The Exploitation of Satellite Data at the U.K. Met Office

Total Page:16

File Type:pdf, Size:1020Kb

The Exploitation of Satellite Data at the U.K. Met Office The Exploitation of Satellite Data at the U.K. Met Office Roger Saunders with the help of Steve English Bill Bell, Mary Forsythe, Brett Candy, James Cameron and many others © Crown copyright 2006 Page 1 Talk topics The Met Office satellite group and NWP SAF Current status of models and observation use Recent upgrades to use of satellite data Satellite data impacts Research into use of new data types Meteosat Second Generation METOP © Crown copyright 2006 Page 2 Satellite Group Head John Eyre Radiance Imagery for NWP Active sensors Data Processing Hi res models assimilation and forecasters Dave Offiler Dick Francis Bryan Conway Steve English Roger Saunders Reading SatelliteSatelliteSatelliteSatelliteNWP/nowcasting/imagery Radiance Imagery ActiveApplications ApplicationAssimilationSensing Reading Group Group Group © Crown copyright 2006 Page 3 Satellite Group Funding SA Funding 2006/07 31 Staff in total Core Govt EUMETSAT Defence Aviation ESA Climate © Crown copyright 2006 Page 4 NWP Satellite Application Facility The Met Office leads the NWP SAF In final year of initial operational phase Preparing proposal for follow-on operational phase (5 years) to start in March 2007. Major deliverables are: AAPP (ATOVS/AVHRR direct readout software) RTTOV (Fast radiative transfer model) 1DVAR (Met Office and ECMWF versions) Satellite data monitoring (Radiance, AMVs, O3) Scatterometer processor Reports on many aspects of satellite data Also involved in GRAS (GPS RO) SAF © Crown copyright 2006 Page 5 Summary of model –AIRS observations © Crown copyright 2006 Page 6 Talk topics The Met Office satellite group Current status of models and observation use Recent upgrades to use of satellite data Satellite data impacts Research into use of new data types Meteosat Second Generation METOP © Crown copyright 2006 Page 7 Met Office Operational Models : 2006 ¾Global ~40km ~50Level ¾North Atlantic/Europe 12km ~30level ¾UK 4km ~30Level ¾Re-locatable Defence and Civilian ¾Trial Ensemble (global & regional) at half horizontal resolution ¾Data assimilation 4DVar 6 hour window for global and regional models © Crown copyright 2006 Page 8 Operational data usage (Apr 2006) Observation group Observation Items used Daily extracted % used in Sub-group assimilation Ground-based TEMP T, V, RH processed to 1250 87,92,50 vertical profiles PILOT model layer average 850 92 As TEMP, but V only PROFILER As TEMP, but V only 6500 40 Satellite-based AMSU-A/B Radiances directly 430000 3 vertical profiles NOAA-15/16/18 assimilated with channel selection dependent on Aqua AIRS surface instrument and cloudiness Aircraft Manual T, V as reported with 24000 14 AIREPS duplicate checking and 185000 28 blacklist Automated AMDARS Satellite GOES 10,12 BUFR High resolution IR winds 110000 10 atmospheric Meteosat 5, 8 BUFR IR, VIS and WV winds 190000 5 IR and VIS winds motion vectors MTSAT SATOB IR and WV 4000 55 Aqua/Terra MODIS Satellite-based SSMI-13,15 In-house 1DVAR wind-speed 3000000 1 surface winds Seawinds, ERS-2 retrieval 1800000 1.5 NESDIS retrieval of ambiguous winds. Ambiguity removal in 4DVAR. Ground-based Land SYNOP Pressure only (processed to 28000 75 surface SHIP, Fixed Buoy model surface) 6700 94, 92 Pressure and wind Drifting BUOY 10000 76 © Crown copyright 2006 Pressure Page 9 Talk topics The Met Office satellite group Current status of models and observation use Recent upgrades to use of satellite data Satellite data impacts Research into use of new data types Meteosat Second Generation METOP © Crown copyright 2006 Page 10 Recent changes to use of satellite data Aqua AMSU-A replaced by NOAA-18 AMSU Better coverage with NOAA-18 Issue of Aqua AMSU-A antenna correction AIRS central fov replaced by AIRS warmest fov Reintroduction of ERS-2 scatterometer winds Meteosat-7 AMVs replaced by Meteosat-8 AMVs © Crown copyright 2006 Page 11 Satellite data delays Main run data cutoff SSMI F15 SSMI F14 SSMI F13 MODIS Terra MODIS Aqua SSMIS Max Delay QuikScat Average Delay AIRS ATOVS N18 ATOVS N16 ATOVS N15 ATOVS Aqua 0 60 120 180 240 300 360 420 480 540 Delay (minutes) © Crown copyright 2006 Page 12 Average AMSU Data Assimilated for a Main forecast Run Control Experiment N15 N16 N18 Aqua Total N15 N16 N18 Aqua Total 14000 14000 12000 12000 10000 10000 8000 8000 6000 6000 4000 4000 2000 2000 0 0 © Crown copyright 2006 Page 13 EARS-Mitigating Data Delay EARS System Overview © Crown copyright 2006 Page 14 EARS (2) EARS timeliness © Crown copyright 2006 Page 15 EARS (3) There are plans to: EARS coverage • extend coverage of EARS to the whole extra-tropical NH • develop other regional systems (e.g. S. America, Australia / NZ) © Crown copyright 2006 Page 16 Arrival Times of Data Global 109229 obs EARS 93979 Obs 100 • North Atlantic Main Run Update Run Region 90 NESDIS 25% both 100% • six-hour window EARS 75% 80 09/09/2003 09:00- 15:00 70 60 50 40 Percentage of Observations Percentage 30 20 First Overpass 10 0 09 00 10 00 11 00 12 00 13 00 14 00 15 00 16 00 17 00 18 00 © Crown copyright 2006 window Page 17 Moved to use AIRS warmest FOV Centre FOV Warmest FOV any of 9 This results in an increased coverage of AIRS clear sky radiances © Crown copyright 2006 Page 18 Removed Double Peaked AIRS Channels Channel 2107 at 2386cm-1 (4.19 microns), FWHM 1.880cm-1 The sharp, strong absorption CO2 lines cause a double peak in the Jacobian. © Crown copyright 2006 Page 19 AIRS q increments No AIRS AIRSWF © Crown copyright 2006 Page 20 Impact on AMSU-B Channels 183 ± 7 GHz First Iteration No AIRS AIRSWF Final Iteration No AIRS AIRSWF © Crown copyright 2006 Page 21 Summary Assimilating AIRS leads to significant humidity changes. All AIRS trials show improved fits to SSMI TCWV (not assimilated) and all AMSU-B channels. An improvement to RH is not confirmed by sondes, where no particular effect is apparent. We have not seen a big improvement in forecasts going from AIRS to AIRSWF. © Crown copyright 2006 Page 22 What is the NWP SAF AMV monitoring? NWP SAF –Numerical Weather Prediction Satellite Application Facility A EUMETSAT-funded initiative, led by the Met Office, with partners ECMWF, KNMI and Météo-France Aim to improve the benefits derived by European National Met. Services from NWP by developing techniques for more effective use of satellite data and to prepare for effective exploitation of new data/products. AMV Monitoring Displays comparable AMV monitoring output from different NWP centres in order to help identify and partition error contributions from AMVs and NWP models. Analysis reports produced periodically (planned every 2 years to coincide with winds workshops). Intended to stimulate discussion and to lead to improvements in AMV derivation and AMV use in NWP. http://ww© Crown copyrightw. 2006metoffice.gov.uk/research/interproj/nwpsaf/satwind_report Page 23 Data used - Mar 2006 MODIS polar winds (TERRA and AQUA) 60N equator 60S GOES-10 GOES-12 Meteosat-8 Meteosat-5 MTSAT-1R 1. 8th Feb 05 - Introduce NESDIS MODIS polar winds 2. 14th Jun 05 – GOES SATOB IR -> GOES BUFR IR SATOB and cloudy WV st BUFR 3. 1 Sep 05 – start using MTSAT-1R SATOB th © Crown copyright 2006 4. 14 Mar 06 – Meteosat-7 -> Meteosat-8 Page 24 Meteosat-7 Meteosat-8 Replace Meteosat-7 IR, WV and VIS with Meteosat-8 IR10.8, WV7.3, HRVIS and VIS0.8 using same QC as applied to Meteosat-7 Root mean square vector difference 100-400 hPa 400-700 hPa 700-1000 hPa Met-7 IR Met-8 IR 10.8 Impact neutral in Jul-Aug and moderately positive in Dec-Jan. Main benefit from tropical wind fields (W250 and W850) and southern hemisphere PMSL (against both observations and analyses). Few forecast parameters improved or degraded by more than 2%. © Crown copyright 2006 Page 25 MODIS winds © Crown copyright 2006 Page 26 Forecast error evolution Aug 14th, 2004 500 hPa geopotential height CONTROL MODIS T+24 T+48 T+24 T+48 T+72 T+96 T+72 T+96 T+120 T+144 T+120 T+144 © Crown copyright 2006 Page 27 AMVs Why do we struggle to see impact from AMVs? Is it poor height assignment of some winds? We are starting to investigate this Discussed at IWW in Beijing © Crown copyright 2006 Page 28 Comparison to model best-fit pressure 2 2 Vector Differencei = √((ObU – BgUi) + (ObV – BgVi) ) 100 200 Model best-fit at minimum in vector 300 difference profile. 400 AMV pressure and model best-fit pressure 500 agree well in this case. 600 Pressure (hPa) 700 u component 800 v component Diff 900 1000 -20 0 20 40 60 © Crown copyright 2006 m/s Page 29 Case studies – Sahara 8th Dec MSG wind height (hPa) MSG wind – model best fit (hPa) MODIS Cloud Top Pressure (hPa) From 7th December 21:00 UTC to 8th December 2005 3:00UTC (night time) Can also compare to other cloud top pressure products © Crown copyright 2006 Page 30 Talk topics The Met Office satellite group Current status of models and observation use Recent upgrades to use of satellite data Satellite data impacts Research into use of new data types Meteosat Second Generation METOP © Crown copyright 2006 Page 31 DirectDirect radianceradiance assimilationassimilation ATOVSATOVS && 3D-var3D-var © Crown copyright 2006 Page 32 Comparison of impact of observing sounding data 30 No Satellite Losing all microwave sounders Losing all infrared sounder Losing all radiosonde T, q and u Global degradation Losing all radiosonde T 01020 and q Analysis Ten years ago? TOVS NESDIS retrievals, AMV, © Crown copyright 2006more but lower quality radiosondes Page 33 Forecast skill vs time More forecast busts without satellite data © Crown copyright 2006 Page 34 Talk topics The Met Office satellite group Current status of models and observation use Recent upgrades to use of satellite data Satellite data impacts Research into use of new data types Meteosat Second Generation METOP © Crown copyright 2006 Page 35 Work in progress….
Recommended publications
  • Scientific Collaborations (2014-2019)
    Scientific Collaborations (2014-2019) NOAA ● National Environmental Satellite, Data and Information Service ○ Center for Satellite Applications and Research ○ CoastWatch ○ National Centers for Environmental Information ○ OceanWatch ● National Marine Fisheries Service ○ Alaska Fisheries Science Center ○ Northeast Fisheries Science Center ○ Northwest Fisheries Science Center ○ Pacific Islands Fisheries Science Center ○ Office of Science and Technology ○ Southeast Fisheries Science Center ○ Southeast Regional Office ○ Southwest Fisheries Science Center ● National Ocean Service ○ U.S. Integrated Ocean Observing System ■ Caribbean Regional Association for Coastal Ocean Observing (CARICOOS) ■ Gulf of Mexico Coastal Ocean Observing System (GCOOS) ● Gulf of Mexico Coastal Acidification Network (GCAN) ■ Mid-Atlantic Coastal Ocean Observing System (MARACOOS) ■ Pacific Islands Ocean Observing System (PacIOOS) ■ Southeast Coastal Ocean Observing Regional Association (SECOORA) ● Southeast Ocean and Coastal Acidification Network (SOCAN) ○ National Centers for Coastal Ocean Science ○ National Geodetic Survey ○ Office of National Marine Sanctuaries ■ Florida Keys National Marine Sanctuary ■ Flower Gardens Bank National Marine Sanctuary ■ National Marine Sanctuary of American Samoa ■ Olympic Coast National Marine Sanctuary ○ Office of Response and Restoration ● National Weather Service ○ Climate Prediction Center ○ Environmental Modeling Center ○ National Centers for Environmental Prediction ○ National Data Buoy Center ○ National Hurricane Center 1 ○ Office
    [Show full text]
  • List of Participants
    WMO Sypmposium on Impact Based Forecasting and Warning Services Met Office, United Kingdom 2-4 December 2019 LIST OF PARTICIPANTS Name Organisation 1 Abdoulaye Diakhete National Agency of Civil Aviation and Meteorology 2 Angelia Guy National Meteorological Service of Belize 3 Brian Golding Met Office Science Fellow - WMO HIWeather WCRP Impact based Forecast Team, Korea Meteorological 4 Byungwoo Jung Administration 5 Carolina Gisele Cerrudo National Meteorological Service Argentina 6 Caroline Zastiral British Red Cross 7 Catalina Jaime Red Cross Climate Centre Directorate for Space, Security and Migration Chiara Proietti 8 Disaster Risk Management Unit 9 Chris Tubbs Met Office, UK 10 Christophe Isson Météo France 11 Christopher John Noble Met Service, New Zealand 12 Dan Beardsley National Weather Service NOAA/National Weather Service, International Affairs Office 13 Daniel Muller 14 David Rogers World Bank GFDRR 15 Dr. Frederiek Sperna Weiland Deltares 16 Dr. Xu Tang Weather & Disaster Risk Reduction Service, WMO National center for hydro-meteorological forecasting, Viet Nam 17 Du Duc Tien 18 Elizabeth May Webster South African Weather Service 19 Elizabeth Page UCAR/COMET 20 Elliot Jacks NOAA 21 Gerald Fleming Public Weather Service Delivery for WMO 22 Germund Haugen Met No 23 Haleh Kootval World Bank Group 24 Helen Bye Met Office, UK 25 Helene Correa Météo-France Impact based Forecast Team, Korea Meteorological 26 Hyo Jin Han Administration Impact based Forecast Team, Korea Meteorological 27 Inhwa Ham Administration Meteorological Service
    [Show full text]
  • SRNWP-V Programme: a Comparison of Regional European Forecast Models
    SRNWP-V programme: a comparison of regional European forecast models Clive Wilson , Marion Mittermaier Sep 2011 © Crown copyright Met Office Outline & motivation • Short Range Numerical Weather Prediction – EUMETNET programme • Desire to benchmark operational models cf CBS global exchange • Phase 1 2009-2010 • Establish framework, recommend methods • Phase 2 2011-2012 • Continue comparison, more parameters • Use radar/extra observations • Extremal measures © Crown copyright Met Office EUMETNET/SRNWP programme - Deliverables • D1: Operational verification comparison of deterministic forecasts from one version of each of the 4 regional models of Europe (available for all the participating members) • D2: Additional intercomparison of other versions of the consortia models including high resolution models • D3: Inventory and recommendations of “new” scale-selective verification methods. • D4: Catalogue of sources of non-GTS data • D5 Exchange methods and code for verification of severe weather forecasts © Crown copyright Met Office 15km 12km 7km 10km 5 km (10km) Hirlam UM COSMO ALADIN Aladin-Lace © Crown copyright Met Office Parameter Scores Mean sea level mean bias and root mean pressure square errors 2m temperature Bias, rmse 2m relative humidity Bias, rmse mean bias speed error 10m winds and root mean square vector wind error equitable threat score and 6 hourly total frequency bias for 0.5, precipitation 1.0 and 4.0 mm 6h -1 © Crown copyright Met Office Key Model Label Hirlam reference run by FMI UK-FI Aladin-France run by Meteo-France
    [Show full text]
  • Magazine Issue 35 | Improvements to the Seasonal Forecast System and the New UK Climate Projections (UKCP18) Which Come out Next Year
    Barometer Magazine issue 35 | www.metoffice.gov.uk improvements to the seasonal forecast system and the new UK Climate Projections (UKCP18) which come out next year. I also refocused the climate science programme Professor Stephen onto both science and services, and substantially increased Belcher, Met Office Chief our international work, for example through the Climate Scientist, describes his Science for Service Partnership China (CSSP China). passion for his new role Capitalising on the new supercomputer and work addressing the Our new supercomputer was delivered ahead of schedule challenges of big data which has meant that many of the latest science upgrades and climate change. are now going operational and are helping to improve our forecasts (page 19). Leading science A new supercomputer also means huge volumes of data. July 2017 Now, data is one thing, but information is another, so we are Barometer is a controlled circulation magazine looking at intelligent ways of creating useful information distributed free of charge to decision-makers in to services government, science and commerce, for whom and extracting value from that data (page 4). That is where weather and climate information has an impact. the science to service aspect comes in. Improvements to Product information is correct at the time of eing Chief Scientist at the Met Office is a wonderful our weather and climate models will enable development publication but may be subject to change. job because of the broad range of science done of better services, particularly relevant in our support of the For queries about Barometer contact: in the Met Office, as well as the world-leading scientists Government’s emerging Industrial Strategy (page 7) and in Jon Stanford who produce it.
    [Show full text]
  • Public Weather Service Value for Money Review
    Public Weather Service Value for Money Review March 2015 Mike Gray Public Weather Service Customer Group Secretariat Page 1 of 25 Public Weather Service Value for Money Review Executive Summary Through analysing existing studies and literature on the economic value of weather forecasts, and using up to date figures, this review concludes with high confidence that the benefits of the Public Weather Service (PWS) to the UK are very likely to exceed £1bn per annum, and are likely to be close to £1.5bn per annum. This is consistent with the findings of the previous value for money study prepared for the PWS Customer Group (PWSCG) by PA from 2007 which assessed the economic benefits of the PWS at £614m per annum and, given its limited scope, considered the benefits to be many times that figure. Sectors considered in the review were the perceived value to the public (which had an estimated benefit of £480m per annum), value to aviation (£400m per annum), added value to other sectors of the economy (£400m per annum), storm damage avoidance (£80m per annum), value to land transport (£100m per annum) and flood damage avoidance (£64m per annum). Other benefits included the hosting of the European Centre for Medium-range Weather Forecasting (ECMWF) in the UK (£60m per annum) and business of over €200m for the UK space industry by being able to bid for EUMETSAT (the European Organisation for the Exploitation of Meteorological Satellites) contracts by virtue of UK membership paid for by the PWS. It is estimated that the PWS contributes to reducing deaths from high impact weather by many tens per year, and many more during individual severe events such as North Sea coastal flooding.
    [Show full text]
  • Advanced GNSS Tropospheric Products for Monitoring Severe
    Advanced GNSS Tropospheric Products for Monitoring Severe Weather Events and Climate Jonathan Jones • Guergana Guerova Jan Douša • Galina Dick • Siebren de Haan Eric Pottiaux • Olivier Bock • Rosa Pacione Roeland van Malderen Editors Advanced GNSS Tropospheric Products for Monitoring Severe Weather Events and Climate COST Action ES1206 Final Action Dissemination Report Funded by the Horizon 2020 Framework Programme of the European Union Editors Jonathan Jones Guergana Guerova Met Office Physics Faculty, Department of Meteorology and Exeter, UK Geophysics Sofia University “St. Kliment Ohridski” Jan Douša Sofia, Bulgaria Geodetic Observatory Pecný, RIGTC Ondřejov, Czech Republic Galina Dick GFZ German Research Centre for Geosciences Siebren de Haan Helmholtz Centre Potsdam Royal Netherlands Meteorological Institute Potsdam, Germany De Bilt, The Netherlands Eric Pottiaux Olivier Bock Royal Observatory of Belgium IGN Institut national de l’information Brussels, Belgium géographique et forestière Paris, France Rosa Pacione e-GEOS/Centro di Geodesia Spaziale-Agenzia Roeland van Malderen Spaziale Italiana Royal Meteorological Institute (RMI) Matera, MT, Italy Brussels, Belgium This publication is based upon work from COST Action ES1206: Advanced Global Navigation Satellite Systems tropospheric products for monitoring severe weather events and climate, supported by COST (European Cooperation in Science and Technology). www.cost.eu COST (European Cooperation in Science and Technology) is a funding agency for research and innovation networks. Our Actions help connect research initiatives across Europe and enable scientists to grow their ideas by sharing them with their peers. This boosts their research, career and innovation. ISBN 978-3-030-13900-1 ISBN 978-3-030-13901-8 (eBook) https://doi.org/10.1007/978-3-030-13901-8 © Springer Nature Switzerland AG 2020 This work is subject to copyright.
    [Show full text]
  • Draft List of Participants
    Draft List of Participants 24th session of the Atmospheric Observation Panel for Climate (AOPC-24) Ms Imke Durre Mr Rainer Hollmann Center for Weather and Climate Deutscher Wetterdienst NOAA's National Centers for Environmental Offenbach, Germany Information (NCEI) Asheville, NC, United States Mr Kenneth Holmlund Mr Robert H. Holzworth European Organisation for the Exploitation of University of Washington Meteorological Satellites (EUMETSAT) Seattle, WA, United States Darmstadt, Germany Mr Dale F. Hurst Ms Elizabeth Kent NOAA Earth System Research Laboratory University of Southampton Waterfront Boulder, CO, United States Campus Southampton, United Kingdom Mr Shinya Kobayashi Mr Paolo Laj Japan Meteorological Agency Université Grenoble Alpes Tokyo, Japan Saint-Martin-d'Hères, France Mr Christian Lanconelli Ms Johanna Tamminen European Commission, Joint Research Centre Finnish Meteorological Institute Ispra, Italy Helsinki, Finland Mr Peter Thorne Mr Peng Zhang National University of Ireland Maynooth China Meteorological Administration Maynooth, Ireland National Satellite Meteorological Center Beijing, China 22nd session of the Ocean Observations Panel for Physics and Climate (OOPC-22) Mr Nic Bax Ms Maria Paz Chidichimo CSIRO Oceans and Atmosphere Universidad de Buenos Aires Hobart, Australia Buenos Aires, Argentina OOPC OOPC Ms Meghan Cronin Mr Masao Ishi National Oceanic and Atmospheric Japan Meteorological Agency Administration Meteorological Research Institute Seattle, WA, United States Tsukuba, Japan Mr Johannes Karstensen Ms Marjolaine
    [Show full text]
  • The Public Weather Service's Contribution to the UK Economy
    Met Office The Public Weather Service’s contribution to the UK economy May 2007 “The Met Office is a big success story. You are world leaders in your field. Renowned and respected throughout the world to the extent you’re practically a global brand. We in the MoD are absolutely determined to make sure you stay that way.” Under Secretary of State for Defence “The Met Office have set up a unit internally which is excellent at providing emergency response data, critical to our ability to plan for a nuclear incident.” Defra “The independent capability of the Met Office provides a latitude in decision making for the MoD that otherwise would not be possible.” MoD “The work of the Met Office based on PWS’ model allows the UK to punch above its weight in terms of climate change insight.” Defra “The work being carried out by the Met Office is integral to the ongoing success of the National Traffic Control Centre, reducing loss of life, injury, and damage to property.” Highways Agency “The Met Office bring a clear, well considered and precise view to the table. This was particularly evident in the Buncefield incident which allowed our team to make appropriate decisions at critical times.” Cabinet Office The Met Office's model is great. It provides an invaluable input to our preparations for dealing with bluetongue - enabling us to have an idea of when the midges might arrive on these shores.” Contingency Planning Director, State Veterinary Service “The Severe Weather Warnings issued by you last week made sure the country was able to prepare and plan.
    [Show full text]
  • Review of Met Office Weather Forecast Accuracy
    REVIEW OF MET OFFICE WEATHER FORECAST ACC URACY Weather Forecasts National Grid currently procures its main weather forecasts for electricity demand forecasting from the Met Office. National Grid is currently in the middle of a three year contract for these forecasts. The Met Office won the contract via an open tender process run by National Grid in accordance with all National Grid’s standard procurement policies. As part of the tender assessment process, the accuracy of trial forecasts provided by different companies tendering for the contract were assessed. During this process the Met Office was found to be the most accurate of the companies that tendered for the contract. The Met Office state on their website that “The World Meteorological Organization compares similar statistics among national meteorological services around the world. These show that the Met Office is consistently one of the top two operational services in the world.” (http://www.metoffice.gov.uk/about-us/who/accuracy/forecasts) Use of Weather Forecasts in Electricity Demand Forecasts Weather forecasts are used in three areas of electricity demand forecasting. The first area is in forecasting consumer demand. People are more likely to put heating on if it is cold, or turn air conditioning on if it is hot, or turn the lights on earlier if it is dull and overcast. National Grid derive correlations between demand at different cardinal points of the day and a variety of weather variables, primarily average temperature over last four hours, average temperature at a specific time of day over the last few days, weighted towards most recent temperatures, wind speed and light levels.
    [Show full text]
  • Helping You Understand the Facts About Weather Forecasting Forecasting the Weather Is Essential to Help You Prepare for the Best and the Worst of Our Climate
    Clarity Helping you understand the facts about weather forecasting Forecasting the weather is essential to help you prepare for the best and the worst of our climate. Met Office forecasters work 24/7, 365 days of the year, using one of the world’s largest supercomputers to predict the weather for hours, days, weeks, seasons and even years ahead. Operating as part of an international network to collect weather data, we also partner with research institutes worldwide to develop the very latest techniques. We strive to ensure that you always have the very best advice in print, on air, and via the web. Our forecasts for tomorrow are right six times out of seven. Here you will find some facts about weather forecasting – an insight into our foresight. Weather forecasting — the big picture 01 Observations are essential FACT 1 — Before we forecast the weather, we collect observations. Observations Assimilation Observations of the weather are made Next we turn observational data into a 24 hours a day, all over the world. numerical representation of the current The main observations are from weather atmospheric conditions. This process is satellites, balloons, land­based known as assimilation. instruments, ships, buoys and aircraft. Small changes in atmospheric conditions Each day, the Met Office uses around lead to very different weather patterns, half a million observations of so it’s vital that the current state of the temperature, pressure, wind speed and atmosphere is represented as accurately direction, humidity and many other as possible. properties to provide the starting conditions of our weather forecast model. We continually update our Copyright European Space Agency (ESA), D.
    [Show full text]
  • Mahony, Elizabeth, Ed. a South Asia Curriculum
    DOCUMENT RESUME ED 421 440 SO 029 232 AUTHOR Greenberg, Hazel Sara; Mahony, Elizabeth, Ed. TITLE A South Asia Curriculum: Teaching about India. INSTITUTION American Forum for Global Education, New York, NY. SPONS AGENCY Department of Education, Washington, DC. ISBN ISBN-09-44675-52-2 PUB DATE 1994-00-00 NOTE 443p. AVAILABLE FROM American Forum for Global Education, 45 John St., Suite 908, New York, NY 10038; telephone: 212-732-8606 ($60). PUB TYPE Guides - Non-Classroom (055) EDRS PRICE MF01/PC18 Plus Postage. DESCRIPTORS Area Studies; *Asian Studies; Cultural Awareness; *Culture; Foreign Countries; Global Education; *Indians; Instructional Materials; Multicultural Education; *Non Western Civilization; Secondary Education; Social Studies; State Curriculum Guides; *World History IDENTIFIERS *India; New York ABSTRACT This curriculum evolved as an interactive cooperation between South Asian scholars and an educator/curriculum writer. The materials are congruent with the mandates of the New York State Global Studies program. Each lesson provides focus questions, performance objectives, procedures with accompanying student materials, and a summary/application. Teaching strategies also are included. Each student worksheet is keyed to thelesson with the same title and sequentially numbered worksheets. The teacher'sguide is divided into the following themes: (1) "The Physical/Historical Setting"; (2) "The Dynamics of Change"; (3) "Contemporary South Asian Nations and Cultures"; (4) "Economic Development in South Asia"; and (5)"South Asia in the
    [Show full text]
  • ECMWF, Met Office, UKSA
    Memo From: UK Space Agency, Met Office, ECMWF To: Ofcom Subject: Discussion of attenuation 175-191 GHz Date: 1 July 2020 Executive Summary The conclusion of this new study is that it has been determined that the protection provided by the additional path losses due to water vapour were over-estimated in the original Ofcom study. As a consequence, the proposed power limits and mitigation do not provide the expected level of protection to passive Earth Observation in the 175-191 GHz band and measurements from the AMSU-B and MHS instruments, which are used operationally for weather forecasting, including extreme events, would be at risk. In order to fully protect these measurements, we conclude that an additional 7 dB reduction in interference levels would be required. Introduction The recent Ofcom consultation “Supporting innovation in the 100-200 GHz range” focussed on sharing studies for bands centres on 118 and 183 GHz that are used by operational weather forecast and climate services. In undertaking technical studies on whether sharing is possible with the existing services using these bands, Ofcom made a number of assumptions. Of particular importance for the bands between 175-191 GHz, was that a global mean atmospheric profile was used to calculate atmospheric attenuation, to calculate how much an emission at the surface is reduced due to atmospheric absorption before reaching a sensor on a satellite. On examining this assumption, we note that this does not cater for cases where the atmosphere is much drier than the global mean profile. The strongest test would be to repeat the calculations assuming no atmospheric water vapour, because that is by construction the most extreme case possible (water vapour can’t go negative).
    [Show full text]