Met Office’s Post

30 years ago I was part way through my degree in Meteorology at the University of Reading. Since then, much has changed, including our climate. While I might have not followed a career in the subject, environmental sustainability is still something I keep a close eye on, not least leading ISG's Market Lens study on sustainability earlier in the year: https://lnkd.in/dYs2AiXp Data visualisation is something that is very much part of my day-to-day role, and Professor Ed Hawkins climate stripes are a great example of how great data visualisation can change the narrative. Today is #ShowYourStripesDay. #ClimateStripes #ClimateChange #UniversityOfReading

Researchers are working to predict weather conditions one month in advance. We’re working in partnership with the Met Office and the European Centre for Medium-Range Weather Forecasts, to improve the predictability of UK weather. “It will not be possible to predict one month ahead whether a particular day will be sunny or rainy. However, we hope to be able to say we are likely to experience a period of very wet and windy weather – or enjoy sunny weather – four weeks in advance,” explains Professor Rowan Sutton, a climate scientist at the National Centre for Atmospheric Science and University of Reading. As more extreme weather events occur with climate change, knowing far enough in advance that a particular weather event may occur allows for time to prepare - helping to protect infrastructure, lives and livelihoods. Find out how weather forecasts are made, and the applications of advanced weather forecasting: https://lnkd.in/dY6R5nan

Dig into the various climate and remote sensing datasets available in the Climate Engine App and API! https://lnkd.in/gaxDntib #climatedata #remotesensing #analysis #charts #maps #research

The National Neighborhood Data Archive (NaNDA) just dropped our largest dataset to date - Weather by County 2003-2016 (https://lnkd.in/gx5J-hAd) . Using data from the Global Historical Climatology Network (GHCN) distributed by the National Oceanic and Atmospheric Administration (NOAA), NaNDA researchers have created individual datasets on: average daily temperature freezing weather extremely cold weather extremely hot weather rain snow Datasets are separated by type of weather and year, and include daily observations at the county level across the United States. These datasets can easily be combined to address research questions about weather at the county level.

𝐄𝐧𝐠𝐥𝐚𝐧𝐝 𝐟𝐨𝐮𝐧𝐝 𝐚 𝐰𝐚𝐲 𝐭𝐨 𝐬𝐩𝐞𝐞𝐝 𝐮𝐩 𝐰𝐞𝐚𝐭𝐡𝐞𝐫 𝐟𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠 𝐛𝐲 𝟏𝟎𝐱 British scientists from Oxford University have unveiled a new algorithm that can speed up computer forecasting of weather and climate by 10 times. The study, published in the journal Science Advances (SciAdv), promises more accurate forecasts of storms, hurricanes and sea level changes. Climate models, considered among the most complex programs, have been given a new lease of life thanks to a mathematical method called "sequential acceleration." Its principle is to use information already available to extrapolate into the future. In other words, to calculate, the computer applies data about events that have already happened to estimate climate processes that have not yet occurred. The head of the study, Samar Khatiwala, notes that their program has significantly reduced the time of modeling processes in the ocean, moving calculations from months to weeks. This promises improved forecast accuracy and better prediction of adverse weather events. #archtown #climate

𝙎𝙘𝙞𝙚𝙣𝙩𝙞𝙨𝙩 𝙞𝙣 𝙩𝙝𝙚 𝙨𝙥𝙤𝙩𝙡𝙞𝙜𝙝𝙩: Dr Ir Anouk Bomers With climate change, we should no longer be surprised by droughts or rivers bursting their banks in areas where we are not used to it. Fortunately, Anouk researches the behaviour of rivers during floods, using extremely detailed numerical models. Computing time is a problem because to act quickly, she needs a quick overview of where things might go wrong, where dikes might need to be raised or strengthened by for example temporary sandbags, or where people and animals might need to be evacuated. For a speedy heads up she uses machine learning. Anouk: “I want to develop a flood forecasting dashboard based on real-time measurements for Rijkswaterstaat so that it is immediately known where an evacuation should take place. This dashboard guarantees immediate adequate action and it ensures that you have sufficient time to do so without being surprised by rising water.” Read more about Anouk Bomers and her research on how to predict river flooding at https://ut.onl/AnoukBomers

I see a lot of talk today about how climate scientists will be studying the #mauiwildfires disaster. As a climate scientist myself, I can attest to the importance of understanding both the meteorological conditions and #climatechange aspects that lead to these disasters. However, time and again what I see missing from the conversation is the great work that agencies like #NIST, #FEMA, and the broader interdisciplinary disaster research community do in conducting longitudinal studies of the entire disaster, from the hazard, to engineering aspects, understanding the cause of injuries and fatalities, to social science components/economics, and the trajectory and pace of recovery, among many other things. When combined with climate science and meteorology, powerful lessons are learned, and thus actionable recommendations can be implemented to make sure nothing like this happens again, as we continue to adapt to our changing climate!

Steve Ambrose Chief Climate Scientist at SAIC, was recognized by WashingtonExec as one of their Top Climate Change Execs to Watch in 2023! Learn more about how Steve is leading the use of data analytics and geospatial technologies to help the government make better data-driven decisions. #ClimateChange

"Hello connections! I've been immersed in learning GIS through the ArcGIS Suite and recently had the privilege of completing two MOOCs by Esri. The latest one, "GIS and Climate Action," delved into using GIS for analyzing, predicting, and developing policies related to climate change. In today's world, where climate change poses significant challenges—from the rise in average global temperature to sea level increases and the unusual adaptation of vector insects like mosquitoes—GIS emerges as a powerful tool. It aids analysts and policymakers in crafting effective strategies for humanity. Here's a snapshot of what I learned in the course: 1) Utilizing VRP (Vehicle Routing Problem) in the Network Analyst Tool to optimize travel routes and reduce greenhouse gas emissions. 2) Quantifying deforestation in the Amazon. 3) Identifying suitable locations for tapping solar energy, such as rooftop solar plants in Washington DC, using Solar Radiation Tools. 4) Visualizing and analyzing sea level rise through ArcGIS 3D. 5) Predicting food security issues, particularly maize production in Africa, using the Presence-only prediction (MaxEnt) tool. 6) Employing Spatial Analysis to determine the HRI (Heat Risk Index) of Athens in Greece, helping decision-makers identify zones with UHI (Urban Heat Island) effects and take necessary actions. 7) Developing an interactive dashboard to pinpoint areas with coral bleaching. As a culmination, a story map was created using ArcGIS Story Maps, encapsulating everything learned in the course. The link is attached here— https://arcg.is/1iDniv0 please review it. While the examples might be from a different region than yours, the shared problems are universal. I hope this story map inspires you to take suitable actions in your respective communities. Thank you!" #climatemooc #climateaction #esri #gis

We are pleased to share our latest publication (led by Julie Peeling) "Gap-free 16-year (2005–2020) sub-diurnal surface meteorological observations across Florida" in Nature Scientific Data The objective of this paper is to apply a set of data gap filling strategies to develop a gap-free dataset with 15-minute observations for the sub-tropical region of Florida. Using data from the Florida Automated Weather Network (FAWN), methods of linear interpolation, trend continuation, reference to external sources, and nearest station substitution were applied to fill the data gaps depending on the extent of the gap. The outcome of this study provides continuous, publicly accessible surface meteorological observations for 30 FAWN stations at 15-minute intervals for years 2005–2020. Vasubandhu Misra Jasmeet Judge William R. Lusher Florida State University University of Florida Center for Ocean-Atmospheric Prediction Studies Read more: https://lnkd.in/ghvqCqem