dynamic regionalization (downscaling). Three members plus the control were selected to measure the degree of uncertainty in the global model, since they represent reasonably well the weather over South America. Thus, a larger possible range of regional model simulations of plausible future climate can be generated.
The sets of the boundary conditions of the HadCM3 passed to the INPE Eta model were named Cntrl, High, Mid and Low. The Cntrl member is not perturbed; The High is a member with high climate sensitivity, the Mid is a member with an average sensitivity and Low is a member with low sensitivity. The sensitivity of the unperturbed member is intermediate between that of the members of low and medium sensitivity. Although only one emission scenario (A1B) is available, the differences in sensitivity of the models can provide a representative view of plausible future climate through different emission paths. The high-sensitivity member provides potential changes similar to those of scenarios A2 and A1FI. Likewise, the changes seen in the low-sensitivity member may provide a qualitative illustration of a low-emissions scenario, such as B1 [
The Eta model nested to the boundary conditions of HadCM3 is referred to as Eta-HadCM3 from now onwards. The model was run in time slice mode: for the present climate, 1961-1990, and future climates 2011- 2040, 2041-2070 and 2071-2100. In this work, the study is done for the time interval 2041-2070. The choice of this period is due to the fact that using a too-distant future period, such as the end of the century, would be more difficult for police makers decision to grasp. Moreover, it is from the 2040s on that the trends of climate change begin to show a greater dispersion in the model simulations with the Eta-HadCM3.
Since the Eta-HadCM3 model runs are provided at intervals of 6 hours (0, 6, 12 and 18 UTC), the maximum (minimum) daily temperature is taken as the highest (lowest) value of the four outputs. Daily rainfall is taken as the total accumulated during the four intervals ending between 18 UTC of the previous day and 12 UTC of the day in question, as established by the World Meteorological Organization (WMO).
In relation to future projections, the assessment of trends as indicators of climatic extremes is based on differences between the future climate (2041-2070) and the present climate (1961-1990). Maps of mean differences of index values (minimum and maximum values among the four members) in future climate and the average of the four members for the present climate from the Eta-HadCM3 runs are generated.
The Eta model topography and the regions in the state of Rio de Janeiro are presented in
The nine indicators of climatic extremes used in this study are presented in
The indicators of climatic extremes listed in
Indicator | Definition | Unit |
---|---|---|
TMINmean | Mean annual minimum temperature | ˚C |
TN10p | Annual percentage of days for which TN < 10th percentile | % |
TN90p | Annual percentage of days for which TN > 90th percentile | % |
TMAXmean | Mean annual maximum temperature | ˚C |
TX10p | Annual percentage of days for which TX < 10th percentile | % |
TX90p | Annual percentage of days for which TX > 90th percentile | % |
PRCPTOT | Total annual precipitation | mm |
R95p | Total annual precipitation on days with PRCP > 95th percentile | mm |
CDD | Maximum number of consecutive dry days in the year (PRCP < 1 mm) | days |
In this section we present the results of future projections of climate extremes indicators obtained from Eta- HadCM3 simulations, based on the difference between the future (2041-2070) and present (1961-1990), considering the behavior of the four model members (Cntrl, Low, Mid and High).
The results show that future projections for the periods 2011-2040, 2041-2070 and 2071-2100 differ only in relation to the magnitudes of the differences of the indicators compared to the present climate, always keeping the same sign of increase or decrease. The analyses are performed by evaluation of the minimum and maximum values present among the four members of the model, i.e., one map with a depiction of the smallest differences and another showing the largest differences between the future (2041-2070) and present (1961-1990).
In
The spatial distributions of the indicators TN10p and TX10p, built along the same lines as
to the rest of the state, as described in [
The spatial distributions of the differences between the future (2041-2070) and present (1961-1990) of the indices PRCPTOT and R95p and their minimum and maximum values projected by the Eta-HadCM3 model for the state of Rio de Janeiro are shown in
highest increases in intense rainfall, with values ranging from +50 and +300 mm in the period 2041-2070. It is worth remembering that this area already has high annual rainfall, especially the regions near Angra dos Reis (at Green Coast) and Resende (at Paraiba Valley) cities. In addition, the southern region of the state also has an important concentration of power plants, including thermoelectric, thermonuclear and hydroelectric, and the efficiency of the last one depending directly on accumulated rainfall totals.
The indicator CDD is shown in
In this study, we conducted an assessment of future projections (2041-2070) of indicators of climatic extremes associated with temperature and precipitation in the state of Rio de Janeiro, using the Eta-HadCM3 regional climate simulations, considering the dispersion (uncertainty) among its four members.
In relation to future projections of climatic extremes of temperature, we note that the projections are showing an increase of the minimum and maximum annual average temperatures throughout the state of Rio de Janeiro. Note that the projections show increases in warm nights and warm days throughout the state, with a greater warming in coastal areas. Future projections of climate extremes of precipitation indicate that the range of variation between increases and decreases in the mean annual rainfall is large throughout the state of Rio de Janeiro. Note that the projections increase the total amounts associated with heavy rainfall throughout the state, with the exception of the extreme North and Northwest portions.
According to future projections, the Northern and Northwestern parts of the state of Rio de Janeiro present the greatest susceptibility to climatic extremes. In these areas, the projections of temperature increase are the highest compared with those for the rest of the state. Extremes are also present in projections of precipitation, indicating the possibility of a reduction or an increase in the total annual rainfall, as well as an increase in dry periods.
Concerning these model projections, it is important to emphasize that the simulations take into account only the increase in the concentration of greenhouse gases and not changes in land use or the heat island effect due to urban expansion. Furthermore, when it comes to the regional model, the reliability of the simulations for high resolution depends on the quality of the lateral boundary condition, which is provided by the global model, and also the actual capacity of the regional model itself to reproduce realistic regional characteristics of the present climate.
The first author would like to thank the Coordination for Improvement of Higher Education Personnel (CAPES) for supporting the study. The authors are grateful to the Foundation for Research Support of the state of São Paulo (FAPESP) for collaboration through project No. 2008/58161-1―“Assessment of Impacts and Vulnerability to Climate Change in Brazil and Strategies for Adaptation Options”.