DOCSLIB.ORG

Chapter 12 the Synoptic Code

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Chapter 12 the Synoptic Code Amendment no i ~ October 1994 CHAPTER 12 THE SYNOPTIC CODE - DETAILED DESCRIPTION 12.1 GENERAL. Detailed coding instructions for each element of each group of the Synoptic code are given below. The instructions often include reference to entries on the Surface Weather Record Form 63—2322. In most cases, the observerwill findthat the preparation ofthe Synoptic message is simplifiedifthe appropriate entries forlines andcolumns I to 42aon Form 63—2322 are completedbefore preparing the coded fl message. Observers may find that Form63—9028, Tables forSynoptic Code, will assistthem in encoding the synoptic report. 12.1 .1 Complete instructions for recording the observed data on Form 63—2322 are given in Chapter 13. 12.2 SECTION 0 12.2.1 Group MIMIMJMJ This group is inserted by the commmunications computer in the message header foridentification of synoptic bulletinsand is encoded AAXX for synoptic reports from land stations. It is the first group of the second line of the message header. (M1M1M~M~ is encoded BBXX forsy- noptic reports from ship stations.) 12.2.2 Group YYGGIW This groupis insertedby the communicationscomputer as the second group of the second line of the message header of a synoptic bulletin originating from a land station. 12.2.2.1 YY — Day of the month (UTC). 12.2.2.2 GG — Hour of the observation (UTC). 12.2.2.3 i~ — Wind indicator, showing the units of wind speed and whether the wind speed is measured or estimated. The communications computer will insert the figure 4 fori~, atCanadian land stations. Observers on ships will have the o ption of specifying a3 or 4, depending on whether or not the ships are equipped with anemometers. The following table for i~ is given for decoding purposes. Code figure Wind indicator 0 Wind speed estimated Wind speed in metres Wind speed obtained from anemometer Z per second Wind speed in Wind speed estimated 3 knots 4 Wind speed obtained from anemometer Z 12.2.3 Group lliii 12.2.3.1 II — Block number. All Canadian land stations use 71. 12.2.3.2 iii — Station number, as found in METSTAT. 12—2 Amend. No. 10 Nov. 1, 1989 12.3 SECTION 1 12.3.1 Group iRixhVV 12.3.1.1 iR — This symbol is an indicator to show whether or not the precipitation group 6RRRtRis included in the message and, ifincluded, in whatSection of the message it appears. The followingcode table shall be used. WMO Code 1819 Code Figure Precipitation data are reported Group 6RRRtR is: iR 0 in Sections 1 and 3 included in both Sections in Section 1 included 2 in Section 3 included 3 in none of the two sections omitted (precipitation land 3 amount =0) 4 in none of the two sections omitted (precipitation I and 3 amount not available) 12.3.1.1.1 Code figure 0 is not used for iR in Canada.When the group6RRRtR is included in the main synop- tic report, it is included in Section I, and iR is encoded 1. When precipitation occurs at a station which trans- mits i ntermediatesynoptic reports, andit occursbetween amain synoptic hour and the subsequentintermedi- ate synoptic hour,the 6RRRtR group will be included in the intermediate synoptic report, and iR will be en- coded 2. 12.3.1 .2 i,~ — This symbol indicates whether the synoptic message has originated from amanned or an auto- matic station and secondly, whether or not the present and past weathergroup, 7wwW1W2 is included. The following code table shall be used. 12—3 Amend. No. 11 Dec. 1991 WMO Code 1860 Code Figure Type of station Group 7wwW;W 7wawaWalWa2 operation 2 or staffed included 2 staffed omitted (no significant phenomenon to report) 3 staffed omitted (not observed, data not available) 4 automatic included using Code tables 4677 and 4561 5 automatic omitted(no significant phenomenon to report) 6 automatic omitted (not observed, data not available) 7 automatic included using Code tables 4680 and 4531 Note: Current automatic stations do not use indicator i,~ = 4; they normally use indicator i,~ = 5, 6, or 7. 12.3.1 .2.1 Insignificant weather phenomena referred to by code figure 2 are defined in para. 12.3.10. 12.3.1.3 h — height, above ground ofthe base oflowestcloud. When CL clouds exist, the height ofthe base of the lowest layeris reported by h. When no CL clouds exist, h is coded with reference to the height of the base of the lowest CM cloud.The following code table shall be used. WMO Codel600 Code Figure Coded Heights (Hourly Reports) h 0 Otolessthan SOm 0, 1 I S0mtolessthan lOOm 2, 3 2 l00mtolessthan 200m 4, 5, 6 3 200mtolessthan 300m 7, 8, 9 4 300 m to less than 600 m 10 tol9 5 600mto less than lOOOm 20 to 33 6 l000mtolessthan 1500m 34to49 7 1500 m to less than 2000 m 50 to 66 8 2000 m to less than 2500 m 67 to 83 9 Greater than 2500 m Greater than 83 or no cloud (or no cloud) / Sky completely obscured, no cloud visible. If coded cloud heights in the hourly report do not fit within the adjacent range of metric heights because of rounding, give precedence to the actual cloud height in selecting the code for h, rather than the coded value of the hourly report. For example, cloud height 290 m: code as 10 in hourly report; code h as 3 in synoptic report. Note: When CH clouds are observed without CL or CM clouds being present, h shall always be coded as 9. 12—4 12.3.1 .3.1 If the sky is partiallyobscuredby fogor otherobscuring phenomena, h refers to the base of the lowest cloud observed, ifany. 12.3.1 .3.2 If the sky is completely obscured, h is recorded as X; however, ifthe sky is completely ob- scured and clouds are visible below the obscuration, hisreported as observed. For example, ifthe sky is com- pletely obscured by snow in which the vertical visibility is 300 m and 1/10 of Stratus Fractus is observed at 150 m the coding for h would be 2. 12.3.1.4 VV — The horizontal visibility (Col. 31) shall be coded using the following table: WMO Code 4377 Miles Code Code Code Miles Figure Visibility Figure VV vV 7 61 Less than 55 yards 90 1/8 02 8 62 55 yards, but less than 220 91 1/4 04 9 64 220 yards, but less than 550 92 3/8 06 10 66 550 yards, but less than 1100 93 1/2 08 11 67 1100 yards, but less than 2200 94 5/8 10 12 69 2200 yards, but less than 4400 (2.2 naut. mi.) 95 3/4 12 13 70 4400 yds., but less than 11,000 (5.4 naut. mi.) 96 16 14 72 5.4 naut. mi. but less than II naut. mi. 97 1 1/4 20 15 74 11 naut. mi., but less than 27 naut. ml. 98 1 1/2 24 19 80 27 naut. mi. or greater 99 1 3/4 28 22 81 2 32 25 82 Note I. Code figures 90 to 99 2 1/4 36 28 83 shall not be used except on special 2 1/2 40 32 84 instructions from the ADMA 3 48 35 85 4 56 38 86 Note 2. When an hourly and 5 58 41 87 a Synoptic Observation are taken 6 59 44 88 at the same time and the entry more 89 in Column 31 is 15+, VV shall be than 44 reported as Code 74. r 12—5 Amendment n0 13 October 1994 12.3.1.4.1 If the visibility recorded in Column 31 falls between two code figures, use the lower codefigure. Thus, 20 miles shall be coded as 80; 30 miles as 83 etc. 12.3.2 Group Nddff 12.3.2.1 N — This symbol gives the fraction ofthe celestial dome covered by clouds, irrespective of theirtype. The following code table shall be used. WMO Code 2700 Code Figure N 0 0 0 1/10 or less, 1 oktas or less, but not zero but not zero 2 2/10 — 3/10 2 oktas 3 4/10 3 oktas 4 5/10 4 oktas 5 6/10 5 oktas 6 7/10 and 8/10 6 oktas 7 9/10 or more but 7 oktas or more, not 10/10 but not 8 oktas 8 10/10 8 oktas 9 Sky completely obscured by a surface—based layer or by an obscuring phenomenon based aloft. / Cloud cover is not discernable for reasons other than fog or other meteorological phe nomena,or,an observation is not made. The symbol “r’ is normally used only in autostation reports. U 12.3.2.1.1 Normally N shall be coded with reference to the entry in Column 26 (Total Amount). However, becauseof some differences in the procedures forcoding Hourly andSynoptic Observations some exceptions are necessary as indicated below: (a) When blue sky or stars are seen through alayerof fogor otherobscuring phenomenon with- out any trace of cloud above this layer, N is reported as 0. 12—6 (b) If clouds are seen through fogor otherobscuring phenomenontheir amount shall be evalu- ated as through the obscuration did not exist. In other words, partial obscurations may be disregarded and N is determined by considering that portion of the sky which is not ob- scured to be the entire sky. Examples follow: Example 1: Refer to 0700 and 0800 observations. The sky is partially concealed by fog.
Load more

Recommended publications
  • Soaring Weather
    Chapter 16 SOARING WEATHER While horse racing may be the "Sport of Kings," of the craft depends on the weather and the skill soaring may be considered the "King of Sports." of the pilot. Forward thrust comes from gliding Soaring bears the relationship to flying that sailing downward relative to the air the same as thrust bears to power boating. Soaring has made notable is developed in a power-off glide by a conven­ contributions to meteorology. For example, soar­ tional aircraft. Therefore, to gain or maintain ing pilots have probed thunderstorms and moun­ altitude, the soaring pilot must rely on upward tain waves with findings that have made flying motion of the air. safer for all pilots. However, soaring is primarily To a sailplane pilot, "lift" means the rate of recreational. climb he can achieve in an up-current, while "sink" A sailplane must have auxiliary power to be­ denotes his rate of descent in a downdraft or in come airborne such as a winch, a ground tow, or neutral air. "Zero sink" means that upward cur­ a tow by a powered aircraft. Once the sailcraft is rents are just strong enough to enable him to hold airborne and the tow cable released, performance altitude but not to climb. Sailplanes are highly 171 r efficient machines; a sink rate of a mere 2 feet per second. There is no point in trying to soar until second provides an airspeed of about 40 knots, and weather conditions favor vertical speeds greater a sink rate of 6 feet per second gives an airspeed than the minimum sink rate of the aircraft.
    [Show full text]
  • Manuscript Was Written Jointly by YL, CK, and MZ
    A simplified method for the detection of convection using high resolution imagery from GOES-16 Yoonjin Lee1, Christian D. Kummerow1,2, Milija Zupanski2 1Department of Atmospheric Science, Colorado state university, Fort Collins, CO 80521, USA 5 2Cooperative Institute for Research in the Atmosphere, Colorado state university, Fort Collins, CO 80521, USA Correspondence to: Yoonjin Lee ([email protected]) Abstract. The ability to detect convective regions and adding heating in these regions is the most important skill in forecasting severe weather systems. Since radars are most directly related to precipitation and are available in high temporal resolution, their data are often used for both detecting convection and estimating latent heating. However, radar data are limited to land areas, 10 largely in developed nations, and early convection is not detectable from radars until drops become large enough to produce significant echoes. Visible and Infrared sensors on a geostationary satellite can provide data that are more sensitive to small droplets, but they also have shortcomings: their information is almost exclusively from the cloud top. Relatively new geostationary satellites, Geostationary Operational Environmental Satellites-16 and -17 (GOES-16 and GOES-17), along with Himawari-8, can make up for some of this lack of vertical information through the use of very high spatial and temporal 15 resolutions. This study develops two algorithms to detect convection at vertically growing clouds and mature convective clouds using 1-minute GOES-16 Advanced Baseline Imager (ABI) data. Two case studies are used to explain the two methods, followed by results applied to one month of data over the contiguous United States.
    [Show full text]
  • Assessing and Improving Cloud-Height Based Parameterisations of Global Lightning Flash Rate, and Their Impact on Lightning-Produced Nox and Tropospheric Composition
    https://doi.org/10.5194/acp-2020-885 Preprint. Discussion started: 2 October 2020 c Author(s) 2020. CC BY 4.0 License. Assessing and improving cloud-height based parameterisations of global lightning flash rate, and their impact on lightning-produced NOx and tropospheric composition 5 Ashok K. Luhar1, Ian E. Galbally1, Matthew T. Woodhouse1, and Nathan Luke Abraham2,3 1CSIRO Oceans and Atmosphere, Aspendale, 3195, Australia 2National Centre for Atmospheric Science, Department of Chemistry, University of Cambridge, Cambridge, UK 3Department of Chemistry, University of Cambridge, Cambridge, UK 10 Correspondence to: Ashok K. Luhar ([email protected]) Abstract. Although lightning-generated oxides of nitrogen (LNOx) account for only approximately 10% of the global NOx source, it has a disproportionately large impact on tropospheric photochemistry due to the conducive conditions in the tropical upper troposphere where lightning is mostly discharged. In most global composition models, lightning flash rates used to calculate LNOx are expressed in terms of convective cloud-top height via the Price and Rind (1992) (PR92) 15 parameterisations for land and ocean. We conduct a critical assessment of flash-rate parameterisations that are based on cloud-top height and validate them within the ACCESS-UKCA global chemistry-climate model using the LIS/OTD satellite data. While the PR92 parameterisation for land yields satisfactory predictions, the oceanic parameterisation underestimates the observed flash-rate density severely, yielding a global average of 0.33 flashes s-1 compared to the observed 9.16 -1 flashes s over the ocean and leading to LNOx being underestimated proportionally. We formulate new/alternative flash-rate 20 parameterisations following Boccippio’s (2002) scaling relationships between thunderstorm electrical generator power and storm geometry coupled with available data.
    [Show full text]
  • Cloud-Base Height Derived from a Ground-Based Infrared Sensor and a Comparison with a Collocated Cloud Radar
    VOLUME 35 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY APRIL 2018 Cloud-Base Height Derived from a Ground-Based Infrared Sensor and a Comparison with a Collocated Cloud Radar ZHE WANG Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol–Cloud–Precipitation, and School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, and Training Center, China Meteorological Administration, Beijing, China ZHENHUI WANG Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, CMA Key Laboratory for Aerosol–Cloud–Precipitation, and School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, China XIAOZHONG CAO,JIAJIA MAO,FA TAO, AND SHUZHEN HU Atmosphere Observation Test Bed, and Meteorological Observation Center, China Meteorological Administration, Beijing, China (Manuscript received 12 June 2017, in final form 31 October 2017) ABSTRACT An improved algorithm to calculate cloud-base height (CBH) from infrared temperature sensor (IRT) observations that accompany a microwave radiometer was described, the results of which were compared with the CBHs derived from ground-based millimeter-wavelength cloud radar reflectivity data. The results were superior to the original CBH product of IRT and closer to the cloud radar data, which could be used as a reference for comparative analysis and synergistic cloud measurements. Based on the data obtained by these two kinds of instruments for the same period (January–December 2016) from the Beijing Nanjiao Weather Observatory, the results showed that the consistency of cloud detection was good and that the consistency rate between the two datasets was 81.6%. The correlation coefficient between the two CBH datasets reached 0.62, based on 73 545 samples, and the average difference was 0.1 km.
    [Show full text]
  • METAR/SPECI Reporting Changes for Snow Pellets (GS) and Hail (GR)
    U.S. DEPARTMENT OF TRANSPORTATION N JO 7900.11 NOTICE FEDERAL AVIATION ADMINISTRATION Effective Date: Air Traffic Organization Policy September 1, 2018 Cancellation Date: September 1, 2019 SUBJ: METAR/SPECI Reporting Changes for Snow Pellets (GS) and Hail (GR) 1. Purpose of this Notice. This Notice coincides with a revision to the Federal Meteorological Handbook (FMH-1) that was effective on November 30, 2017. The Office of the Federal Coordinator for Meteorological Services and Supporting Research (OFCM) approved the changes to the reporting requirements of small hail and snow pellets in weather observations (METAR/SPECI) to assist commercial operators in deicing operations. 2. Audience. This order applies to all FAA and FAA-contract weather observers, Limited Aviation Weather Reporting Stations (LAWRS) personnel, and Non-Federal Observation (NF- OBS) Program personnel. 3. Where can I Find This Notice? This order is available on the FAA Web site at http://faa.gov/air_traffic/publications and http://employees.faa.gov/tools_resources/orders_notices/. 4. Cancellation. This notice will be cancelled with the publication of the next available change to FAA Order 7900.5D. 5. Procedures/Responsibilities/Action. This Notice amends the following paragraphs and tables in FAA Order 7900.5. Table 3-2: Remarks Section of Observation Remarks Section of Observation Element Paragraph Brief Description METAR SPECI Volcanic eruptions must be reported whenever first noted. Pre-eruption activity must not be reported. (Use Volcanic Eruptions 14.20 X X PIREPs to report pre-eruption activity.) Encode volcanic eruptions as described in Chapter 14. Distribution: Electronic 1 Initiated By: AJT-2 09/01/2018 N JO 7900.11 Remarks Section of Observation Element Paragraph Brief Description METAR SPECI Whenever tornadoes, funnel clouds, or waterspouts begin, are in progress, end, or disappear from sight, the event should be described directly after the "RMK" element.
    [Show full text]
  • CLOUDSCLOUDS and the Earth’S Radiant Energy System
    Educational Product Educators Grades 5–8 Investigating the Climate System CLOUDSCLOUDS And the Earth’s Radiant Energy System PROBLEM-BASED CLASSROOM MODULES Responding to National Education Standards in: English Language Arts ◆ Geography ◆ Mathematics Science ◆ Social Studies Investigating the Climate System CLOUDSCLOUDS And the Earth’s Radiant Energy System Authored by: CONTENTS Sallie M. Smith, Howard B. Owens Science Center, Greenbelt, Maryland Scenario; Grade Levels; Time Required; Objectives; Prepared by: Disciplines Encompassed; Key Terms & Concepts; Stacey Rudolph, Senior Science Prerequisite Knowledge . 2 Education Specialist, Institute for Global Environmental Strategies Student Weather Intern Training Activities . 4 (IGES), Arlington, Virginia Activity One; Activity Two. 4 John Theon, Former Program Activity Three. 5 Scientist for NASA TRMM Activity Four. 6 Editorial Assistance, Dan Stillman, Science Communications Specialist, Activity Five . 9 Institute for Global Environmental Activity Six . 11 Strategies (IGES), Arlington, Virginia Appendix A: Resources . 12 Graphic Design by: Susie Duckworth Graphic Design & Appendix B: Assessment Rubrics & Answer Keys. 13 Illustration, Falls Church, Virginia Funded by: Appendix C: National Education Standards. 18 NASA TRMM Grant #NAG5-9641 Give us your feedback: Appendix D: Problem-Based Learning . 20 To provide feedback on the modules online, go to: Appendix E: TRMM Introduction/Instruments . 22 https://ehb2.gsfc.nasa.gov/edcats/ educational_product Appendix F: Online Resources . 24 and click on “Investigating the Climate System.” Appendix G: Glossary . 29 NOTE: This module was developed as part of the series “Investigating the Climate System.”The series includes five modules: Clouds, Energy, Precipitation, Weather, and Winds. While these materials were developed under one series title, they were designed so that each module could be used independently.
    [Show full text]
  • Metar Abbreviations Metar/Taf List of Abbreviations and Acronyms
    METAR ABBREVIATIONS http://www.alaska.faa.gov/fai/afss/metar%20taf/metcont.htm METAR/TAF LIST OF ABBREVIATIONS AND ACRONYMS $ maintenance check indicator - light intensity indicator that visual range data follows; separator between + heavy intensity / temperature and dew point data. ACFT ACC altocumulus castellanus aircraft mishap MSHP ACSL altocumulus standing lenticular cloud AO1 automated station without precipitation discriminator AO2 automated station with precipitation discriminator ALP airport location point APCH approach APRNT apparent APRX approximately ATCT airport traffic control tower AUTO fully automated report B began BC patches BKN broken BL blowing BR mist C center (with reference to runway designation) CA cloud-air lightning CB cumulonimbus cloud CBMAM cumulonimbus mammatus cloud CC cloud-cloud lightning CCSL cirrocumulus standing lenticular cloud cd candela CG cloud-ground lightning CHI cloud-height indicator CHINO sky condition at secondary location not available CIG ceiling CLR clear CONS continuous COR correction to a previously disseminated observation DOC Department of Commerce DOD Department of Defense DOT Department of Transportation DR low drifting DS duststorm DSIPTG dissipating DSNT distant DU widespread dust DVR dispatch visual range DZ drizzle E east, ended, estimated ceiling (SAO) FAA Federal Aviation Administration FC funnel cloud FEW few clouds FG fog FIBI filed but impracticable to transmit FIRST first observation after a break in coverage at manual station Federal Meteorological Handbook No.1, Surface
    [Show full text]
  • Objective Satellite-Based Detection of Overshooting Tops Using Infrared Window Channel Brightness Temperature Gradients
    VOLUME 49 JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY FEBRUARY 2010 Objective Satellite-Based Detection of Overshooting Tops Using Infrared Window Channel Brightness Temperature Gradients KRISTOPHER BEDKA,JASON BRUNNER,RICHARD DWORAK,WAYNE FELTZ, JASON OTKIN, AND THOMAS GREENWALD Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin—Madison, Madison, Wisconsin (Manuscript received 19 May 2009, in final form 31 August 2009) ABSTRACT Deep convective storms with overshooting tops (OTs) are capable of producing hazardous weather con- ditions such as aviation turbulence, frequent lightning, heavy rainfall, large hail, damaging wind, and tor- nadoes. This paper presents a new objective infrared-only satellite OT detection method called infrared window (IRW)-texture. This method uses a combination of 1) infrared window channel brightness temper- ature (BT) gradients, 2) an NWP tropopause temperature forecast, and 3) OT size and BT criteria defined through analysis of 450 thunderstorm events within 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) imagery. Qualitative validation of the IRW-texture and the well-documented water vapor (WV) minus IRW BT difference (BTD) technique is performed using visible channel imagery, CloudSat Cloud Profiling Radar, and/or Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud-top height for selected cases. Quantitative validation of these two techniques is obtained though comparison with OT detections from synthetic satellite imagery derived from a cloud-resolving NWP simulation. The results show that the IRW-texture method false-alarm rate ranges from 4.2% to 38.8%, depending upon the magnitude of the overshooting and algo- rithm quality control settings.
    [Show full text]
  • Cloud Height Determination and Comparison with Observed Rainfall by Using Meteosat Second Generation (Msg) Imageries
    CLOUD HEIGHT DETERMINATION AND COMPARISON WITH OBSERVED RAINFALL BY USING METEOSAT SECOND GENERATION (MSG) IMAGERIES Peter S. Masika Kenya Meteorological Department, P.O Box 30259 00100, Nairobi, KENYA. Email: [email protected] ABSTRACT: To obtain accurate estimates of surface and cloud parameters from satellite data an algorithm has to be developed which identifies cloud-free and cloud-contaminated pixels. Data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat Second Generation (MSG) satellites have been available since February 2004. The data is accessible to National Meteorological and Hydrological Services (NMHSs). This study attempts to utilize available MSG data for developing simple cloud mask and height algorithms and thereafter compare and determine the relationship between cloud height and observed rainfall on a ground station. A multispectral threshold technique has been used: the test sequence depends on solar illumination conditions and geographical location whereas most thresholds used here were empirically determined and applied to each individual pixel to determine whether that pixel is cloud-free or cloud- contaminated. The study starts from the premise of an acceptable trade-off between calculation speed and accuracy in the output data. For this reason, only three infrared channels of MSG satellite were used alongside climatological data provided by National Oceanographic and Atmospheric Administration (NOAA) and also land surface climatological data available from the WorldClim website. The accurate measurement of spatial and temporal variation of tropical rainfall around the globe remains one of the critical unresolved problems in the field of meteorology. This study attempted to compare computed cloud height and observed rainfall on ground station (CGIS-Butare, Rwanda) and derived cloud height-total rainfall relationship from storms over the same station.
    [Show full text]
  • Cloudphysical Parameters in Dependence on Height Above Cloud Base in Different Clouds
    Meteorol. Atmos. Phys. 41,247-254 (1989) Meteorology, and Atmospheric Physics by Springer-Verlag 1989 551.576.1 DLR 1-Institute for Atmospheric Physics, Oberpfaffenhofen, Federal Republic of Germany Cloudphysical Parameters in Dependence on Height Above Cloud Base in Different Clouds H.-E. Hoffmann and R. Roth With 5 Figures Received February 9, 1989 Revised August 7, 1989 Summary 1. Introduction On flights with the DLR icing research aircraft the depend- ence of aircraft icing on cloudphysical parameters was de- About four years ago, the Institute for Atmos- termined; both for aircraft-referred icing and for normalized pheric Physics of the DLR began to work on re- icing, as well as for various clouds and locations in clouds. search project "Icing of aircraft", One of the ob- This is done with an improvement of icing predicitons in jects of this research is defined by Hoffmann and mind. The species of the cloud and the distance from cloud base are called here "cloud parameters"; while under "cloud- Demmel (1984) as Determination of Flight Re- physical parameters" are understood liquid water content, strictions of Aircraft Caused by Icing in Dependence temperature, particle size distribution and particle phase. Re- on Meteorological Parameters. sults from four icing flights are discussed, selected from a Meteorological parameters here are: Cloud- total of forty vertical soundings.- The results are arranged physical, synoptic and cloud parameters. First re- in four classes: Stratus/cumulus mixed, stratus; with and without precipitation at the ground. sults, concerning the dependence of the normal- 1. Stratus/cumulus with either simultaneous or earlier ized ice thickness, and by this also of the nor- (3 h) precipitation at ground: Maxima of liquid water content malized icing-degree, on the cloudphysical param- (LWC: 0.75 and 0.55 g/m3, resp.) and maxima of the median eters liquid water content, temperature, particle volume diameter (MVD: 183 and 123 gin, resp.) both located size distribution and particle phase, were pub- in lower half of clouds, 2.
    [Show full text]
  • Changes in Cloud-Ceiling Heights and Frequencies Over the United States Since the Early 1950S
    3956 JOURNAL OF CLIMATE VOLUME 20 Changes in Cloud-Ceiling Heights and Frequencies over the United States since the Early 1950s BOMIN SUN NOAA/National Climatic Data Center, and STG, Inc., Asheville, North Carolina THOMAS R. KARL NOAA/National Climatic Data Center, Asheville, North Carolina DIAN J. SEIDEL NOAA/Air Resources Laboratory, Silver Spring, Maryland (Manuscript received 11 July 2006, in final form 7 November 2006) ABSTRACT U.S. weather stations operated by NOAA’s National Weather Service (NWS) have undergone significant changes in reporting and measuring cloud ceilings. Stations operated by the Department of Defense have maintained more consistent reporting practices. By comparing cloud-ceiling data from 223 NWS first-order stations with those from 117 military stations, and by further comparison with changes in physically related parameters, inhomogeneous records, including all NWS records based only on automated observing systems and the military records prior to the early 1960s, were identified and discarded. Data from the two networks were then used to determine changes in daytime ceiling height (the above-ground height of the lowest sky-cover layer that is more than half opaque) and ceiling occurrence frequency (percentage of total observations that have ceilings) over the contiguous United States since the 1950s. Cloud-ceiling height in the surface–3.6-km layer generally increased during 1951–2003, with more sig- nificant changes in the period after the early 1970s and in the surface–2-km layer. These increases were mostly over the western United States and in the coastal regions. No significant change was found in surface–3.6-km ceiling occurrence during 1951–2003, but during the period since the early 1970s, there is a tendency for a decrease in frequency of ceilings with height below 3.6 km.
    [Show full text]
  • Cloud Top Properties and Cloud Phase Algorithm Theoretical Basis Document
    CLOUD TOP PROPERTIES AND CLOUD PHASE ALGORITHM THEORETICAL BASIS DOCUMENT W. Paul Menzel Space Science and Engineering Center University of Wisconsin – Madison Richard A. Frey Cooperative Institute for Meteorological Satellite Studies University of Wisconsin - Madison Bryan A. Baum Space Science and Engineering Center University of Wisconsin – Madison (May 2015, version 11) 1 Table of Contents 1.0 INTRODUCTION 3 2.0 OVERVIEW 7 3.0 ALGORITHM DESCRIPTION 8 3.1 THEORETICAL DESCRIPTION 8 3.1.1 PHYSICAL BASIS OF THE CLOUD TOP PRESSURE/TEMPERATURE/HEIGHT ALGORITHM 9 3.1.2 PHYSICAL BASIS OF INFRARED CLOUD PHASE ALGORITHM 14 3.1.3 MATHEMATICAL APPLICATION OF CLOUD TOP PRESSURE/TEMPERATURE/HEIGHT ALGORITHM 17 3.1.4 MATHEMATICAL APPLICATION OF THE CLOUD PHASE ALGORITHM 24 3.1.5 ESTIMATE OF ERRORS ASSOCIATED WITH THE CLOUD TOP PROPERTIES ALGORITHM 25 3.2 PRACTICAL CONSIDERATIONS 36 3.2.1.A RADIANCE BIASES AND NUMERICAL CONSIDERATIONS OF CLOUD TOP PRESSURE ALGORITHM 36 3.2.1.B NUMERICAL CONSIDERATIONS OF CLOUD PHASE ALGORITHM 37 3.2.2 PROGRAMMING CONSIDERATIONS OF CLOUD TOP PROPERTIES ALGORITHM 37 3.2.3 VALIDATION 37 3.2.5 EXCEPTION HANDLING 47 3.2.6.A DATA DEPENDENCIES OF CLOUD TOP PROPERTIES ALGORITHM 47 3.2.6.B DATA DEPENDENCIES OF CLOUD PHASE ALGORITHM 50 3.2.7.A LEVEL 2 OUTPUT PRODUCT OF CLOUD TOP PROPERTIES AND CLOUD PHASE ALGORITHM 50 3.2.7.B LEVEL 3 OUTPUT PRODUCT OF CLOUD TOP PROPERTIES AND CLOUD PHASE ALGORITHM 51 3.3 REFERENCES 51 4. ASSUMPTIONS 56 4.1 ASSUMPTIONS OF CLOUD TOP PROPERTIES ALGORITHM 56 4.2 ASSUMPTIONS OF IR CLOUD PHASE ALGORITHM 56 1.0 Introduction This ATBD summarizes the Collection 6 (C6) refinements in the MODIS operational cloud top properties algorithms for cloud top pressure/temperature/height and cloud thermodynamic phase.
    [Show full text]