n What has happened? n Why has it happened? n What is happening? n Why is it happening? n What will happen? n Why will it happen?

Forecast   Techniques ATMOS   5010:  Weather   Forecasting Forecasting   Tools  and   Techniques Jim  Steenburgh Department  of  Atmospheric  Scienc...
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Forecast   Techniques

ATMOS   5010:  Weather   Forecasting Forecasting   Tools  and   Techniques

Jim  Steenburgh Department  of  Atmospheric  Sciences University  of  Utah [email protected]

Successful   Forecasting   Requires n

– – – – – n

AKA:  The  Human-­Machine   Mix

Knowledgeable,  well-­trained,  &  engaged  forecasters Meteorological   knowledge   and   experience Local   weather   &   climate   knowledge User   need   recognition Model   strength,   weakness,   and   bias   assessment Human   cognition   and   interpretation

Skillful  &  reliable  NWP  guidance,  forecast  t ools,  and   other  aids Image:   whistlerdiaries.com

Human  Cognition                                                                              Automated  Systems

The  Forecast   Process

Critical  Forecast  Questions n n

What  has  happened? Why  has  it  happened?


What  is  happening? Why  is  it  happening? What  will   happen?


Why  will   it  happen?

n n

Easy  to  concentrate only  on  this  

M orss  an d  Ralp h  (2 0 07)

=  NWP,  tools,  aids,  etc. =  Knowledgeable,  well   trained,  &  engaged   forecasters

S o u rce :  Bo sa rt (2 0 0 3 )


The  Forecast   Methodology

Critical  Forecast  Questions n

What  has  happened?



Why  has  it  happened? What  is  happening? Why  is  it  happening? What  will   happen?


Why  will   it  happen?

n n


Important  when NWP  goes  awry or  cannot  resolve local  orographic effects

To  answer  these   questions,  use  the   forecast  funnel – Begin  at  planetary   scale – Focus  attention  on   progressively  s maller   scales – In  complex  t errain,   build  in  orographic   effects

Planetary  Scale Synoptic  Scale Mesoscale Local  Scale

S o u rce :  Bo sa rt (2 0 0 3 )

The  Forecast   Methodology n

Answer   the   what   and   the   why   in   the   past,   present,   and   future


Avoid   “meso-­myopia”

– Understand  larger  scales   before   progressing   to  smaller  scales – When  using  high-­resolution   models,  evaluate  confidence   in   large-­scale  forecast  before   progressing   to  smaller  scales – Expect   limited  local   skill   if  large-­ scale   is  not  well  forecast


Forecast   Funnel  in  Practice

Beware   when   the   atmosphere   is  in   outlier   mode

Planetary  Scale Synoptic  Scale Mesoscale

– Generalizations   break  down

Local  Scale

The  Forecast   Funnel  in  Practice

Evaluate  past,  current,  and  future   planetary  scale  setting

The  Forecast   Funnel  in  Practice

Evaluate  confidence  in  synoptic-­scale   forecast Funnel  to  synoptic  scale


The  Forecast   Funnel  in  Practice

The  Forecast   Funnel  in  Practice





? Funnel  to  mesoscale Consider  mesoscale,  o rographic,  and   land-­surface  processes

Adjust  for  local  e ffects

Real-­Time   Example  Using  IDV

Humans  Make  a  Difference

S ou rce:  NCEP/HPC

“This  continuing  skill  advantage   [indicates]  that  dedicated  and  trained   forecasters can  extract  maximum  advantage  from  improvements  in  operational  weather   prediction   models” -­Bosart (2003)

On  the  other  Hand….

“Forecasters  who  grow  accustomed  to  letting  MOS  and  the  models  do  their   thinking…on   a  regular   basis…are  at  high  risk  of  “going  down  in  flames” when  the   atmosphere  is  in  an  outlier   mode” -­ Bosart (2003)

Don’t  be  on  Autopilot

Although  NWP  is  important,  basic  understanding,  pattern   recognition  and  climatology  c ontinue  t o  play  an  essential   role because  of  limitations  in  c urrent  NWP  s ystems,   including  inadequate  t errain  representation,  initial   condition  uncertainty,  and  parameterization  uncertainty


Forecast   Tools

Bottom  Line n

“Forecasters   have   a  clear   role   in   the   forecast   process,   by   contributing   a  wealth   of   knowledge,   tools   and   techniques   that   cannot   be   duplicated   by   computers   or   NWP” – McCarthy  et  al.  (2007)


But  forecasters   need   to   be   engaged   and   increasingly   need   an   advanced   education to   extract   maximum   benefit   from   today’s   sophisticated   forecast   tools


This   class  begins   that   education

Forecast   Tools

Forecast   Tools Climatology Persistence n Observations n n

– – – – – –

A  meteorologist  knows  their  tools, including  their  strengths  and weaknesses “All  observations  are  bad,  but  some are  useful”

n n

“All  models  a re  wrong,  b ut  some   are  useful” n n

Your  eyes In-­situ  surface  and  upper-­air Wind  profiler/RASS Satellite Radar Weather  cameras

Manual   analysis NWP   Models

– Numerical   analyses – Global   and  mesoscale models – Ensemble   forecast  systems

Model   Output   Statistics   (MOS) Scientific   analysis   and   visualization   systems

S o u rce :  Ga ry  La rso n ,   Th e  F a r  S i d e

S o u rce :  Ga ry  La rso n ,   Th e  F a r  S i d e

Forecast   Tools:  Climatology

Forecast   Tools:  Climatology


The  statistics  of  weather


More  than  just  long-­term  mean – Mean,  variance,  extremes,  probabilities – Impacts  of  ENSO  and  modes  of  climate  variability § PDO,   NAO,  etc.


Local  and  mesoscale effects – Complex  terrain  results  in  large  climatological  gradients – Often  poorly  resolved  by  computer  models – Climatology  to  used  “downscale”  or  “bias  correct”  model   forecasts  for  local  effects – Can  be  overused § e.g.,  Not  all   storms  have   the  climatological   precipitation-­altitu de   relationship

Is  this  useful???? Means  and  Probabilities   for  Forecast  Practicum  Variables


Forecast   Tools:  Climatology

Forecast   Tools:  Persistence n

Persistence:   What  has  happened  recently – Including  trends


Provides   context for  forecast


Relevance   for  forecast   varies  from   high  to   low – High  during  slowly  evolving  patterns – Low  during  major  pattern  shifts

Think  Beyond  the  Mean

Forecast   Tools:  Persistence

Forecast   Tools:  Your  Eyes n

Context  for  forecast During   this  period  is Different  at  LGU  &  WBB

Forecast  T ools:  Sfc/Upper-­Air  Data

Never  underestimate   the  value  of  looking   out  the  window  or  going  outside   to  feel   the  weather

S o u rce :  ca rto o n sti ck.co m ,  co l l a b o ra ti ve jo u rn e ys.co m

Forecast   Tools:  Satellite

ASOS,   Springfield,   IL  ( NWS)

Weather  Balloon   ( NWS)

Wind  Profiler   ( Wikipedia)

Wind   profilers  provide   more  than  wind!

Visible  Imagery Visible  radiation   reflected  back  to  space  by  clouds,   aerosols,  snow,  land  surface,  etc.


Forecast   Tools:  Satellite

Forecast   Tools:  Satellite

“Window”   IR  Imagery Long-­wave  radiation   emitted  primarily   by  clouds,  land-­surface,  etc. Cloud-­top  temperature  and   land-­surface  temperature

Water  Vapor  Channel  (IR)  Imagery Long-­wave  radiation   emitted  primarily   by  upper-­tropospheric   clouds  and  water  vapor Upper-­level  flow,  troughs,  etc.

Forecast   Tools:  Satellite

Forecast   Tools:  Radar

Precipitable Water  from Polar-­orbiting   microwave  s ensors

NEXRAD  Doppler  Radar NEXRAD  vs.  TDWR

Now:  Polarimetric NEXRAD GOES  Fog  D etection Longwave IR   ( 10.7  micron) -­Shortwave   IR   ( 3.9  micron)


S o u rce s:  S S E C,  NE S DIS

S o u rce s:  NOAA/S P C

Forecast  T ools:  Weather  Cameras

Forecast  T ools:  Manual  Analysis

Click  for  Animation

S o u rce s:  Bo sa rt a n d  S e i m o n (1 9 8 8 );;  Ne i m an  e t  al .  (1 9 8 8)

A  manual  surface  analysis  helps  you  “feel  the  weather  in  your  veins”


Useful   Sites  for  Observations n http://mesowest.ut ah.edu

n n

n n

– Surface  observations  &  t ime  s eries – Radar  overlays http://weather.r ap.uc ar.edu – Satellite,  radar,  s urface  m aps,  upper-­air  m aps http://www.spc.noaa.gov/ ex per – Upper-­air  s oundings,  upper-­air  m aps,  s urface   mesoanalysis http://www.wunder gr ound.com /w underm ap/ – You  name  it http://weather.c od.edu/satr ad/ – Satellite  and  radar

Useful  IDV  Bundles  for  Obs n

– KMTX-­3DTopo – KMTX-­2D-­Obs+Anal n

Global  Forecast   System   (GFS) – Medium  range  (out  to  384  hours)   global   analyses  a nd  forecasts  every   6 h – Effective  grid  spacing  of  ~13  km  to  192  h   (lower  resolution  thereafter) – Available  on  lower-­resolution  grids – Strengths  relative  to  other  NCEP  models

Forecast  T ools:  NWP  Models n North   American   Mesoscale Model   (NAM) – Based   on  the   “WRF-­NMM” – Short-­range   (out   to  84  hours)   forecasts  f or  North   America  every   6  h – Grid   spacing   of  ~12  km § Higher  resolution  4-­km  CONUS  nest  available

– Available   on   lower-­resolution   grids – Strengths   relative  to  other   NCEP   models

§ Accuracy  of  large-­scale  f orecast

§ Terrain  representation,  mesoscale detail

– Weaknesses

– Weaknesses

§ Terrain  representation § Precip structure

§ Limited  area,  large-­scale  accuracy

Forecast  T ools:  NWP  Models n Rapid   Refresh   (RAP) – Analyses  for  CONUS   every   hour – Very-­Short-­range   (out  to  18   hours)   forecasts  for   CONUS   every   3  h – Grid   spacing   of  ~13  km – Available   on   lower-­resolution   grids – Strengths   relative  to  other   NCEP   models § High  frequency  analyses  and  forecasts § Resolution,  terrain  representation,  mesoscale details

– Weaknesses § Limited  area,  large-­scale  accuracy

Real-­Time-­WX>Analyses> – Global-­10day – Global-­2day – Supernational – Conus-­East – Conus-­West

Forecast  T ools:  NWP  Models n


Forecast  T ools:  NWP  Models n

High  Resolution   Rapid  Refresh  (HRRR) – Analyses  for  CONUS  every   hour – Very-­Short-­range   (out  to  12  hours)  forecasts   for  CONUS  every  hour – Grid  spacing  of  ~ 3  km – Strengths  relative  to  other  NCEP  models § High  frequency  analyses  and  f orecasts § Resolution,  t errain  representation,  m esoscale details

– Weaknesses § Limited  area,  large-­scale  accuracy


Forecast   Tools:  NWP  Models n

Weather  Research   and  Forecast   Model   (WRF)

Forecast  T ools:  NWP  Models n Short   Range  Ensemble   Forecast   System  

(SREF) – 21   members  @  16-­km   grid   spacing   based   on   differing   models,   model   configurations,   and   initial   conditions – Forecasts  out   to  87  h   every  6-­h   (0300   UTC,  etc.) – Strengths  

– Run  in  various  configurations  at  NCEP  and   other  locations – Some  configurations  provide  high  resolution   (

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