Evolution of the Relationship Between Forecasters and Numerical Models
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Transcript Evolution of the Relationship Between Forecasters and Numerical Models
Evolution of the Relationship Between
Forecasters and Numerical Models
Over the Last 50 Years
Model-driven evolution
Support-system-driven
evolution
Emerging forecaster-model
relationships
The result
Symposium on the 50th Anniversary of
Operational Numerical Weather Prediction
June 16, 2004
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Jim Hoke
Director, HPC
Director, OPC
Numerical modeling progress
has driven the evolution of the
human role in weather prediction
• Forecasts were produced by hand, based heavily on
forecaster experience, rules of thumb, and intuition
• Forecasters began using numerical forecasts as one tool
to enhance their own forecast skill
• the numerical forecasts added
value to the human forecasts
• As their skill improved, numerical
forecasts increasingly supplanted
human forecasts
• The forecaster role now is viewed
more as adding value to the
numerical forecasts
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HPC QPF verification
1-inch threat score
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HPC QPF verification vs. the models
Day 1, 1 inch
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HPC medium-range Tmax verification
% reduction in Mean Absolute Error over MOS
(by year) (adjusted stations only)
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Support-system progress
has also driven the evolution of the
human role in weather prediction
• Initially at weather centers, a small number of forecasters
was supported by a large number of technicians
• Grease pencils, acetates, light tables, plotters,
and scanners
• Limited access to observations
• Few models, forecast fields, output times, colors
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Support-system progress
has also driven the evolution of the
human role in weather prediction (continued)
• Now weather centers are heavily staffed by
forecasters
• Sophisticated meteorological workstations
• Rapid access to huge volume of observations
• Many models & ensembles, many forecast fields,
many output times, many colors
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Estimated HPC meteorological
technician & reproduction-equipment
technician staffing by year
year
1970
1975
1980
1986
1990
met
techs
97
82
47
28
21
1994
1995
1997
12
9
4
7
6
0
19
15
4
2002
3
0
3
8
repro
techs total
15
112
14
96
14
61
11
39
8
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“Emerging” relationship of
forecasters and numerical models
Enhancing objective surface analyses, esp. regarding
mesoscale features and over the oceans
Providing oversight of observation, analysis, and
numerical deterministic & probabilistic forecast systems
An abnormal transit?
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Providing oversight (continued)
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“Emerging” relationship of
forecasters and numerical models
Enhancing objective surface analyses, esp. regarding
mesoscale features and over the oceans
Providing oversight of observation, analysis, and numerical
deterministic and probabilistic forecast systems
Determining most probable forecast states, their likely
spread, and uncertainty of the forecasts (using ensembles)
Determining modeling system deficiencies
(deterministic & probabilistic)
Evaluating proposed model
changes
Providing model interpretation
for customers
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Providing model interpretation
for customers (continued)
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“Emerging” relationship of
forecasters and numerical models
Enhancing objective surface analyses, esp. regarding
mesoscale features and over the oceans
Providing oversight of observation, analysis, and
numerical deterministic and probabilistic forecast
systems
Determining most probable forecast states, their likely
spread, and uncertainty of the forecasts (using
ensembles)
Determining modeling system deficiencies (deterministic
& probabilistic)
Evaluating proposed model changes
Providing model interpretation for customers
Collaboration among forecasters
– Forecasts (multiple forecast offices)
– Analyses (seamless surface analysis)
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NWS Unified Surface Analysis
First operational issuance – 12 UTC June 14, 2004
HPC, OPC, TPC, & HFO
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Concluding remarks -The numerical models & forecasters:
a love/hate relationship?
• Numerical forecasts initially viewed as threat to job security
& satisfaction
• Inner workings of numerical models still appear arcane &
difficult to fathom
• When models change, forecasters must learn the new model biases,
strengths, & weaknesses
• Improving numerical guidance gives forecasters less room to make
improvements
• Yet forecasters want to improve
the quality of their products &
services, so they demand more
accurate numerical tools
• Result-- Forecasters, numerical
guidance, and meteorological
workstations are inseparable,
tightly interwoven in the
forecast process
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