Fig. 1 China climate prediction system\u2019s criteria and uncertainty<\/span><\/i><\/p>\n 2. Uncertainty<\/b><\/p>\n Interdecadal climate prediction and climate prediction have large uncertainties due to the long forecasting time<\/span>[3]<\/span>, and the determinants of these uncertainties are different in different periods in the future, so the research methods are also different. In general, the uncertainties of interdecadal climate projections and climate projections mainly come from three aspects: The response uncertainty (variability of point of response for a given pattern), uncertainty of internal variability of the climate system, and uncertainty of emission scenarios.\u00a0<\/span><\/p>\n 2.1 Response Uncertainty<\/b><\/p>\n Including the carbon cycle response; Responses and interactions of atmosphere, land, cryosphere and ocean to greenhouse gases in the Earth system; Feedback mechanism of frozen soil; Accounting of CO<\/span>2<\/span> and non-CO<\/span>2<\/span> greenhouse gases and their feedback mechanisms; The nonlinear response of the earth system and the contribution of natural variability. Reducing the uncertainty of the process and mechanism of temperature response to greenhouse gases will provide a scientific basis for accurate carbon budget calculation in the future. Including the carbon cycle response; Responses and interactions of atmosphere, land, cryosphere and ocean to greenhouse gases in the Earth system; Feedback mechanism of frozen soil; Accounting of CO<\/span>2<\/span> and non-CO<\/span>2<\/span> greenhouse gases and their feedback mechanisms; The nonlinear response of the earth system and the contribution of natural variability. Reducing the uncertainty of the process and mechanism of temperature response to greenhouse gases will provide a scientific basis for accurate carbon budget calculation in the future.<\/span><\/p>\n 2.2 Uncertainty of internal variability<\/b><\/p>\n Uncertainty from internal unforced variability: the fact that a projection of climate is uncertain at any given point in the future due to the chaotic and thus unpredictable evolution of the climate system. This uncertainty is inherently irreducible on timescales after which initial condition information has been lost (typically a few years or less for the atmosphere, e.g., Lorenz, 1963, 1996). Internal variability in a climate model can be best estimated from a long control simulation or a large ensemble, including how variability might change under external forcing<\/span>[7]<\/span>.<\/span><\/p>\n 2.3 Uncertainty of emission scenarios<\/b><\/p>\n Plausible representations of the future development of emissions of greenhouse gases and aerosols based on a coherent and internally consistent set of assumptions about driving forces (such as demographic and socioeconomic development, technological change) and their key relationships. Concentration scenarios, derived from emission scenarios, are used as input to climate models to compute climate projections at multiple scales<\/span>[8]<\/span>.<\/span><\/p>\n Han Zhenyu breaks down the future period into the near, medium and long term. In future near-term climate projections, uncertainties in model response and variability within the climate system are the dominant factors, he said. Among them, the internal variability uncertainty accounts for a larger proportion<\/span>[4][5]<\/span>, partly due to the inability to accurately predict the decadal phase change of the climate system, which is the problem to be solved by the decadal climate prediction. For the medium and long term future, the uncertainty of emission scenarios dominates<\/span>[6]<\/span>, so climate projections mainly consider the impact of different emission scenarios on the external forcing of the climate system, and the internal variability of the climate system is treated as “noise” and eliminated through multi-model sets.\u00a0<\/span><\/p>\n <\/p>\n 3. Future Research Directions and Prospects<\/b><\/p>\n In the future, a climate change monitoring index system is useful to deeply understand the multi-layer interaction process and mechanism of the climate system, dynamically assess the global climate situation, and provide a scientific data basis for addressing climate change.<\/span><\/p>\n <\/p>\n References:<\/b><\/p>\n 1. Detailed division According to the report, between 2000 and 2019, 577 natural disasters occurred in China, ranking first in the world [1]. In China, the forecast and prediction of the future weather and climate by the meteorological department are divided according to the length of time, which can be divided into weather forecast, climateContinue reading “Detailed division of climate forecast by the Chinese Climate Prediction System by Shuyue Qu”<\/span><\/a><\/p>\n","protected":false},"author":126,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[203,9],"tags":[],"class_list":["post-3137","post","type-post","status-publish","format-standard","hentry","category-blog-posts-2023","category-no-category-set"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=\/wp\/v2\/posts\/3137","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=\/wp\/v2\/users\/126"}],"replies":[{"embeddable":true,"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3137"}],"version-history":[{"count":3,"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=\/wp\/v2\/posts\/3137\/revisions"}],"predecessor-version":[{"id":3185,"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=\/wp\/v2\/posts\/3137\/revisions\/3185"}],"wp:attachment":[{"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3137"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3137"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3137"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"\"](\"https:\/\/uncertain2degrees.blogs.uni-hamburg.de\/wp-content\/uploads\/2023\/08\/WhatsApp-Image-2023-08-20-at-19.36.16-300x83.jpeg\")
<\/span><\/p>\n\n