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and vegetation Neil Kaye Neil specialises in creating bespoke visualisations and interactive web tools for climate science Dr Fraser Lott Fraser works on the detection and attribution of climate change, particularly of climate-related events. Dr Gareth S Jones Gareth's main research activity

capacity horizontal of user organisation(s) scaling Enhancing Planning to Increasing Enhancing the the scalability address capacity the enabling of of spontaneous the service environment developer scaling Determining Increasing team the role users’ of diversification capacity Planning to Making

Deeper discovery Session 2 – Climate change and 2050’s forecast https://showyourstripes.info/ Professor Ed Hawkins Global temperature change www.metoffice.gov.uk/schools 2 © Crown Copyright 2024, Met Office Global Projections www.metoffice.gov.uk/schools 3 © Crown Copyright 2024, Met Office Met

for results at 250hPa (which equates to FL340), over the Northern Hemisphere (90N-20N). The graphs below display the accuracy of these two forecasts, with the smaller the error being a better value forecast to airline operators. Performance measure: ≤ 2.85m/s for Wind and ≤ 0.56K for Temperature (based

of 2018. Weather, 74: 390- 396. https://doi.org/10.1002/wea.3628 Murphy JM, Harris GR, Sexton DMH, Kendon EJ, Bett PE, Clark RT, Eagle KE, Fosser G, Fung F, Lowe JA, McDonald RE, McInnes RN, McSweeney CF, Mitchell JFB, Rostron JW, Thornton HE, Tucker S, Yamazaki K. (2019) UKCP18 Land Projections

information for any warnings by omission of missing timesteps. The metadata header will only expose the timesteps that have been generated successfully, therefore if a timestep/s is missing then it should be concluded that they have failed to be generated for that time/s

value forecast to airline operators. Performance measure: ≤ 2.85m/s for Wind and ≤ 0.56K for Temperature (based on 12-month mean values) Root Mean Square Vector Error 4.00 3.80 3.60 3.40 3.20 3.00 2.80 Northern Hemisphere T+24 Wind (m/s) at 250hPa Monthly Rolling 12-month mean Target Latest value

-Kendall trend test for mean temperature data from all the six models for the whole Tamil Nadu Model Mann-Kendall statistic (S) Kendall’s tau p value (two-tailed test) Alpha Test interpretation 2020s 2050s 2080s 2020s 2050s 2080s 2020s 2050s 2080s 2020s 2050s 2080s HadCM3Q0 227 173 −42 0.488 0.398 −0.111

for the whole Tamil Nadu Model Mann-Kendall statistic (S) Kendall’s tau p value (two-tailed test) Alpha Test interpretation 2020s 2050s 2080s 2020s 2050s 2080s 2020s 2050s 2080s 2020s 2050s 2080s HadCM3Q0 227 173 −42 0.488 0.398 −0.111 <0.0001 0.002 0.422 0.05 R-H0 R-H0 A-H0 HadCM3Q1 77 251 108 0.166 0.577

-potential modeling showing the frequency of CMEs • More progress will be made in the next 5 years – Combining IPS & FR Next Steps - Technical • Define Detailed Instrument Requirements: FOVs, Cadence, Resolution, Range etc • Justifications for each of the instruments • Refine S/C Accommodation (Carrington