{"id":1487,"date":"2026-08-26T11:18:13","date_gmt":"2026-08-26T11:18:13","guid":{"rendered":"https:\/\/katmal.co.uk\/wordpress\/?p=1487"},"modified":"2026-08-26T11:18:13","modified_gmt":"2026-08-26T11:18:13","slug":"outlying-weather-conditions","status":"publish","type":"post","link":"https:\/\/katmal.co.uk\/wordpress\/index.php\/2026\/08\/26\/outlying-weather-conditions\/","title":{"rendered":"Outlying weather conditions"},"content":{"rendered":"\n<p><\/p>\n\n\n\n<p>It is common to assess the potential impact of a particular incident at a nuclear power station by estimating a source term for the event and then repeatedly running the source term through an atmospheric dispersion code with different weather conditions to provide a statistical distribution of off-site doses or other impacts.<\/p>\n\n\n\n<p>Met data can be obtained from a variety of sources. These include local observations, nearby (or not so nearby) observations, or synthetic data obtained from the massive weather forecasting and recording models and databases. With improvements in the recording of weather data, synthetic data is increasingly seen as the better option.<\/p>\n\n\n\n<p>Methodologies might run the dispersion code for each line of met data available or may sample the data to reduce computing costs\/times but in the hope of the results remaining representative.<\/p>\n\n\n\n<p>ERA5 met data were collected from the Climate Data Store at <a href=\"https:\/\/cds.climate.copernicus.eu\/datasets\/reanalysis-era5-single-levels?tab=download\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/cds.climate.copernicus.eu\/datasets\/reanalysis-era5-single-levels?tab=download<\/a> for a node at (103.75E, 1.25N) for the full period 2015 &#8211; 2025 and used to deduce the stability category. &nbsp;<\/p>\n\n\n\n<p>The resulting wind-speed rose is shown below.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"959\" src=\"https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windrose1-1024x959.png\" alt=\"\" class=\"wp-image-1489\" srcset=\"https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windrose1-1024x959.png 1024w, https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windrose1-300x281.png 300w, https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windrose1-768x719.png 768w, https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windrose1.png 1379w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>and the wind direction frequency below:<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"417\" src=\"https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windfreq-1024x417.png\" alt=\"\" class=\"wp-image-1490\" srcset=\"https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windfreq-1024x417.png 1024w, https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windfreq-300x122.png 300w, https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windfreq-768x312.png 768w, https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/windfreq.png 1379w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>What this presentation fails to show is the outlying sequences, met sequences that might be expected to cause high doses further downwind than usual. These include sequences with very low mixing layers and sequences with very low wind speed (see table)<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><td>Sequence<\/td><td>Mix Layer\/ m<\/td><td>Cat<\/td><td>Wind speed\/ m\/s<\/td><td>Rainfall<\/td><\/tr><tr><td>1802<\/td><td>16<\/td><td>F<\/td><td>0.41<\/td><td>0<\/td><\/tr><tr><td>1803<\/td><td>14<\/td><td>E<\/td><td>0.19<\/td><td>0<\/td><\/tr><tr><td>1804<\/td><td>17<\/td><td>E<\/td><td>0.49<\/td><td>0<\/td><\/tr><tr><td>2608<\/td><td>85<\/td><td>B<\/td><td>0.11<\/td><td>0<\/td><\/tr><tr><td>2698<\/td><td>457<\/td><td>B<\/td><td>0.45<\/td><td>0<\/td><\/tr><tr><td>2699<\/td><td>268<\/td><td>B<\/td><td>0.5<\/td><td>0<\/td><\/tr><tr><td>2700<\/td><td>312<\/td><td>B<\/td><td>0.17<\/td><td>0<\/td><\/tr><tr><td>3921<\/td><td>42<\/td><td>B<\/td><td>0.4<\/td><td>0.317<\/td><\/tr><tr><td>3951<\/td><td>129<\/td><td>B<\/td><td>0.35<\/td><td>0.05<\/td><\/tr><tr><td>4090<\/td><td>221<\/td><td>B<\/td><td>0.03<\/td><td>0<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>One of these (1802) is for a wind direction of 92 degrees. The figure below shows the dose as a function of downwind distance estimated using the ADEPT R-91 type dispersion code in the PACE model (<a href=\"https:\/\/www.ukhsa-protectionservices.org.uk\/pace\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/www.ukhsa-protectionservices.org.uk\/pace<\/a>) calculated for all angle with a 92-degree wind direction with sequence 1802 highlighted.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"659\" src=\"https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/dosevdist-1024x659.png\" alt=\"\" class=\"wp-image-1491\" srcset=\"https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/dosevdist-1024x659.png 1024w, https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/dosevdist-300x193.png 300w, https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/dosevdist-768x494.png 768w, https:\/\/katmal.co.uk\/wordpress\/wp-content\/uploads\/2026\/08\/dosevdist.png 1379w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p>This plot highlights a minor issue with the impact of a change in grid sizes and an issue with the linear interpolation I used to determine the dose at the downwind point of interest (PACE works on a grid rather than your chosen array of points). But it makes the point; there are weather conditions that may produce very different dispersion patterns.<\/p>\n\n\n\n<p>This poses the question \u201cshould our emergency planning zones (assuming the source term is accepted as appropriate) be based on the average downwind distance for an exceedance, a high percentile (P95, P98, P100) of the downwind exceedance, or an exceedance by the average dose or a percentile dose at a particular distance\u201d?<\/p>\n\n\n\n<p>UK guidance is to use P95 which should eliminate these outliers (unless your random sample picks up too many of them).<\/p>\n\n\n\n<p>Emergency planners should be aware that an accident could happen on a particularly cold night with very low wind speeds and, if it does, actionable radiation doses might extend much further than expected.<\/p>\n\n\n\n<p>Of course, they might not. With these low wind speeds the penetration of the plume will be very sensitive to deposition (the assumption above is vg=1E-3 m\/s) and to changes in the wind speed and direction. Not a good night to depend on your default arrangements or your dispersion code.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>It is common to assess the potential impact of a particular incident at a nuclear power station by estimating a source term for the event and then repeatedly running the source term through an atmospheric dispersion code with different weather conditions to provide a statistical distribution of off-site doses or other impacts. Met data can &hellip; <a href=\"https:\/\/katmal.co.uk\/wordpress\/index.php\/2026\/08\/26\/outlying-weather-conditions\/\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">Outlying weather conditions<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1,47,12],"tags":[50,52,54,28,53,56],"class_list":["post-1487","post","type-post","status-publish","format-standard","hentry","category-blog","category-epr-computer-models","category-thoughts","tag-nuclear-emergency-planning","tag-pace","tag-paz","tag-protective-actions","tag-ukhsa","tag-upaz"],"_links":{"self":[{"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/posts\/1487","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/comments?post=1487"}],"version-history":[{"count":2,"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/posts\/1487\/revisions"}],"predecessor-version":[{"id":1493,"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/posts\/1487\/revisions\/1493"}],"wp:attachment":[{"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/media?parent=1487"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/categories?post=1487"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/katmal.co.uk\/wordpress\/index.php\/wp-json\/wp\/v2\/tags?post=1487"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}