Tailored climate indices for DRR (infrastructure) Elena Akentyeva Main Geophysical Observatory, ST. PETERSBURG, RF

С П А С И Б О З А В Н И М А Н И Е! Main Geophysical Observatory (MGO) is a scientific unit of Roshydromet that researches impacts of climate change on infrastructure including energy sector, transport, oil and gas pipelines, and building construction. Costs and benefits of adaptation options are estimated on the basis of risk assessment and probabilities. The effort is directed to quantify physical impacts of climate change for above-mentioned sectors. MGO fulfills this research for a long period in collaboration with end users. As a result the systems of tailored climate products or impact indexes were created. Expected deviations of these indexes express change of climate conditions and can be used when adaptation measures are working out. Presented results include examples of general and tailored climate indexes for infrastructure and their observed and expected changes. These projected indexes were generated using the ensemble of 16 global climate models of IPCC as well as MGO regional climate model (A2 scenario )

“The tree” of power industry and appropriate general climate impact indexes

“The tree” of building construction and appropriate general climate impact indexes

“The tree” of health protection and appropriate climate impact indexes

Climate and Energy (tailored climate indexes)

Climate and Building (tailored climate indexes)

Tailored climate indices included in Building codes (examples): Climate indices of the cold period: Air temperature of the coldest 5 days and twenty-four hours 92th and 98th percentiles; Daily temperature range in the coldest month, 0 С; Annual count of days when the mean daily temperature < 0, 8, 10 0 С; mean air temperature of these periods; Average relative humidity at 3 pm in the coldest month, %; Annual precipitation sums (separately liquid, solid, mixed) in cold period (November-March), mm; Wind speed 80th percentiles in the heating period, m/s; Annual count of days with wind speed more than 10 m/s in subsero weather

Climate indices of warm period: Long-term average of station pressure; Daily air temperature 99th, 98th, 96th, 95th percentiles; Long-term average of annual daily maximal air temperature, 0 С; Absolute maximal air temperature, 0 С; Daily temperature range in the hottest month, 0С; Average relative humidity in the hottest month, %; Average relative humidity at 3 pm in the hottest month, %; Annual precipitation sums (separately (separately liquid, solid, mixed) in warm period (April-Oktober), mm; Maximum one-day rainfall, mm;

Tailored climate indexes for separating of homogeneous climate regions (building zoning): Long-term average of absolute annual minimal air temperature, 0 С; Long-term average of absolute annual maximal air temperature, 0 С; Coldest and hottest month averages, 0 С; Average wind speed of three cold months, m/s; Average relative humidity at 1 pm in the hottest month, %

PROJECTED CHANGES OF THE COLDEST 24-HOUR PERIOD TEMPERATURE BY 2015 ( 0 С)

The coldest 24- hour temperature 92th percentile (A); (B)

Probable increase of periods with air temperature higher than С (days) by 2015

PROJECTED REDUCTION OF THE HEATING PERIOD DURATION OVER TERRITORY OF RUSSIA BY 2015 (days)

RIVER BASIN, REGION PROJECTED CHANGES OF THE RIVER FLOW BY MID-21 ST CENTURY (%) PROJECTED CHANGES OF THE TOTAL HYDROPOWER RESURSES BY MID-21ST CENTURY (%) The Yenisei The Lena The Chukchi Peninsula Western Siberia Eastern Siberia RF River flow and hydropower resources

PROJECTED CHANGES OF THE TOTAL HYDROPOWER RESURSES BY MID-21ST CENTURY (%)

Tailored climate indices for over–normative loads estimation

Dangerous weather event and climate anomaly Thunder storm Wind speed > 20 m/c Air tempe- rature < – 30 0 С Air tempe- rature < – 40 0 С Whirl wind Complex: Wind speed > 15 m/с, > 22 m/с, > 35 m/с; air temperature < С, < С, < – 40 0 С Risk3* * Fuzzy set method High weather and climate related risk (with confidence 0,48); Medium weather and climate related risk; (with confidence 0,52) Risk assessment of dangerous weather events and climate anomalies for oil and gas industry (example)

С П А С И Б О З А В Н И М А Н И Е! Projected changes of annual count of days with icing hazard (complex: air temperature from +2 to С, precipitation day) by relative to (days)

С П А С И Б О З А В Н И М А Н И Е! Conclusion Tailored climate indices for DRR in infrastructure include: Daily temperature, precipitation, wind speed values more (less) than specific percentiles (e.g. 92, 98, 99,9 etc) Exceedance probability of threshold values of temperature, precipitation, wind speed, humidity (e.g. daily temperature: + 25, 30, 35, 40 0 C, daily precipitation sum: 30, 50 mm etc. ) Conditional and two-dimensional probabilities of specific temperature- humidity and wind-temperature complexes Temperature, precipitation, wind speed, humidity values more (less) than specific percentiles for non-standard time periods (e.g. work hours) Complex climate indexes that include parameters of specific objects (effective temperature, equivalent wind speed

С П А С И Б О З А В Н И М А Н И Е! Thank you for your attention!