Forecast: The basics
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Numerical model is a
computer program designed to simulate some real system
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In meteorology a numerical model is used to forecast the weather process called a
Numerical Weather Prediction (NWP)
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Numerical Weather Prediction (NWP) models are based on
laws of PHYSICS
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(NWP) Equations based on laws of PHYSICS are integrated
FORWARD in time to simulate changes in the atmosphere
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Parameterization
used to estimate the effects of important processes that CANNOT be predicted directly by the NWP model
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A parameterization estimates the effect of a process using variable that can be
PREDICTED by the model
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Most models (NWP) CANNOT
Predict Individual clouds
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Primary GOAL of NWP is
to forecast the effects of clouds and precipitation production
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NWP model MUST include a ____________ _______________ to attempt to forecast the effect of clouds based on the other variables predicted by the model
CLOUD PARAMETERIZATION
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Twin supercomputers
Dogwood and Cactus are the newest additions to NOAA's weather and climate operational supercomputing system
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NWP Model Components (INPUT DATA)
1. Surface observations
2. Rawinsode observations
3. Satellite data
4. Radar data
5. Profiler observations
6. Aircraft observations
2. Rawinsode observations
3. Satellite data
4. Radar data
5. Profiler observations
6. Aircraft observations
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Initialization
the process of taking data and preparing it for input into a numerical model
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Data from different sources and times may contain errors, so must _________ ________________
blend together
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NWP (Initialization-Previous Runs) Use short-term (3, 6, or 12 hours) forecast from
previous run model
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Some initialization schemes (NPW) use PREVIOUS MODEL RUNS to act as
"FIRST GUESS" about the status of the atmosphere
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(NWP) Initialization then adds in data at appropriate times and places and
"nudges" (i.e., modifies) the previous model forecast as it integrates up to the current time
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The result (of ADDING DATA) is a
physically consistent data set that is used as the initial conditions for the NWP model
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Initialization: Continued Process
1. Quality Control
2. Data Assimilation
3. Generate initial analysis fields
2. Data Assimilation
3. Generate initial analysis fields
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Quality Control
Identifies obvious errors in input data
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Data Assimilation
Combine data from different sources
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Generate initial analysis fields
(i.e., conditions at time t=0 in forecast run)
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