Meteorological Impacts and Benefits of AMDAR Data Lee Cronce Ralph Petersen Cooperative Institute for Meteorological Satellite Studies (CIMSS) Space Science

Meteorological Impacts and Benefits of AMDAR Data

Lee CronceRalph Petersen

Cooperative Institute for Meteorological Satellite Studies (CIMSS)Space Science and Engineering Center (SSEC)

University of Wisconsin - Madison

AMDAR Regional Science and Technology WorkshopMexico City, Mexico9 November 2011

Atmospheric Data Realities

• Vertical variation of temperature, moisture and wind within the atmosphere is what drives Atmospheric Science

• In situ profiles of these data (i.e., radiosondes) remain the backbone of any NWP analysis system

• The details within these profiles are especially important for recognizing and predicting hazardous weather events





• The locations of radiosonde sites are sparse, and the number of radiosonde reports is decreasing worldwide





• The locations of radiosonde sites are sparse, and the number of radiosonde reports is decreasing worldwide

• Satellites provide global coverage; however, not at detail necessary (especially near the surface)

• AMDAR fills this void!

AMDAR in a Nutshell• Temperature and Wind Observations from

Commercial Aircraft– High quality, high resolution data– Available at:• Flight Level• In Ascent / Descent

– Instruments already on aircraft– Economical (~100 times less expensive than radiosondes)

– Asynoptic (not only available at 00 and 12UTC, not a problem for NWP)

– Looks, feels, tastes like radiosonde data– Retrieved through ACARS and MDCRS

Usage of AMDAR Data

WHO WOULD BENEFIT FROM THIS

DATA SOURCE?

How does NCEP use AMDAR data?In all of its atmospheric models

• NCEP runs a suite of Atmospheric and Oceanic models to meet a variety of user needs. AMDAR data are used in:– Climate (Coupling Atmosphere and Ocean)– Global (Medium Range Forecasts)• 4/day - Deterministic and Probabilistic

– Mesoscale (Higher-Resolution Weather Forecasts)• 4/day - Deterministic and Probabilistic• Rapid Update Cycle (RUC) [soon to be Rapid Refresh Model]

– Hourly - Aviation and Hazardous Weather» Mexico included in coverage, so immediate use available

• Vertical profiles of wind, temperature and humidity are the foundation of every NWP system

• NCEP has been using AMDAR data in its NWP models for over 10 years

• Over 300,000 reports arrive daily– Data delivered in real-time 24 hours daily– Most contain wind and temperature only

• Increasing numbers include humidity– The data arrive in BUFR format

• The program is a cooperative venture between data providers and users– Everyone benefits from the results


“Rule of Thumb”• In Numerical Weather Prediction (NWP), one bad

observation does more damage than the benefit that comes from 100 good observations!

• AMDAR data are extremely accurate and reliable, but

– Good Quality Control of all observations is essential• Requires multiple observations


A major advantage of AMDAR data – multiple observations corroborate each otherWeekly Data counts by Cycle

Data Volume/Coverage by Layers

700-300mb

300-100mb

1000-700mb

Six hours of data

Note locations Of Ascent/descent Reports

←←

FORECAST IMPACTS OF AMDAR DATA

Determining Forecast Improvement from increased AMDAR volume – Use Wind forecasts as a measure of impact

•During weekday, when more AMDAR reports are available, short range forecasts are consistently better

•0000-1200 UTC (overnight) AMDAR volume average• Tu-Sa >70,000 reports• Su-Mo only ~25,000 reports

•Difference is primarily due to lack of parcel delivery flights

General Observation

Quantifying these Observations using theRapid Update Cycle - RUC

RUC is designed to produce hourly analyses andupdates to very short range forecasts (0-12 hrs)

Real-time 1-hourly analysis/forecast cycle Analyses intended to fit data very closely Forecasts only from 3 to 12 hours into future In general, 3 hr RUC wind forecasts are more accurate than 12 hr forecasts

Examination of verification against Radiosonde observations

Weekend minus Weekday 3 hr

Wind Forecast Errors for Jan-Oct

RUC Wind forecasts-Verification against raob data

Weekend-weekday 3h wind fcst error

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

850 700 500 400 300 250 200 150

Pressure level (hPa)

Win

d fc

st e

rror

dif

f (m

/s)

0.35 m/s / ~5.0 m/s= 7% better forecasts during weekdays due to more AMDAR reports at 200 hPa

Off-time data on weekends produces

less impact, especially after

reduced overnightpackage carriers reports

Hourly AMDAR VolumeReceived at FSL (ESRL)

2-15 Sept 01(starting 00z 2 Sept)

0

1000

2000

3000

4000

5000

6000

1 25 49 73 97 121 145

Hour of week

Air

craf

t rep

orts

/ ho

ur

Series1

0

1000

2000

3000

4000

5000

6000

1 25 49 73 97 121 145

Hour of week

Air

craf

t rep

orts

/ ho

ur

Series1

Su Mo Tu We Th Fr Sa

2-8 Sept 01

9-16 Sept 01

Su Mo Tu We Th Fr Sa

Notable reductions of aircraft dataavailable to RUC at FSL

on weekends andimmediately after Sept. 11, 2001

Improvement in 3 hr over 12 hr wind forecasts

during September 2001

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

1 5 9 13 17 21 25 29 33 37 41

12h periods - 1 Sept 01 to 21 Sept

12h-

3h fo

reca

st e

rror

diff

Series1

RUC 250mb wind forecasts verified against raob data

Period of data outage11-13 Sept 2001

Forecasts fromoperational RUCrun at NCEP

11-13 September 2011• No AMDAR data• 20% loss of 3hr

RUC wind forecast skill at 250mb

• 3 hr fcst skill ≅12hr skill

• No skill added by other off-time reports!!!

Impact of AMDAR Ascent/Descent Data in Rapid Update Cycle (RUC) forecasts

• Test performed using operational 20 km RUC– Ran data assimilation / forecast system for 3 weeks in June

2002 using two configurations:1. Including all data2. Eliminated aircraft data below 350 hPa

– Kept High-level En-route Data– Ignored Ascent /Descent Data

– Compared analyses and all forecasts (3, 6, 9, 12 Hr) against radiosonde at 00 and 12 UTC over CONUS

– Results expressed in improvement due to Ascent/Descent Data

EMC OSE by Ralph Petersen, Geoff Manikin and Dennis Keyser


• Question 1– What was the effect of the addition of

ascent/descent data on the data assimilation system and resulting 00 and 12 UTC analyses?

•Significant improvement by including Ascent / Descent data• Positive effects at all levels• Greatest effect at 30,000’ and below• Positive impact on Winds, Temp and RH.

Normalize error: compares

forecast differenceswith

overall forecast error


• Question 2– What was the effect of these analysis differences

on the 12 hr forecasts?

Tropospheric Improvementsup to twice

those in changingRUC from 40 to 20 km

•Significant improvement by including Ascent / Descent data• Positive effects at all levels on Winds, Temp and RH

• Above 25,000’, impact comparable to analysis differences• Below 25,000’, impact still large - but slightly smaller than in analysis

Impact of AMDAR Ascent/Descent data in Rapid Update Cycle (RUC) forecasts

• The fundamental purpose of the RUC is to use ‘off-time’ data to make repeated corrections to traditional ‘on-time’ model guidance

• Question 3– How did the continued data assimilation affect

model performance?

•After 9 hrs of continued use of ascent/descent data, tropospheric forecasts have improved by yet another 1-2%

Tropospheric Improvementsare 2-3 times greater than

those in changingRUC from 40 to 20 km

12 Hr Forecast Error – Red 3 Hr Forecast Error – Blue

Both forecasts valid at same times

Impact of AMDAR Ascent/Descent data in updating operational RUC forecasts

10–20% improvementat all levels

from forecast updates

Descent


• The fundamental purpose of the RUC is to use ‘off-time’ data to make repeated corrections to traditional ‘on-time’ model guidance

• Overall question now becomes:

– How much of the impact was the result of including ‘off-time’ ascent / descent data?

Assimilation/forecasts with Ascent/Descent Data– RedAssimilation/forecasts without Ascent/Descent Data– Blue

Difference between 12 hr operational RUC forecast and a later 3 hr forecast (valid at the same time but using additional asynoptic

reports) from systems with & without ascent/descents

Lack ofascent/descent data

in assim./fcstseliminates virtually all tropospheric benefits

of off-time updates anddegrades upper-levels

Descent

LOCAL APPLICATIONS OF

AMDAR DATA

• Severe Weather– Capping Inversions– Convective Instability– Wind Shear

• Precipitation and Type– Timing, Location,

Intensity

• Fog Onset/Dissipation– Trapping Inversion

Development/Decay– Calm Winds

• Air Quality/Fire Weather– Wind, Stability, Mixing,

Extended Coverage

Local Applications

Low-Level Wind Shear

• Based on this observation, the aviation forecaster was able to update the TAF and begin the LLWS more than 3 hours earlier than the prior forecast.

• Green Bay, Wisconsin, 29 October 2005• LLWS was forecast to begin after 0600 UTC in the TAF• Aircraft soundings near 0120 UTC already showed LLWS

Low Ceilings, Visibilities and Fog• Detroit, Michigan, 4 February 2005• Soundings near 2230 UTC showed light boundary layer winds, near-

surface moisture, dryness above• Commonly favorable conditions for fog development

• Based on the observations, the TAFs for 09 and 12 UTC were amended, reducing visibilities to ½ mile.• METARS showed that visibilities did decrease

KDTW 0532z 00000kt 2sm br clr KDTW 0739z 17003kt 1 3/4sm br r04/ 1000v3500 KDTW 0936z 17004kt 1/4sm fg r04/ 0500v0600 KDTW 1154z 16004kt 1/4sm fg r04/ 2800v0600

• Buffalo, New York, 15 December 2005• Forecasters initially were calling for larger snow accumulations• AMDAR temperature profile shows a larger than expected warm layer aloft

Precipitation Type

• With the existence of this deep warm layer aloft, forecasters amended the forecast calling for smaller snow accumulations and increased chances for sleet and freezing rain

Convective Storms• Central Wisconsin, 6 July 2005• Linear mesoscale convective system expected to persist into Wisconsin• Severe thunderstorm watch was issued at 1530 UTC for most of Central

Wisconsin

Convective Storms• Aircraft soundings from watch area at watch issuance and later showed

strong capping inversion unlikely to break• Forecasters lowered the chance for storms and the severe

thunderstorm watch was cancelled

• Very dry air could be seen on aircraft soundings earlier in the day when the Red Flag Warning was issued

• Later soundings showed there was sufficient dry air in other parts of the forecast area to expand the warning• Temperature >75F, RH <25%, winds >25 mph

Fire Weather• Northern and Central Wisconsin, 15 June 2006• Aircraft data showed extremely dry conditions coupled with the

potential for high winds due to mixing

In Summary

• AMDAR is a very important and necessary data set

• Fills spatial and temporal voids apparent in radiosonde and satellite data sets

• En-route data, but more so, ascent/descent data are vital to NWP skill

• Not just a NWP benefit, but an important local forecast area data set

Documents

Meteorological Impacts and Benefits of AMDAR Data Lee Cronce Ralph Petersen Cooperative Institute for Meteorological Satellite Studies (CIMSS) Space Science