LT Tom Moneymaker Advisor: Prof Peter Guest

Slides:



Advertisements
Similar presentations
21M062007D The Shaw Group Inc. ® An Analytical Screening Technique to Estimate the Effect of Cooling Ponds on Meteorological Measurements – A Case Study.
Advertisements

A thermodynamic model for estimating sea and lake ice thickness with optical satellite data Student presentation for GGS656 Sanmei Li April 17, 2012.
Part 6. Altimetry. Part 6. Altimetry TOPICS Pressure, Humidity & Temperature ISA and the Aircraft Altimeter 4 Pressure, Humidity & Temperature 4 ISA.
Skyler Goldman, Meteorology, DMES RELATIONSHIP BETWEEN ROUGHNESS LENGTH, STATIC STABILITY, AND DRAG COEFFICIENT IN A DUNE ENVIRONMENT.
VOSClim Project Information. Why do we want the VOSClim information? The purpose of VOSClim Project To provide a high-quality set of marine met obs Detailed.
Training course: boundary layer II Similarity theory: Outline Goals, Buckingham Pi Theorem and examples Surface layer (Monin Obukhov) similarity Asymptotic.
Weather Part IV Storms Reference: CK-12.org Earth Sciences Chapter 16 By: Robert Smith.
EM propagation paths 1/17/12. Introduction Motivation: For all remote sensing instruments, an understanding of propagation is necessary to properly interpret.
Add To Table of Contents:
Atmospheric Moisture Vapor pressure (e, Pa) The partial pressure exerted by the molecules of vapor in the air. Saturation vapor pressure (e s, Pa ) The.
© TAFE MECAT 2008 Chapter 6(b) Where & how we take measurements.
Air-Sea Exchange in Hurricanes by Peter G. Black & Hurricane Intensity and Eyewall Replacement by Robert A. Houze Jr. Lynsie M. Schwerer Atmospheric Science.
Gathering Weather Data pg. 79. Surface Data Instruments thermometer- filled with mercury or alcohol; expands when heated barometer- measures air pressure;
SCCOOS Website Training Meteorological Stations. 1. Go to the Recent Meteorological Stations and Observations webpage at
Bulk Parameterizations for Wind Stress and Heat Fluxes (Chou 1993; Chou et al. 2003) Outlines: Eddy correlation (covariance) method Eddy correlation (covariance)
AMSR-E Vapor and Cloud Validation Atmospheric Water Vapor –In Situ Data Radiosondes –Calibration differences between different radiosonde manufactures.
One-dimensional assimilation method for the humidity estimation with the wind profiling radar data using the MSM forecast as the first guess Jun-ichi Furumoto,
Instruments. In Situ In situ instruments measure what is occurring in their immediate proximity. E.g., a thermometer or a wind vane. Remote sensing uses.
Atmospheric profile and precipitation properties derived from radar and radiosondes during RICO Louise Nuijens With thanks to: Bjorn Stevens (UCLA) Margreet.
IC2_I Scenarios of future changes in the occurrence of extreme storm surges Nilima Natoo A. Paul, M. Schulz (University of Bremen) M.
Chapter 20 Section 5 Forecasting Weather Objectives: -Compare and contrast the different technologies used to gather weather data -Analyze weather symbols,
The Course of Synoptic Meteorology
Trade Wind Inversion.
Principles of weather forecasting
Upper Air Data The Atmosphere is 3D and can not be understood or forecast by using surface data alone.
New Unit! Climate Change.
Constant Pressure Maps
Weather Instruments.
Weather Forecasting Lesson Objectives
Air Pollution and Control (Elective- I)
Essential Questions Why is accurate weather data important?
Upper air Meteorological charts
The Course of Meteorological Instrumentation and Observations
Weather Instruments.
Operational Oceanography: Modeling EM Propagation Characteristics
LCDR Thomas Keefer OC SEP2006
Section 3: Gathering Weather Data
OC 3750 Operational Oceanography
Comparison of Different Sea Surface Temperature Measurements
AREPS Probability of Detection Validation Project
Upper Air Observations The atmosphere is 3D and can not be understood or forecast by using surface data alone ATM 101W2019.
Comparison of Aircraft Observations With Surface Observations from
The Use of Tethered Balloons to Measure the Evaporation Duct
By: LT ‘Chuck’ Williams
Impact of Sea Surface Temperature Errors on Evaporative Duct Height
Examination of a Boundary Layer Jet
Atmospheric phase correction for ALMA
Assessment of the Surface Mixed Layer Using Glider and Buoy Data
OC 3570 January 2006 Cruise Project
Does Weather Control Your Life???
Operational Oceanography
OC3570 Operational Meteorology
Effects of various SST sources on estimates of the Height of the Stratocumulus Topped Boundary Layer LCDR Mike Cooper.
Marine Environment Radio-Sonde Verification of High Resolution Mesoscale MM5 Model Runs   OC 3570 Project By LCDR Jimmy Horne.
Evaporation Duct Profile Comparisons Using Kites and Bulk Methods
Evaporation Duct Profiles
Comparison of Sea Surface Temperature Collection Methods at Sea
Rawinsonde Kite Profiles
Data Comparison and Analysis of the Frontal Passage Event on 2 FEB 04
ALTIMETRY.
Water Vapor Analysis using ship launched Rawinsondes and MODIS
Evaluation of a Statistical Refractivity Model using Observations from R/V PT SUR OC3570 LCDR Henry A. Miller 18 September 2001.
Validating NAVO’s Navy Coastal Ocean Model
Operational Oceanography
Does Weather Control Your Life???
Analysis of the Monterey Bay
Compare and Contrast of cloud base height data
A Futile Comparison of the Refractive Conditions in the Monterey Bay
RF Propagation Characteristics on Leg 1 of July 06 OC3570 Cruise
Unit 2: “Earth and Space Science”
Presentation transcript:

LT Tom Moneymaker Advisor: Prof Peter Guest Comparison of Measured Evaporative Duct Height to the Bulk Model in Coastal Regions LT Tom Moneymaker Advisor: Prof Peter Guest

Outline Why? Background Procedures Data Analysis Conclusions Background: Talk about the different Duct, the Evaporative Duct Height, and the Bulk model Procedures: How we collected the data and what data was used. Data Analysis: Compare the data to the model.

Why? It is related to my thesis EM background at MET San Diego Significant operational applications How available is METOC data Modern tactical concern Mandatory to do a brief for this class

Background (Ducting) Height (m) M 300 200 100 Elevated Duct Surface-based Duct Height (m) Radar propagation in the atmosphere is dependent on the vertical gradient of the modified index of refraction, M (or modified refractivity). M is a function of pressure (p), temperature (T), and the partial pressure of water vapor (e). There are 3 Ducts that the Navy focuses on. The Elevated Duct, Surface Based Duct, Evaporation Duct. While I was stationed on the MET in San Diego about the USS SHILOH find these Duct’s were a big part of my day. But the think down there was that If you had a SURFACE BASED DUCT THAT YOU WOULDN’T need to worry about the EVAPORTION DUCT b b/c the Surface based duct was so storg but it turns out that the Evap Duct actually helps fill holes of coverage from the SURFACE BASED DUCT Evaporation Duct M

Propagation Loss for Radar Within Evaporation Duct Duct Ht = 65 ft, radar @ 55 ft Evaporation ducting greatly increases radar frequency propagation distances in relation to standard atmosphere propagation distance. Greatly Increased Detection Ranges Possible Duct

Background (Evaporation Duct) 15 10 5 Z* Height (m) Evap Duct The level at which dM/dz = 0 is the evaporation duct height. M is a function of pressure, air temperature and vapor pressure (the latter derived from relative humidity and air temperature) Most operational situations do not allow for direct profile measurements of e, T and p, and therefore M. In these cases the use of bulk methods are used to estimate the profiles M 80 90 100 RH (%)

Model: Monin Obukhov Scaling profiles with bulk model: Monin-Obukhov scaling parameters are determined by measurements at two levels, the surface and an arbitrary reference height (z) within 20 meters of the surface. Specific parameters are the sea surface temperature (SST), an assumed sea surface humidity of 98% and reference height temperature (Tair), humidity and wind speed.

Background (Rel Humidity –vs- True Winds) the predicted EDH is influenced primarily by air–surface humidity (RH) and wind speed for an unstable atmosphere Tair- SST value and wind speed for stable conditions.

Procedures Collect kite data and boat data Massaged the data so as to get rid of the dirty data. Run the data to get M profile Compare kite data to bulk method

Kite-borne Radiosonde R/V Point Sur’s UDAS system 17 meters from the sea surface Three independent systems measured the atmospheric parameters needed to calculate M in-situ and to derive M profiles using bulk methods. R/V Point Sur’s UDAS was used to obtain air temperature, wind speed, relative humidity, pressure and sea surface temperature. All of the instruments (except the sea surface boom probe) were mounted 17 meters from the sea surface. The NPS designed a kite-borne radiosonde system, aimed at measuring the atmospheric surface layer, from near surface (1 meter) up to approximately 100 meters. The sonde can be attached to the kite and measures vertical profiles of pressure, temperature and vapor pressure, the determining parameters for EM propagation, in two-second intervals.

Prof P. Guest A.F. NAVY Program assumes height based on press Negative heights not possible Modify based on in-situ height and time recordings (purple line) Purple line indicates where One meter above the sea surface would be. The Blue down ward spikes indicate where the kite sonde got down to. So the purple line was based off of the measured heights that we took that day and then added onto the end of the blue spike to give the purple line.

Method and Manipulation Bad data Select bad data (purple) Ship influence Readings prior to launch Kite dipping Green is ship data Difference in press, temp and RH

Bad Data Edited Averaging periods determined by subjective temp and RH values

Method and Manipulation Select interval average based on similar airmass characteristics Fairall’s Bulk Method derived Pot Temp, RH and M profile (black line) Mean kite data over interval (lavender circles)

Method and Manipulation Select interval average based on similar airmass characteristics Fairall’s Bulk Method derived Pot Temp, RH and M profile (black line) Mean kite data over interval (lavender circles)