Historical, time-varying forcing data are then used to enable climate, simulations to run for 1951–2014, a longer period than the, standard AMIP setup. (2011). PDF | On Jan 1, 1999, R. W. Bodman and others published Evaluation of CMIP6 AMIP climate simulations with the ACCESS-AM2 model | Find, read and cite all the research you need on ResearchGate The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2-AO) which was the submission to CMIP5. These differ in the prescription of their annual cycle and in their optical properties, thereby implicitly accounting for different contributions of absorbing aerosol to the different plumes. CABLE, has a column of soil below each of its tiles while JULES uses one, soil column per grid cell. A small number of studies have centred on the representations of climate concepts that are found in the textbooks, though (Choi et al., 2010). © 2008-2021 ResearchGate GmbH. considering surface temperature and precipitation patterns, followed by the teleconnections or climate drivers that influence, precipitation variability, including El Nin, tion (ENSO), the Indian Ocean Dipole (IOD) and the Southern, The current ACCESS atmosphere-only climate model, (hereinafter AM2) configured for CMIP6 is based on the UK, Met Office’s (UKMO) Unified Model (UM) Global Atmo-, sphere (GA) 7.1 with some differences to suit local require-, ments, particularly in regard to having the atmospheric model, compatible with the fully coupled version of the model, which, uses different ocean, sea ice and land-surface models to that of, the UKMO’s climate model, HadGEM3. for the individual CABLE realisations, CABLE ensemble (magenta) and JULES ensemble (yellow), and bars are the AWAP observations. (2012). (a) Contour map of global-mean MSLP, 1979-2014, for the CABLE ensemble mean; (b) bias against ERA-Interim; (c) DJF seasonal bias and (d) JJA seasonal bias. No overall significant trend is noted in the global precipitation mean value, unlike that for surface temperature and atmospheric water vapor. realisations, then ending with the CABLE ensemble mean case. equator but with a cold stratosphere above Antarctica. Maps of average MSLP for, 1979–2014 and model biases for the CABLE ensemble are, ensemble versions. In: Climate Change 2007: The Physical Science Basis. The shape of the plumes is fit to the Max Planck Institute Aerosol Climatology, version 2, whose present-day (2005) distribution is anchored by surface-based observations. means. There is a bias towards, lower MSLP over the Antarctic, weaker in DJF than in JJA, which points towards changes in the UM’s dynamical core and, gravity drag scheme as contributors to this problem, with a large, high pressure bias over the polar oceans and low pressure bias, bias maps (1979–2014). The annual zonal mean RMSE error for the CABLE ensemble is, close to that of the ACCESS 1.0 AMIP CMIP5 realisation, 2.52. compared to 2.30 m/s, and smaller than for ACCESS 1.3 (3.04 m/s). Mean, DJF season SAM index. Further work is needed to investigate other, climate features such as surface radiation and albedo, soil, moisture and runoff. Monitoring and evaluation (ME) of climate change adaptation (CCA) poses an assortment of thorny methodological challenges. large impacts on ecosystems and societies. Alors je furète sur le… Ajouter un … Biases in Evaluation of aerosol distribution and optical depth in the Geophysical Fluid Dynamics Laboratory coupled model CM2.1 for present climate Paul Ginoux,1 Larry W. Horowitz,1 V. Ramaswamy,1 Igor V. Geogdzhayev,2 Brent N. Holben,3 Georgiy Stenchikov,4 and Xuexi Tie5 Received 25 September 2005; revised 5 May 2006; accepted 16 June 2006; published 21 November 2006. Simulated annual means for minimum, mean, Maps of simulated Australian land-only mean 1979–2014 ACCESS-AM2 CABLE ensemble: (, S land-only temperature correlations are 0.97, . These observed patterns are a result of a combination of inter-decadal variations and the effect of the global warming during the period. This dry bias is progressively reduced by increased model resolutions from N96 to N216 and improved model physics from GA6 to GA7. sis data at the global scale and for the Australian region. These data are processed by the UKCA Glomap-, contain monthly aerosol and aerosol precursor emissions from, anthropogenic and biomass burning sources that allow for, sulfates and black and organic carbon. The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. We describe Global Atmosphere 7.0 and Global Land 7.0 (GA7.0/GL7.0), the latest science configurations of the Met Office Unified Model (UM) and the Joint UK Land Environment Simulator (JULES) land surface model developed for use across weather and climate timescales. Comparisons of palaeocli-mate simulations and palaeoenvironmental reconstructions have been carried out for several decades (Braconnot et al., 2007; Joussaume and Taylor, 1995) and show that … For SAT, these, results confirm that the AM2 CABLE and JULES realisations, are very similar for the two land-surface models and generally, similar when comparing the ensemble means, although with, some seasonal difference in the RMSE values for DJF. Corresponding author. The land-surface models use a, different partitioning of land cover into surface types with, differences in the number and types of tiles per grid cell. provides the foundation for future experiments that will examine how We primarily focus on evaluation of near-surface air temper-, ature (SAT) and precipitation at the global scale and for the, Australian region. The most significant biases include the upper-tropospheric cold and polar warm biases, a westerly wind bias in the tropical upper troposphere and easterly wind biases in the southern and northern mid-latitudes, a narrower than observed Hadley circulation cell, a stronger Walker circulation cell, and drying (moistening) near the outer edges of the ascending (descending) branch of the Hadley cell. There are accompanying variations of zonal wind and temperature associated with these modes, which have an equivalent barotropic vertical structure in the extratropics. It is important to realise, that the observed correlation will have some uncertainty due to, natural variability as well as variability arising from climate, modes such as ENSO, IOD and SAM, which may be as large as, the differences in the correlations between the individual, Another important influence on Australian climate is the, the largest forced response in DJF. microphysics model for the UKCA composition-climate model. Williams, K. D., Copsey, D., Blockley, E. W., Bodas-Salcedo, A., Calvert. This required interpo-, land–sea fractional mask for N96, modifying the data to ensure, daily values computed by the model average to the monthly, value in the source data, and production of the ancillary files to, Solar forcing includes a revised, lower, mean total solar, in the CMIP5 versions of ACCESS) along with, a spectral file that provides monthly time-varying details for the, Information about changing GHG concentrations is provided. Impact Evaluation Guidebook for Climate Change Adaptation Projects 4 Glossary. Many climate models have dry biases in tropical monsoon regions, but it is less clear how these errors can affect these model-simulated tropical–extratropical interactions and rainfall teleconnections. P. T., Woodhouse, M. T., Schmidt, A., Breider, T. J., Emmerson, K. M.. Reddington, C. L., Chipperfield, M. P., and Pickering, S. J. Evaluation - Bilan - les climats sur Terre - Cycle 3 Evaluation de géographie : les climats sur Terre Cm1 - Cm2 Consignes pour cette évaluation : 1/Quelles sont les différentes zones climatiques que l'on trouve sur terre ? Our study clearly demonstrates that uncertainty associated with monsoon simulations needs to be considered in future climate projections even outside the monsoon domain. The role of transient eddies in low-frequency zonal. Taylor, 2007: Cilmate Models and Their Evaluation. projecting future changes (although using a longer period, e.g. The observed variability, C, and the corresponding ERA-Interim value is 14.38, Maps of simulated global-mean SAT, 1979–2014: (, ) CABLE ensemble annual, DJF seasonal and JJA seasonal bias (model, ). Posté le janvier 13, 2012. This may require a careful demonstration that the work is consistent with the contract terms. Climate Science Centre, Oceans and Atmosphere, CSIRO, Canberra, Australia. tations within the same 3-D global chemical transport model. GPCP precipitation and all anomalies relative to 1986–2000. Evaluation of climate models using palaeoclimatic data Pascale Braconnot1, Sandy P. Harrison2, Masa Kageyama1, Patrick J. Bartlein3, Valerie Masson-Delmotte1, Ayako Abe-Ouchi4, Bette Otto-Bliesner5 and Yan Zhao2 There is large uncertainty about the magnitude of warming and how rainfall patterns will change in response to any given scenario of future changes in atmospheric … In many ways, the changing context and trends in evaluation in international development can support and integrate the needs for CCAI evaluation. Uncertainty estimates are provided based on the spread of the individual realisations, All figure content in this area was uploaded by David J. Karoly, Evaluation of CMIP6 AMIP climate simulations with the. Our analysis because of the larger internal variability at regional scales. Jan 13 2012. pdQ5��ۆ`�Ǭ� �^@�3�[eǭSe�� Arep adaptation review and evaluation procedures ccAp Climate Change action plan 2010-2014 cSS Climate Safeguards System eSAp environmental and Social assessment procedures eSiA environmental and Social impact assessment orQr Quality assurance and results department orQr.3 Compliance and Safeguards division pcn project Concept note pAr project appraisal report rmcs regional member … The DJF Antarctic, cool bias in ACCESS 1.3 is reversed in AM2 and Australia has a, greater warm bias in the new model, while the warm bias over, the Indian sub-continent apparent in JJA is common to all of the, tively, very similar to each other but more than the 2.69 mm/day, used as the basis for evaluation, narrows the difference. tools for studying underlying processes and amplifying effects associated MACv2-SP provides a prescription of anthropogenic aerosol optical properties and an associated Twomey effect. (2019). with extremes. Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J.. Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van. The objective of this report is to: Provide an easy-to-read synthesis of current adaptation and resilience M&E resources, frameworks, and …