Climate Change Impact - Part 9 - Kyrgyzstan

Climate Change Impact


Part 9: Example –Kyrgyzstan


Summary

Kyrgyzstan has a continental climate with cold winters and hot summers. Most of the rain falls in the summer months and temperatures are below freezing for most of the winter months. It is projected that storm rainfall will increase by up to 20% and that the duration of lying snow will decrease.

Introduction

Kyrgyzstan is in central Asia and has severe winters with temperature below zero for many months, particularly in mountainous areas.



Figure 1 Map of Kyrgyzstan showing project road

Climate change can affect roads in many ways. The most obvious is storm rainfall; an increase in storm rainfall could require modification to current design for culverts and longitudinal drains. Other factors include daily temperature range, which could affect expansion joints, and maximum temperature, which could affect the choice of binding agent.

Once current values of these parameters have been determined then the extent to which they will change in the future can be assessed.

The observed climate data were downloaded from internet sites which process data facilitated by international organisations such as the World Meteorological Organisation.

Other documents related to climate change for Kyrgyzstan were downloaded. These included:

  •         UNFCCC Country Brief 2014: Kyrgyzstan
  •         Climate Profile of the Kyrgyz Republic
  •         The Kyrgyz Republic: Intended Nationally Determined Contribution
  •         The Kyrgyz Republic’s Second National Communication to the United Nations Framework Convention on Climate Change

These documents describe the potential change to the climate in general terms but were not specific enough for road design.

Current Climate

Kyrgyzstan has a continental climate with warm summer and cold winters.

 The following chart shows the location of the climate stations which were used to determine current climate parameters. Only stations in the area of the project road are shown. The data were at a daily time step and included: precipitation, depth of snow, average daily temperature, daily maximum temperature and daily minimum temperature. Data were downloaded for the period 1950 to the present.

Figure 2 - Location of sites with climate data


Figure 2 shows the location of sites with climate data. Sites with a solid diamond have precipitation, temperature and snow data. Sites with an open diamond only have precipitation data.

The chart also shows the area covered by the nearest climate model cell as an orange rectangle. It is convenient that the section of road of interest corresponds to one of the climate cells.

Rainfall is highest in the summer months. In winter, average monthly temperatures are often below zero. The road itself passes between two areas with higher elevations and maximum daily rainfall is lower than areas with higher land – around 20 mm per day.

Climate projections

To examine the performance of climate models, their simulation relative to past observed climate for the period 1970 to 1990 was examined. The four models chosen on this basis were:

  •         bcc-csm1-1: Beijing Climate Center Climate System Model (China)
  •         IPSL-CM5A-MR: The Institut Pierre Simon Laplace (France)
  •         CCSM4: The Community Climate System Model Version 4 (USA)
  •         NorESM1-M: Norwegian Earth System Model (Norway)


The conclusions relating to climate change and daily maximum rainfall were:

  •   The average percentage increase for the final 50 years of the present century is 7.3% for the RCP 8.5 projections and 5.5% for the RCP 6.0 projections.
  • The projections of 5-day rainfall, more relevant for rivers which are crossed by the road showed a similar increase which could be translated in into increased flooding.
  • Winter and summer temperatures have been rising in recent years. The rate of increase has been 3.3 °C per century, slightly lower than the projected 5.5 °C per century. This significance of these increases relate to icing in winter and the heat-resistance of the road surface in summer. There is no indication that the diurnal temperature range (important for expansion joints) will increase.
  • On average, the depth of snow reaches 500 mm or even more in an average year.
·         When a range of models was ranked on the projected increase between the present and the year 2100, the difference in projection between the upper and lower quartile was quite modest; of the order of 15%. This applied for both RCP 6.0 and RCP 8.5.

·         When four selected models were compared their difference in projected values for the year 2100 was larger.

·         In most cases the largest percentage increase in daily rainfall for any projection occurred not in the final year of this century but in an earlier year. At any time in the current century the increase in precipitation rarely exceeded 20%, apart from the few models with the highest rate of increase in precipitation. A further consideration following from this is that the maximum increase in rainfall could occur during the projected life of the road.


There are no specific projections related to snow depth. Figure 3 shows two alternative metrics. The first is ‘icing days’; these are days when the daily maximum temperature is below zero. The second is ‘frost days’; these are days when the daily minimum temperature is below zero. The decline in these two variables indicates two things. Firstly, that snow fall will be less frequent and secondly that it will lie for a shorter time.


Figure 3 Days with temperature below freezing for all or part of a day

Conclusions

The main conclusions are that there will be an increase in storm rainfall of up to 20% during the life of the road. The period with lying snow will reduce.








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Climate Change Impact - Part 7 - Vanuatu

Climate Change Impact


Part 7: Example – Vanuatu


Summary

The project examined projected changes to road flooding for four islands of the Vanuatu archipelago. The conclusion was that rainfall intensities would increase for all islands, particularly at the lower durations and return periods critical for road drainage.

Introduction

This example looks at the estimation of road flooding in Vanuatu. The islands of Vanuatu stretch from 13°S to 20°S and 116.e°E to 170.25°E. They lie about 2000 km from the coast of Australia.

The following chart shows the layout of the islands of Vanuatu. The four islands highlighted in green, Ambae, Pentecost, Malekula and Tanna, were included in the study. The red crosses mark the location of climate measurement sites. The roads on the islands are being upgraded and for this it was necessary to ensure that road drainage would be effective for the whole life of the road taking into account projected climate change.

Figure 1 Vanuatu showing the site of climate stations


Flooding on the islands can occur very suddenly and result in flash flooding with rapid increase in flow depth. The following photograph was taken the day following a storm.  The stream itself can been to the left of photograph. The highlighted area, near the tree, shows floating material trapped in the branches showing the depth of flooding. This indicates the degree of flood problems to tackled.


Figure 2 Material trapped in branches during a flood.


Current Climate

Daily observed climate data were obtained from 3 sources:
  •  The Vanuatu Meteorological and Geohazards Department (MGHD)
  •  The National Climate Data Center (NCDC) which is part of the National Oceanographic and Atmospheric Administration in the USA
  • TuTiempo web site


Data from the Meteorological Office was for Bauerfield, Efate and three stations on Tanna. All stations had daily precipitation and Bauerfield included temperature and wind speed. Data from NCDC was for Pekoa, Spiritu Santo, for daily precipitation and temperature. The data from TuTiempo were available for 6 sites and included precipitation, temperature, wind speed and relative humidity.

Where data were available from different sources for overlapping periods, their values were compared and were found to be compatible.

Data were also obtained on storm rainfall profiles. For road drainage, the critical time of a storm is often of the order of a few minutes so daily data on its own is not sufficient.

Climate projections

Projections were provided from PACCSAP (Pacific-Australia Climate Change Science and Adaptation Planning) and included precipitation projections in NetCDF (Network Common Data Format) for the whole world at the grid spacing of the original models. These are:

  •         ACCESS1-3, 1.875° longitude, 1.25° latitude (220km x 147km)
  •         CNRM-CM5, 1.4° longitude, 1.4° latitude (165km x 165 km)
  •         GISS-E2-R, 2.5° longitude, 2.0° latitude (294km x 235 km)


A further data set of projections was provided for which all the files had RX1Day in their title. They had been produced from the 50-km downscaling CCAM normal-cubic atmospheric model, a stretched-grid atmospheric model. They followed the guidelines of “Expert Team on Climate Change Detection and Indices (ETCCDI)”. These had projections of daily rainfall for three RCPs (RCP2.6, RCP4.5 and RCP8.5) and for 4 time-horizons (2030, 2050, 2070 and 2090).

Downscaling was carried out using the Delta Method.

The baseline period was 1987 to 2013 which had observed data. For consistency, the 2030 projection was based on the same number of years, 2027 to 2043. The 2055 projections used values from 2042 to 2068.

The temperature projections were consistent with different models showing similar increases. For precipitation, the projections were less consistent with higher values of RCP leading to higher rainfall for some models and lower rainfall for others.

The conclusions for the four islands were:

  • Ambae: Rainfall intensity is likely to increase for 2030 by about 15% for the 1-in-2-year storm up to about 30% for higher return periods. The additional increase for 2055 relative to 2030 is about 4%.
  • Pentecost: As with Ambae, the percentage increase is less for small return periods, 20% for 1-in-2, but up to 32% for 1-in-100. The 2055 projection is almost identical to the 2030 projection.
  • Malekula: The projections suggest storm rainfall intensity will increase from the baseline to the 2030 time horizon but after that will remain more or less constant. It is also noticeable that increases in storm intensity for low return periods are small, 18%, but increase for longer return periods, about 33%. The 2055 projection is slightly lower than the 2030 projection.
  • Tanna: The projections for this island were lower than those for the other islands.




Figure 3 Daily rainfall intensity for different  islands and return periods

The above chart shows the daily rainfall intensity for different return period on each island for 2055.
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