Climate Model Validation activities at the Met Office Hadley Centre

Transcription

1 Climate Model Validation activities at the Met Office Hadley Centre Roger Saunders, Mark Ringer, Alejandro Bodas-Salcedo and Viju John Crown copyright Met Office

2 Overview Climate model Satellite climate data records under development Confronting the model with observations Crown copyright Met Office

3 Seamless Prediction Unified Model Model Development Model Evaluation Across Timescales RESOLUTION E-S COMPLEXITY Hurrell et. al. (2009), BAMS Crown copyright Met Met Office 3

4 PHYSICAL CLIMATE Direct and Indirect Effects Greenhouse Effect AEROSOLS The Earth System GREENHOUSE GASES Aerosol formation DMS, dust Methane, ozone Iron fertilisation CO 2 CHEMISTRY Biogenic emissions & removal ECOSYSTEMS LAND OCEAN Crown copyright Met Office

5 Temperature increases by 2100 for mitigated and unmitigated scenarios Although the mean temperature rise under is between 1.5 and 2 C by the end of the century, many regions will experience much greater (or lower) increases in temperature. For instance, Arctic increases of about 8 C are possible in 2100 for this scenario. The average warming for land regions is 2.3 C, compared to 1.8 C for the global average. If emissions continue to rise, leading to the RCP 8.5 scenario, then the global temperature is predicted to reach 5.6 C above the preindustrial level by 2100 and is still rising by 0.45 C per decade at the end of the century. Some regions are projected to warm by more than 15 C (Arctic). The impacts of such a scenario are likely to be large and costly. Crown copyright Met Office

6 Crown copyright Met Office Precipitation changes by 2100 for mitigated and unmitigated scenarios

7 Why are we interested in using satellite data? Evaluate the physical processes most relevant to reducing uncertainty in climate predictions, e.g. clouds Inform & prioritise key areas for developing and improving climate models Constrain climate change predictions or at least try and determine if this is possible Detection & attribution of observed variations to natural and anthropogenic forcings Crown copyright Met Office 7

8 METOP fundamental climate records being collected Crown copyright Met Office 8

9 Something good about orbit drift! SNOs occur over all latitudes when Xing times are identical

10 Distribution of collocations Crown copyright Met Office 10

11 Distribution of bias for AMSU-B/MHS Crown copyright Met Office 11

12 IR and MW daily UTH sampling Crown copyright Met Office 12

13 Daily UTH time series Crown copyright Met Office 13

14 Clear-sky bias Crown copyright Met Office 14

15 IR sampling can affect variability and trend More details in John et al., 2011 (submitted to JGR) Crown copyright Met Office 15

16 Refining Satellite SSTs Pinatubo eruption Noisy AVHRR data Crown copyright Met Office 16

17 Climate monitoring and attribution Different groups can produce defensible, but statistically inconsistent estimates of trends. Need for better error characterisation Crown copyright Met Office 17

18 Use of observations evolving.. Observation simulator Forward modelling of measured quantities (radiances, skin SST, radar reflectivities) rather than high-level products (profile retrievals, bulk SST, cloud properties) Ensures more direct comparison of equivalent model variable with observations This was the key for use of satellite cloud data This message is not clearly recognised yet by all the Earth Observation community Crown copyright Met Office 18

19 Biases compared to CERES Annual Mean New Cloud Scheme Old Cloud Scheme SW CRF LW CRF Crown copyright Met Office 19

20 Biases compared to ISCCP Annual Mean High/Medium High/Thick New Scheme Old Scheme Crown copyright Met Office 20

21 ISCCP MODEL Cloud Amount Reflected SW Crown copyright Met Office 21

22 Model CloudSat Comparison with CloudSat using COSP B A A B Crown copyright Met Office 22

23 Multimodel analysis using satellite simulators HadGEM1 MMF 4km CloudSat LMDZ MMF 1km dbz>-25 (Bodas-Salcedo et al., submitted to BAMS) Crown copyright Met Office 23

24 IWC and cloud fraction (Delanoë et al., submitted to QJ) Crown copyright Met Office 24

25 Decadal prediction:global mean surface temperature anomaly Observations Forecast Forecast from 2007 D. Smith et al., Science 2007 Requires data for both initialisation and verification of forecasts. Crown copyright Met Office 25

26 Gridded directly from monthly station anomalies CRUTEM3 (Brohan et al., 2006) at all points with <7 months missing per decade Change in near surface temperature over recent decades Increase in mean near surface temperature (K) from ( ) to ( ) Surface Obs only Warm From ERA Interim reanalysis which uses all data incl satellites Surface+Sat Obs Crown copyright Met Office 26 Cool

27 Questions and answers Crown copyright Met Office