# Presentation: 940947

## Numerical Model Applications and Impact for Aircraft Observations

- Stan Benjamin
- NOAA Earth System Research Laboratory (ESRL)
-         Global Systems Division (GSD)
- Boulder, CO  USA

- Stan.Benjamin@noaa.gov
- http://ruc.noaa.gov

## 	Outline

- Numerical weather prediction
-  - How to get model initial conditions
- History of aircraft observations for NWP
-  - AIREPs, automated reports
- NWP impact of aircraft observations
-  - Relative impact of aircraft
- 	vs. raob, profiler, VAD, surface
-  - Regional – Rapid Update Cycle model
-       - Feb 2001 2-week period, 9-11 Sept 2001
-  - Global – ECMWF model
- Conclusions

## Slide 3

| Data type used 
in the RUC model | Number (resolution) 
of observations | Frequency of 
data insertion |
| --- | --- | --- |
| Rawinsonde | 80 | /12h |
| NOAA/PBL wind profiler | 30 + 25 | /1h |
| VAD winds | 110 - 130 | /1h |
| Aircraft (V, T, some RH) | 1400 - 6000 | /1h |
| Surface / METAR | 1500 - 1700 | /1h |
| Buoy / ship | 100 - 150 | /1h |
| GOES precipitable water | 1500 - 3000 | /1h |
| GOES cloud drift winds | 1000 - 2500 | /1h |
| GOES cloud-top pressure | (10-km resolution) | /1h |
| SSM/I  precipitable water | 1000 - 4000 | /6h |
| GPS precipitable water | ~300 | /1h |
| Mesonetwork data | ~6000 | /1h |
| METAR cloud visibility | ~1500 | /1h |
| Radar / lightning | (4-km resolution) | /1h |
| GOES / POES radiances | WRF-Rapid Refresh + GSI | / 1h |

## RUC Hourly Assimilation Cycle

**11             12              13             14              15              16     **

***Time ***
***(UTC)***

**1-hr**
**fcst**

- Background
- Fields

- Analysis
- Fields

**1-hr**
**fcst**

**1-hr**
**fcst**

**1-hr**
**fcst**

**1-hr**
**fcst**

**1-hr**
**fcst**

## 	Themes

- Uniqueness of aircraft observations
-  - from a private sector and government partnership
- Part of composite observing system on regional and global scales
- Automated reporting of accurate weather reports and continued growth of commercial aviation
-  allowed (and necessitated) high-frequency numerical weather prediction (NWP) (3h-1h updating)
-  contributes strongly to improvements in global NWP

## Some background history

- Late 1970s – International “fuel crisis”
- 1983 – Complaints from airlines to FAA on poor quality in upper-level wind forecasts, even over CONUS, with increasing costs to their operations
- 1984-86 – FAA-sponsored
-     Aviation Weather Forecasting Task Force (AWFTF) –
- Recommendations
-  -  Implement automated aircraft reporting system as component of national meteo weather obs system
-  -  Upgrade aviation weather NWP system to higher frequency than 2x/day
- 1985-1989 – Initial data assimilation tests with automated aircraft observations over US

## History of aircraft reports for NWP

- AIREPs (Aircraft Reports)
- Voice-relayed reports
- Made for transoceanic flights at “waypoints” every 10 deg longitude
- Data quality known to be poor – observation errors usually set as high for assimilation
- Only aircraft data type until late 1980s as automated aircraft reports
- Automated aircraft met obs
- Started in 1980s.   Initially, Delta/United, then Northwest.   (ARINC/ACARS-enabled)
- Was company-confidential data initially, meant only for internal airline met offices for competitive advantage.   Breakthrough for govt/private sharing – AWFTF,     Russ Crawford-Delta, Carl Knable – United.

## Initial tests with assimilation of automated aircraft observations – February 1986 (200-hPa winds)

- Addition of Delta and United automated reports

- Raobs only

## RUC History – NCEP (NMC) implementations

- 1994- First NCEP/NMC operational implementation of RUC
- 60km resolution, 3-h cycle
- Assimilation of aircraft, profiler, raob data initially
- 1998 – 40km resolution, 1-h cycle,
- 		- cloud physics, land-sfc model
- 2002 – 20km resolution
- 		- addition of GOES cloud data in assimilation
- 2005 – 13km resolution, new obs (METAR clouds, GPS moisture), new model physics
- 2006 – Improved convection, improved use of GOES cloud data, improved moisture/cloud forecasts (July)
- 2009 – WRF-based Rapid Refresh planned to replace RUC

## Rapid Update Cycle (RUC) model
1-h update frequency, 13-km resolution
North American Mesoscale (NAM) model
6-h update frequency, 12-km resolution, continental scale
Global Forecast System (GFS) model
6-h update, ~60-km resolution

_**Rapid Update Cycle (RUC) model**_
- 1-h update frequency, 13-km resolution
_**North American Mesoscale (NAM) model**_
- 6-h update frequency, 12-km resolution, continental scale
_**Global Forecast System (GFS) model**_
- 6-h update, ~60-km resolution

## RUC is used over the CONUS domain in the Current Icing Potential (CIP), Forecast Icing Potential (FIP), Graphical Turbulence Guidance (GTG), and the  National Convective Weather Forecast (NCWF) aviation weather products

**1500 Z + 6-h forecast RCPF**

**2100 Z verification**

**Planned WRF-Rapid Refresh domain - 2008**

**Current RUC-13 CONUS domain**

**AWC**

**Turbulence - GTG**

**Icing FIP**

**RCPF**

**13km resolution**

## RUC

- Wind forecast
- Accuracy
- Sept-Dec
- 2002

- Verification against rawinsonde data over RUC domain
- RMS vector difference (forecast vs. obs)

- RUC is able to use recent obs to improve forecast skill down to 1-h projection for winds

- 1

- 3

- 6

- 9

- 12

- Analysis
- ~ ‘truth’

## % Reduction of

- 12-h RUC forecast error
- Sept-Dec 2002

- Wind

- Temperature

- Height

- RH

## Wind errors

- Analysis
- ~ ‘truth’

- 1

- 3

- 6

- 9

- Dec06-Jan07

## Temp errors

- Analysis
- ~ ‘truth’

- Dec06-Jan07

## RH errors

- Analysis
- ~ ‘truth’

- Dec06-Jan07

## RUC vector (m/s) forecast error – 1200 UTC 8 Feb 2001 – 250 hPa

- 12h init 12z

-  9h init 03z

-  6h init 06z

-  3h init 09z

## Obs Sens Experiments (OSEs) w/ RUC 

- Rawinsonde 				    80		/12h
- NOAA 405 MHz profilers  		    31		/  1h
- VAD winds (WSR-88D radars)      110-130	/  1h
- Aircraft (automated) (V,temp)    	1800-5500	/  1h
- Surface/METAR (T,Td,V,p) 		1500-1700	/  1h
- Buoy/ship			 	 100-150	/  1h
- GOES precipitable water		1500-3000	/  1h
- GOES cloud drift winds 		1000-2500	/  1h
- GOES cloud-top pressure/temp	~10km res    /  1h
- SSM/I precipitable water		1000-4000	/  6h
- GPS precipitable water		~300		/  1h
- Radar reflectivity / lightning	4 km
- Mesonet				6000		/  1h
- METAR cloud/vis/wx obs				/  1h

**Obs Sens ****Experiments (OSEs) w/ RUC**** **

-   OSEs

## Spatial coverage for OSE obs types

- Rawinsonde 				    80		/12h
- 	horizontal 	- covers land area
- 	vertical 	– sfc to above 50 hPa
- NOAA 405 MHz profilers  		    31		/  1h
- 	horizontal 	- central US only
- 	vertical 	- surface to 18 km profiles
- VAD winds (WSR-88D radars)      110-130	/  1h
- 	horizontal 	– over continental US
- 	vertical 	- winter: sfc to 150-300 hPa above surface
- Aircraft (ACARS) (V,temp)    	1800-6000	/  1h
- 	horizontal 	– over land area, irregular in time
- 	vertical 	– much at 300-200 hPa, ascent/descent
- Surface/METAR – T/Td/V/p	1500-1700	/  1h
- 	horizontal 	– covers land area completely
- 	vertical 	– surface only

**Spatial coverage for OSE obs types**

## Wind forecast ‘errors’

*Positive difference means CNTL experiment with profiler data had lower error than the EXP-P no-profiler experiment*

-  - defined as rawinsonde
- vs. forecast difference

- Cntl = using all obs
- Exp = deny profiler obs

*Difference* in errors
- between Cntl and Exp
- experiments w/ RUC
- - 4-17 Feb 2001

- Anx Fit
- - ‘truth’

## Experiment design

-  Operational version of RUC run retrospectively for  **4-17 Feb 2001 **
** **20km, 1h cycle, 3DVAR, DFI
-  Eta boundary conditions contain _all_ data sources
-  Verification performed on twice daily rawinsonde data over 2 domains for standard variables (Z, T, RH, winds) for 3, 6, 9, 12 h fcsts
-  Two verification domains
-  Test verification performed using NOAA profiler data (winds only)

- Midwest domain – 26 raobs

- National domain – 91 raobs

- 7 experiments
-  Control
-  No raob
-  No aircraft
-  No profiler
-  No VAD
-  No surface
-  All obs denied (BC only)

## 3 h 

- 6h

- 12 h

**Wind forecast impact – ****US National**** domain**

-  Impact generally greatest for shorter forecast durations.
-  Decreases with projection  **except raobs**
-  Raob impact largest at 12h – raob frequency is 12h.
- Aircraft - largest overall impact at 3h,   profiler next (much smaller)
- Modest VAD and METAR impact aloft;

- 3h

- 6h

- 12h

## Wind forecast impact – US Midwest domain

-  Aircraft still dominant at 200-300 hPa, impact *grows* from 3h to 6h
-  Profiler impact large at 3h but drops off quickly – effect of regional network (not national)
- METAR – important for 850 hPa for 3-6h
- Hourly data – has more ‘room’ to help < 12h

- 6h

- 12h

**Wind forecast impact – ****US Midwest**** domain**

- 3h

## Slide 24

## Temperature forecast impact

- 3h

- 6h

- 12h

**Temperature** forecast impact
- 3 h projection valid 00, 12UTC

## Height forecast impact

- 3h

- 6h

- 12h

**Height** forecast impact
- 3 h projection valid 00, 12UTC

## RUC OSE (3-12h CONUS) Conclusions

-  Limited domain obs system – impact fades more quickly with time in mean statistics.
-   Raob most important ob type for all variables at 12h except jet-level winds.  Importance “grows” from 3h until 12h, matching raob frequency
-  Wind profiler impact – complements aircraft data over midwest US at 3-6h, less so at 12h
-  Aircraft continue to dominate over upper troposphere
-  METAR/VAD have a small effect thru troposphere.
-  Short-range forecast improvement very significant to aviation, severe storm forecasting, NASA, energy industry, sfc transportation...
-  Safety net of multiple obs sources – no catastrophic result when any one is excluded.

- The impact of missing ACARS data on RUC wind forecast skill

-  11-13 September 2001
-  weekends
- (fewer package delivery reports)

## Hourly ACARS volume2-15 Sept 01(starting 00z 2 Sept)

- Su    Mo   Tu     We   Th    Fr      Sa

- 2-8 Sept 01

- 9-16 Sept 01

- Su    Mo   Tu     We   Th    Fr      Sa

## Improvement in 3h over 12h wind fcst- September 2001 

- Improvement in 3h over 12h wind fcst- September 2001

- RUC 250 mb
- Wind forecasts
- Verification
- against raob data

- 11-13 Sep

- Forecasts from
- operational RUC
- run at NCEP

## TAMDAR impact study with RUC parallel cycles

- _TAMDAR impact study with RUC parallel cycles_
-  2005-2007 (ongoing)
- Further improvement in
- RH, temperature, wind
-  Regional coverage (more airports w/ ascent/descent)
-  RH sensor

- Forecast errors – RUCdev (no TAMDAR), RUCdev2 (w/ TAMDAR)

- noTAM

- wTAM

- Temp

- RH

- Wind

- wTAM

- wTAM

- noTAM

- noTAM

- See AMS-IIPS TAMDAR session – Thurs AM

## Trade-offs for 

- obs system network size
- vs.
- duration of forecast impact

-  regional obs networks
-  may help very short-range forecasts
-  may contribute modestly or not at all to 2-5 day skill
-  duration of impact can be extended if network area can be expanded
-  accuracy and representativeness offsets network size

## EUCOS terrestrially based Observing System StudiesJean-Noël Thépaut and  Graeme Kelly

- ECMWF
- email: jean-noel.thepaut@ecmwf.int

## Overview

- Experimental Set Up
- List of experiments
- Model and assimilation configuration
- Winter Results
- Summer results
- Conclusions and Perspectives

## Experimental Set-Up: List of experiments

- (i): BASELINE: all current satellite observations used in NWP (radiances, cloud-drift winds, scatt winds)+ GUAN R/S (RADIOSONDE) network+hourly GSN surface land data+hourly buoys (no ship data)
- (ii): (i) BASELINE + aircraft data
- (iii): (i) BASELINE + non-guan R/S (incl. ASAP) wind profiles
- (iv): (i) BASELINE + non-guan R/S (incl. ASAP) temperature and wind profiles
- (v): (i) BASELINE + wind-profiler data
- (vi): (iv) + aircraft data
- (vii): (iv) + R/S (incl. ASAP) humidity profiles
- (viii): CONTROL: full combined observing system

## GUAN = GCOS Upper-Air Network 

**GUAN = GCOS Upper-Air Network**
- (minimal global raob network – e.g., 6 stations over CONUS)

- GCOS
- Global Climate
- Obs System

## Exp Set Up (ctd): Model/assim configuration

- Winter Experiments:
- 2004120400 until 2005012512 (including 10 day warm up)
- Resolution :
- Model: T511 (40km) L 60
- Assimilation: T511/T159 L60. 12h 4DVAR
- Model cycle 29R1
- Summer experiments:
- 2005071500 until 2005091512 (including 10 day warm up)
- Resolution: idem winter experiments
- Model cycle 29R2
- NOAA18 included (AMSU-A and MHS)

## Winter results: Control-Baseline (Z500)Normalised forecast error difference FC+72h

- Winter results: Control-Baseline (Z500)Normalised forecast error difference FC+72h

## Summer: CONTROL – BASELINEnormalised fcerr + 72H

## Winter results: Z scores (impact of aircrafts)

**NH**

**EUR**

**1000 hPa**

**500 hPa**

## Winter results: Wind scores (impact of aircrafts)

**NH**

**EUR**

**850 hPa**

**300 hPa**

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+12h

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+24h

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+36h

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+48h

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+60h

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+72h

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+84h

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+96h

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+108h

## Winter results: [Baseline + aircrafts] - Baseline (Z500)Normalised forecast error difference FC+120h

## Additional results

- Impact of aircrafts on top of the full R/S (radiosonde) network
- Complementarity between aircraft and R/S network
- Impact of the wind profilers
- Impact of humidity from R/S

## Conclusions (1)

- Even in presence of satellite observations, degrading the current terrestrial Observing System has a significant negative impact on the forecast skill.
- Starting from the degraded baseline (GUAN+GSN+...):
- Additional R/S (T+Wind) and aircrafts (T+Wind) contribute more or less equally to the Observing System (slight advantage for R/S)
- These two Observing Systems are complementary
- Aircrafts add forecast skill to R/S
- R/S add forecast skill to Aircrafts

## Conclusions (2)

- R/S impact:
- R/S winds contribute little on their own
- Radiosonde T contribute marginally more
- This is the combination of wind/T which really provides the impact of the RS on the forecast skill
- Aircraft impact:
- The results are consistent with that of R/S. Aircraft-T alone bring relatively little. Combination of T/Wind makes a big impact

## Conclusions (3)

- Humidity from R/S add very little
- Noticeable but small impact on relative humidity scores up to day 3
- Impact of wind profilers:
- The impact of wind profilers may not be as bad as suggested by the mean scores
- Winter impact:
- The short range forecasts are improved by the US and japanese profilers
- The signal blurs away after day 4-5 and large scale interactions appear
- Sampling?
- European profilers do not bring much

## 	Summary - Overall

- Numerical weather prediction
-  - Aircraft data is part of composite observing system
*Automated*, *accurate* reports critical on both regional (1-24h) and global (3-8 day) scales
- NWP impact of aircraft observations
-  - Relative impact of aircraft
- 	vs. raob, profiler, VAD, surface
-  - Regional – Rapid Update Cycle model
-       - Feb 2001 2-week period, 9-11 Sept 2001
-  - Global – ECMWF model
-       - Aircraft equal in significance to raob (beyond baseline (GUAN-160 station) network

## 	Themes - Overall

- Uniqueness of aircraft observations
-  - from a private sector and government partnership
- Automated reporting of accurate weather reports and continued growth of commercial aviation
-  allowed (and necessitated) high-frequency numerical weather prediction (NWP) (3h-1h updating)
-  contributed strongly to improvements in global NWP