{"query_echo":{"q":"","filters":{"analysis_type":["model integration"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'model integration' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":2,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=model+integration","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"iisd-003139","url":"https://climateinsightsdirectory.org/document/iisd-003139","title":"Integration of Climate Data in the SAVi Energy Model","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"report","language":"en","date_published":"2020-09","source_url":"https://www.iisd.org/system/files/2020-09/intregration-climate-data-savi-energy-model.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document details how climate variables from the Copernicus Climate Data Store (CDS) are integrated into the SAVi Energy model to quantify the impact of climate change on various power generation technologies. It provides a comprehensive literature review of how variables like temperature, wind speed, and precipitation affect the load factor and thermal efficiency of coal, gas, nuclear, biomass, hydro, solar, and wind power, as well as the efficiency of the electricity grid. The report includes a simulation for Johannesburg, South Africa, demonstrating that rising temperatures and changing precipitation patterns can significantly reduce the load factor and revenues for thermal and hydropower assets, while potentially increasing the load factor for wind energy.","ai_generated":true,"unit":"iisd-003139#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Wind power generation is sensitive to wind speed; turbines fail to produce electricity when wind is too low and lose efficiency or stop generating when wind speed exceeds a cut-out limit.","ai_generated":true,"unit":"iisd-003139#insight-1","date_modified":"2026-10-23"},{"text":"Solar PV efficiency is negatively impacted by air temperature and positively influenced by solar radiation and wind speed. Literature suggests a 1°C increase in temperature can decrease efficiency by up to 2%, while a 1 unit (W/m2) increase in irradiance can increase output by 5%.","ai_generated":true,"unit":"iisd-003139#insight-2","date_modified":"2026-10-23"},{"text":"Dust and ash accumulation on solar panels significantly reduces efficiency; for example, ash accumulation of 0.4 mg/cm2 can lead to a 1.5% efficiency decrease or nearly 30% energy reduction per hour.","ai_generated":true,"unit":"iisd-003139#insight-3","date_modified":"2026-10-23"},{"text":"Hydropower generation is highly sensitive to precipitation and river discharge, with a 1% change in either typically resulting in a 1% change in power generation.","ai_generated":true,"unit":"iisd-003139#insight-4","date_modified":"2026-10-23"},{"text":"Nuclear power plant efficiency and output are negatively affected by increasing water temperatures used for cooling. An increase of 1°C in cooling water inlet temperature can decrease thermal efficiency by 0.16% and net power output by approximately 0.39%.","ai_generated":true,"unit":"iisd-003139#insight-5","date_modified":"2026-10-23"},{"text":"Electricity grid efficiency declines as air temperature increases, with network capacity falling by approximately 1% for each 1°C of temperature increase.","ai_generated":true,"unit":"iisd-003139#insight-6","date_modified":"2026-10-23"},{"text":"In a simulation for Johannesburg, South Africa, climate impacts are projected to cause significant load factor reductions for thermal producers (coal, gas, nuclear) starting between 2050 and 2060, with coal's real load factor potentially dropping from 88.64% to 60.65% by 2100.","ai_generated":true,"unit":"iisd-003139#insight-7","date_modified":"2026-10-23"},{"text":"The Johannesburg simulation indicates that while thermal and solar load factors decline, wind power load factors are expected to increase on average by 4.5% by 2100 due to higher future wind speeds.","ai_generated":true,"unit":"iisd-003139#insight-8","date_modified":"2026-10-23"},{"text":"Economic analysis of the Johannesburg simulation shows a net reduction between 5.15% and 8.54% in cumulative revenues for most technologies due to lower capacity utilization, except for onshore wind, which shows a 9.88% increase in cumulative revenues.","ai_generated":true,"unit":"iisd-003139#insight-9","date_modified":"2026-10-23"},{"text":"Reduced grid efficiency due to temperature increases is projected to reduce average annual revenues for power producers in the Johannesburg context by 3.4% compared to a no-climate scenario, totaling ZAR 10.42 billion in cumulative losses between 2022 and 2100.","ai_generated":true,"unit":"iisd-003139#insight-10","date_modified":"2026-10-23"}],"climate_tags":["hydropower","gas-fired power station","coal power","nuclear power","geothermal power","climate finance","climate risk"],"geography_discussed":["Scotland","Black Sea","Greece","United States","Brazil","Zambezi River Basin","Dubai","Saudi Arabia","Vietnam","India","Malaysia","France","World"],"frame_perspective":[],"analysis_type":["literature review","model integration","simulation","cost-benefit analysis"]},{"id":"iisd-003142","url":"https://climateinsightsdirectory.org/document/iisd-003142","title":"Integration of Climate Data in the SAVi Nature-Based Infrastructure Model","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"report","language":"en","date_published":"2020-09","source_url":"https://www.iisd.org/system/files/2020-09/intregration-climate-data-savi-nature-based-infrastructure-model.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document details how authoritative climate data from the Copernicus CDS is integrated into the SAVi model for nature-based infrastructure. It provides a literature review on the impacts of precipitation, vegetation, and temperature on assets like green roofs, wetlands, and urban forests. The report demonstrates the model's application through simulations in Johannesburg, showing how temperature affects phosphorus removal in wetlands and how increasing vegetation cover can mitigate heat-related labor productivity losses.","ai_generated":true,"unit":"iisd-003142#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Green roofs demonstrate significant stormwater retention capabilities; in Chicago, they retained over 75% of a one-inch storm, and in Milwaukee, they can retain 85% of a two-inch downpour.","ai_generated":true,"unit":"iisd-003142#insight-1","date_modified":"2026-10-23"},{"text":"Permeable pavement in typical US alleys can infiltrate 3 inches of rainwater from a 1-hour storm, with an expected infrastructure lifespan of 30 to 35 years.","ai_generated":true,"unit":"iisd-003142#insight-2","date_modified":"2026-10-23"},{"text":"Urban trees provide measurable economic and environmental benefits, such as in Santa Monica, where 29,299 trees intercepted 193,168 m3 of annual rainfall, avoiding $110,890 in stormwater treatment and flood control costs ($3.60 per tree).","ai_generated":true,"unit":"iisd-003142#insight-3","date_modified":"2026-10-23"},{"text":"Vegetation significantly reduces urban temperatures; for instance, a 30% vegetated area in Davis, California, can be cooler by 6°C during the day and retain warmth by 2°C at night.","ai_generated":true,"unit":"iisd-003142#insight-4","date_modified":"2026-10-23"},{"text":"The efficiency of nutrient removal in constructed wetlands is temperature-dependent; for example, in Spain, removal efficiencies for TSS, COD, and ammonium were higher in summer (97.4%-97.8%, 97.1%-96.2%, and 99.9%-88.9%) than in winter (83.5%-74.4%, 73.2%-60.6%, and 19%-NA).","ai_generated":true,"unit":"iisd-003142#insight-5","date_modified":"2026-10-23"},{"text":"Simulations for Johannesburg using the IPSL RCP8.5 scenario indicate that phosphorus (P) removal efficiency in wetlands increases with temperature, leading to a 12% increase in both the amount of P removed and the related avoided wastewater treatment costs compared to a no-impact scenario.","ai_generated":true,"unit":"iisd-003142#insight-6","date_modified":"2026-10-23"},{"text":"In Johannesburg, temperature-related labor productivity impacts—defined as working in temperatures above 25°C—are projected to start occurring around 2050/2060 and become frequent after 2065.","ai_generated":true,"unit":"iisd-003142#insight-7","date_modified":"2026-10-23"},{"text":"Increasing vegetation cover in Johannesburg can mitigate or postpone labor productivity losses; a 75% vegetation cover could potentially mitigate these impacts entirely.","ai_generated":true,"unit":"iisd-003142#insight-8","date_modified":"2026-10-23"}],"climate_tags":["urban heat island","carbon sequestration","air quality"],"geography_discussed":["Johannesburg","Chicago","Milwaukee","Spain","Barcelona","León","United States","Lancaster","Santa Monica","Kumamoto","Davis","People's Republic of China","London","Atlanta","Guangzhou","Seattle","Hangzhou","Athens","Egypt","Sweden"],"frame_perspective":[],"analysis_type":["literature review","model integration","simulation"]}]}