Meteorology made simple - Fundamentals

1. Meteorology made simple - Fundamentals Dr. Dipl.-Met. Christian Werner

2. Outline • Introduction • What is Meteorology? • Focus: Synoptic Meteorology • The Atmosphere • Meteorological variables • Atmospheric Stability • The graphical presentation of air density and humidity at different heights • Key Drivers for Climate and Weather in Australia • Environmental Forecasting • Graphical presentation of meteorological variables • Q&A

3. Introduction How can meteorologists add value? "We're scientists working on analysis and forecasting problems and the pilots require scientific support to ensure safe operations, applied risk management, fly faster and further, so essentially we're delivering scientific products to help them make the best decisions possible for their chosen flight.“ - Dr. Christian Werner, Managing Director

4. What is Meteorology? • Meteorology is the multi and interdisciplinary scientific study of the atmosphere. • Meteorology is part of the atmospheric sciences. • Meteorology is often referred to as atmospheric physics. • The word "meteorology" is from Greek μετέωρος metéōros "lofty; high (in the sky)" (from μετα- meta- "above" and ἐωρ eōr "to lift up") and -λογία -logia "-(o)logy". • Aviation - Gliding Meteorology • Weather Prediction & NWP

5. Synoptic Meteorology • The word synoptic is derived from the Greek word συνοπτικός (sunoptikos), meaning seen together (overview). • Meteorological phenomena in space and how they change over time => weather forecasting • Synoptic methodology: Weather analysis (diagnosis) and prognosis • Fundamental is the knowledge of the current state of the atmosphere and the physical diagnosis of the development state of the observed weather patterns at a given point in time. • Scale analysis (horizontal equation of motion) • WMO No. 418: small scale (<100km), meso scale (100-1000km), large scale (1000-5000km), planetary scale (>5000km) • The Prediction Problem: F=ma, F=dp/dt = d(mv)/dt => dp = sum (F x dt), (p=impulse), this is a prognostic equation for the future state of motion, assuming the initial state is known.

6. The Atmosphere • Air pressure = 1013.25 hPa • Air temperature = 15 degC • Rel. Humidity = 0% • Air density = 1.225 kg/m^3 • Lapse rate = 0.65 degC/100m • Tropopause = 11000m • Tropopause temp = -56.5 degC • Isothermic up to 20km, then temperature increase to 32km with 1 degC/km, composition of air constant up to 80km

7. Meteorological Variables • Temperature, humidity, pressure, wind • Dew point temperature • Radiative Processes • Clouds • Precipitation

8. Atmospheric Stability • dT/dz = lapse rate = -0.98degC/100m • dT/dz =  • dT/dz >  <=> dry stable • dT/dz <  <=> dry unstable • dT/dz =  <=> dry indifferent • Environmental lapse rate (ELR) - actual change of temperature with z (stationary atmosphere - environment - outside) • Dry adiabatic lapse rate (DALR) - dT/dz of a parcel of air (inside) as it moves up/down assuming adiabatic conditions • Outside and inside dT fully independent! • Moist adiabatic lapse rate (MALR)

9. Thermodynamic diagrams • Graphical presentation of air temperature and humidity at different heights • Emagram • Tephigram • Stueve diagram (uses straight lines, but no equal area requirement) • Skew-T log-P diagram • Isobars • Isotherms (and potential temperature) • Dry adiabates • Moist/saturated adiabates • Mixing ratio (dew point)

10. Thermodynamic diagrams • Steep lapse rate => unstable • Shallow or negative lapse rate => stable • When temperature decreases rapidly during climb (approx 3 degC/1000ft), indication of unstable air.

11. Thermodynamic diagrams

12. Key Drivers for Climate and Weather in Australia • Large-scale circulation patterns - basically the spatial and temporal distribution of pressure systems • Large-scale circulation patterns are heavily influenced by ENSO - El Nino Southern Oscillation • ENSO is the main reason for interannual variability of meteorological variables • Cloncurry heat low associated with the QLD trough, driven by insolation • Sea breeze activity for coastal areas

13. Environmental Forecasting for Australia - Challenges & Solutions

14. Environmental Forecasting for Australia - Challenges & Solutions

15. Environmental Forecasting for Australia - Challenges & Solutions

16. Environmental Forecasting for Australia - Challenges & Solutions

17. Environmental Forecasting for Australia - Challenges & Solutions • Challenge: How to best represent topography in environmental models to produce realistic weather and climate patterns? Flatter topo leads to larger forecast errors!

18. Environmental Forecasting for Australia - Challenges & Solutions • Challenge: How to best represent topography in environmental models to produce realistic weather and climate patterns?

19. Environmental Forecasting for Australia - Challenges & Solutions • Challenge: How to best represent topography in environmental models to produce realistic weather and climate patterns? When is enough enough? => TOPO needs to be 1km or less.

20. Environmental Forecasting for Australia and beyond - Challenges & Solutions • Input data:

21. Environmental Forecasting - Challenges & Solutions • Input data => Data Assimilation

22. Environmental Forecasting - Challenges & Solutions • Input data => Data Assimilation • NWP represents an initial value problem (mathematically) • Need to know as precisely as possible the current state of the weather. • Need to know not just at the location of interest, but globally. • Data volume to be processed is approx 10-15 million information quanta, higher data volumes better • Problem: data gaps and delayed data => under-determined initial value problem => weather forecasts are not accurate. Other sources of error/uncertainty are based on numerical schemes employed in the programs, choice of compiler and compiler options. • Solution: additional information, which is statistical and dynamical => use 3D and 4D (VAR) data assimilation, which is used on the basis of incomplete and possibly incorrect observations to analyse the likely current state of the atmosphere and to determine the error in the analysis. • Observations used are: land and sea based weather stations (METAR, SYNOP and SHIP), buoys, aircraft reports, radiosondes, polar-orbiting and geostationary statellites, scatterometer data (winds at sea level height), Doppler RADARS, GPS-signals (additional temperature and humidity profiles). • New ensemble prediction system:

23. Environmental Forecasting - Challenges & Solutions • Ensemble: A set of multiple predictions valid for the same time. • Generated from different initial conditions and/or different models or versions of models. • Provides reliable information on forecast uncertainties from the spread amongst the ensemble members. Provides information about the likelihood of extreme events.

24. Graphical Presentation of meteorological variables

25. Graphical Presentation of meteorological variables

26. Q&A • Difference between ELR and DALR?

27. Q&A • Parcel boundary is flexible, parcel volume expands, which cools the air on the inside. • As the parcel rises, the outside temperature is usually dropping (ELR). Important here is that the outside and inside temperature changes are completely independent, assuming adiabatic process. The outside temperature is dropping as with increasing height we are moving away from the warmer surface. The inside of the parcel is decreasing due to the expanding volume (decreasing pressure).