Static Stability (I) the Concept of Stability (Ii) the Parcel Technique (A
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How Does Convective Self-Aggregation Affect Precipitation Extremes?
EGU21-5216 https://doi.org/10.5194/egusphere-egu21-5216 EGU General Assembly 2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. How does convective self-aggregation affect precipitation extremes? Nicolas Da Silva1, Sara Shamekh2, Caroline Muller2, and Benjamin Fildier2 1Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom 2Laboratoire de Météorologie Dynamique (LMD)/Institut Pierre Simon Laplace (IPSL), École Normale Supérieure, Paris Sciences & Lettres (PSL) Research University, Sorbonne Université, École Polytechnique, CNRS, Paris, France Convective organisation has been associated with extreme precipitation in the tropics. Here we investigate the impact of convective self-aggregation on extreme rainfall rates. We find that convective self-aggregation significantly increases precipitation extremes, for 3-hourly accumulations but also for instantaneous rates (+ 30 %). We show that this latter enhanced instantaneous precipitation is mainly due to the local increase in relative humidity which drives larger accretion efficiency and lower re-evaporation and thus a higher precipitation efficiency. An in-depth analysis based on an adapted scaling of precipitation extremes, reveals that the dynamic contribution decreases (- 25 %) while the thermodynamic is slightly enhanced (+ 5 %) with convective aggregation, leading to lower condensation rates (- 20 %). When the atmosphere is more organized into a moist convecting region, and a dry convection-free region, deep convective updrafts are surrounded by a warmer environment which reduces convective instability and thus the dynamic contribution. The moister boundary-layer explains the positive thermodynamic contribution. The microphysic contribution is increased by + 50 % with aggregation. The latter is partly due to reduced evaporation of rain falling through a moister near-cloud environment (+ 30 %), but also to the associated larger accretion efficiency (+ 20 %). -
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. -
Impacts of Anthropogenic Aerosols on Fog in North China Plain
BNL-209645-2018-JAAM Journal of Geophysical Research: Atmospheres RESEARCH ARTICLE Impacts of Anthropogenic Aerosols on Fog in North China Plain 10.1029/2018JD029437 Xingcan Jia1,2,3 , Jiannong Quan1 , Ziyan Zheng4, Xiange Liu5,6, Quan Liu5,6, Hui He5,6, 2 Key Points: and Yangang Liu • Aerosols strengthen and prolong fog 1 2 events in polluted environment Institute of Urban Meteorology, Chinese Meteorological Administration, Beijing, China, Brookhaven National Laboratory, • Aerosol effects are stronger on Upton, NY, USA, 3Key Laboratory of Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University microphysical properties than of Information Science and Technology, Nanjing, China, 4Institute of Atmospheric Physics, Chinese Academy of Sciences, macrophysical properties Beijing, China, 5Beijing Weather Modification Office, Beijing, China, 6Beijing Key Laboratory of Cloud, Precipitation and • Turbulence is enhanced by aerosols during fog formation and growth but Atmospheric Water Resources, Beijing, China suppressed during fog dissipation Abstract Fog poses a severe environmental problem in the North China Plain, China, which has been Supporting Information: witnessing increases in anthropogenic emission since the early 1980s. This work first uses the WRF/Chem • Supporting Information S1 model coupled with the local anthropogenic emissions to simulate and evaluate a severe fog event occurring Correspondence to: in North China Plain. Comparison of the simulations against observations shows that WRF/Chem well X. Jia and Y. Liu, reproduces the general features of temporal evolution of PM2.5 mass concentration, fog spatial distribution, [email protected]; visibility, and vertical profiles of temperature, water vapor content, and relative humidity in the planetary [email protected] boundary layer throughout the whole period of the fog event. -
GEOGRAPHY OPTIONAL by SHAMIM ANWER
GEOGRAPHY OPTIONAL by SHAMIM ANWER LEARNING GEOGRAPHY - A NEVER BEFORE EXPERIENCE PREP SUPPLEMENT CLIMA T OLOGY NOT FOR SALE | Off : 57/17 1st Floor, Old Rajender Nagar 8026506054, 8826506099 | Above Dr, Batra’s Delhi - 110060 Also visit us on www.keynoteias.com | www.facebook.com/keynoteias.in KEYNOTE IAS PHYSICAL GEOGRAPHY CLIMATOLOGY INDEX 1. CIRCULATION OF THE ATMOSPHERE ................................................................1-13 Local Winds; Observed Distribution of Pressure and Winds and Idealized Zonal Pressure Belts; Monsoons, Westerlies and Jet Streams; EL Nino and La Nina. 2. MOISTURE AND ATMOSPHERIC STABILITY ..................................................14-24 Atmospheric Stability and Instability 3. FORMS OF CONDENSATION AND PRECIPITATION ........................................25-38 Types and Global Distribution of Precipitation 4. AIR MASSES...........................................................................................................39-53 Polar-Front Theory; Fronts; Cyclone Formation; Cyclonic and Anticyclonic Circulation PREP-SUPPLEMENT: CLIMATOLOGY 1 1. CIRCULATION OF THE ATMOSPHERE Atmospheric circulation and wind Macroscale Winds: The largest wind patterns, called macroscale winds, are exemplified by the Winds are generated by pressure differences that westerlies and trade winds. These planetary-scale arise because of unequal heating of Earth's surface. flow patterns extend around the entire globe and Global winds are generated because the tropics can remain essentially unchanged for weeks at -
Downloaded 09/29/21 11:17 PM UTC 4144 MONTHLY WEATHER REVIEW VOLUME 128 Ferentiate Among Our Concerns About the Application of TABLE 1
DECEMBER 2000 NOTES AND CORRESPONDENCE 4143 The Intricacies of Instabilities DAVID M. SCHULTZ NOAA/National Severe Storms Laboratory, Norman, Oklahoma PHILIP N. SCHUMACHER NOAA/National Weather Service, Sioux Falls, South Dakota CHARLES A. DOSWELL III NOAA/National Severe Storms Laboratory, Norman, Oklahoma 19 April 2000 and 30 May 2000 ABSTRACT In response to Sherwood's comments and in an attempt to restore proper usage of terminology associated with moist instability, the early history of moist instability is reviewed. This review shows that many of Sherwood's concerns about the terminology were understood at the time of their origination. De®nitions of conditional instability include both the lapse-rate de®nition (i.e., the environmental lapse rate lies between the dry- and the moist-adiabatic lapse rates) and the available-energy de®nition (i.e., a parcel possesses positive buoyant energy; also called latent instability), neither of which can be considered an instability in the classic sense. Furthermore, the lapse-rate de®nition is really a statement of uncertainty about instability. The uncertainty can be resolved by including the effects of moisture through a consideration of the available-energy de®nition (i.e., convective available potential energy) or potential instability. It is shown that such misunderstandings about conditional instability were likely due to the simpli®cations resulting from the substitution of lapse rates for buoyancy in the vertical acceleration equation. Despite these valid concerns about the value of the lapse-rate de®nition of conditional instability, consideration of the lapse rate and moisture separately can be useful in some contexts (e.g., the ingredients-based methodology for forecasting deep, moist convection). -
Atmospheric Stability Atmospheric Lapse Rate
ATMOSPHERIC STABILITY ATMOSPHERIC LAPSE RATE The atmospheric lapse rate ( ) refers to the change of an atmospheric variable with a change of altitude, the variable being temperature unless specified otherwise (such as pressure, density or humidity). While usually applied to Earth's atmosphere, the concept of lapse rate can be extended to atmospheres (if any) that exist on other planets. Lapse rates are usually expressed as the amount of temperature change associated with a specified amount of altitude change, such as 9.8 °Kelvin (K) per kilometer, 0.0098 °K per meter or the equivalent 5.4 °F per 1000 feet. If the atmospheric air cools with increasing altitude, the lapse rate may be expressed as a negative number. If the air heats with increasing altitude, the lapse rate may be expressed as a positive number. Understanding of lapse rates is important in micro-scale air pollution dispersion analysis, as well as urban noise pollution modeling, forest fire-fighting and certain aviation applications. The lapse rate is most often denoted by the Greek capital letter Gamma ( or Γ ) but not always. For example, the U.S. Standard Atmosphere uses L to denote lapse rates. A few others use the Greek lower case letter gamma ( ). Types of lapse rates There are three types of lapse rates that are used to express the rate of temperature change with a change in altitude, namely the dry adiabatic lapse rate, the wet adiabatic lapse rate and the environmental lapse rate. Dry adiabatic lapse rate Since the atmospheric pressure decreases with altitude, the volume of an air parcel expands as it rises. -
Atmospheric Thermal and Dynamic Vertical Structures of Summer Hourly Precipitation in Jiulong of the Tibetan Plateau
atmosphere Article Atmospheric Thermal and Dynamic Vertical Structures of Summer Hourly Precipitation in Jiulong of the Tibetan Plateau Yonglan Tang 1, Guirong Xu 1,*, Rong Wan 1, Xiaofang Wang 1, Junchao Wang 1 and Ping Li 2 1 Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China; [email protected] (Y.T.); [email protected] (R.W.); [email protected] (X.W.); [email protected] (J.W.) 2 Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province, Institute of Plateau Meteorology, China Meteorological Administration, Chengdu 610072, China; [email protected] * Correspondence: [email protected]; Tel.: +86-27-8180-4913 Abstract: It is an important to study atmospheric thermal and dynamic vertical structures over the Tibetan Plateau (TP) and their impact on precipitation by using long-term observation at represen- tative stations. This study exhibits the observational facts of summer precipitation variation on subdiurnal scale and its atmospheric thermal and dynamic vertical structures over the TP with hourly precipitation and intensive soundings in Jiulong during 2013–2020. It is found that precipitation amount and frequency are low in the daytime and high in the nighttime, and hourly precipitation greater than 1 mm mostly occurs at nighttime. Weak precipitation during the daytime may be caused by air advection, and strong precipitation at nighttime may be closely related with air convection. Both humidity and wind speed profiles show obvious fluctuation when precipitation occurs, and the greater the precipitation intensity, the larger the fluctuation. Moreover, the fluctuation of wind speed Citation: Tang, Y.; Xu, G.; Wan, R.; Wang, X.; Wang, J.; Li, P. -
Atmospheric Instability Parameters Derived from Msg Seviri Observations
P3.33 ATMOSPHERIC INSTABILITY PARAMETERS DERIVED FROM MSG SEVIRI OBSERVATIONS Marianne König*, Stephen Tjemkes, Jochen Kerkmann EUMETSAT, Darmstadt, Germany 1. INTRODUCTION K-Index: Convective systems can develop in a thermo- (Tobs(850)–Tobs(500)) + TDobs(850) – (Tobs(700)–TDobs(700)) dynamically unstable atmosphere. Such systems may quickly reach high altitudes and can cause severe Lifted Index: storms. Meteorologists are thus especially interested to Tobs - Tlifted from surface at 500 hPa identify such storm potentials when the respective system is still in a preconvective state. A number of Maximum buoyancy: obs(max betw. surface and 850) obs(min betw. 700 and 300) instability indices have been defined to describe such Qe - Qe situations. Traditionally, these indices are taken from temperature and humidity soundings by radiosondes. As (T is temperature, TD is dewpoint temperature, and Qe radiosondes are only of very limited temporal and is equivalent potential temperature, numbers 850, 700, spatial resolution there is a demand for satellite-derived 300 indicate respective hPa level in the atmosphere) indices. The Meteorological Product Extraction Facility (MPEF) for the new European Meteosat Second and the precipitable water content as additionally Generation (MSG) satellite envisages the operational derived parameter. derivation of a number of instability indices from the brightness temperatures measured by certain SEVIRI 3. DESCRIPTION OF ALGORITHMS channels (Spinning Enhanced Visible and Infrared Imager, the radiometer onboard MSG). The traditional 3.1 The Physical Retrieval physical approach to this kind of retrieval problem is to infer the atmospheric profile via a constrained inversion An iterative solution to the inversion equation (e.g. and compute the indices then directly from the obtained Ma et al. -
Convective to Absolute Instability Transition in a Horizontal Porous Channel with Open Upper Boundary
fluids Article Convective to Absolute Instability Transition in a Horizontal Porous Channel with Open Upper Boundary Antonio Barletta * and Michele Celli Department of Industrial Engineering, Alma Mater Studiorum Università di Bologna, Viale Risorgimento 2, 40136 Bologna, Italy; [email protected] * Correspondence: [email protected]; Tel.: +39-051-209-3287 Academic Editor: Mehrdad Massoudi Received: 28 April 2017; Accepted: 10 June 2017; Published: 14 June 2017 Abstract: A linear stability analysis of the parallel uniform flow in a horizontal channel with open upper boundary is carried out. The lower boundary is considered as an impermeable isothermal wall, while the open upper boundary is subject to a uniform heat flux and it is exposed to an external horizontal fluid stream driving the flow. An eigenvalue problem is obtained for the two-dimensional transverse modes of perturbation. The study of the analytical dispersion relation leads to the conditions for the onset of convective instability as well as to the determination of the parametric threshold for the transition to absolute instability. The results are generalised to the case of three-dimensional perturbations. Keywords: porous medium; Rayleigh number; absolute instability 1. Introduction Cellular convection patterns may develop in an underlying horizontal flow under appropriate thermal boundary conditions. The classic setup for the thermal instability of a horizontal fluid flow is heating from below, and the well-known type of instability is Rayleigh-Bénard [1]. Such a situation can happen in a channel fluid flow or in the filtration of a fluid within a porous channel. Both cases are widely documented in the literature [1,2]. -
Range Forecasts of the Pre-‐Convective Environment Using SEVIRI Data
Enhancing objective short-range forecasts of the pre-convective environment using SEVIRI data Ralph A. Petersen1, Robert Aune2 and Thomas Rink1 1 Cooperative Institute for Meteorological Satellite Studies (CIMSS), University of Wisconsin – Madison 2 NOAA/NESDIS/STAR, Advanced Satellite Products Team, Madison, Wisconsin ABSTRACT: This paper describes development efforts and evaluation results made with the CIMSS NearCasting system during the last year. Tests of the 1-9 hours forecasts of GOES products were made at US National Weather Servicer (NWS) Forecast Offices, CIMMS, and both the Storm Prediction Center (SPC) and the Aviation Weather Center (AWC) divisions of the National Centers for Environmental Prediction (NCEP). The tests at the two centers focused both on where/when severe convection will occur, as well as all forms of deep convection will and will not occur. The results showed that the prediction period could be successfully increased from 6 to 9 hours, that the analysis improved by increasing the number of observations projected forward from previous, that the NearCast wind fields can provide information about low-level triggering mechanisms and storm severity, that the NearCasts enhanced NWP guidance by isolating which forecasts areas were and were not likely to experience convection and when, and that successful use of the NearCasting tools requires increased forecaster training and education - both about the NearCast system itself and interpreting satellite observations and derived products. INTRODUCTION: This paper provides an update to Petersen et al., 2010. During the past year, primary emphasis of CIMSS NearCasting activities has focused on testing and evaluation of the short-range forecasting system internally at CIMSS, at local US National Weather Servicer (NWS) Forecast Offices, and both the Storm Prediction Center (SPC) and the Aviation Weather Center (AWC) divisions of the National Centers for Environmental Prediction (NCEP). -
Methods for Diagnosing Regions of Conditional Symmetric Instability
Methods for Diagnosing Regions of Conditional Symmetric Instability James T. Moore Cooperative Institute for Precipitation Systems Saint Louis University Dept. of Earth & Atmospheric Sciences Ted Funk Science and Operations Officer WFO Louisville, KY Spectrum of Instabilities Which Can Result in Enhanced Precipitation • Inertial Instability • Potential Symmetric Instability • Conditional Symmetric Instability • Weak Symmetric Stability • Elevated Convective Instability 1 Inertial Instability Inertial instability is the horizontal analog to gravitational instability; i.e., if a parcel is displaced horizontally from its geostrophically balanced base state, will it return to its original position or will it accelerate further from that position? Inertially unstable regions are diagnosed where: .g + f < 0 ; absolute geostrophic vorticity < 0 OR if we define Mg = vg + fx = absolute geostrophic momentum, then inertially unstable regions are diagnosed where: MMg/ Mx = Mvg/ Mx + f < 0 ; since .g = Mvg/ Mx (NOTE: vg = geostrophic wind normal to the thermal gradient) x = a fixed point; for wind increasing with height, Mg surfaces become more horizontal (i.e., Mg increases with height) Inertial Instability (cont.) Inertial stability is weak or unstable typically in two regions (Blanchard et al. 1998, MWR): .g + f = (V/Rs - MV/ Mn) + f ; in natural coordinates where V/Rs = curvature term and MV/ Mn = shear term • Equatorward of a westerly wind maximum (jet streak) where the anticyclonic relative geostrophic vorticity is large (to offset the Coriolis -
Chapter 3 Mesoscale Processes and Severe Convective Weather
CHAPTER 3 JOHNSON AND MAPES Chapter 3 Mesoscale Processes and Severe Convective Weather RICHARD H. JOHNSON Department of Atmospheric Science. Colorado State University, Fort Collins, Colorado BRIAN E. MAPES CIRESICDC, University of Colorado, Boulder, Colorado REVIEW PANEL: David B. Parsons (Chair), K. Emanuel, J. M. Fritsch, M. Weisman, D.-L. Zhang 3.1. Introduction tion, mesoscale phenomena occur on horizontal scales between ten and several hundred kilometers. This Severe convective weather events-tornadoes, hail range generally encompasses motions for which both storms, high winds, flash floods-are inherently mesoscale ageostrophic advections and Coriolis effects are im phenomena. While the large-scale flow establishes envi portant (Emanuel 1986). In general, we apply such a ronmental conditions favorable for severe weather, pro definition here; however, strict application is difficult cesses on the mesoscale initiate such storms, affect their since so many mesoscale phenomena are "multiscale." evolution, and influence their environment. A rich variety For example, a -100-km-Iong gust front can be less of mesocale processes are involved in severe weather, than -1 km across. The triggering of a storm by the ranging from environmental preconditioning to storm initi collision of gust fronts can actually occur on a ation to feedback of convection on the environment. In the -lOO-m scale (the microscale). Nevertheless, we will space available, it is not possible to treat all of these treat this overall process (and others similar to it) as processes in detail. Rather, we will introduce s~veral mesoscale since gust fronts are generally regarded as general classifications of mesoscale processes relatmg to mesoscale phenomena.