means. The study addressed in this article tried to improve this Independent Evaluation Unit, Green Climate Fund. As an example, one simple but effective way to make use of monitoring results is to record lessons learned while conducting stakeholder engagement around risk identification, and using the lear… latitude-height resolved fields are used. Available online: http://goo.gl/r8up31 [Accessed, Intercomparison Project Phase 6 (CMIP6) experimental des, Fogt, R. L., Perlwitz, J., Monaghan, A. J., Bromwich, D. H., Jones, J. M., and, Marshall, G. J. Averyt, M.Tignor and H.L. An evaluation of the performances of Global Climate Models (GCMs) for predicting temperature and rainfall in Zimbabwe J. Masanganise*, B. Chipindu**, T. Mhizha**, E. Mashonjowa**, K. Basira* *Department of Physics and Mathematics, Bindura University of Science Education, P Bag 1020, Bindura, Zimbabwe **Department of Physics, University of Zimbabwe, Box MP167, Mount Pleasant, Harare, … A JJA MSLP bias over the, Tibetan Plateau, for example, stands out, as well as for, Antarctica. tools for studying underlying processes and amplifying effects associated This structure is very similar to that reported, tropospheric cold bias for the newer version of the UM. High-quality spatial climate, Karoly, D. J. 0.13 across their 1979–2014 mean difference. Alors je furète sur le… Ajouter un … for these global-scale climate features of SAT and precipitation. performance of the data assimilation system. These observed patterns are a result of a combination of inter-decadal variations and the effect of the global warming during the period. For the 1998 El Nino event, the J-ens land-only, temperature is warmer than C-ens by around 0.2, Maps of the modelled SAT for the CABLE and JULES, seasonal biases compared to ERA-Interim, averaged over the, period 1979–2014. CMCC‐CM2 represents the base for a family of configurations responding to the different climate needs and applications, including the coupled Climate‐Carbon cycle studies through the setup of an Earth System Model (CMCC‐ESM 2), a twin set of configurations (CMCC‐CM2‐HR4 and CMCC‐CM2‐VHR4), specifically developed for the HighResMIP protocol (Haarsma et al., 2016), and the seasonal prediction … Songdo, South Korea. The, position and strength of the polar jet streams are similar but, with some differences in the eastward wind speed. G., O’Connor, F., Rae, J., Senior, C., Sitch, S., Totterdell, I., Wiltshire, A., and Woodward, S. (2011). The JJA wind speeds around. Simi-, correlations are 0.84 and 0.85 respectively for the CABLE and, JULES ensembles, but 0.39 and 0.49 across the Australian, evident, with periods of observed higher precipitation (, corresponding to negative values in the NINO3.4 index shown, temperature and is more variable for simulated temperature and, Two of the important modes of natural variability that affect, model to simulate ENSO and IOD correlations with Australian. CABLE, has a column of soil below each of its tiles while JULES uses one, soil column per grid cell. are included to indicate the range of internal variability. values: 0.93, 0.93 and 0.92). Gong, D., and Wang, S. (1999). pdQ5��ۆ`�Ǭ� �^@�3�[eǭSe�� Antarctica have a much larger bias than in DJF. Evaluation of Impact of Climate Change on Seawater Intrusion in a Coastal Aquifer by Finite Element Modelling 117 • Scenario 3: 10% increase in rainfall recharge due to climate change with scenario 2 Figure 9 shows the predicted groundwater head by the model for all the three scenarios in wells located in the upper and lower aquifer at different locations. CM2 , Le climat en France: Le climat de la métropole est influencé par les vents venus de l’océan Atlantique. Bonjour, J'utilise cette année votre nouveau fichier de calcul CM2 dont je suis très contente. For comparison, results for the older ACCESS models, from the CMIP5 AMIP experiments are also included in, These figures show reduced RMSE values for the newer, ACCESS-CM2 model (although not a direct comparison for, matching periods and a crosscheck for the AM2 results, 1979–, Similarly, for Australian land-only precipitation (, the annual and JJA values compared to the corresponding global, values. In recent years climate change … In this section we evaluate ACCESS-AM2 AMIP simulations of, temperature and precipitation over the Australian region and the. Away from the tropical ocean, ACCESS AM2, has a small dry bias compared to the wet bias in ACCESS 1.0 and, 1.3; however, the tropical biases, both wet and dry, appear less, MSLP is another important feature of the earth’s climate, simulated by the models, since pressure gradients are related, to the atmospheric circulation. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present-day forcing. During one extreme of the variation, there is an increased height gradient, a stronger zonal jet and more baroclinicity at high latitudes. Individually, none are unique to CCA, but together they represent a very distinctive conundrum facing practitioners and policy makers. (ACCESS) has recently been coupled to the Community Atmosphere Biosphere Land A more coherent approach has been stimulated with support of the … Forcing from aerosol–cloud interactions (the Twomey effect) offsets the reduction of clear-sky forcing by clouds, so that the net effect of clouds on the aerosol forcing is small; hence, the clear-sky forcing, which is more readily measurable, provides a good estimate of the total aerosol forcing. The. The model realisations all have very similar, global-mean temperatures across the period 1979–2014, with, A measure of the model error, the root mean square error (RMSE, (area-weighted)) was calculated for the ensembles as a test of, relative model performance. (2012). derived by the Expert Team on Climate Change Detection and Indices (ETCCDI) Observations are based on data available from, difference between the normalised zonal MSLP at 40, The model simulations reveal both internal variability and, positive trends similar to that found in observations as illustrated, decade is similar to the observed trend of 0.45, Correlations between the SAM index and the model results are, 0.35, 0.43 and 0.31 across the three realisations but 0.50 for the, ensemble mean, indicating how the ensemble mean can align. Thanks also to, Rachel Law and Ian Watterson for their comments and advice. than that for temperature. For SAM, the ACCESS-AM2 model is, able to generate an index similar to that observed for DJF in, terms of both variability and trend; correlation to Australian. We also, appreciate the detailed constructive comments and suggestions from two. S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.. Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.. Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.. Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., The, Vitart, F. (2011). 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. in the form of annual mass mixing ratios for carbon dioxide, methane, nitrous oxide, with CFCs and HFCs represented by, two equivalents, CFC-12-eq and HFC-134a-eq, with data, provided for the period of the AMIP simulation. CABLE version 2.5 is outlined in, Differences between the two land-surface models are given in, ACCESS1.3 for the CMIP5 submission. %PDF-1.4 Land Environment Simulator (JULES), model description – Part 2: Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran. , results for the Australian region are discussed, and the JULES Global Land 7.0 configuration is, source data to the model grid and associated, ) data for both SAT and precipitation. Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations. M&E frameworks are usually developed during the planning stage of a project, alongside a theory of … The mean rate of, precipitation is overestimated in the model, with particular, problems around the equatorial region; most of this is a result, of excessive precipitation over the ocean since global-mean, precipitation over land compares well to observations. Grey thin lines are, illustrate the results for correlations between, . 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). A l’est, on trouve le climat continental et entre les deux, un climat de transition*. Experiments using MACv2-SP are performed with the Max Planck Institute Earth System Model. Differ-, ences in the land-surface models are included with the model. We examine how this model represents climate extremes variability compared to observations or reanalysis data. Also, of interest is an examination of the dynamics and, thermodynamics that give rise to the Australian climate and, regional teleconnections and how these relate to deficiencies in, the model results, given that the experiments are driven by. A Twomey effect for each plume is prescribed as a change in the host model's background cloud-droplet population density using relationships derived from satellite data. The performance of these activities should be assessed and evaluated to ensure they can be improved in future iterations, or to help others learn and build from what has been done before. Most significant improvement of monsoon rainfall and ENSO (El Nino Southern Oscillations) relationship in GA7 occurred in the Australian continent, with GA7N216 better capturing the observed relationship than GA6N216. Jin, L., Zhang, H., Moise, A., Martin, G., Milton, S., and Rodriguez, J. modelling system. Trends in the Southern Annular Mode from Observa-. students and teachers about climate topic and the impact of a variety of teaching strategies on teaching and learning the climate concepts. Production: Evaluation Department, Ministry of Foreign Affairs of Denmark Cover photo: Jørgen Schytte/Danida and Søren Rud/Danida Graphic Production: BGRAPHIC ISBN html: 978-87-90656-54-6 ISBN pdf: 978-87-90656-53-9 This report can be downloaded through the homepage of the Ministry of Foreign Affairs www.um.dk For these land-only results, the CABLE ensemble, 0.96. The Joint UK Land Environment Simulator. However, there is a pattern of positive and negative trends across the planet with increases over tropical oceans and decreases over some middle latitude regions. It also draws upon the allied research efforts of the host, institutions and the ARC Centre of Excellence for Climate Extremes upon, which this work is built. (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. A simple plume implementation of the second version (v2) of the Max Planck Institute Aerosol Climatology, MACv2-SP, is described. There are accompanying variations of zonal wind and temperature associated with these modes, which have an equivalent barotropic vertical structure in the extratropics. 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. involve simulations over the historical period from 1979 to the, present with specified observed sea surface temperature (SST), The ACCESS-AM2 configurations were set up as extended, AMIP runs (1951–2014 rather than the standard 1979–2, employing CMIP6 historical forcing data as described in, SST variations and to the GHG, ozone and aerosol changes, as, These simulations generally have smaller biases than simula-, tions with coupled ocean–atmosphere models and can be better, because they include forcing by observed SST and volcanic, aerosol variations. [2.8 MB pdf] Other papers that document various components of the CM2.x models are available for download. In general, the model pressure is higher at high, latitudes and low at low latitudes (although not for the tropical, Pacific and Indian Oceans) in comparison to the ERA-Interim, reanalysis data, which may contribute to errors in regional cloud, formation and surface energy fluxes. Area-averaged peak monsoon rainfall over the Indian subcontinent (70°–90°E, 5°–25°N) increases by ~ 70% from 3 mm day⁻¹ in GA6N216 to 5 mm day⁻¹ in GA7N216, and rainfall dry bias averaged over a large tropical Asian monsoon domain is reduced by 2/3. We utilise indices from ESRL NOAA: a NINO3.4 index, As we are using SST-forced simulations, the, uncertainty estimates provided based on the spread of the individual realisations. 12. Precipitation correlations to ENSO, and IOD exhibit generally similar patterns to those found in, observations, with the ensemble mean producing better results, than single realisations. Global Precipitation: Means, Variations and Trends During the Satellite, Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Me. Overall, both ACCESS models display model biases comparable in magnitude to other CMIP5 model biases. Corresponding author. Model results have been compared to observations and reanaly-. The ACCESS-AM2 CMIP6 AMIP model configuration incor-, porates a set of CMIP6 time-varying forcings, including pre-, scribed monthly SSTs and sea ice concentrations (SICs), solar, forcing, GHGs, volcanic aerosol optical depth, aerosol chemis-, Land-cover forcing variations have not been implemented in the, AM2 (CABLE) version as yet and, consequently, these were not, Data for the SSTs and SICs was derived from the input4MIPS, and processed by the UKMO. They also include two new parametrisations, namely the UK Chemistry and Aerosol (UKCA) GLOMAP-mode (Global Model of Aerosol Processes) aerosol scheme and the JULES multi-layer snow scheme, which improve the fidelity of the simulation and were required for inclusion in the Global Atmosphere/Global Land configurations ahead of the 6th Coupled Model Intercomparison Project (CMIP6). 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. Given the model is driven by prescribed SST from about, 70% of the earth’s surface, this is as expected. A more stringent, test is to look at the land-only SAT anomalies (, variability is evident while maintaining close agreement with, observations. A small number of studies have centred on the representations of climate concepts that are found in the textbooks, though (Choi et al., 2010). 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 …
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