DOCSLIB.ORG

Open Tobin Dissertation V2.Pdf

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Open Tobin Dissertation V2.Pdf The Pennsylvania State University The Graduate School A MULTI-FACETED VIEW OF WINTER PRECIPITATION: SOCIETAL IMPACTS, POLARIMETRIC RADAR DETECTION, AND MICROPHYSICAL MODELING OF TRANSITIONAL WINTER PRECIPITATION A Dissertation in Meteorology and Atmospheric Science by Dana Marie Tobin 2020 Dana Marie Tobin Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy December 2020 ii The dissertation of Dana Marie Tobin was reviewed and approved by the following: Matthew R. Kumjian Associate Professor of Meteorology Dissertation Advisor Chair of Committee Eugene E. Clothiaux Professor of Meteorology Jerry Y. Harrington Professor of Meteorology Vikash V. Gayah Associate Professor of Civil and Environmental Engineering David J. Stensrud Professor of Meteorology Head of the Department iii ABSTRACT There remain several unanswered questions related to transitional winter precipitation, ranging from the impacts that it has on society to what microphysical processes are involved with its formation. With an improved understanding of the formation and impacts of transitional winter precipitation types, it is possible to reduce or minimize their adverse societal impacts in the future by improving their detection and forecasting. Precipitation is known to have an adverse effect on motor vehicle transportation, but no study has quantified the effects of ice pellets or freezing precipitation. An investigation of the number of vehicle-related fatalities during each precipitation type reveals a bias in the number of transitional-winter-precipitation type categories such that the fatality data cannot be used as-is to quantify the impacts of precipitation on vehicle fatalities with certainty. Matching traffic crash data to nearby precipitation-type reports provides an avenue to identify periods of precipitation during which a crash occurred. This analysis allows crash risk to be estimated during each precipitation type, resulting in a hierarchy of risk based on precipitation, with transitional winter precipitation having a higher overall crash risk than rain or snow. A polarimetric signature indicative of hydrometeor refreezing was recently documented, yet the underlying microphysical explanation remains unclear. The signature is characterized by a prominent and unexpected enhancement in differential reflectivity (ZDR) within a layer of decreasing radar reflectivity (ZH) towards the ground. These observations were made during prolonged periods of ice pellets where hydrometeors were fully melted prior to refreezing. The most probable explanation from the literature currently for the observed ZDR enhancement is preferential refreezing of small drops prior to the larger liquid drops. In contrast to previously published observations, no ZDR enhancement is found during an ice pellet and rain mixture event using high-resolution polarimetric radar data. Although refreezing did occur from small-to-large iv particles, these particles were not completely melted prior to refreezing, and the smallest fully melted hydrometeors did not refreeze. The presence of liquid drops and/or the freezing of partially melted (not fully melted) hydrometeors are likely the culprits of the lack of a ZDR enhancement, yet the observations alone are not sufficient to elucidate why that is the case. A steady-state, one-dimensional column microphysical model is developed to model snowflake melting and the refreezing of fully or partially melted hydrometeors, and coupled with a polarimetric radar forward operator. Simple tests of sequentially freezing size bins of an assumed drop size distribution indicate that preferential refreezing of drops still produces a ZDR enhancement even if the smallest drops remain liquid. The full-physics model simulation, however, produced no ZDR enhancement. Reducing the axis ratio of the liquid cores of freezing drops, as a crude representation of asymmetric freezing of an ice shell, successfully produced a realistic polarimetric refreezing signature. An even greater ZDR enhancement, more similar to observations, is produced by assuming that particle wobbling does not increase with freezing. It is thus suggested that a combination of asymmetric freezing and minimal increases in particle wobbling are responsible for the observed signature when fully melted particles refreeze. There is no such signature for the refreezing of partially melted particles, suggesting that the presence or absence of a ZDR enhancement in the refreezing layer may be used to distinguish between the refreezing of fully melted and partially melted hydrometeors. v TABLE OF CONTENTS LIST OF FIGURES ................................................................................................................. vii LIST OF TABLES ................................................................................................................... xiv ACKNOWLEDGEMENTS ..................................................................................................... xvi Chapter 1 Motivation .............................................................................................................. 1 Chapter 2 Extracting Precipitation-Type Information from ASOS and AWOS Reports: and Overview and Detailed Methods ............................................................................... 10 2.1 Introduction ................................................................................................................ 10 2.2 Background ................................................................................................................ 13 2.2.1 ASOS Development and Systems ................................................................... 13 2.2.2 AWOS Development and Systems.................................................................. 15 2.2.3 Reporting Formats and System Decoding ....................................................... 17 2.2.4 Precipitation-Type Definitions and Abbreviations .......................................... 21 2.2.5 Automated System Operations and Limitations of Precipitation Type ........... 27 2.3 Precipitation-Type Capture and Decoding Procedures .............................................. 38 2.3.1 Raw Weather Report Archive ......................................................................... 39 2.3.2 Present Weather Observations......................................................................... 40 2.3.3 Precipitation-Type Beginning and Ending Times ........................................... 52 2.4 Decoder Utility and Conclusions ............................................................................... 60 Chapter 3 Characteristics of Recent Vehicle-Related Fatalities during Active Precipitation in the United States ..................................................................................... 63 3.1 Introduction ................................................................................................................ 65 3.2 Methods ...................................................................................................................... 71 3.2.1 Characterization of Precipitation Type from FARS ........................................ 71 3.2.2 Characterization of Precipitation Type from ASOS/AWOS ........................... 72 3.2.3 Matching FARS to ASOS/AWOS Precipitation-Type Reports ...................... 74 3.3 Analysis of FARS Precipitation-Related Fatalities .................................................... 76 3.3.1 Precipitation-Related Fatality Totals ............................................................... 78 3.3.2 Roadway Surface Conditions .......................................................................... 79 3.3.3 Climatology of Precipitation-Related Fatalities .............................................. 81 3.4 Assessment of Nearby Precipitation-Type Reports ................................................... 90 3.4.1 Precipitation- Versus Non-Precipitation-Related Fatalities ............................ 90 3.4.2 Precipitation-Related Fatalities ....................................................................... 92 3.5 Discussion .................................................................................................................. 93 3.6 Summary and Conclusion .......................................................................................... 95 Chapter 4 Effects of Precipitation Type on Crash Relative Risk Estimates in Kansas ........... 99 4.1 Introduction ................................................................................................................ 99 4.2 Data and Methods ...................................................................................................... 103 vi 4.2.1 Crash Data ....................................................................................................... 103 4.2.2 Precipitation-Type Data .................................................................................. 106 4.2.3 Event and Control Periods ............................................................................... 109 4.2.4 Relative Risk Estimates ................................................................................... 111 4.3 Results ........................................................................................................................ 113 4.3.1 Sensitivity Testing ........................................................................................... 120 4.3.2 Time of Day and Day of Week Risk Estimates ..............................................
Load more

Recommended publications
  • Operating Instructions Present Weather Sensor Parsivel
    Operating instructions Present Weather Sensor Parsivel English We reserve the right to make technical changes! Table of contents 1 Scope of delivery 5 2 Part numbers 5 3 Parsivel Factory Settings 6 4 Safety instructions 7 5 Introduction 8 5.1 Functional principle 8 5.2 Connection Options for the Parsivel 9 6 Installing the Parsivel 10 6.1 Cable Selection 10 6.2 Wiring the Parsivel 11 6.3 Grounding the Parsivel 13 6.4 Installing the Parsivel 14 7 Connecting the Parsivel to a data logger 15 7.1 Connecting the Parsivel to the LogoSens Station Manager via RS-485 interface 15 7.2 Connecting the Parsivel to a Data logger via the SDI-12 Interface 17 7.3 Connecting the Parsivel to a Data Logger with Impulse/Status Input 21 8 Connecting the Parsivel to a PC 23 8.1 Connecting the Parsivel to Interface Converter RS-485/RS-232 (Accessories) 23 8.2 Connecting the Parsivel to the ADAM-4520 Converter RS-485/RS-232 (Accessories) 25 8.3 Connecting the Parsivel to Interface Converter RS-485/USB (Accessories) 26 8.4 Connecting the Parsivel to any RS-485 Interface Converter 27 8.5 Connecting the Parsivel for configuration via the Service-Tool to a PC 27 9 Connecting the Parsivel to a Power Supply (Accessory) 29 10 Heating the Parsivel sensor heads 30 11 Operating Parsivel with a Terminal software 31 11.1 Set up communications between the Parsivel and the terminal program 31 11.2 Measured value numbers 32 11.3 Defining the formatting string 33 11.4 OTT telegram 33 11.5 Updating Parsivel Firmware 34 12 Maintenance 36 12.1 Cleaning the laser’s protective glass
    [Show full text]
  • Comment Chapter Team Response Id Page Line Page Line 2257 2 0 0 0 0 Excellent Comprehensive and Rich Report
    SROCC Second Order Draft Government and Expert Review Comments - Chapter 2 Comment Chapter From From To To Comment Chapter Team Response id page line page line 2257 2 0 0 0 0 Excellent comprehensive and rich report. I have only few rather technical remarks. A more Taken into account – sentence included in permafrost section general recommendation relates to the new landscapes which are rapidli forming in deglaciating mountain areas and need comprehensive anticipation/modeling/treatment. This is an emerging research field (Haeberli, W. (2017): Integrative modelling and managing new landscapes and environments in de-glaciating mountain ranges: An emerging trans- disciplinary research field. Forestry Research and Engineering: International Journal 1(1). doi:10.15406/freij.2017.01.00005). This could be more strongly emphasized, for instance, in section 2.4 on page 47 an don page 5, line 53. Such new landscapes will be characterized by strong and long-lasting disequilibria, especially concerning slope stability, sediment cascades or eco-systems. One important factor thereby is the strongly different response time of cryosphere components: snow = almost immediate, mountain glaciers = years to decades, mountain permafrost =decades to centuries to even millennia. As an example, in many mountain chains, permafrost inside high peaks will probably continue to exist (far out of thermal equilibrium) when glaciers will have already long disappeared. [Wilfried Haeberli, Switzerland] 2259 2 0 0 0 0 The figures are interesting but rather overloaded and not easy to read and understand. Accepted - The figures have been revised to improve readability. [Wilfried Haeberli, Switzerland] 2415 2 0 0 0 It is puzzling to see that chapter authors have consciously chosen to ignore the pre- Rejected - Pre-industrial changes are not part of the government industrial, pre-Little-Ice-Age palaeoclimatic context.
    [Show full text]
  • How to Get Weather and Pest Data?
    How to get weather and pest data? François Brun (ACTA) with contributions of the other lecturers IPM CC, October 2016 Which data ? • Weather and Climate – Weather : conditions of the atmosphere over a short period of time – climate : atmosphere behavior over relatively long periods of time. • Pest and Disease data – Effects of conditions : experiments – Epidemiology : observation / monitoring networks Weather and Climate data Past Weather Historical Climate Data – Ground weather station – Average and variability – Satellite,… – Real long time series – Reconstituted long series – Simulated long series (1961- 1990 : reference) Forecast Weather Climate projections – Prediction with model – Prediction with model – Short term : 1h, 3h, 12h, 24, – IPCC report 3 day, 15 day. – 2021-2050 : middle of – Seasonal prediction : 1 to 6 century period months (~ el nino ) – 2071-2100 : end of century period Past Weather data Standard weather station Standard : at 2 m height • Frequent Useful for us – Thermometer : temperature – Anemometer : wind speed – Wind vane : wind direction – Hygrometer : humidity – Barometer : atmospheric pressure • Less frequent – Ceilometer : cloud height – Present weather sensor – Visibility sensor – Rain gauge : liquid-equivalent precipitation – Ultrasonic snow depth sensor for measuring depth of snow © Choi – Pyranometer : solar radiation Past Weather data In field / micro weather observations Wetness duration Temperature and humidity in canopy Water in soil © Choi Past Weather data Where to retrieve them ? • Your own weather
    [Show full text]
  • ICICLE Program Updates (Stephanie Divito, FAA)
    In-Cloud ICing and Large-drop Experiment Stephanie DiVito, FAA October 13, 2020 New FAA Flight program: ICICLE In-Cloud ICing and Large-drop Experiment Other Participants: Desert Research Institute (DRI), National Oceanic and Atmospheric Association (NOAA) Earth System Research Laboratory (ESRL), National Aeronautics and Space Administration (NASA) Langley Research Center, Meteo-France, UK Met Office, Deutscher Wetterdienst (German Meteorological Office), Northern Illinois University, Iowa State University, University of Illinois at Urbana-Champaign, and Valparaiso University 10/13/2020 FPAW: ICICLE 2 Flight Program Overview • January 27 – March 8, 2019 • Operations Base: Rockford, Illinois – Domain: 200 nmi radius • NRC Convair-580 aircraft – Owned and operated by NRC Flight Research Laboratory – Jointly instrumented by NRC and ECCC – Extensively used in icing research for over 25 years • 120 flight hours (110 for research) • 26 research flights (30 total) 10/13/2020 FPAW: ICICLE 3 Scientific & Technical Objectives • Observe, document, and further characterize a variety of in-flight and surface-level icing conditions – Environmental parameters and particle size distribution for: . Small-drop icing, FZDZ and FZRA – Transitions between those environments & non-icing environments – Synoptic, mesoscale & local effects • Assess ability of operational data, icing tools and products to diagnose and forecast those features – Satellite – GOES-16 – Radar – Individual NEXRADs, MRMS – Surface based – ASOS, AWOS, etc. – Numerical Weather Prediction (NWP) models – Microphysical parameterizations, TLE, etc. – Icing Products - CIP, FIP, other icing tools 10/13/2020 FPAW: ICICLE 4 Sampling Objectives (1/2) • Collect data in a wide variety of icing and non-icing conditions – Small-drop and large-drop . Including those with (& without) FZDZ and FZRA – Null icing environments .
    [Show full text]
  • Indian Monsoon Basic Drivers and Variability
    Indian Monsoon Basic Drivers and Variability GOTHAM International Summer School PIK, Potsdam, Germany, 18-22 Sep 2017 R. Krishnan Indian Institute of Tropical Meteorology, Pune, India The Indian (South Asian) Monsoon Tibetan Plateau India Indian Ocean Monsoon circulation and rainfall: A convectively coupled phenomenon Requires a thermal contrast between land & ocean to set up the monsoon circulation Once established, a positive feedback between circulation and latent heat release maintains the monsoon The year to year variations in the seasonal (June – September) summer monsoon rains over India are influenced internal dynamics and external drivers Long-term climatology of total rainfall over India during (1 Jun - 30 Sep) summer monsoon season (http://www.tropmet.res.in) Interannual variability of the Indian Summer Monsoon Rainfall Primary synoptic & smaller scale circulation features that affect cloudiness & precipitation. Locations of June to September rainfall exceeding 100 cm over the land west of 100oE associated with the southwest monsoon are indicated (Source: Rao, 1981). Multi-scale interactions Low frequency Synoptic Systems:Lows, sub-seasonal Depressions, MTC variability – Large scale Active and monsoon Break monsoon Organized convection, Embedded mesoscale systems , heavy rainfall (intensity > 10 cm/day) Winds at 925hPa DJF West African Monsoon Asian Monsoon Austral Monsoon JJA Courtesy: J.M. Slingo, Univ of Reading Land/Sea Temperature contrasts Nov./Dec. West African Monsoon Asian Monsoon Austral Monsoon May/June Courtesy:
    [Show full text]
  • Precipitation Type Graphic Documentation Page
    Precipitation Type Graphic Documentation Page Purpose: The National Weather Service in Caribou and Gray has created graphics that easily display precipitation types for mixed winter weather events. These graphics can be used by core customers for briefing purposes on upcoming winter events. Product Creation: These graphics are created automatically when each individual weather forecast office updates the official forecast. An individual forecast graphic will be created in 3 hour increments through the first 24 hours, then in 6 hour increments thereafter through 120 hours (5 days). Depending on how many forecast updates will dictate how often these graphics are created, but on average the first 24 hour forecast will be updated 6 times a day and the day 2 to 5 period will be updated twice daily (~ 3 p.m. and 3 a.m.). Product Location: Graphics will be hosted via the NWS Internet pages at the following URL: http://www.weather.gov/car/WeatherTypeCovForecast Note: The URL will be hidden for the first test season (winter 2015-16) and will only be available for a small test group to evaluate the graphics. Precipitation Type Graphic Example: The precipitation type page consists of the main graphic with the toggle commands at the bottom of the page. See image below for number reference locations: 1. Valid Time – Provides you with the graphic valid time in either 3hr or 6hr forecast time periods 2. Legend – Simple legend that explains what the precipitation type graphic colors are representing (a more detailed description of this legend is in the following section of this document).
    [Show full text]
  • Downloaded 09/24/21 05:27 PM UTC Fig
    Using Citizen Science Reports to Evaluate Estimates of Surface Precipitation Type BY SHENG CHEN, JONATHAN J. GOURLEY, YANG HONG, QING CAO, NICHOLAS CARR, PIERRE-EMMANUEL KIRSTETTER, JIAN ZHANG, AND ZAC FLAMIG he Multi-Radar Multi-Sensor (MRMS) system tree logic. To date, there has not yet been a system- uses data from the Next Generation Radar net- atic evaluation of the MRMS surface precipitation T work (NEXRAD) combined with model analyses type products beyond case studies. An opportunity from the Rapid Refresh (RAP) system to provide pre- exists to employ newly collected citizen-scientist (also cipitation rate and type products on a grid with 1-km referred to as “crowdsourced”) reports made possible horizontal resolution every 2 min (Zhang et al. 2011). through the meteorological Phenomena Indication The model analysis fields were found to be useful for Near the Ground (mPING) project to accomplish estimating precipitation type at the surface, which algorithm evaluations (Elmore et al. 2014). differs from the various Hydrometeor Classification Human weather observers have the ability to use Algorithms (HCA) designed to identify hydrometeors multiple clues in order to make a decision about at the height of radar sampling (e.g., Park et al. 2008). a given precipitation type. They typically begin These sampled hydrometeors undergo changes in with eyesight in order to assess the fall speed of the terms of their sizes, shapes, orientation, and phase as hydrometeor, its color, size, and shape. If uncertainty they fall and reach the surface. During the cool-season remains, then they may use other observations such months, these changes often occur below the height as touch to determine its phase (liquid, frozen, or of radar sampling.
    [Show full text]
  • Ott Parsivel - Enhanced Precipitation Identifier for Present Weather, Drop Size Distribution and Radar Reflectivity - Ott Messtechnik, Germany
    ® OTT PARSIVEL - ENHANCED PRECIPITATION IDENTIFIER FOR PRESENT WEATHER, DROP SIZE DISTRIBUTION AND RADAR REFLECTIVITY - OTT MESSTECHNIK, GERMANY Kurt Nemeth1, Martin Löffler-Mang2 1 OTT Messtechnik GmbH & Co. KG, Kempten (Germany) 2 HTW, Saarbrücken (Germany) as a laser-optic enhanced precipitation identifier and present weather sensor. The patented extinction method for simultaneous measurements of particle size and velocity of all liquid and solid precipitation employs a direct physical measurement principle and classification of hydrometeors. The instrument provides a full picture of precipitation events during any kind of weather phenomenon and provides accurate reporting of precipitation types, accumulation and intensities without degradation of per- formance in severe outdoor environments. Parsivel® operates in any climate regime and the built-in heating device minimizes the negative effect of freezing and frozen precipitation accreting critical surfaces on the instrument. Parsivel® can be integrated into an Automated Surface/ Weather Observing System (ASOS/AWOS) as part of the sensor suite. The derived data can be processed and 1. Introduction included into transmitted weather observation reports and messages (WMO, SYNOP, METAR and NWS codes). ® OTT Parsivel : Laser based optical Disdrometer for 1.2. Performance, accuracy and calibration procedure simultaneous measurement of PARticle SIze and VELocity of all liquid and solid precipitation. This state The new generation of Parsivel® disdrometer provides of the art instrument, designed to operate under all the latest state of the art optical laser technology. Each weather conditions, is capable of fulfilling multiple hydrometeor, which falls through the measuring area is meteorological applications: present weather sensing, measured simultaneously for size and velocity with an optical precipitation gauging, enhanced precipitation acquisition cycle of 50 kHz.
    [Show full text]
  • Launching of New RS90-AG Radiosonde Valuable
    40813_VaisalaNews_155 7.12.2000 18:29 Sivu 1 155/2001155/2001 After Extensive Field Testing: Launching of New RS90-AG Radiosonde Customer Satisfaction Survey for WOBS Customers: Valuable Customer Feedback Using Product Platforms: Next Generation of Surface Weather Software Products New ROSA Weather Station Generation: Evolution Rather Than Revolution 40813_VaisalaNews_155 7.12.2000 18:29 Sivu 2 Contents President’s Column 3 Serving Better Our Customers 4 Customer Satisfaction Survey for WOBS Customers: Valuable Customer Feedback 6 Next Generation of Surface Weather Software Products 8 Meteorological Data Management System: Aurora’s payload system was MetMan for Multi-purpose Data Collection 10 developed for high altitude dropsonde missions, for use on Compact MAWS301 Automatic Weather Station 12 low speed platforms such as Demanding Tactical Military Needs 14 Pathfinder, Altus and Perseus B. Due to funding cuts, the Vaisala Technology for the U.S. Air Force 17 dropsonde payload was not Military Exhibition EUROSATORY 2000 in France 18 permitted to be deployed and Climatological Conditions on the My Thuan Bridge 19 operated from Pathfinder. Nevertheless, Aurora tested and Major Contract from the U.S. qualified the payload for flight, National Weather Service 20 using its high altitude test Using L and S-Band Boundary Layer Radars and a chambers. Vaisala’s dropsondes were an integral part of this Millimeter-wave Doppler Radar with Vaisala MAWS: scientific experiment. Weather Observations 20 Researchers are using dropson- Royal Botanic Gardens Melbourne: des to get a more accurate pic- Fostering Plant Conservation 24 ture of hurricanes. Fire RAWS Unit on the Bircher Burned Over 26 Launching of RS90-AG Radiosonde 29 Vaisala’s MAWS301 Automatic Global Positioning System 31 Weather Station is a new gener- ation weather station especially Significant Radiosonde Order designed for applications where from Met Service Canada 32 no commercial power or com- Vaisala’s Next Generation munication networks are avail- 32 able or economically installed.
    [Show full text]
  • Observation of Present and Past Weather; State of the Ground
    CHAPTER CONTENTS Page CHAPTER 14. OBSERVATION OF PRESENT AND PAST WEATHER; STATE OF THE GROUND .. 450 14.1 General ................................................................... 450 14.1.1 Definitions ......................................................... 450 14.1.2 Units and scales ..................................................... 450 14.1.3 Meteorological requirements ......................................... 451 14.1.4 Observation methods. 451 14.2 Observation of present and past weather ...................................... 451 14.2.1 Precipitation. 452 14.2.1.1 Objects of observation ....................................... 452 14.2.1.2 Instruments and measuring devices: precipitation type ........... 452 14.2.1.3 Instruments and measuring devices: precipitation intensity and character ............................................... 454 14.2.1.4 Instruments and measuring devices: multi-sensor approach ....... 455 14.2.2 Atmospheric obscurity and suspensoids ................................ 455 14.2.2.1 Objects of observation ....................................... 455 14.2.2.2 Instruments and measuring devices for obscurity and suspensoid characteristics .................................... 455 14.2.3 Other weather events ................................................ 456 14.2.3.1 Objects of observation ....................................... 456 14.2.3.2 Instruments and measuring devices. 457 14.2.4 State of the sky ...................................................... 457 14.2.4.1 Objects of observation ......................................
    [Show full text]
  • Climate Modeling in Las Leñas, Central Andes of Argentina
    Glacier - climate modeling in Las Leñas, Central Andes of Argentina Master’s Thesis Faculty of Science University of Bern presented by Philippe Wäger 2009 Supervisor: Prof. Dr. Heinz Veit Institute of Geography and Oeschger Centre for Climate Change Research Advisor: Dr. Christoph Kull Institute of Geography and Organ consultatif sur les changements climatiques OcCC Abstract Studies investigating late Pleistocene glaciations in the Chilean Lake District (~40-43°S) and in Patagonia have been carried out for several decades and have led to a well established glacial chronology. Knowledge about the timing of late Pleistocene glaciations in the arid Central Andes (~15-30°S) and the mechanisms triggering them has also strongly increased in the past years, although it still remains limited compared to regions in the Northern Hemisphere. The Southern Central Andes between 31-40°S are only poorly investigated so far, which is mainly due to the remoteness of the formerly glaciated valleys and poor age control. The present study is located in Las Leñas at 35°S, where late Pleistocene glaciation has left impressive and quite well preserved moraines. A glacier-climate model (Kull 1999) was applied to investigate the climate conditions that have triggered this local last glacial maximum (LLGM) advance. The model used was originally built to investigate glacio-climatological conditions in a summer precipitation regime, and all previous studies working with it were located in the arid Central Andes between ~17- 30°S. Regarding the methodology applied, the present study has established the southernmost study site so far, and the first lying in midlatitudes with dominant and regular winter precipitation from the Westerlies.
    [Show full text]
  • NATS 101 Section 13: Lecture 22 Fronts
    NATS 101 Section 13: Lecture 22 Fronts Last time we talked about how air masses are created. When air masses meet, or clash, the transition zone is called a front. The concept of “fronts” in weather developed from the idea of the front line of battle, specifically in Europe during World War I How are weather fronts analogous to battle fronts in a war? Which air mass “wins” depends on what type of front it is. Four types of fronts COLD FRONT: Cold air overtakes warm air. B to C WARM FRONT: Warm air overtakes cold air. C to D OCCLUDED FRONT: Cold air catches up to the warm front. C to Low pressure center STATIONARY FRONT: No movement of air masses. A to B Fronts and Extratropical Cyclones Feb. 24, 2007 Case In mid-latitudes, fronts are part of the structure of extratropical cyclones. Extratropical cyclones form because of the horizontal temperature gradient. How are they a part of the general circulation? Type of weather and air masses in relation to fronts: Feb. 24, 2007 case mPmP cPcP mTmT Characteristics of a front 1. Sharp temperature changes over a short distance 2. Changes in moisture content 3. Wind shifts 4. A lowering of surface pressure, or pressure trough 5. Clouds and precipitation We’ll see how these characteristics manifest themselves for fronts in North America using the example from Feb. 2007… COLDCOLD FRONTFRONT Horizontal extent: About 50 km AHEAD OF FRONT: Warm and southerly winds. Cirrus or cirrostratus clouds. Called the warm sector. AT FRONT: Pressure trough and wind shift.
    [Show full text]