knowledge Generation of related to future climate: downscaling by the Meteorological Service of Catalonia

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1 knowledge Generation of related to future climate: downscaling by the Meteorological Service of Catalonia Jéssica Amaro, Antoni Barrera- Escoda, and Vicent Altava- Ortiz Servei Meteorològic de Catalunya (SMC)

2 Building knowledge Source:

3 Building knowledge Scientific evidence of global warming is unequivocal - Intergovernmental Panel on Climate Change Natural Disaster Natural Hazard = + Vulnerabilit y

4 Building knowledge 2015 Barcelona Lyon Liverpool Data source: NASA/GISS Credit: NASA Scientific Visualization Studio

5 Building knowledge Circulation Global Models (CGM) ESAMB Project from IPCC-AR5: MPI- ESM Max Planck Institute for Meteorology GFDL- ESM2G Geophysical Fluid Dynamics Laboratory CanESM2 Canadian Centre for Climate Modelling an Analysis

6 Building knowledge Circulation Global Models Weather Stations Mesoescale Circulation

7 Building knowledge Downscaling Methodologies Dynamical techniques Full Physical Explanation WRF Model nesting into ECHAM5/MPIOM Statistical techniques Weather- type Analogs Problem Day Candidate Days A B C D Weather Dataset (in the past) A B C D A B C D A B C D Best analog A B C D Ø Transferringweather data values

8 Building knowledge 52% Forests, beaches and non-occupied land 20% Residential 7% Industrial areas 6% Equipments 6% Infrastructures & Services 3% Parks 6% Other uses

9 Building knowledge Matar mosques a canonades Killing flies with tanks

10 Building knowledge Matar mosques a canonades

11 Building knowledge RESULTS AT 10-km RESOLUTION (example ESCAT Project) RESULTS AT 1-km RESOLUTION Using an Interpolation WRF+EH5OMs1_CTROL: Annual-mean Minimum Temperature (ºC) Barcelona PERIOD: / RESOLUTION: 10 KM

Building knowledge RESULTS AT 10-km RESOLUTION (example ESCAT Project) WRF+EH5OMs1_CTROL: Annual-mean Minimum Temperature (ºC) RESULTS AT 1-km RESOLUTION

12 Building knowledge RESULTS AT 10-km RESOLUTION (example ESCAT Project) WRF+EH5OMs1_CTROL: Annual-mean Minimum Temperature (ºC) RESULTS AT 1-km RESOLUTION (example ESAMB Project) WRF+EH5OMs1_CTROL: Annual-mean Minimum Temperature (ºC) Barcelona PERIOD: / RESOLUTION: 10 KM PERIOD: / RESOLUTION: 1 KM

13 Building knowledge

14 Building knowledge knowledge about our Cities Future Conditions is necessary to adapt them

15 ESAMB Project Concentration (ppm) Temporal evolution of the CO2 concentration in the atmosphere by RCP scenarios ( ) RCP8.5 RCP4.5 RCP2.6 OBS NO MITIGATION MITIGATION SINCE 2050s ( PARÍS) MITIGATION SINCE 2010s ( KYOTO)

16 ESAMB Project Outputs (Temperature and Precipitation): Ø PDFs (Probability Density Functions): Changes in the probability of occurrence (frequency) Ø Temporal evolution Graphs: Identifying possible trends Ø Variation/Change Maps: Identifying areas of maximum and minimum variations All results are presented for each RCP as the median (50 th percentile) of the three models in order to summarize the projected variations.

17 ESAMB Project This project is «pioneering» due to the combination of dynamical and statistical methodologies, as well as because of the downscaling technique applied from a 1-km resolution observational datagrid, considering the most recent emission scenarios at this moments (RCPs).

Results: Methodology Abili 1 2 J F M A M J J A S O N D J F M A

mean values, of temperature & precipitation for observations

18 Results: Methodology Abili 1 2 J F M A M J J A S O N D J F M A M J J A S O N D 3 4 Spatial and temporal patterns, as well as mean values, of temperature & precipitation for observations are well captured by the statistical downscaling for the control period ( ). J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D 4

Results: Temperature It is projected a clear increase for temperature independently from the considered emission scenario. The maximum increases would be located in mountainous areas.

19 Results: Temperature It is projected a clear increase for temperature independently from the considered emission scenario. The maximum increases would be located in mountainous areas. Begues would be the municipality with the highest variation, up to +3.8ºC for the annual-mean temperature at the end of the 21st century under RCP8.5. Projected temporal evolution for Annual-mean Temperature in AMB ( ) Temperature anomalies (ºC) compared to average

20 Results: Temperature Extreme cold events would suffer little reduction, while extreme hot events would significantly increase its probability of occurrence. Projected PDFs for Monthly-mean Temperature in AMB ( ) Probability of occurrence (dimensionless) Monthly-mean Temperature (ºC)

Projected temporal evolution for Spring Annual-mean Temperature in AMB (1971-2100) Projected temporal evolution for Autumn Annual-mean Temperature in AMB (1971-2100) Temperature Anomalies

21 Results: Temperature All computed trends for seasonal-mean temperature are statistically significant at 99% confidence level, under RCP4.5 & RCP8.5. The highest increases are projected for spring and autumn. Projected temporal evolution for Spring Annual-mean Temperature in AMB ( ) Projected temporal evolution for Autumn Annual-mean Temperature in AMB ( ) Temperature Anomalies (ºC) compared to average Projected temporal evolution for Summer Annual-mean Temperature in AMB ( ) Temperature Anomalies (ºC) compared to average Temperature Anomalies (ºC) compared to average Projected temporal evolution for Winter Annual-mean Temperature in AMB ( ) Temperature Anomalies (ºC) compared to average

Projected temporal evolution for Annual-mean Minimum Temperature in AMB (1971-2100) Projected temporal evolution for

22 Results: Temperature Extre Although it is projected an increase for annual minimum temperature, there would still be days with similar current low-temperature values. However, its probability of occurrence would be lesser. Projected temporal evolution for Annual-mean Minimum Temperature in AMB ( ) Projected temporal evolution for Annual-minimum Minimum Temperature in AMB ( ) Temperature Anomalies (ºC) compared to average Temperature Anomalies (ºC) compared to average

Results: Temperature Clim In the littoral area, where it is concentrated almost all population in AMB, it is projected an increase close to 2 months for the annual number of tropical nights (TN > 20

23 Results: Temperature Clim In the littoral area, where it is concentrated almost all population in AMB, it is projected an increase close to 2 months for the annual number of tropical nights (TN > 20 ºC) at the end of the 21st century. Projected temporal evolution for Annual number of Tropical Nights in AMB ( ) Anomalies for Tropical Nights (days) compared to average Tropical Nights (TN > 20ºC) P50_RCP4.5 P50_RCP8.5

Results: Temperature Clim In the inner areas and valleys, such as the municipalities in Vallès county, it is projected an increase of more than 1-2 months for the number of warm days (TX >

24 Results: Temperature Clim In the inner areas and valleys, such as the municipalities in Vallès county, it is projected an increase of more than 1-2 months for the number of warm days (TX > 30ºC). Projected temporal evolution for Annual number of Warm Days in AMB ( ) Anomalies for Tropical Nights (days) compared to average Warm Days (TX > 30ºC) P50_RCP4.5 P50_RCP8.5

Results: Temperature Clim It is only projected changes for the annual number of torrid nights (TN > 25ºC) in a 30% of the municipalities under RCP4.5 & RCP8.5 scenarios.

25 Results: Temperature Clim It is only projected changes for the annual number of torrid nights (TN > 25ºC) in a 30% of the municipalities under RCP4.5 & RCP8.5 scenarios. However, some municipalities that currently do not record almost no torrid night per year (Besòs Valley and low Llobregat Delta), would suffer torrid nights some summers. Projected temporal evolution for Annual number of Torrid Nights in AMB ( ) Torrid Nights (TN > 25ºC) Anomalies for Torrid Nights (days) compared to average P50_RCP4.5 P50_RCP8.5

Results: Temperature Clim Although Torrid Days (TX > 35ºC) present a lower projected increase in comparison of other climate indices, it has to be considered that some areas would have an increase of

26 Results: Temperature Clim Although Torrid Days (TX > 35ºC) present a lower projected increase in comparison of other climate indices, it has to be considered that some areas would have an increase of one month for the annual number of days with maximum temperature above 35ºC. Projected temporal evolution for Annual number of Torrid Days in AMB ( ) Torrid Days (TX > 35ºC) Anomalies for Torrid Days (days) compared to average P50_RCP4.5 P50_RCP8.5

Results: Temperature Clim Although some increases are projected for Frost Days (TN < 0ºC) in some areas, they are not relevant in comparison of the general projected decreases.

27 Results: Temperature Clim Although some increases are projected for Frost Days (TN < 0ºC) in some areas, they are not relevant in comparison of the general projected decreases. Those decreases could be higher due to the lack of model ability to reproduce past variability. Projected temporal evolution for Annual number of Frost Days in AMB ( ) Frost Days (TN < 0ºC) Anomalies for Frost Days (days) compared to average P50_RCP4.5 P50_RCP8.5

28 Results: Precipitation It is found a linear reduction of 13.6 mm per decade during the period for the annual-mean precipitation under the RCP8.5 scenario (statistically signficant at 99% confidence level). Precipitation anomalies (%) compared to average ) (% a n 50 itja m c te e sp 25 re c ió ita c ip re 0 p e d s a lie m- 25 o n A - 50 Projected temporal Evolució temporal evolution projectada for Annual de la Total PMA Precipitation (%) a l'amb ( ) in AMB ( ) Mitjana AMB ( ) OBS = 602,1 mm CTROL = 565,4 mm CTROL OBS P5 P95 P50_RCP26 P50_RCP45 P50_RCP85

29 Results: Precipitation Although it is projected a greater frequency of drought periods at the end of the 21st century, it will remain the alternation among wet and dry years during this century. Projected PDFs for Monthly-mean Precipitation in AMB ( ) Probability of occurrence (dimensionless) Monthly Precipitation (mm)

30 Results: Precipitation Summer shows a statistically significant diminution of -2.6 mm/decade (RCP4.5 95% confidence level) and -6.6 mm/decade (RCP8.5, 99% confidence level) for the period. Anomalies de precipitació respecte mitjana (mm) Precipitation anomalies (%) compared to average Projected Evolució temporal evolution projectada for de Summer la PPT (mm) Total d'estiu Precipitation a l'amb in ( ) AMB ( ) Mitjana AMB ( ) OBS = 146,9 mm CTROL = 131,5 mm CTROL OBS P5 P95 P50_RCP26 P50_RCP45 P50_RCP85

31 Results: Precipitation Extre It is projected an increase in the probability of occurrence for highprecipitation days (>100 mm) FDPs Projected projectades PDFs per for Monthly a la PPTX Maximum diària mensual Daily a Precipitation la AMB ( ) in AMB ( ) Probability of Probabilitat occurrence (adimensional) (dimensionless) Precipitació Monthly Maximum diària màxima Daily mensual Precipitation (mm) (mm) PPTX CTROL_ PPTX OBS_ P50_CTROL_ P50_RCP26_ P50_RCP45_ P50_RCP85_ P50_RCP26_ P50_RCP45_ P50_RCP85_ P50_RCP26_ P50_RCP45_ P50_RCP85_ OBS_

32 Results: Precipitation Clim A reduction for the annual number of low-precipitation days (< 5 mm) would be up to 20% in almost all AMB. Anomalies (days) Anomalies compared respecte mitjana to (dies) average Projected Evolució temporal temporal evolution projectada for Annual dels number n5ppt (dies) of low-precipitation mitjana anual a l'amb days in ( ) AMB ( ) Mitjana AMB ( ) OBS = 67,5 dies CTROL = 81,0 dies P50_RCP CTROL OBS P5 P95 P50_B1 P50_A1B P50_A2 P50_RCP26 P50_RCP45 P50_RCP85 P50_RCP8.5

33 Results: Precipitation Clim It is projected a significant increase for the annual number of days above 50 mm, because the projected variation is higher than the current annualmean value (1.1 events per year). Projected Evolució temporal temporal evolution projectada for Annual dels number n50ppt (dies) of days mitjana above anual 50 mm a l'amb in AMB ( ) ( ) 6,0 5,5 5,0 Mitjana AMB ( ) OBS = 1,07 dies CTROL = 1,12 dies Anomalies (days) Anomalies compared respecte mitjana to (dies) average 4,5 4,0 3,5 3,0 2,5 2,0 1,5 1,0 0,5 0,0-0,5-1,0-1,5 P50_RCP4.5-2, CTROL OBS P5 P95 P50_B1 P50_A1B P50_A2 P50_RCP26 P50_RCP45 P50_RCP85 P50_RCP8.5

34 Summary Mean values Projected variation

35 The authors would like to acknowledge to all of those technicians from AMB and BR for their participation, support and confidence within the development of the ESAMB project. Thank you very much for your attention

Extremes Events in Climate Change Projections Jana Sillmann

Extremes Events in Climate Change Projections Jana Sillmann Max Planck Institute for Meteorology International Max Planck Research School on Earth System Modeling Temperature distribution IPCC (2001) Outline