Search results (2,564)

Ocean (Figure 3). Figure 3. Annual CO2 growth rate for years 1960 to 2023 and predicted for 2024 relative to the preceding year, vs. the Niño3.4 index for April of the preceding year to March of the current year. The Niño3.4 index is the sea surface temperature (SST) anomaly in region 5°N to 5°S

@metoffice.gov.uk This report should be cited as: Kendon, M., McCarthy, M., Jevrejeva, S. and Legg, T. (2017): State of the UK Climate 2016, Met Office, Exeter, UK. This work was supported by the Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). 4 Executive Summary Land

....................................................................................................................39 © Crown copyright 2021 Met Office Page 2 of 100 OFFICIAL 5.5 Limitation(s)………..............................................................................................................40 5.6 Recommendations

be cited as: Carter, S., Steynor, A., Vincent, K., Visman, E., and Waagsaether, K. (2019) ‘Co-production of African weather and climate services’. Second edition. Manual, Cape Town: Future Climate for Africa and Weather and Climate Information Services for Africa (https://futureclimateafrica.org

. Contributing authors: Harris, G., Brown, S., Lowe, J., McCarthy, M., Jevrejeva, S., Watts, G., Johns, D. and Bell, M. Report prepared for the Adaptation Sub-Committee of the Committee on Climate Change, London Use and interpretation of ‘extreme’ and ‘worst case’ climate scenarios in the UK 34

before application for climate monitoring. In addition time series of near-coast sea-surface temperature and sea-level rise are also presented. This report should be cited as: Kendon, M., McCarthy, M., and S. Jevrejeva (2015): State of the UK Climate 2014, Met Office, Exeter, UK. This work was supported

index for April of the preceding year to March of the current year. The Niño3.4 index is the sea surface temperature (SST) anomaly in region 5°N to 5°S and 170°W to 120°W in the Pacific Ocean, de-trended to remove the effect of longterm warming. This shows that for short periods such as individual

challenges presented by the use of the automatic code generation required by the DSL(s) and also the data workflow challenges presented by the ensemble system and cycling data assimilation. • An optimal strategy for the coupling of the component models together that minimises the data dependencies

England 53.827, -1.147 Manual Charlwood England 51.144, -0.228 Automatic Charsfield England 52.162, 1.281 Automatic Chillingham Barns No 2 England 55.529, -1.919 Automatic Chivenor England 51.089, -4.147 Automatic Church Lawford England 52.358, -1.33 Automatic Cippenham S Wks England 51.506, -0.641

to 2023 and predicted for 2025 relative to the preceding year, vs. the Niño3.4 index for April of the preceding year to March of the current year. The Niño3.4 index is the sea surface temperature (SST) anomaly in region 5°N to 5°S and 170°W to 120°W in the Pacific Ocean, de-trended to remove the effect