Country

Turkey

Explore historical and projected climate data, climate data by sector, impacts, key vulnerabilities and what adaptation measures are being taken. Explore the overview for a general context of how climate change is affecting Turkey.

Climate by Sector Water

The supply of water is directly affected by weather and climate. Next to the critical water input through precipitation at daily, monthly and seasonal scales, also the loss through evapotranspiration should be taken into consideration. Particularly high temperatures, low humidity and high winds can efficiently remove water from the land surface. Equally, the demand for water is expected to evolve under climate change, particularly as they relate to often rapidly changing demographic and economic settings. These changes generally increase the operational challenges and risk for the water sector.

This section provides the visualization of four climate indices that are most relevant for water sector.

Precipitation: Seasonal Variability

Implications

The annual distribution of rainfall is of great interest to the water industry. Particularly in areas with large seasonality, the distribution of water throughout the year is critical for planning of resources as well as for safety against disasters. Infrastructure and management are closely tuned to the annual cycle of supply and demand. Operational monitoring of the supply is critical for optimal management of the resources. systematic changes in the annual cycle are initially not beyond what the interannual variability has been providing, but changes over time might limit the flexibilities in response, or the more extreme conditions might surpass previously experienced conditions and a reanalysis of the infrastructure and management system might be warranted. The projected changes in the seasonal cycle of rainfall offer insight into systematic trends in the water supply in a warming world. Depending on location, the separation between the different RCPs is clearer.

Data

The graph shows projected change in Monthly Mean Precipitation per month by 2050 compared to the reference period (1986-2005) under all RCPs of CIMP5 ensemble modeling. Positive values indicate that monthly rainfall will likely to increase compared to the baseline, and vice versa. The shaded area represents the range between the 10th and 90th percentile of all climate projections.

Caveats

The median is a fairly robust measure as it reduces the lower quality simulations of precipitation still prevalent in many models. But the ranges at the country level might also be fairly large because there can be decadal variability in climate leading to changes in the mean established over just 20 years. The signal is more robust when multiple models and RCPs show the same direction of change and if that signal remains robust over several decades.

Precipitation: Time Series

Implications

Raising temperatures bring along a change in the potential carrying capacity of moisture in the air. With ~7% increase of theoretical water holding with every degree Celsius, the potential for heavy rainfall is increasing. Looking at the changes in the number of days with at least 20mm of daily rainfall helps to estimate how likely the impacts are of heavy rainfall. Water routing, and thus storage and other management options, are often very different if the input comes in form of many weak or a series of heavy rainfall events. 20mm is one of the thresholds used and represents very heavy precipitation. In some regions, this might be quite common, in others such amounts are exceedingly rare. Other absolute thresholds could be chosen, or return levels for a particular time interval could be looked at. Together, these indicators provide a picture of potential impact of the projected changes.

Data

The graph shows the recorded number of Days with Vey Heavy Rainfall (20mm/day) each year for 1986-2005, and projected values for 2020-2100 under all RCPs of CIMP5 ensemble modeling. Note, the shaded ranges illustrate the inter-model differences, here using the +/- one standard deviation. The reason for using a narrower metric compared to the 10th and 90th percentile is that the inter-model difference is large for precipitation, and in particular for the count of days with rainfall.

Caveats

The representation of intense rainfall is a challenge for coarse resolution climate models as the processes that lead to such events are generally not resolved. However, in recent years at least the intermediate extremes have been improved and thus the representation of 20mm per day is more reliable. Nevertheless, there remain substantial differences between models.

Precipitation: Extreme Events

Implications

The most extreme rainfall episodes generally have the danger of leading to significant floods. Individual daily rainfall is often linked to flash-floods of limited spatial extent, but multi-day rainfall generally has a broader spatial footprint and thus more extensive flooding can be explained. The 5-day cumulative rainfall indicator shown here focuses on the maximum rainfall amount that is expected over a 25-yr period. Any changes can have significant impacts on infrastructure and endanger life and property through direct physical effects and potentially through water quality issues. Any significant changes in their magnitudes need to be understood.

Data

The boxplot shows recorded 5-Day Cumulative Rainfall for 1986-2005 and projected 5-Day Cumulative Rainfall 25-yr Return Level by 2050 under all RCPs of CIMP5 ensemble modeling. This indicator focuses on the maximum 5-day cumulative rainfall amount that can be expected within a 25-yr period.

Caveats

The calculation of return levels, the maximum amount expected over a given time period, is done based on the monthly and annual maxima. The number of samples over a 20-yr period is limited and thus the results are inherently noisy. The main indicators of change should be drawn from the changes in the medians (horizontal lines inside the box plots) and the shift in the central half of the samples (the box itself). Often these are not significantly different from the historical period (1986-2005), in part because averaging over a larger domain might obfuscate some of the signals. The indicated changes are pointers, and if of specific importance to a project or investment, then a more detailed study based on the longest available series should be performed.

Drought: Spatial Variability

Implications

Changes in the water balance is of increasing concern on a warmer planet. As a broad rule of thumb, areas that are traditionally dry are expected to become drier, and areas traditionally wet will likely become wetter. But that average pattern is also reflected in the interannual variability as higher temperatures enhance the feedback from more quickly drying soils, even if precipitation doesn't change. Therefore, there is a need to plan for more severe and more frequent drought years, almost anywhere. The standardized precipitation evapo-transpiration index (SPEI), computed over 12 month periods, captures the cumulative balance between gain and loss of water across the interannual time scale. The likelihood for severe drought analyzes the frequency at which prolonged dry conditions are expected, and shown in the map is the probability for change by 2050, using the most aggressive RCP8.5. Other scenarios will show similar direction of changes, albeit as somewhat reduced probabilities.

Data

The map shows change in projected Annual Likelihood of Severe Drought by 2050 compared to the reference period (1986-2005) under RCP 8.5 of CIMP5 ensemble modeling. Brown/Yellow areas are more likely to experience severe drought compared to the baseline period. Meanwhile, Blue/Green areas are less likely to experience severe drought.

Caveats

Drought projections are somewhat controversial because a large part of the outcome hinges on the evapo-transpiration (ET) feedback. The literature covers both projections of significant increases in global drought as well as some lesser trends. Here, an intermediate ET formulation is used that is less sensitive to warming than some, but also doesn't require many assumptions of surface conditions that are required for others because the models don't represent these well enough. Ultimately, because drought potential increases everywhere, the likelihood for severe drought offers insight if a region is in a broader domain where increases could be substantial or if the region might not be less affected by changes in precipitation and moisture.