Home Training National Himawari-8 Training Campaign Learning Action Map and Learning Outcomes

Learning Action Map and Learning Outcomes

Learning Action Map

Accessible version of the schematic view

Learning Outcomes

The titles of the Familiarisation Resources are mapped against the underpinning Learning Outcomes, WMO-1083 Capabilities and BOM Enabling Skills in the table below. Components of the WMO-1083 Capabilities and BOM Enabling Skills covered in these Resources are highlighted in bold.

Familiarisation Resource Title

Underpinning Learning Outcomes, WMO-1083 Capabilities and BOM Enabling Skills

Forecaster Feedback on the use of Rapid Scan Data (Part A)

At the end of this exercise you will:

Have a better knowledge how 10 minute rapid scan data is an advantage to the Operational Forecaster in monitoring and nowcasting and short term forecasting of tropical cyclone development, thunderstorm development and volcanic ash eruptions

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

WMO 1083 2.3.3.2 – Tropical cyclones: Apply physical and dynamical reasoning to explain the structure and characteristics of tropical cyclones, the main dynamical processes involved in their development, and the techniques used to forecast the development and evolution of tropical storms;

WMO 1083 2.3.3.3 – Convective systems: Apply physical and dynamical reasoning to explain the structure and formation of isolated convective systems such as thunderstorms and convective storms (including single cell, multicell and supercell storms);

Enabling Skills Document Element 2, Performance Component 2 - Identify Cumulonimbus clouds, their intensity and their stage of development.

Enabling Skills Document Element 3, Performance Component 2 - Anticyclones and cyclones (including rapid cyclogenesis), including tropical cyclones and depressions, extratropical and polar lows and cyclones, at upper and lower levels

Enabling Skills Document Element 3, Performance Component 3 - Convective cells and cloud systems (including pulse convection, multicells, supercells, squall lines, mesoscale convective complexes and systems) and associated mesoscale features including outflow boundaries and storm top features. Mesoscale boundaries and interactions, dry lines

Enabling Skills Document Element 4, Skills, Performance component pertaining to "Volcanic Ash particulates"

Forecaster Feedback on the use of Rapid Scan Data (Part B)

At the end of this exercise you will:

have a better knowledge of the advantage of using 10 minute rapid scan satellite data over hourly data in monitoring, nowcasting and short term forecasting of smoke and fire.
Appreciate the advantage of using 10 minute rapid scan satellite data in verifying high spatial resolution Numerical Weather Prediction models.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog ??, sand, volcanic ash, dust, fires, etc.);WMO 1083 2.3.2.2 - Strengths and weaknesses of NWP: Assess the strengths and weaknesses of NWP and the reasons why there are limits to atmospheric predictability;

Enabling Skills Document Element 4, Performance component pertaining to "Fire and Smoke"

Forecaster use of Rapid Scan Data

(part A)

At the end of this exercise you will:

Have a basic knowledge of some tools, specifically Alerts, that the Operational Forecaster can use to effectively use 10 minute rapid scan satellite data within their busy forecasting routine.
Have a basic understanding of the details of existing Alerts for thunderstorm detection and monitoring.
Be familiar with a forecast funnel procedure to interrogate 10 minute rapid scan satellite data more effectively.
Have a better understanding of how the new generation of satellite data may best be delivered to the Operational Forecaster.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3 - Describe service delivery in terms of the nature, use and benefits of the key products and services, including warnings and assessment of weather-related risks.

WMO 1083 2.3.3.3 – Convective systems: Apply physical and dynamical reasoning to explain the structure and formation of isolated convective systems such as thunderstorms and convective storms (including single cell, multicell and supercell storms);

WMO 10832.3.3.5 – Forecast process: Describe the main components of the forecast process, including observation, analysis, diagnosis, prognosis, product preparation, product delivery and product verification;

Enabling Skills Document Element 2, Performance Component 2 - Identify Cumulonimbus clouds, their intensity and their stage of development.

Enabling Skills Document Element 3, Performance Component 3 - Convective cells and cloud systems (including pulse convection, multicells, supercells, squall lines, mesoscale convective complexes and systems) and associated mesoscale features including outflow boundaries and storm top features.

Forecaster use of Rapid Scan Data

(part B)

At the end of this exercise you will:

Have a better understanding of how the new generation of satellite data may best be delivered to the Operational Forecaster.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Integrating conventional and remote-sensing data: Integrate remote-sensing data and synoptic observations to identify synoptic and mesoscale systems and diagnose the weather situation through relating features found in radar and satellite imagery to features observed from other data sources;

No Enabling Skill for this topic

Forecaster use of Rapid Scan Data

(part C)

At the end of this exercise you will:

Have a basic knowledge of some tools, specifically Alerts, that the Operational Forecaster can use to effectively use 10 minute rapid scan satellite data within their busy forecasting routine.
Gain an understanding of how these Alerts can be incorporated into the forecasting process of an Operational Forecaster.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.)

WMO 1083 2.3.3 - Describe service delivery in terms of the nature, use and benefits of the key products and services, including warnings and assessment of weather-related risks.

Enabling Skills Document Element 2, Performance Component 2 - Identify Cumulonimbus clouds, their intensity and their stage of development.

Broadscale Case Study (Japan)

At the end of this exercise you will:

Be able to interpret 10 minute rapid scan satellite data of a simple RGB product
Be able to integrate this satellite data with other meteorological data in order to assist in identifying meteorological features of interest to the forecaster, including fog/low cloud, atmospheric shear, convection, upper atmospheric features including turbulence, upper lows etc.
Have a better understanding of the advantage of using Rapid Scan data over existing hourly satellite image data.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

Enabling Skills Document Element 2, Performance Component 2 - Identify cumulonimbus clouds, their intensity and stage of development.

Enabling Skills Document Element 2, Performance Component 3 - Identify fogs and discriminate between fog and low cloud

Enabling Skills Document Element 3, Performance Component 2 - Jet streams, convergence and frontal zones, conveyor belts

Enabling Skills Document Element 3, Performance Component 2 - Anticyclones and cyclones (including rapid cyclogenesis), including tropical cyclones and depressions, extratropical and polar lows and cyclones, at upper and lower levels

Enabling Skills Document Element 4, Skills, Performance component pertaining to "Features indicating regions of turbulence (clear air turbulence)"

Rapid Scan vs RADAR (Gippsland region, Australia)

At the end of this exercise you will:

Through feedback from Operational Forecasters and through participation in this exercise gain a better understanding of how Rapid Scan satellite imagery (in the visible channel) compares with RADAR in monitoring, nowcasting and short range forecasting of a developing thunderstorm.
Be able to use 10 minute rapid scan satellite data to interpret RADAR signals for convection, smoke, anomalous propagation.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting radar data: Interpret common radar displays, including use of enhancements and animated imagery, to identify features associated with convective and mesoscale processes;

Enabling Skills Document Element 2, Performance Component 2 - Identify cumulonimbus clouds, their intensity and stage of development.

Enabling Skills Document Element 4, Performance Component pertaining to "Fires and Smoke"

Diurnal Tropical Convection (Java, Indonesia)

At the end of this exercise you will:

Be able to use 10 minute rapid scan satellite data to monitor and identify features of interest to the Operational Forecaster in the development of cloud and convection for a location in the deep tropics.
Have a better understanding of the advantage of using Rapid Scan data over existing hourly satellite image data for the monitoring, nowcasting and short term forecasting of convective development in the deep tropics.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

Enabling Skills Document Element 2, Performance Component 2 - Identify cumulonimbus clouds, their intensity and stage of development.

Enabling Skills Document Element 2, Performance Component 3 - Identify fogs and discriminate between fog and low cloud

Monsoon Squall Lines (Arafura Sea, Australia)

At the end of this exercise you will:

Be able to use 10 minute rapid scan satellite data to monitor and identify features of interest to the Operational Forecaster in the development of monsoonal squall lines and other features of interest within the monsoonal flow in the deep tropics.
Have a better understanding of the advantage of using Rapid Scan data over existing hourly satellite image data for the monitoring, nowcasting and short term forecasting of monsoonal squall lines and other features of interest within the monsoonal flow in the deep tropics.
Gain an understanding how the 10 minute rapid scan satellite data can be integrated into other meteorological data (RADAR data, METARS).

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts; Yes – radar superposition on image

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

WMO 1083 2.3.3.2 – Extreme weather: Describe the weather, with emphasis on any extreme or hazardous conditions that might be associated with tropical weather systems (including tropical cyclones and monsoons) and the likely impact of such conditions;

WMO 1083 2.3.3.4 (maybe not here…) – Integrating conventional and remote-sensing data: Integrate remote-sensing data and synoptic observations to identify synoptic and mesoscale systems and diagnose the weather situation through relating features found in radar and satellite imagery to features observed from other data sources;

Enabling Skills Document Element 3, Performance Component 1 - Intertropical convergence zones, monsoon and trade wind regimes

Enabling Skills Document Element 2, Performance Component 2 - Identify cumulonimbus clouds, their intensity and stage of development.

Turbulence Signatures over Honshu (Japan)

At the end of this exercise you will:

Be able to use 10 minute rapid scan satellite data to identify features of interest to the Operational Forecaster in the development of cloud indicating possible atmospheric turbulence including Jetstream turbulence, mountain waves, lee clouds etc.
Be able to use 10 minute rapid scan satellite data in combination with other meteorological data such as atmospheric soundings, cloud drift winds, atmospheric shear to verify areas of atmospheric turbulence.
Understand and be able to apply appropriate criteria to determine severity of associated turbulence.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

WMO 1083 2.3.3.3 – Orographic mesoscale phenomena: Apply physical and dynamical reasoning to explain the structure and formation of orographic mesoscale phenomena (lee waves, rotors, up-slope and down-slope winds, valley winds, gap flows, lee lows, etc.);

WMO 1083 2.3.1.2 - Thermodynamic diagrams: Use a thermodynamic diagram to analyse atmospheric processes, including assessing atmospheric stability, determining common parameters used to describe the state of the atmosphere (including cloud parameters), and interpreting the key features of a sounding;

WMO 1083 2.3.3.4 – Integrating conventional and remote-sensing data: Integrate remote-sensing data and synoptic observations to identify synoptic and mesoscale systems and diagnose the weather situation through relating features found in radar and satellite imagery to features observed from other data sources;

WMO 1083 2.3.3.1 - Jet streaks and jet stream: Apply physical and dynamical reasoning to explain the development, structure and impact of jet streaks and the relationship between the jet stream and the development of mid-latitude depressions;

Enabling Skills Document Element 3, Performance component 3 pertaining to "Gravity Waves"

Enabling Skills Document Element 4, Skills, Performance component pertaining to "Features indicating regions of turbulence (clear air turbulence)"

Turbulence Signatures over Queensland (Australia)

At the end of this exercise you will:

Be able to use 10 minute rapid scan satellite data to identify features of interest to the Operational Forecaster in the development of cloud indicating possible upper atmospheric turbulence.
Have a better understanding of the advantage of using Rapid Scan data over existing hourly satellite image data for the monitoring, nowcasting and short term forecasting of cloud indicating possible upper atmospheric turbulence and for verifying NWP.
Be able to verify turbulence in cloud signatures by correctly referencing the BNOC SIGWX chart.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

WMO 1083 2.3.3.1 - Jet streaks and jet stream: Apply physical and dynamical reasoning to explain the development, structure and impact of jet streaks and the relationship between the jet stream and the development of mid-latitude depressions;

Enabling Skills Document Element 4, Performance component pertaining to "Features indicating regions of turbulence (clear air turbulence)"

Enabling Skills Document Element 3, Performance component 2 pertaining to "Jet Streams, convergence and frontal zones, conveyor belts "

Fog and Low Cloud (South Australia)

At the end of this exercise you will:

Have a better understanding of how 10 minute rapid scan satellite data is used by Operational Forecasters for monitoring, nowcasting and short-term forecasting of fog and low cloud, both during the night time and during the day.
Have a better understanding of the advantage of using Rapid Scan data over existing hourly satellite image data for the monitoring, nowcasting and short term forecasting of fog and low cloud, both during the night time and during the day.
Be able to verify fog/low cloud using other meteorological data (ie. ceilometer).

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

Enabling Skills Document Element 2, Performance Component 3 - Identify fogs and discriminate between fog and low cloud

Smoke and Fire (Victoria, Australia)

At the end of this exercise you will:

Have a better understanding of how 10 minute rapid scan satellite data is used by Operational Forecasters for monitoring, nowcasting and short-term forecasting of smoke during the day and fire hotspots during the night.
Have a better understanding of the advantage of using Rapid Scan data over existing hourly satellite image data for the monitoring and nowcasting of fire hotspots during the night.

WMO 1083 2.3.3 – Monitor and observe the weather situation, and use real-time or historic data, including satellite and radar data, to prepare analyses and basic forecasts;

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

Enabling Skills Document Element 4, Skills, Performance component pertaining to "Fires and Smoke"

Introduction to Red-Green-Blue (RGB) products

At the end of this exercise you will:

Have a good basic understanding of Red-Green-Blue (RGB) satellite products and why these are important to the Operational Forecaster with the advent of the new generation of Geostationary satellites (eg. Himawari-8, GOES-R etc.)
The important RGB products endorsed by EUMETSAT and where to find RGB product data on the Internet

WMO 1083 2.3.3 - Describe service delivery in terms of the nature, use and benefits of the key products and services, including warnings and assessment of weather-related risks.

No Enabling Skill for this topic

Introduction to the Dust RGB product (China / Sudan).

At the end of this exercise you will:

Have a basic knowledge how the Dust RGB product is constructed from multiple satellite channels and the physics and meteorology underpinning this.
Have a better understanding of the advantages and the limitations of the Dust RGB product in comparison with visible and infrared satellite imagery in the operational monitoring, nowcasting and short term forecasting of dust.
Be able to identify and locate dust and other specific meteorological features using the Dust RGB product.
Have a better appreciation of the advantages in using the Dust RGB in rapid scan animation when monitoring, nowcasting and short term forecasting of Dust.

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

Enabling Skills Document: Element 4, Performance Component "Dust and sandstorms and plumes and areas of raised dust"

Introduction to the Volcanic Ash RGB product (Indonesia)

At the end of this exercise you will:

Have a basic knowledge how the Volcanic Ash RGB product is constructed from multiple satellite channels and the physics and meteorology underpinning this.
A better understanding of the advantages and the limitations of the Volcanic Ash RGB product in comparison with visible and infrared satellite imagery in the operational monitoring, nowcasting and short term forecasting of a volcanic eruption over Indonesia.
Be able to identify and locate volcanic ash (and volcanic SO2) and other specific meteorological features in the Volcanic Ash RGB product.

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

Enabling Skills Document: Element 4, Performance Component "Volcanic Ash particulates and chemical emissions"

Introduction to the Airmass RGB product (Southern Atlantic / western Europe)

At the end of this exercise you will:

Have a basic knowledge how the Airmass RGB product is constructed from multiple satellite channels and the physics and meteorology underpinning this.
Have a better understanding of the advantages and the limitations of the Airmass RGB product in comparison with single channel water vapour satellite imagery in the operational monitoring, nowcasting and short term forecasting of features in the middle and upper levels of the atmosphere.
Be able to identify and locate mid and upper atmosphere features such as ozone rich intrusions associated with jetstreams, upper lows etc. in the Airmass RGB product.
Have a better appreciation of using the Airmass RGB product in rapid scan animation when monitoring, nowcasting and short term forecasting of features in the middle and upper levels of the atmosphere.

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

WMO 1083 2.3.1.5 - Passive sensing systems: Explain how passive sensing systems are used to provide digital data (such as visible, near infrared, infrared and water vapour imagery channels) and derived information about surface temperature and lightning, and atmospheric properties (including temperature, humidity, wind and atmospheric constituents);

No Enabling Skill for this topic

Introduction to the Severe Storm RGB (Africa / Spain)

At the end of this exercise you will:

Have a basic knowledge how the Severe Convection RGB product is constructed from multiple satellite channels and the physics and meteorology underpinning this.
Have a better understanding of the advantages and the limitations of the Severe Storm RGB product in comparison with infrared satellite imagery in the operational monitoring, nowcasting and short term forecasting of thunderstorms.
Have a better appreciation of using the Severe Storm RGB in rapid scan animation when monitoring, nowcasting and short term forecasting of thunderstorms.

WMO 1083 2.3.3.4 – Interpreting satellite imagery: Interpret satellite images, including use of common wavelengths (infrared, visible, water vapour and near infrared) and enhancements and animated imagery, to identify cloud types and patterns, synoptic and mesoscale systems, and special features (fog, sand, volcanic ash, dust, fires, etc.);

WMO 1083 2.3.3.3 - Extreme weather: Describe the weather, with emphasis on any extreme or hazardous conditions that might be associated with convective and mesoscale phenomena, and the likely impact of such conditions;

Enabling Skills Document Element 2, Performance Component 2 - Identify cumulonimbus clouds, their intensity and stage of development.

Enabling Skills Document Element 2, Performance Component 7 - Discriminate between clouds with small or large cloud particles

Adapting RGB products to low latitudes

At the end of this exercise you will:

Have a basic understanding of some modifications that are required for the Severe Convection RGB and the Microphysics RGB products so that these can be effectively used by Operational Forecasters at low latitudes.

WMO 1083 2.3.3.2 - Weather systems: Explain how tropical weather systems differ from those in mid-latitudes and polar regions;

No Enabling Skill for this topic