Methods of Oabservation at Sea
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Comparing Historical and Modern Methods of Sea Surface Temperature
EGU Journal Logos (RGB) Open Access Open Access Open Access Advances in Annales Nonlinear Processes Geosciences Geophysicae in Geophysics Open Access Open Access Natural Hazards Natural Hazards and Earth System and Earth System Sciences Sciences Discussions Open Access Open Access Atmospheric Atmospheric Chemistry Chemistry and Physics and Physics Discussions Open Access Open Access Atmospheric Atmospheric Measurement Measurement Techniques Techniques Discussions Open Access Open Access Biogeosciences Biogeosciences Discussions Open Access Open Access Climate Climate of the Past of the Past Discussions Open Access Open Access Earth System Earth System Dynamics Dynamics Discussions Open Access Geoscientific Geoscientific Open Access Instrumentation Instrumentation Methods and Methods and Data Systems Data Systems Discussions Open Access Open Access Geoscientific Geoscientific Model Development Model Development Discussions Open Access Open Access Hydrology and Hydrology and Earth System Earth System Sciences Sciences Discussions Open Access Ocean Sci., 9, 683–694, 2013 Open Access www.ocean-sci.net/9/683/2013/ Ocean Science doi:10.5194/os-9-683-2013 Ocean Science Discussions © Author(s) 2013. CC Attribution 3.0 License. Open Access Open Access Solid Earth Solid Earth Discussions Comparing historical and modern methods of sea surface Open Access Open Access The Cryosphere The Cryosphere temperature measurement – Part 1: Review of methods, Discussions field comparisons and dataset adjustments J. B. R. Matthews School of Earth and Ocean Sciences, University of Victoria, Victoria, BC, Canada Correspondence to: J. B. R. Matthews ([email protected]) Received: 3 August 2012 – Published in Ocean Sci. Discuss.: 20 September 2012 Revised: 31 May 2013 – Accepted: 12 June 2013 – Published: 30 July 2013 Abstract. Sea surface temperature (SST) has been obtained 1 Introduction from a variety of different platforms, instruments and depths over the past 150 yr. -
The Unnamed Atlantic Tropical Storms of 1970
944 MONTHLY WEATHER REVIEW Vol. 99, No. 12 UDC 551.515.23:661.507.35!2:551.607.362.2(261) “1970.08-.lo” THE UNNAMED ATLANTIC TROPICAL STORMS OF 1970 DAVID B. SPIEGLER Allied Research Associates, Inc., Concord, Mass. ABSTRACT A detailed analysis of conventional and aircraft reconnaissance data and satellite pictures for two unnamed Atlantic Ocean cyclones during 1970 indicates that the stqrms were of tropical nature and were probably of at least minimal hurricane intensity for part of their life history. Prior to becoming a hurricane, one of the storms exhibited characteristics not typical of any of the recognized classical cyclone types [i.e., tropical, extratropical, and subtropical (Kona)]. The implications of this are discussed and the concept of semitropical cyclones as a separate cyclone category is advanced. 6. INTRODUCTION ing recognition of hybrid-type storms provides additional support for the recommendation. During the 1970 tropical cyclone season, tn7o storms occurred that were not given names at the time. The 2. UNNAMED STORM NO. I-AUG. Q3-$8, 6970 National Hurricane Center (NHC) monitored their prog- ress and issued bulletins throughout their life history but A mell-organized tropical disturbance noted on satellite they mere not officially recognized as tropical cyclones of pictures during August 8, south of the Cape Verde Islands tropical storm or hurricane intensity. In their annual post- in the far eastern tropical Atlantic, intensified to ti strong season summary of the hurricane season, NHC discusses depression as it moved westmarcl. On Thursday, August 13, these storms in some detail (Simpson and Pelissier 1971) some further intensification of the system appeared to be but thej- are not presently included in the official list of taking place while the depression was about 250 mi 1970 tropical storms. -
Aerodrome Actual Weather – METAR Decode
Aerodrome Actual Weather – METAR decode Code element Example Decode Notes 1 Identification METAR — Meteorological Airfield Report, SPECI — selected special (not from UK civil METAR or SPECI METAR METAR aerodromes) Location indicator EGLL London Heathrow Station four-letter indicator 'ten twenty Zulu on the Date/Time 291020Z 29th' AUTO Metars will only be disseminated when an aerodrome is closed or at H24 aerodromes, A fully automated where the accredited met. observer is on duty break overnight. Users are reminded that reports AUTO report with no human of visibility, present weather and cloud from automated systems should be treated with caution intervention due to the limitations of the sensors themselves and the spatial area sampled by the sensors. 2 Wind 'three one zero Wind degrees, fifteen knots, Max only given if >= 10KT greater than the mean. VRB = variable. 00000KT = calm. 31015G27KT direction/speed max twenty seven Wind direction is given in degrees true. knots' 'varying between two Extreme direction 280V350 eight zero and three Variation given in clockwise direction, but only when mean speed is greater than 3 KT. variance five zero degrees' 3 Visibility 'three thousand two Prevailing visibility 3200 0000 = 'less than 50 metres' 9999 = 'ten kilometres or more'. No direction is required. hundred metres' Minimum visibility 'Twelve hundred The minimum visibility is also included alongside the prevailing visibility when the visibility in one (in addition to the 1200SW metres to the south- direction, which is not the prevailing visibility, is less than 1500 metres or less than 50% of the prevailing visibility west' prevailing visibility. A direction is also added as one of the eight points of the compass. -
A User's Guide to Co-Ops Visibility Sensor
A USER’S GUIDE TO CO-OPS VISIBILITY SENSOR OBSERVATIONS The American Meteorological Society defines visibility as “the greatest distance in a given direction at which it is just possible to see and identify with the unaided eye (a) in the daytime, a prominent dark object against the sky at the horizon, and (b) at night, a known, preferably unfocused, moderately intense light source. A wide variety of factors contribute to changing this distance. CO-OPS deploys automated visibility sensors at locations selected in concert with supporting PORTS® partners. The sites must be both acceptable for sensor operation and useful for the user. Because fog can be patchy, it is important for users to understand how to interpret the disseminated data. The sensors used by CO-OPS optically examine a small volume of air to determine the scattering characteristics of the air parcel, the most common technique used to measure visibility. Scatter can be caused by fog, smog, dust – any particles in the air will suffice. When the scatter is small the visibility is good, while large scatter means the visibility at the location of the sensor is poor. It is important to realize that the visibility range provided by the sensor, more correctly known as Meteorological Optical Range (MOR), is a measurement made at a single point. When fog or other scattering particles are uniformly widespread it may be reasonable to presume the MOR applies over large distances, ie. a reading of 5 nautical miles means a person will see sufficiently large objects at that distance. But such a presumption may not be valid, and the sensor has no way of observing MOR except at the deployment site. -
ESSENTIALS of METEOROLOGY (7Th Ed.) GLOSSARY
ESSENTIALS OF METEOROLOGY (7th ed.) GLOSSARY Chapter 1 Aerosols Tiny suspended solid particles (dust, smoke, etc.) or liquid droplets that enter the atmosphere from either natural or human (anthropogenic) sources, such as the burning of fossil fuels. Sulfur-containing fossil fuels, such as coal, produce sulfate aerosols. Air density The ratio of the mass of a substance to the volume occupied by it. Air density is usually expressed as g/cm3 or kg/m3. Also See Density. Air pressure The pressure exerted by the mass of air above a given point, usually expressed in millibars (mb), inches of (atmospheric mercury (Hg) or in hectopascals (hPa). pressure) Atmosphere The envelope of gases that surround a planet and are held to it by the planet's gravitational attraction. The earth's atmosphere is mainly nitrogen and oxygen. Carbon dioxide (CO2) A colorless, odorless gas whose concentration is about 0.039 percent (390 ppm) in a volume of air near sea level. It is a selective absorber of infrared radiation and, consequently, it is important in the earth's atmospheric greenhouse effect. Solid CO2 is called dry ice. Climate The accumulation of daily and seasonal weather events over a long period of time. Front The transition zone between two distinct air masses. Hurricane A tropical cyclone having winds in excess of 64 knots (74 mi/hr). Ionosphere An electrified region of the upper atmosphere where fairly large concentrations of ions and free electrons exist. Lapse rate The rate at which an atmospheric variable (usually temperature) decreases with height. (See Environmental lapse rate.) Mesosphere The atmospheric layer between the stratosphere and the thermosphere. -
Automated Underway Oceanic and Atmospheric Measurements from Ships
AUTOMATED UNDERWAY OCEANIC AND ATMOSPHERIC MEASUREMENTS FROM SHIPS Shawn R. Smith (1), Mark A. Bourassa (1), E. Frank Bradley (2), Catherine Cosca (3), Christopher W. Fairall (4), Gustavo J. Goni (5), John T. Gunn (6), Maria Hood (7), Darren L. Jackson (8), Elizabeth C. Kent (9), Gary Lagerloef (6), Philip McGillivary (10), Loic Petit de la Villéon (11), Rachel T. Pinker (12), Eric Schulz (13), Janet Sprintall (14), Detlef Stammer (15), Alain Weill (16), Gary A. Wick (17), Margaret J. Yelland (9) (1) Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL 32306-2840, USA, Emails: [email protected], [email protected] (2) CSIRO Land and Water, PO Box 1666, Canberra, ACT 2601, AUSTRALIA, Email: [email protected] (3) NOAA/PMEL, 7600 Sand Point Way NE, Seattle, WA 98115, USA, Email: [email protected] (4) NOAA/ESRL/PSD, R/PSD3, 325 Broadway, Boulder, CO 80305-3328, USA, Email: [email protected] (5) USDC/NOAA/AOML/PHOD, 4301 Rickenbacker Causeway, Miami, FL 33149, USA, Email: [email protected] (6) Earth and Space Research, 2101 Fourth Ave., Suite 1310, Seattle, WA, 98121, USA, Emails: [email protected], [email protected] (7) Intergovernmental Oceanographic Commission UNESCO, 1, rue Miollis, 75732 Paris Cedex 15, FRANCE, Email: [email protected] (8) Cooperative Institute for Research in Environmental Sciences, NOAA/ESRL/PSD, 325 Broadway, R/PSD2, Boulder, CO 80305, USA, Email: [email protected] (9) National Oceanography Centre, European Way, Southampton, SO14 3ZH, UK, Emails: [email protected], -
Impact of Meteorology and Atmospheric Pollutants on Visibility
Atmos. Chem. Phys., 17, 2085–2101, 2017 www.atmos-chem-phys.net/17/2085/2017/ doi:10.5194/acp-17-2085-2017 © Author(s) 2017. CC Attribution 3.0 License. 60 years of UK visibility measurements: impact of meteorology and atmospheric pollutants on visibility Ajit Singh, William J. Bloss, and Francis D. Pope School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK Correspondence to: Francis D. Pope ([email protected]) Received: 16 August 2016 – Discussion started: 26 August 2016 Revised: 6 January 2017 – Accepted: 17 January 2017 – Published: 13 February 2017 Abstract. Reduced visibility is an indicator of poor air qual- in aerosol particle properties. This approach may help con- ity. Moreover, degradation in visibility can be hazardous to strain global model simulations which attempt to generate human safety; for example, low visibility can lead to road, aerosol fields for time periods when observational data are rail, sea and air accidents. In this paper, we explore the com- scarce or non-existent. Both the measured visibility and the bined influence of atmospheric aerosol particle and gas char- modelled aerosol properties reported in this paper highlight acteristics, and meteorology, on long-term visibility. We use the success of the UK’s Clean Air Act, which was passed in visibility data from eight meteorological stations, situated in 1956, in cleaning the atmosphere of visibility-reducing pol- the UK, which have been running since the 1950s. The site lutants. locations include urban, rural and marine environments. Most stations show a long-term trend of increasing visi- bility, which is indicative of reductions in air pollution, es- pecially in urban areas. -
P2.55 Visibility Versus Precipitation Rate and Relative Humidity
P2.55 VISIBILITY VERSUS PRECIPITATION RATE AND RELATIVE HUMIDITY I. Gultepe1,2, and G. A. Isaac1 1Cloud Physics and Severe Weather Research Section, Science and Technology Branch, Environment Canada Toronto, Ontario, M3H 5T4, Canada 1. INTRODUCTION 2. OBSERVATIONS The purpose of this work is to analyze the The main observations used in the analysis were relationships between visibility and precipitation the precipitation rates for rain and snow from the rate (PR), and visibility and relative humidity Desert Research Institute (DRI) manufactured with respect to water (RHw), obtained from hot plates (Rasmussen et al., 2002), the surface measurements. Precipitation Occurrence Sensor System (POSS) (Sheppard, 1990), and from the Visalia FD12P, Presently, visibility parameterizations related to ice and liquid particle characteristics from the precipitation type in forecast models are not optical probes, visibility from the Belfort adequate because they represent mid-latitude visibility meter, the Vaisala FD12P and from the cloud systems (Stoelinga, 1999). Some previous fog measuring device (FMD), and relative works have shown that particle phase is an humidity and temperature from the Campbell important factor in the visibility calculation but Scientific instruments. Details on these usually it is ignored (Rasmussen et al., 1999). instruments can be found in Isaac et al. (2005) The relative humidity with respect to water in and Gultepe et al. (2006). forecast models is used for visibility parameterization but changes have been 3. ANALYSIS AND RESULTS continuously made because of the uncertainty in The data were collected during the Alliance Icing accurate RHw measurements (Smirnova et al., Research Study (AIRS 2) which was conducted 2000). -
A Review of Ocean/Sea Subsurface Water Temperature Studies from Remote Sensing and Non-Remote Sensing Methods
water Review A Review of Ocean/Sea Subsurface Water Temperature Studies from Remote Sensing and Non-Remote Sensing Methods Elahe Akbari 1,2, Seyed Kazem Alavipanah 1,*, Mehrdad Jeihouni 1, Mohammad Hajeb 1,3, Dagmar Haase 4,5 and Sadroddin Alavipanah 4 1 Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran 1417853933, Iran; [email protected] (E.A.); [email protected] (M.J.); [email protected] (M.H.) 2 Department of Climatology and Geomorphology, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar 9617976487, Iran 3 Department of Remote Sensing and GIS, Shahid Beheshti University, Tehran 1983963113, Iran 4 Department of Geography, Humboldt University of Berlin, Unter den Linden 6, 10099 Berlin, Germany; [email protected] (D.H.); [email protected] (S.A.) 5 Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research UFZ, 04318 Leipzig, Germany * Correspondence: [email protected]; Tel.: +98-21-6111-3536 Received: 3 October 2017; Accepted: 16 November 2017; Published: 14 December 2017 Abstract: Oceans/Seas are important components of Earth that are affected by global warming and climate change. Recent studies have indicated that the deeper oceans are responsible for climate variability by changing the Earth’s ecosystem; therefore, assessing them has become more important. Remote sensing can provide sea surface data at high spatial/temporal resolution and with large spatial coverage, which allows for remarkable discoveries in the ocean sciences. The deep layers of the ocean/sea, however, cannot be directly detected by satellite remote sensors. -
Section 5 Development of and Studies with Regional and Smaller-Scale
Section 5 Development of and studies with regional and smaller-scale atmospheric models, regional ensemble forecasting Verification of mesoscale forecasts by a high resolution non-hydrostatic model at JMA Kohei Aranami and Tomonori Segawa Numerical Prediction Division, 1-3-4 Otemachi, Chiyoda-ku, Tokyo 100-8122, Japan E-mail: [email protected], [email protected] 1 Introduction etary boundary layer is reduced to be half of 10km- Japan Meteorological Agency (JMA) started op- NHM. The horizontal mixing length is reduced to erating a mesoscale numerical weather prediction the same value of that of vertical. system for disaster prevention in March 2001 us- The Kessler-type conversion threshold from con- ing a hydrostatic model (MSM) with a horizon- vective condensate to precipitation is increased tal resolution 10 km. A non-hydrostatic model and life times of deep and shallow convection are (JMANHM, Saito et al., 2006, hereafter 10km- changed in the Kain Fritsch cumulus parameteri- NHM) has been operating since September 2004 zation scheme (Kain and Fritsch, 1993) that affects with the same horizontal resolution. The horizon- greatly the accuracy of precipitation forecasts. tal resolution is planned to be enhanced to 5 km 3 Verification results (5km-NHM) in March 2006 on the new computer In this section, the performance of 5km-NHM is system of JMA. shown in terms of statistical verification scores in 2 Specifications of 5km-NHM comparison with 10km-NHM for the period of June In this section, the specifications which are to July in 2004 and January to February in 2005. -
NATIONAL WEATHER SERVICE INSTRUCTION 10-813 NOVEMBER 18, 2020 Operations and Services Aviation Weather Services, NWSPD 10-8 TERMINAL AERODROME FORECASTS
Department of Commerce • National Oceanic & Atmospheric Administration • National Weather Service NATIONAL WEATHER SERVICE INSTRUCTION 10-813 NOVEMBER 18, 2020 Operations and Services Aviation Weather Services, NWSPD 10-8 TERMINAL AERODROME FORECASTS NOTICE: This publication is available at: http://www.nws.noaa.gov/directives/. OPR: W/AFS24 (M. Graf) Certified by: W/AFS24 (B. Entwistle) Type of Issuance: Routine SUMMARY OF REVISIONS: This directive supersedes NWS Instruction 10-813, Terminal Aerodrome Forecasts, dated November 21, 2016. Changes made include: • Section 3 – updated links and removed unnecessary footnote • Section 4 – updated ICAO and WMO manual and regulation numbers • Section 4 – allowed up to 8 FM groups for 30 hour TAF locations • Section 4.1 – updated coordination section to include the AWC (including NAMs) and the AAWU. Also included the 10-803 link. • Section 4.2 – Introduced topic of Digital Aviation Services (DAS) • Section 4.2 – added the word “specifically” to the definition of vicinity as defined by the FAA • Section 4.3 – updated to include the link for ASOS/AWOS limitations. • Section 4.9 – added ICAO verbiage to address the grey window for 00/06/12/18 UTC issuances • Section 4.11 – updated to include the link to the FAA’s list of core airports. • Section 4.13 – revised TAF examples to clearly show format of AMD NOT SKED • Section 6 – updated to include the link to 10-2003. • Section 7 – updated the Performance and Evaluation Branch’s verification link. • Appendix A – updated the definitions of Hail (GR) and Snow Pellets (GS) in the table. • Appendix B – renumbered sections • Appendix B Section 1 – the IWXXM TAF is explained (LT) • Appendix B Section 2.4.2 – updated wording to add more detail for low winds • Appendix B Section 2.6 – added verbiage to use 3 winter weather types judiciously • Appendix B Section 2.8 – LLWS section rewritten to improve clarity • Appendix B Section 2.9.1 – moved NDFD wording from TCF discussion to section 2.6 • Appendix B Section 2.9.1 – updated CDM/CCFP to TFM/TCF. -
Information Contained in a METAR Example METAR Codes
METAR METAR is a format for reporting weather information. A METAR weather report is predominantly used by pilots in fulfillment of a part of a pre-flight weather briefing, and by meteorologists, who use aggregated METAR information to assist in weather forecasting. Raw METAR is the most common format in the world for the transmission of observational weather data. [citation needed] It is highly standardized through the International Civil Aviation Organization (ICAO), which allows it to be understood throughout most of the world. Information contained in a METAR A typical METAR contains data for the temperature, dew point, wind speed and direction, precipitation, cloud cover and heights, visibility, and barometric pressure. A METAR may also contain information on precipitation amounts, lightning, and other information that would be of interest to pilots or meteorologists such as a pilot report or PIREP, colour states and runway visual range (RVR). In addition, a short period forecast called a TRED may be added at the end of the METAR covering likely changes in weather conditions in the two hours following the observation. These are in the same format as a Terminal Aerodrome Forecast (TAF). The complement to METARs, reporting forecast weather rather than current weather, are TAFs. METARs and TAFs are used in VOLMET broadcasts. Example METAR codes International METAR codes The following is an example METAR from Burgas Airport in Burgas, Bulgaria. It was taken on 4 February 2005 at 16:00 Coordinated Universal Time (UTC). METAR LBBG 041600Z 12003MPS 310V290 1400 R04/P1500 R22/P1500U +S BK022 OVC050 M04/M07 Q1020 OSIG 9949//91= • METAR indicates that the following is a standard hourly observation.