Remote Sensing and Atmospheric Observations
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Questions and Answers

What are the limitations of the Global Telecommunications System (GTS) in terms of weather and climate data reporting?

The GTS does not provide comprehensive real-time reporting for weather forecasting and has even fewer stations for climate records.

How does the availability of balloons for atmospheric observations compare to other types of measurement devices in the GTS?

Fewer balloons are available for observing the vertical structure of the atmosphere compared to other measurement devices.

Why is it significant to have extensive but not comprehensive observational coverage of the globe?

Extensive coverage is crucial for gathering data but its incompleteness can lead to inaccuracies in understanding global weather and climate patterns.

What is the difference between in situ and ex situ observations in the context of remote sensing?

<p>In situ observations are made directly at the measurement site, while ex situ observations are made from afar, such as through satellites or airplanes.</p> Signup and view all the answers

What advancements in remote sensing occurred after World War II?

<p>Advancements included the introduction of RADAR observations, airplane observations, and satellite observations.</p> Signup and view all the answers

What force is introduced in the context of fluid dynamics in a rotating frame of reference?

<p>The Coriolis effect is introduced as a pseudo force in this context.</p> Signup and view all the answers

What is a primary function of RADAR in active remote sensing?

<p>RADAR is primarily used for measuring Sea Surface Height (SSH) and rainfall.</p> Signup and view all the answers

What is the role of LIDAR in remote sensing?

<p>LIDAR is used to measure aerosols, ocean surface winds, and recently, upper-atmosphere winds.</p> Signup and view all the answers

How does the density of water influence the geostrophic approximation in the ocean?

<p>The geostrophic approximation is more significant in the ocean due to the greater density of water.</p> Signup and view all the answers

What is the starting point for linearizing equations in the study of geophysical fluids?

<p>The quasi-geostrophic approximation serves as the starting point for linearization.</p> Signup and view all the answers

What common feature do Meteosat and the James Webb Space Telescope share?

<p>Both are satellites designed for observing Earth and space from orbit.</p> Signup and view all the answers

What information do geostationary satellites like GOES-T help to gather?

<p>Geostationary satellites collect data on weather patterns and environmental changes over a fixed area.</p> Signup and view all the answers

What is the significance of parametrizations in climate modeling?

<p>Parametrizations address the limitations of truncated primitive equations by including effects rather than detailed processes, particularly for complex phenomena like cloud formation.</p> Signup and view all the answers

Which historical event is associated with the Barotropic Rossby Wave Equation?

<p>The first numerical weather forecast was attempted using a simulation of this equation.</p> Signup and view all the answers

Describe the difference between weather and climate models.

<p>Weather models focus on initial condition problems for short-term predictions, while climate models examine long-term sensitivity to changing boundary conditions.</p> Signup and view all the answers

What do the Primitive Equations encompass in fluid dynamics?

<p>The Primitive Equations include the Navier-Stokes equations, thermodynamic energy equation, continuity equation, and ideal gas law.</p> Signup and view all the answers

How do active remote sensing technologies differ from passive ones?

<p>Active remote sensing technologies, like RADAR and LIDAR, emit their own signals to measure distances and gather data, while passive ones rely on natural energy.</p> Signup and view all the answers

What are the key factors in cloud formation mentioned in the content?

<p>Temperature, humidity, dust, and ice crystals are key factors in cloud formation.</p> Signup and view all the answers

Why is the treatment of the discretized grid important in numerical forecasting?

<p>The treatment of the grid significantly affects forecast accuracy.</p> Signup and view all the answers

How do models like CP4-Africa contribute to climate simulations?

<p>Models like CP4-Africa provide higher resolution simulations that can better capture localized climate phenomena, such as convection.</p> Signup and view all the answers

How are the Primitive Equations modified for numerical applications?

<p>The Primitive Equations are discretized both in space and time for numerical solutions.</p> Signup and view all the answers

What is the significance of the Coriolis effect in the context of weather patterns?

<p>The Coriolis effect significantly influences the rotation of air masses and ocean currents.</p> Signup and view all the answers

What role does albedo play in climate modeling?

<p>Albedo, or reflectivity, affects the amount of solar radiation absorbed by the Earth, influencing temperature and climate dynamics.</p> Signup and view all the answers

Explain the term 'buoyancy wave effects' in the context of climate modeling.

<p>Buoyancy wave effects refer to the impacts of buoyancy-driven flows in the atmosphere, which must be represented in models to accurately simulate convection.</p> Signup and view all the answers

What is the relevance of longwave radiation in climate modeling?

<p>Outgoing longwave radiation serves as a proxy for assessing deep convective cloud activity in climate models.</p> Signup and view all the answers

Discuss the impact of increased computing power on climate models.

<p>Increased computing power has allowed for more complex climate models with higher resolutions and longer simulations.</p> Signup and view all the answers

What are the main gases that absorb radiation in the atmosphere?

<p>Water vapor, carbon dioxide, and methane are the main gases that absorb radiation.</p> Signup and view all the answers

What significant observation did Eunice Foote make in 1856 regarding carbon dioxide?

<p>Eunice Foote observed that a glass cylinder containing carbon dioxide heated up more than other gases.</p> Signup and view all the answers

How did John Tyndall contribute to our understanding of greenhouse gases?

<p>John Tyndall quantified the radiative absorption of CO2, water vapor, and methane, showing their effectiveness.</p> Signup and view all the answers

What was Svante Arrhenius's contribution to climate science in 1896?

<p>Svante Arrhenius calculated how much the greenhouse effect might increase Earth's surface temperatures.</p> Signup and view all the answers

What did Guy Callendar estimate in 1938 concerning carbon emissions?

<p>Guy Callendar quantified the effect of anthropogenic carbon emissions on global mean temperature.</p> Signup and view all the answers

According to Hawkins and Jones (2013), what is a key factor influencing global temperature changes?

<p>The imbalance of energy input and output significantly influences global temperature changes.</p> Signup and view all the answers

What trend is observed in the amplitude of the annual temperature range?

<p>The annual temperature range amplitude is higher at higher latitudes and over land compared to water.</p> Signup and view all the answers

What do the terms x2 and x4 CO2 signify in climate modeling?

<p>x2 CO2 and x4 CO2 refer to doubling and quadrupling carbon dioxide levels, indicating significant warming scenarios.</p> Signup and view all the answers

What type of orbits do satellites utilize for specific observational coverage?

<p>Satellites utilize polar orbits for specific observational coverage.</p> Signup and view all the answers

What is the trade-off mentioned when discussing satellite data coverage?

<p>The trade-off is between temporal coverage and spatial coverage.</p> Signup and view all the answers

What are proxy records, and why are they important?

<p>Proxy records are indirect measurements that provide information about past climate conditions, and they are important for understanding long-term climate changes.</p> Signup and view all the answers

What challenges are associated with merging heterogeneous data from various observations?

<p>Challenges include dealing with different observation types, time sampling, spatial coverage, and uncertainty sources.</p> Signup and view all the answers

What is the significance of data assimilation in climate modeling?

<p>Data assimilation is significant as it optimally fits a model to observational data across four dimensions: latitude, longitude, height, and time.</p> Signup and view all the answers

Why is data pipelining considered a critical part of Machine Learning applications?

<p>Data pipelining is critical because it organizes and processes raw data, which is often time-consuming and essential for effective ML application development.</p> Signup and view all the answers

What observational challenges need to be addressed for effective climate modeling?

<p>Challenges include accounting for observational uncertainty, inhomogeneity in space, and intermittency in time.</p> Signup and view all the answers

What is ECMWF Reanalysis 5, and why will it be covered in more detail in a future lecture?

<p>ECMWF Reanalysis 5 is a data assimilation model that provides comprehensive weather and climate data, and it will be covered in detail due to its importance in climate research.</p> Signup and view all the answers

Study Notes

AI in Weather and Climate Science

  • This lecture series focuses on applying AI to weather and climate science.
  • The first week covers fundamental principles in Earth System Science, including modern weather and climate models.
  • A UK Met Office YouTube playlist is recommended for further study, with videos addressing global circulation, differential heating, the three cells, and the Coriolis effect.

Spatiotemporal Continuum of Processes

  • Modeling weather/climate requires addressing a wide range of spatial and temporal scales.
  • Specific models are developed to focus on particular spatiotemporal scales.
  • Global models aim to incorporate all ranges.
  • Processes vary in their horizontal length scales, which vary from minutes to centuries.

Climate and Climate Change

  • Boundary forcing factors that affect weather and climate include:
    • solar energy (roughly constant)
    • atmospheric composition (with greenhouse gases increasing and aerosols fluctuating)
  • Boundary forcing alters the probabilities of weather events, including the forcing of monsoons related to aerosols.

Climate and Climate Change

  • Historically, once Clean Air Acts were passed, there was a recovery in rainfall.
  • Key indicators like CMIP6 are used to evaluate climate change.

Weather Prediction

  • Climate models accurately represent the likelihood of a weather event.
  • Predictions are based accurately on the current climate conditions.
  • Weather predictions aim to determine precise future weather events (hourly, daily, or weekly).

Timescales of Predictability

  • Model predictability reduces with longer timescales.
  • Weather forecasts have high predictability over short timescales.
  • Seasonal to interannual outlooks have moderate predictability.
  • Climate projections have low predictability.

Analogy for model to predict weather

  • Non-linear dynamical systems are extremely sensitive to initial conditions.
  • Mathematics for the analogy of a pendulum's motion are included (link is present).

So how to construct a model?

  • Models are constructed using interconnected physics.

Primitive Equations in Derivatives

  • The Navier-Stokes equations govern fluid motion.
  • Thermodynamic energy equations describe temperature changes.
  • Continuity Equation describes mass conservation.
  • The Ideal Gas Law and Moisture Conservation are other fundamental principles inherent to weather/climate models.

Growth of Climate Modeling

  • Climate model development has progressively included more components over time.
  • Over time, models have included:
  • atmospheric/surface processes/vegetation
  • coupled climate models; sea-ice
  • sulfate aerosols and biogeochemical cycles, carbon cycle, ice sheets
  • upper atmosphere/atmospheric chemistry
  • marine ecosystems.

Atmospheric General Circulation Model (AGCM)

  • AGCMs are 3D grid-box models.
  • They integrate factors like back radiation, incoming solar radiation, air-sea interactions, and water vapor.

Progression of Climate Models

  • Models have improved with better spatial resolution in both the atmosphere and the ocean.

Land Topography in UK Met Office HadCM3 Model

  • The resolution of a model in terms of spatial coverage affects predicted outputs.
  • Spatial resolution of models affect the level of detail captured when creating weather predictions.

Hadley Centre Climate Models

  • Different models have different spatial and temporal resolutions.

Progression in Horizontal Resolution

  • Improving the horizontal resolution of models is crucial for improved atmospheric and ocean data outputs.

Spatiotemporal Continuum of Processes

  • Primitive equations always must be truncated in space, and this is especially important.

Need for Parameterizations

  • Parameterization is needed to tackle physical phenomena at scales too small to be resolved in a model.
  • Addressing clouds and precipitation are important considerations.
  • Parameterizing vegetation albedo and precipitaion is also important.
  • Addressing "buoyancy wave" effects is also important to parameterize.

New Model: Convection permitting Africa (CP4-Africa) simulations

  • The model has 10 year simulations of the present day weather patterns (1997/03-2007/02) and the future RCP8.5 scenario (2097/03-2107/02).

First Rains project simulations

  • The Met Office Unified Model is tested in 3-month long prediction experiments (seasonal prediction).
  • The outgoing longwave radiation is a proxy for deep convective clouds.

Summary

  • Weather prediction involves initial conditions, whereas climate simulation considers the effects of changing boundary conditions(such as atmospheric composition).
  • Primitive equations underpin both weather and climate models.
  • Model improvement aligns with growing computing power.
  • Parametrisation is essential due to the limitations of model resolution.
  • Significant advance has been made on explicit deep convection, which is useful for modeling tropical weather.
  • The Navier-Stokes equations are critical for describing fluid flow, but they are complex in a rotating frame of reference (e.g., Earth's atmosphere).
  • The Coriolis effect is a critical factor to account for when analyzing fluid flow or weather.
  • The Navier-Stokes equations remain an open problem in mathematics.
  • Numerical solutions are used as an approximate solution to the fundamental equations for describing fluid flow and the movement of climate systems. The complex nature of the actual differential equations is noted, with an attempt to solve the underlying system of equations at a given time by the Clay Mathematics Institute.

So lets unpick what this says

  • The Navier-Stokes equation includes terms for flow velocity change, pressure gradient, and friction, but in a rotating frame of reference.
  • The Coriolis effect adds another term.
  • Understanding the interactions of these factors allows for the analysis of climate models.

Flow in a Pipe? vs. Flow in the Atmosphere or Ocean

  • Flow in a pipe is simpler than flow in the atmosphere/ocean due to the Earth's rotation.
  • This rotation introduces the Coriolis effect.

The Coriolis Effect (a pseudo force)

  • The Coriolis effect is a result of the conservation of angular momentum.
  • It exists in rotating reference frames.

Scale Analysis of the Equation

  • The sizes of relevant variables can be estimated in order to simplify the Navier-Stokes equation.
  • Estimating scales is useful for understanding the underlying processes affecting weather patterns in a more simplified mathematical framework.

Geostrophic Approximation

  • In the ocean, the balance between pressure gradients and the Coriolis effect is a strong factor and more significant than in the atmosphere.
  • This is due to the higher density of water in the ocean than air.

Quasi-geostrophic approximation

  • This approximation is the starting point for analyzing analytical solutions of the underlying system of differential equations.

Barotropic Rossby Wave Equation

  • The barotropic Rossby wave equation is relevant in the context of numerical weather forecasting.

Primitive Equations in Derivatives

  • Review of the underlying primitive equations of atmospheric fluid dynamics.

The Primitive Equations are Discretized

  • Physical processes are incorporated into models through the use of discretization methodologies in space and time.
  • The details of the discretized grid methodology may affect the accuracy of the weather forecast, thereby requiring appropriate computational methodology.

So bigger computer, finer grids, smaller timesteps = better forecasts?

  • Increased computational power, along with smaller timesteps and finer grids, are important for accuracy in weather forecasting.
  • However, the inherent non-linearity inherent in weather and climate prediction means that there is a limit to the level of accuracy that can be achieved by increasing computational power.

A non-linear (dynamical) system

  • Non-linear dynamical systems can exhibit sensitive dependence on initial conditions.

Initial condition ensemble forecasts are necessary

  • Ensemble forecasting methods are useful for managing uncertainty in the atmosphere.

The Quiet Revolution in NWP

  • Numerical weather prediction models have seen significant improvements in accuracy, moving from short-term to medium-range predictive capability.

Timescales of Predictability

  • Model predictability reduces with increasing time scales for forecasts in weather modeling.

Summary

  • Understanding fundamental equations, discretization, and observational uncertainty are needed for accurate forecasting.
  • Operational weather prediction relies on the speed of simulation.

Core Learning Goals: Week 1

  • Observing weather and climate and their interplay.
  • Understanding the components of Earth's radiation budget, as a boundary value problem and initial value problem.
  • Formulating the Navier-Stokes equation as a key to understanding atmospheric dynamics, and the associated models of the ocean-atmosphere system.

Today's Lecture

  • The use of problem-driven research methodologies and the rationale behind the need for such methodologies.

What Drives Our Climate?

  • The sun is the primary driver of Earth's climate.
  • Earth's distance from the sun, size, and atmospheric composition contribute to its habitable nature.
  • Water occurs in all 3 phases (solid, liquid, gas)

EM Radiation Emission and Reflection by Earth

  • Solar radiation is dominant at shorter wavelengths (visible spectrum).
  • Earth's radiation is dominant at longer wavelengths (infrared).

Visible Spectrum Imaging

  • Features having higher reflectance (e.g., snow, clouds) show up brighter.
  • Features having low reflectance (e.g., oceans, dense forest) show up darker.

Infrared Spectrum Imaging

  • Infrared images show differences in temperature.
  • Warmer entities appear darker and cooler entities appear brighter.
  • Certain areas of astrophysics and meteorology have overlapping study methodologies.

Active remote-sensing from space

  • RADAR and LIDAR technologies allow for the remote observation of the earth's surface.
  • These technologies also yield insights into atmospheric phenomena.

Where to put the satellites? Orbits

  • Satellites are used for remote-sensing information, with appropriate placement in specific orbital configurations to effectively capture relevant data.

Trade off: Temporal vs Spatial coverage

  • There's a trade-off between temporal and spatial resolution in satellite observations, since temporal coverage is related to satellite orbital patterns, which impacts the geographical space that can be obtained, via the use of that specific satellite.

Timing of the Instrumental Record

  • Different types of observations exist with differing time-stamps.
  • The most recent observations exist in the most recent decade or so.

Summary

  • Vast, heterogeneous observation networks exist for a broad array of types (observations).
  • Robust models require careful consideration of data uncertainties and time-dependent variations in collected observation data.

Other Topics

Group Conversations

  • Discussing personal experiences with weather and climate.
  • Discussions may be in class to aid with understanding the personal, historical, and current realities of climate phenomena across the globe.

Problems/Experiences

  • Examined specific historical issues relating to water and climate patterns in particular regions (e.g., floods, droughts).
  • Several websites for obtaining real-time weather/climate data are available.

Core Learning Goals: Week 1

  • Observational methodologies; weather/climate systems; and associated modeling paradigms.

Today's Lecture

  • Problem-driven research methodology, and background on the topic of research.

Two Lecturers

  • Introduction of the class leaders, with contact details.

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AI in Weather and Climate Science PDF

Description

This quiz explores the limitations of the Global Telecommunications System (GTS) for weather and climate data reporting. It also delves into the roles of various observational methods, advancements in remote sensing since World War II, and the significance of different data types in geophysical studies.

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