#nwp — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #nwp, aggregated by home.social.
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Ab sofort bis zum 25. Juni können Sie Kommentare und Anregungen zum Entwurf des Nationalen Wiederherstellungsplans (NWP) über die Online-Beteiligungsplattform des Bundesumweltministeriums abgeben: https://beteiligung.bundesumweltministerium.de/de/nationaler-wiederherstellungsplan
Foto: PeopleImages via Getty Image
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Ab sofort bis zum 25. Juni können Sie Kommentare und Anregungen zum Entwurf des Nationalen Wiederherstellungsplans (NWP) über die Online-Beteiligungsplattform des Bundesumweltministeriums abgeben: https://beteiligung.bundesumweltministerium.de/de/nationaler-wiederherstellungsplan
Foto: PeopleImages via Getty Image
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Ab sofort bis zum 25. Juni können Sie Kommentare und Anregungen zum Entwurf des Nationalen Wiederherstellungsplans (NWP) über die Online-Beteiligungsplattform des Bundesumweltministeriums abgeben: https://beteiligung.bundesumweltministerium.de/de/nationaler-wiederherstellungsplan
Foto: PeopleImages via Getty Image
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Ab sofort bis zum 25. Juni können Sie Kommentare und Anregungen zum Entwurf des Nationalen Wiederherstellungsplans (NWP) über die Online-Beteiligungsplattform des Bundesumweltministeriums abgeben: https://beteiligung.bundesumweltministerium.de/de/nationaler-wiederherstellungsplan
Foto: PeopleImages via Getty Image
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Ab sofort bis zum 25. Juni können Sie Kommentare und Anregungen zum Entwurf des Nationalen Wiederherstellungsplans (NWP) über die Online-Beteiligungsplattform des Bundesumweltministeriums abgeben: https://beteiligung.bundesumweltministerium.de/de/nationaler-wiederherstellungsplan
Foto: PeopleImages via Getty Image
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The Bulletin of the American Meteorological Society has published a critique of ML by Leonard A Smith and Alan Thorpe. It compares the role and value of physics-based and statistical models in weather and climate forecasting, and tempers the ebulition around AI/ML.
The article content is accessible to non-specialists in either ML or meteorology.
https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-25-0214.1/BAMS-D-25-0214.1.pdf
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The Bulletin of the American Meteorological Society has published a critique of ML by Leonard A Smith and Alan Thorpe. It compares the role and value of physics-based and statistical models in weather and climate forecasting, and tempers the ebulition around AI/ML.
The article content is accessible to non-specialists in either ML or meteorology.
https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-25-0214.1/BAMS-D-25-0214.1.pdf
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The Bulletin of the American Meteorological Society has published a critique of ML by Leonard A Smith and Alan Thorpe. It compares the role and value of physics-based and statistical models in weather and climate forecasting, and tempers the ebulition around AI/ML.
The article content is accessible to non-specialists in either ML or meteorology.
https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-25-0214.1/BAMS-D-25-0214.1.pdf
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The Bulletin of the American Meteorological Society has published a critique of ML by Leonard A Smith and Alan Thorpe. It compares the role and value of physics-based and statistical models in weather and climate forecasting, and tempers the ebulition around AI/ML.
The article content is accessible to non-specialists in either ML or meteorology.
https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-25-0214.1/BAMS-D-25-0214.1.pdf
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The Bulletin of the American Meteorological Society has published a critique of ML by Leonard A Smith and Alan Thorpe. It compares the role and value of physics-based and statistical models in weather and climate forecasting, and tempers the ebulition around AI/ML.
The article content is accessible to non-specialists in either ML or meteorology.
https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-25-0214.1/BAMS-D-25-0214.1.pdf
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Happy to report the earliest (and final) stream for #ORAS6 has entered production. Just in the spinup period now, but we have some #reanalysis data valid in 1944 already. Now just to be patient until this reaches 1993 where the already produced stream awaits...
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Happy to report the earliest (and final) stream for #ORAS6 has entered production. Just in the spinup period now, but we have some #reanalysis data valid in 1944 already. Now just to be patient until this reaches 1993 where the already produced stream awaits...
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Happy to report the earliest (and final) stream for #ORAS6 has entered production. Just in the spinup period now, but we have some #reanalysis data valid in 1944 already. Now just to be patient until this reaches 1993 where the already produced stream awaits...
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Happy to report the earliest (and final) stream for #ORAS6 has entered production. Just in the spinup period now, but we have some #reanalysis data valid in 1944 already. Now just to be patient until this reaches 1993 where the already produced stream awaits...
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Happy to report the earliest (and final) stream for #ORAS6 has entered production. Just in the spinup period now, but we have some #reanalysis data valid in 1944 already. Now just to be patient until this reaches 1993 where the already produced stream awaits...
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BIG news from #ECMWF: a portable version of our global forecasting model is now open source! Development of #IFS started in 1987 and just a year before entering its 4th decade it is now available to all.
This continues our journey that started a few years ago, when we made a first and growing number of several key model components available.
See the news article for more details: https://www.ecmwf.int/en/about/media-centre/news/2026/openifs-open-source
Code repository: https://github.com/ecmwf-ifs/openifs
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BIG news from #ECMWF: a portable version of our global forecasting model is now open source! Development of #IFS started in 1987 and just a year before entering its 4th decade it is now available to all.
This continues our journey that started a few years ago, when we made a first and growing number of several key model components available.
See the news article for more details: https://www.ecmwf.int/en/about/media-centre/news/2026/openifs-open-source
Code repository: https://github.com/ecmwf-ifs/openifs
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BIG news from #ECMWF: a portable version of our global forecasting model is now open source! Development of #IFS started in 1987 and just a year before entering its 4th decade it is now available to all.
This continues our journey that started a few years ago, when we made a first and growing number of several key model components available.
See the news article for more details: https://www.ecmwf.int/en/about/media-centre/news/2026/openifs-open-source
Code repository: https://github.com/ecmwf-ifs/openifs
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BIG news from #ECMWF: a portable version of our global forecasting model is now open source! Development of #IFS started in 1987 and just a year before entering its 4th decade it is now available to all.
This continues our journey that started a few years ago, when we made a first and growing number of several key model components available.
See the news article for more details: https://www.ecmwf.int/en/about/media-centre/news/2026/openifs-open-source
Code repository: https://github.com/ecmwf-ifs/openifs
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BIG news from #ECMWF: a portable version of our global forecasting model is now open source! Development of #IFS started in 1987 and just a year before entering its 4th decade it is now available to all.
This continues our journey that started a few years ago, when we made a first and growing number of several key model components available.
See the news article for more details: https://www.ecmwf.int/en/about/media-centre/news/2026/openifs-open-source
Code repository: https://github.com/ecmwf-ifs/openifs
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ECMWF annual seminar 2026 is on "Advancing the assimilation of Earth system observations with new methodology and Machine Learning"
Registration is open:
https://events.ecmwf.int/event/513/overview -
ECMWF annual seminar 2026 is on "Advancing the assimilation of Earth system observations with new methodology and Machine Learning"
Registration is open:
https://events.ecmwf.int/event/513/overview -
ECMWF annual seminar 2026 is on "Advancing the assimilation of Earth system observations with new methodology and Machine Learning"
Registration is open:
https://events.ecmwf.int/event/513/overview -
ECMWF annual seminar 2026 is on "Advancing the assimilation of Earth system observations with new methodology and Machine Learning"
Registration is open:
https://events.ecmwf.int/event/513/overview -
ECMWF annual seminar 2026 is on "Advancing the assimilation of Earth system observations with new methodology and Machine Learning"
Registration is open:
https://events.ecmwf.int/event/513/overview -
@tinoeberl #ECMWF recognized “AI” #NWP is accurate for large scale ~2,000 km features only. Let’s put some science based constraints to the “AI” hype.
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@tinoeberl #ECMWF recognized “AI” #NWP is accurate for large scale ~2,000 km features only. Let’s put some science based constraints to the “AI” hype.
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@tinoeberl #ECMWF recognized “AI” #NWP is accurate for large scale ~2,000 km features only. Let’s put some science based constraints to the “AI” hype.
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@tinoeberl #ECMWF recognized “AI” #NWP is accurate for large scale ~2,000 km features only. Let’s put some science based constraints to the “AI” hype.
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@tinoeberl #ECMWF recognized “AI” #NWP is accurate for large scale ~2,000 km features only. Let’s put some science based constraints to the “AI” hype.
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D-Wave Quantum (QBTS) and North Wales Police (NWP) Announce Completion of Joint Proof-of-technology Project https://www.byteseu.com/1421140/ #DWaveQuantumInc. #NorthWalesPolice #NWP #PoliceVehicles #QuantumComputing #Technology
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#EUMETSAT via #businesswire:
"
Revolutionärer Metop-SGA1 überträgt bereits Instrumentendaten
"
"Weniger als drei Wochen nach dem Start von Metop-Satellit A1 der zweiten Generation (Metop-SGA1) am 13. August überträgt der Satellit bereits Daten von zwei seiner sechs Instrumente."https://www.businesswire.com/news/home/20250902406888/de
https://www.eumetsat.int/revolutionary-metop-sga1-already-transmitting-instrument-data
2.9.2025
#EO #Erdbeobachtung #ESA #Europa #NWP #MetOpSG #MetOpSGA1 #MWS #Raumfahrt #RO #Satelliten #SpaceFlight #Wettervorhersage #Wettersatellit
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#EUMETSAT via #businesswire:
"
Revolutionärer Metop-SGA1 überträgt bereits Instrumentendaten
"
"Weniger als drei Wochen nach dem Start von Metop-Satellit A1 der zweiten Generation (Metop-SGA1) am 13. August überträgt der Satellit bereits Daten von zwei seiner sechs Instrumente."https://www.businesswire.com/news/home/20250902406888/de
https://www.eumetsat.int/revolutionary-metop-sga1-already-transmitting-instrument-data
2.9.2025
#EO #Erdbeobachtung #ESA #Europa #NWP #MetOpSG #MetOpSGA1 #MWS #Raumfahrt #RO #Satelliten #SpaceFlight #Wettervorhersage #Wettersatellit
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#EUMETSAT via #businesswire:
"
Revolutionärer Metop-SGA1 überträgt bereits Instrumentendaten
"
"Weniger als drei Wochen nach dem Start von Metop-Satellit A1 der zweiten Generation (Metop-SGA1) am 13. August überträgt der Satellit bereits Daten von zwei seiner sechs Instrumente."https://www.businesswire.com/news/home/20250902406888/de
https://www.eumetsat.int/revolutionary-metop-sga1-already-transmitting-instrument-data
2.9.2025
#EO #Erdbeobachtung #ESA #Europa #NWP #MetOpSG #MetOpSGA1 #MWS #Raumfahrt #RO #Satelliten #SpaceFlight #Wettervorhersage #Wettersatellit
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#EUMETSAT via #businesswire:
"
Revolutionärer Metop-SGA1 überträgt bereits Instrumentendaten
"
"Weniger als drei Wochen nach dem Start von Metop-Satellit A1 der zweiten Generation (Metop-SGA1) am 13. August überträgt der Satellit bereits Daten von zwei seiner sechs Instrumente."https://www.businesswire.com/news/home/20250902406888/de
https://www.eumetsat.int/revolutionary-metop-sga1-already-transmitting-instrument-data
2.9.2025
#EO #Erdbeobachtung #ESA #Europa #NWP #MetOpSG #MetOpSGA1 #MWS #Raumfahrt #RO #Satelliten #SpaceFlight #Wettervorhersage #Wettersatellit
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#EUMETSAT via #businesswire:
"
Revolutionärer Metop-SGA1 überträgt bereits Instrumentendaten
"
"Weniger als drei Wochen nach dem Start von Metop-Satellit A1 der zweiten Generation (Metop-SGA1) am 13. August überträgt der Satellit bereits Daten von zwei seiner sechs Instrumente."https://www.businesswire.com/news/home/20250902406888/de
https://www.eumetsat.int/revolutionary-metop-sga1-already-transmitting-instrument-data
2.9.2025
#EO #Erdbeobachtung #ESA #Europa #NWP #MetOpSG #MetOpSGA1 #MWS #Raumfahrt #RO #Satelliten #SpaceFlight #Wettervorhersage #Wettersatellit
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Machine Learning is making a big impression in Numerical Weather Prediction these days. However, explicitly physics-based models still outperform AI models when it comes to extreme events. #meteorology #nwp
https://arxiv.org/abs/2508.15724
Hey sometimes my LinkedIn feed isn't all Facebook for office grunts.
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Machine Learning is making a big impression in Numerical Weather Prediction these days. However, explicitly physics-based models still outperform AI models when it comes to extreme events. #meteorology #nwp
https://arxiv.org/abs/2508.15724
Hey sometimes my LinkedIn feed isn't all Facebook for office grunts.
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Machine Learning is making a big impression in Numerical Weather Prediction these days. However, explicitly physics-based models still outperform AI models when it comes to extreme events. #meteorology #nwp
https://arxiv.org/abs/2508.15724
Hey sometimes my LinkedIn feed isn't all Facebook for office grunts.
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Basics of Numerical Weather Prediction (NWP):
1. THE HORIZONTAL MOMENTUM EQUATION:
\[
\frac{d\mathbf{V}}{dt} + f\hat{k} \times \mathbf{V} = -\nabla \phi + \frac{\sigma}{p_s} \frac{\partial \phi}{\partial \sigma} \nabla p_s + \mathbf{F}
\]2. THE CONTINUITY EQUATION:
\[
\frac{\partial p_s}{\partial t} + \nabla \cdot (p_s \mathbf{V}) + \frac{\partial}{\partial \sigma}(p_s \dot{\sigma}) = 0
\]3. THE THERMODYNAMIC ENERGY EQUATION:
\[
\frac{1}{R} \frac{d}{dt} \left[ \sigma \frac{\partial \phi}{\partial \sigma} \right] + \frac{RT}{C_p p} \left[ p_s \dot{\sigma} + \sigma\dot{p_s} \right] = -Q
\]4. HYDROSTATIC EQUATION:
\[
\frac{\partial \phi}{\partial \sigma} = -\frac{RT_v}{\sigma}
\]5. SURFACE PRESSURE TENDENCY EQUATION:
\[\displaystyle
\frac{\partial p_s}{\partial t} = -\int_{0}^{1} \nabla\cdot (p_s \mathbf{V}) \, d\sigma
\]6. MOISTURE EQUATION:
\[\displaystyle
\frac{\partial}{\partial t} (p_s q) + \nabla\cdot (p_s q \mathbf{V}) + \frac{\partial}{\partial \sigma} (p_s q \dot{\sigma}) = p_s S
\]The six primary unknowns are: \(\mathbf{V}\) (horizontal wind velocity), \(p_s\) (surface pressure), \(T\) (temperature), \(q\) (specific humidity or moisture), \(\phi\) (geopotential), and \(\dot{\sigma}\) (sigma velocity or vertical velocity in \(\sigma\)-coordinates).
#NWP #Weather #NumericalWeatherPrediction #Meteorology #Climate #ClimateScience #Earth #EarthScience #ClimateChange #ClimateSciences #Science #WeatherPrediction #Humidity #Moisture #Pressure #Velocity #SurfacePressure #HydrostaticEquation #WeatherPrediction #Ocean #Atmosphere #AOS #ClimateDynamics #WeatherDynamics #Geopotential #SigmaVelocity #VerticalVelocity #MoistureEquation #Thermodynamics #Dynamics #NavierStokes
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Basics of Numerical Weather Prediction (NWP):
1. THE HORIZONTAL MOMENTUM EQUATION:
\[
\frac{d\mathbf{V}}{dt} + f\hat{k} \times \mathbf{V} = -\nabla \phi + \frac{\sigma}{p_s} \frac{\partial \phi}{\partial \sigma} \nabla p_s + \mathbf{F}
\]2. THE CONTINUITY EQUATION:
\[
\frac{\partial p_s}{\partial t} + \nabla \cdot (p_s \mathbf{V}) + \frac{\partial}{\partial \sigma}(p_s \dot{\sigma}) = 0
\]3. THE THERMODYNAMIC ENERGY EQUATION:
\[
\frac{1}{R} \frac{d}{dt} \left[ \sigma \frac{\partial \phi}{\partial \sigma} \right] + \frac{RT}{C_p p} \left[ p_s \dot{\sigma} + \sigma\dot{p_s} \right] = -Q
\]4. HYDROSTATIC EQUATION:
\[
\frac{\partial \phi}{\partial \sigma} = -\frac{RT_v}{\sigma}
\]5. SURFACE PRESSURE TENDENCY EQUATION:
\[\displaystyle
\frac{\partial p_s}{\partial t} = -\int_{0}^{1} \nabla\cdot (p_s \mathbf{V}) \, d\sigma
\]6. MOISTURE EQUATION:
\[\displaystyle
\frac{\partial}{\partial t} (p_s q) + \nabla\cdot (p_s q \mathbf{V}) + \frac{\partial}{\partial \sigma} (p_s q \dot{\sigma}) = p_s S
\]The six primary unknowns are: \(\mathbf{V}\) (horizontal wind velocity), \(p_s\) (surface pressure), \(T\) (temperature), \(q\) (specific humidity or moisture), \(\phi\) (geopotential), and \(\dot{\sigma}\) (sigma velocity or vertical velocity in \(\sigma\)-coordinates).
#NWP #Weather #NumericalWeatherPrediction #Meteorology #Climate #ClimateScience #Earth #EarthScience #ClimateChange #ClimateSciences #Science #WeatherPrediction #Humidity #Moisture #Pressure #Velocity #SurfacePressure #HydrostaticEquation #WeatherPrediction #Ocean #Atmosphere #AOS #ClimateDynamics #WeatherDynamics #Geopotential #SigmaVelocity #VerticalVelocity #MoistureEquation #Thermodynamics #Dynamics #NavierStokes
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Basics of Numerical Weather Prediction (NWP):
1. THE HORIZONTAL MOMENTUM EQUATION:
\[
\frac{d\mathbf{V}}{dt} + f\hat{k} \times \mathbf{V} = -\nabla \phi + \frac{\sigma}{p_s} \frac{\partial \phi}{\partial \sigma} \nabla p_s + \mathbf{F}
\]2. THE CONTINUITY EQUATION:
\[
\frac{\partial p_s}{\partial t} + \nabla \cdot (p_s \mathbf{V}) + \frac{\partial}{\partial \sigma}(p_s \dot{\sigma}) = 0
\]3. THE THERMODYNAMIC ENERGY EQUATION:
\[
\frac{1}{R} \frac{d}{dt} \left[ \sigma \frac{\partial \phi}{\partial \sigma} \right] + \frac{RT}{C_p p} \left[ p_s \dot{\sigma} + \sigma\dot{p_s} \right] = -Q
\]4. HYDROSTATIC EQUATION:
\[
\frac{\partial \phi}{\partial \sigma} = -\frac{RT_v}{\sigma}
\]5. SURFACE PRESSURE TENDENCY EQUATION:
\[\displaystyle
\frac{\partial p_s}{\partial t} = -\int_{0}^{1} \nabla\cdot (p_s \mathbf{V}) \, d\sigma
\]6. MOISTURE EQUATION:
\[\displaystyle
\frac{\partial}{\partial t} (p_s q) + \nabla\cdot (p_s q \mathbf{V}) + \frac{\partial}{\partial \sigma} (p_s q \dot{\sigma}) = p_s S
\]The six primary unknowns are: \(\mathbf{V}\) (horizontal wind velocity), \(p_s\) (surface pressure), \(T\) (temperature), \(q\) (specific humidity or moisture), \(\phi\) (geopotential), and \(\dot{\sigma}\) (sigma velocity or vertical velocity in \(\sigma\)-coordinates).
#NWP #Weather #NumericalWeatherPrediction #Meteorology #Climate #ClimateScience #Earth #EarthScience #ClimateChange #ClimateSciences #Science #WeatherPrediction #Humidity #Moisture #Pressure #Velocity #SurfacePressure #HydrostaticEquation #WeatherPrediction #Ocean #Atmosphere #AOS #ClimateDynamics #WeatherDynamics #Geopotential #SigmaVelocity #VerticalVelocity #MoistureEquation #Thermodynamics #Dynamics #NavierStokes
-
Basics of Numerical Weather Prediction (NWP):
1. THE HORIZONTAL MOMENTUM EQUATION:
\[
\frac{d\mathbf{V}}{dt} + f\hat{k} \times \mathbf{V} = -\nabla \phi + \frac{\sigma}{p_s} \frac{\partial \phi}{\partial \sigma} \nabla p_s + \mathbf{F}
\]2. THE CONTINUITY EQUATION:
\[
\frac{\partial p_s}{\partial t} + \nabla \cdot (p_s \mathbf{V}) + \frac{\partial}{\partial \sigma}(p_s \dot{\sigma}) = 0
\]3. THE THERMODYNAMIC ENERGY EQUATION:
\[
\frac{1}{R} \frac{d}{dt} \left[ \sigma \frac{\partial \phi}{\partial \sigma} \right] + \frac{RT}{C_p p} \left[ p_s \dot{\sigma} + \sigma\dot{p_s} \right] = -Q
\]4. HYDROSTATIC EQUATION:
\[
\frac{\partial \phi}{\partial \sigma} = -\frac{RT_v}{\sigma}
\]5. SURFACE PRESSURE TENDENCY EQUATION:
\[\displaystyle
\frac{\partial p_s}{\partial t} = -\int_{0}^{1} \nabla\cdot (p_s \mathbf{V}) \, d\sigma
\]6. MOISTURE EQUATION:
\[\displaystyle
\frac{\partial}{\partial t} (p_s q) + \nabla\cdot (p_s q \mathbf{V}) + \frac{\partial}{\partial \sigma} (p_s q \dot{\sigma}) = p_s S
\]The six primary unknowns are: \(\mathbf{V}\) (horizontal wind velocity), \(p_s\) (surface pressure), \(T\) (temperature), \(q\) (specific humidity or moisture), \(\phi\) (geopotential), and \(\dot{\sigma}\) (sigma velocity or vertical velocity in \(\sigma\)-coordinates).
#NWP #Weather #NumericalWeatherPrediction #Meteorology #Climate #ClimateScience #Earth #EarthScience #ClimateChange #ClimateSciences #Science #WeatherPrediction #Humidity #Moisture #Pressure #Velocity #SurfacePressure #HydrostaticEquation #WeatherPrediction #Ocean #Atmosphere #AOS #ClimateDynamics #WeatherDynamics #Geopotential #SigmaVelocity #VerticalVelocity #MoistureEquation #Thermodynamics #Dynamics #NavierStokes
-
Basics of Numerical Weather Prediction (NWP):
1. THE HORIZONTAL MOMENTUM EQUATION:
\[
\frac{d\mathbf{V}}{dt} + f\hat{k} \times \mathbf{V} = -\nabla \phi + \frac{\sigma}{p_s} \frac{\partial \phi}{\partial \sigma} \nabla p_s + \mathbf{F}
\]2. THE CONTINUITY EQUATION:
\[
\frac{\partial p_s}{\partial t} + \nabla \cdot (p_s \mathbf{V}) + \frac{\partial}{\partial \sigma}(p_s \dot{\sigma}) = 0
\]3. THE THERMODYNAMIC ENERGY EQUATION:
\[
\frac{1}{R} \frac{d}{dt} \left[ \sigma \frac{\partial \phi}{\partial \sigma} \right] + \frac{RT}{C_p p} \left[ p_s \dot{\sigma} + \sigma\dot{p_s} \right] = -Q
\]4. HYDROSTATIC EQUATION:
\[
\frac{\partial \phi}{\partial \sigma} = -\frac{RT_v}{\sigma}
\]5. SURFACE PRESSURE TENDENCY EQUATION:
\[\displaystyle
\frac{\partial p_s}{\partial t} = -\int_{0}^{1} \nabla\cdot (p_s \mathbf{V}) \, d\sigma
\]6. MOISTURE EQUATION:
\[\displaystyle
\frac{\partial}{\partial t} (p_s q) + \nabla\cdot (p_s q \mathbf{V}) + \frac{\partial}{\partial \sigma} (p_s q \dot{\sigma}) = p_s S
\]The six primary unknowns are: \(\mathbf{V}\) (horizontal wind velocity), \(p_s\) (surface pressure), \(T\) (temperature), \(q\) (specific humidity or moisture), \(\phi\) (geopotential), and \(\dot{\sigma}\) (sigma velocity or vertical velocity in \(\sigma\)-coordinates).
#NWP #Weather #NumericalWeatherPrediction #Meteorology #Climate #ClimateScience #Earth #EarthScience #ClimateChange #ClimateSciences #Science #WeatherPrediction #Humidity #Moisture #Pressure #Velocity #SurfacePressure #HydrostaticEquation #WeatherPrediction #Ocean #Atmosphere #AOS #ClimateDynamics #WeatherDynamics #Geopotential #SigmaVelocity #VerticalVelocity #MoistureEquation #Thermodynamics #Dynamics #NavierStokes
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A largely cloud free satellite image of the central Northwest Passage shows that the prior melt ponds along the southern route have drained, and that melt ponds have now formed on the northern route through McClure Strait:
https://GreatWhiteCon.info/2025/05/the-northwest-passage-in-2025/#Jun-22
