Forecast: The basics

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1
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
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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
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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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