# Presentation: 945072

## FSL Infrastructure developed for the GLFE (1)

- Aircraft display (http://amdar.noaa.gov/)
- shows Wind, T, Td, RH, Turbulence, Icing
- TAMDAR and non-TAMDAR can be selected
- Soundings displays
- available from aircraft display
- available as separate page
- (http://www-frd.fsl.noaa.gov/soundings/java/)

## FSL Infrastructure (2)

- MADIS distribution system provides TAMDAR and other aircraft data for
- ingest into local models
- display on AWIPS
- some difficulty displaying humidity with AWIPS soundings has been addressed recently

## FSL Infrastructure (3)

- Matched real-time RUC models
- “dev” **does** **not** include TAMDAR
- “dev2” **includes** TAMDAR
- otherwise dev is identical to dev2
- Stan will discuss this in more detail

## FSL Infrastructure (4)

- Aircraft-RUC database
- stores 1h forecasts from dev, dev2, and operational RUC models interpolated to aircraft data points
- Partial output available at
- http://amdar.noaa.gov/ruc_acars/
- Statistics by FSL aircraft ID
- 7-day summary is sortable in many ways
- Recently: information about which obs were rejected in each RUC run
- A (highly restricted) plan-view page
- restricted because it allows individual airlines to be displayed

## Sensor Performance Statistics

- TAMDAR (and other aircraft) observations are compared with 20km RUC 1-h forecast
- 1h forecast is more independent of the data than the analysis
- RUC forecast interpolated in x,y, and log-p to each observation point
- Only data passing RUC QC are shown
- with the exception of Dash-8’s, which are all rejected by the RUC currently
- We don’t consider the RUC perfect, but it is consistent in space and time, so can reveal some observation errors

## Airline Comparison, 2 - 17 August 2005, in TAMDAR region, daytime only, p > 500 mb

**             ****Temperature (°C)     **
**Airline    N  avg mb   T****RUC****    Bias   RMS      **
**    ****AA  20143   782   12.7    0.05   0.8 **
**CN-CRJ  26881   802   12.0    0.16   1.1   **
**CN-D8*  50937   809   12.9    0.97   2.0  **
**    ****DL   5871   730    9.4    0.39   1.2  **
**    ****FX  16447   787   12.8    0.33   1.0  **
**    ****NW   9118   731    8.4    0.28   1.0  **
**    ****SW   9323   822   15.7   -0.02   1.1 **
**TAMDAR 180583   807   13.1    0.08   1.2**** **
**    ****UA  26457   709    7.7    0.02   0.8  **
**    ****UP  22698   779   13.0    0.29   0.9**
**(* all CN-D8’s are currently rejected by RUC)****  **
**     **

**Notes:**
TAMDAR Temperature is comparable with the other fleets, but see the ascent/descent breakdown in a few slides.
(Dash-8’s have a known warm bias)
These numbers change negligibly when all data are included.
# Airline comparison
(this query, placed her for my future reference, shows a time window ending 22 Aug.  But there was a gap in the database from 17-22 august)
select
 airline,  
 count(t) as N_T,avg(press)/10 as avg_mb,
 avg(tf)/100 as avg_TF,avg(t-tf)/100 as bias_T,
sqrt(avg((t-tf)*(t-tf)))/100 as rms_T,
std(t-tf)/100 as std_T
 from acars,DV2,tail where
 acars.aid = DV2.aid
 and acars.xid = tail.xid
and press > 5000  # 500 mb
and lat > 3700 and lat < 4900
and lon > -10100 and lon < -7500
and (err is null or not (err%2 = 1 or err%16 >= 8))  # T error or T blacklist 
and date > '2005-08-02 00:00:00'
and date < '2005-08-22 00:00:00'
and !( extract(hour_minute from date) > 0300 and extract(hour_minute from date) <= 1159)
group by airline;

## Airline Comparison, 2 - 17 August 2005, in TAMDAR region, daytime only, p > 500 mb, passing RUC QC

**        ****Vector Wind Difference (m/s)    **
**Airline    N  avg mb   S****RUC****    Avg    RMS**
**    ****AA  19986   776    6.2    2.69   3.1**
**CN-CRJ  27588   802    8.8    2.99   3.5**
**CN-D8*  40200   810    8.0    4.71   5.5**
**    ****DL   4072   719    5.8    3.21   3.9**
**    ****FX  16262   788    6.5    2.74   3.2**
**    ****NW   9822   731    8.5    2.82   3.3**
**    ****SW   9364   822    5.9    3.19   3.7**
**TAMDAR 119069   791    7.7    4.23   4.9**
**    ****UA  26267   709    7.4    2.65   3.1**
**    ****UP  22944   775    5.7    2.60   3.0**
**(* all CN-D8’s are currently rejected)**
** **

**Notes:**
TAMDAR winds are notably worse than other fleets (except Dash-8’s)
These numbers change negligibly when all data are included.
# Airline comparison
(this query, placed her for my future reference, shows a time window ending 22 Aug.  But there was a gap in the database from 17-22 august)
select
 airline,  
 count(t) as N_T,avg(press)/10 as avg_mb,
 avg(tf)/100 as avg_TF,avg(t-tf)/100 as bias_T,
sqrt(avg((t-tf)*(t-tf)))/100 as rms_T,
std(t-tf)/100 as std_T
 from acars,DV2,tail where
 acars.aid = DV2.aid
 and acars.xid = tail.xid
and press > 5000  # 500 mb
and lat > 3700 and lat < 4900
and lon > -10100 and lon < -7500
and (err is null or not (err%2 = 1 or err%16 >= 8))  # T error or T blacklist 
and date > '2005-08-02 00:00:00'
and date < '2005-08-22 00:00:00'
and !( extract(hour_minute from date) > 0300 and extract(hour_minute from date) <= 1159)
group by airline;

## Airline Comparison, 2 - 17 August 2005, in TAMDAR region, day and night, up and down, p > 500 mb, passing RUC QC

**        ****Relative Humidity Difference (%RH)    **
**Airline       N  avg mb  RH****RUC****    Bias   RMS  **
**TAMDAR    179768   810   55.9   -0.30   12.0**
**TAMDAR-up  71106   850   59.0   -1.29   11.1**
**TAMDAR-dn  78074   854   58.2    0.98   11.5**

**Notes:**
“avg” is RUC average

# Airline comparison
(this query, placed her for my future reference, shows a time window ending 22 Aug.  But there was a gap in the database from 17-22 august)
select
 airline,  
count(rh) as N_R,avg(press)/10 as avg_mb,
avg(rhf) as avg_RF,avg(rh-rhf) as bias_R,
sqrt(avg((rh-rhf)*(rh-rhf))) as rms_R
 from acars,DV2,tail where
 acars.aid = DV2.aid
 and acars.xid = tail.xid
and rh is not null
and rh <= 100
and press > 5000  # 500 mb
and lat > 3700 and lat < 4900
and lon > -10100 and lon < -7500
and (err is null or not (err%8 >= 4 or err%64 >= 32))  # R error or R blacklist 
and date > '2005-08-02 00:00:00'
and date < '2005-08-22 00:00:00'
and up_dn = -1
#and !( extract(hour_minute from date) > 0300 and extract(hour_minute from date) <= 1159)
 group by airline;

## A Detailed look at TAMDAR compared with other airlines

- Most of the following plots show:
- Data from 1 - 17 Aug 2005
- Differences between ob and dev2 RUC
- (ob minus model)
- for data passing RUC QC (and not on reject list)
- (**we reject about 2% of TAMDAR Temperature obs)**
**(we reject about 10% of TAMDAR Wind and RH obs)**
- To facilitate comparison with other airlines:
- No data between 0300 and 1200 UTC
- Only data in the TAMDAR region
- lat between 37°N and 49°N
- lon between 75°W and 101°W
- “Other” is all airlines except
- TAMDAR and CN-D8

## Temperature

**Notes:**
Although overall TAMDAR T bias is good, there is a substantial bias in ascents and descents, perhaps due to a hysteresis effect.
Other fleets also show that ascents are warmer than descents, generally, except very near the surface (low speed effects?)
select
 ceil(press/500)*50 - 25 as mb , avg(press)/10 as avg_mb, 
 count(t) as N_T,avg(t)/100 as avg_T,
 avg(tf)/100 as avg_TF,avg(t-tf)/100 as bias_T,
sqrt(avg((t-tf)*(t-tf)))/100 as rms_T
 from acars,DV2,tail where
 acars.aid = DV2.aid
 and acars.xid = tail.xid
and airline != 'TAMDAR'
and airline != 'CN-D8'
 and t > -9990
#and press > 5000  # 500 mb
and lat > 3700 and lat < 4900
and lon > -10100 and lon < -7500
and (err is null or not (err%2 = 1 or err%16 >= 8))  # T error or T blacklist 
and date > '2005-08-01 00:00:00'
and date < '2005-08-17 00:00:00'
and up_dn = 1
group by mb
having N_T > 500
;

## Vector obs-RUC  Wind difference (m/s)

**Notes:**
Note: TAMDAR descents have large wind errors, probably due to maneuvering. But, even TAMDAR ascents show larger errors than the other fleets.
This disappointing result will be reflected in RUC statistics.
select
ceil(press/500)*50 - 25 as mb , avg(press)/10 as avg_mb,
count(dir) as N_W,
avg(sf)/100 as avg_SF,
avg(sqrt(pow(s,2)+pow(sf,2)-2*s*sf*cos((dir-dirf)/5729.58)))/100
    as avg_W,
avg(sqrt(pow(s,2)+pow(sf,2)-2*s*sf*cos((dir-dirf)/5729.58)))/avg(sf)*100 as pct_W_err,
sqrt(sum(pow(s,2)+pow(sf,2)-2*s*sf*cos((dir-dirf)/5729.58))/count(dir))/100
    as rms_W
 from acars,DV2,tail where
 acars.aid = DV2.aid
 and acars.xid = tail.xid
and dir is not null
and airline != 'TAMDAR'
and airline != 'CN-D8'
and lat > 3700 and lat < 4900
and lon > -10100 and lon < -7500
and (err is null or not (err%4 >= 2 or err%32 >= 16))  # W error or W blacklist
and date > '2005-08-01 00:00:00'
and date < '2005-08-17 00:00:00'  # latest time available
and !( extract(hour_minute from date) > 0300 and extract(hour_minute from date) <= 1159)
and up_dn = -1
group by mb
having N_W > 500;

## BUT, RUC wind speeds are slightly larger where TAMDAR flies

**Notes:**
(Wind speed in m/s)
This is true even though we’ve restricted ourselves to the TAMDAR domain.

## TAMDAR data in the box, yesterday

## “Other” data are further south, so sample lower winds below 500 mb.

- “Other” data are further south, so sample lower winds below 500 mb.

## Vector wind difference normalized to RUC wind speed (pct)

**Notes:**
Bottom  line: TAMDAR winds are not as accurate as the other fleets, and TAMDAR descents are substantially worse than ascents.
Percent errors for all fleets are highest near the ground, where wind speeds are smallest
TAMDAR down N = 52255
TAMDAR up N = 40733
other down N = 58858
other up N = 105200
only levels with N > 500 are plotted

## Wind errors: some are isolated, like this one.  AC #7139 measures 54 kt winds at 9882 ft on ascent from MSP. (Caught by RUC QC.)

- Wind errors: some are isolated, like this one.  AC #7139 measures 54 kt winds at 9882 ft on ascent from MSP. (Caught by RUC QC.)

**Notes:**
This aircraft is not on the reject list.

## Wind Errors.  Some are grouped. AC#5577 measures 36 - 42 kt winds between 8100 ft and 4100 ft on descent into MSP.  (Caught by RUC QC.)

- Wind Errors.  Some are grouped. AC#5577 measures 36 - 42 kt winds between 8100 ft and 4100 ft on descent into MSP.  (Caught by RUC QC.)

**Notes:**
But more subtle errors are not caught, and can result in a negative impact on the RUC.
This aircraft is not on the reject list.

## TAMDAR Relative Humidity Bias

**Notes:**
In percent
Dry bias on ascent, moist bias on descent.  Consistent with a hysteresis effect.
All hours included, not just daytime hours.  (But most flights occur in daytime)
select
ceil(press/500)*50 - 25 as mb , avg(press)/10 as avg_mb,
count(rh) as N_R,avg(press)/10 as avg_mb,
avg(rhf) as avg_RF,avg(rh-rhf) as bias_R,
sqrt(avg((rh-rhf)*(rh-rhf))) as rms_R
 from acars,DV2,tail where
 acars.aid = DV2.aid
 and acars.xid = tail.xid
and dir is not null
and airline = 'TAMDAR'
and airline != 'CN-D8'
and lat > 3700 and lat < 4900
and lon > -10100 and lon < -7500
and (err is null or not (err%8 >= 4 or err%64 >= 32))  # R error or R blacklist 
and date > '2005-08-01 00:00:00'
and date < '2005-08-17 00:00:00'
#and !( extract(hour_minute from date) > 0300 and extract(hour_minute from date) <= 1159)
and up_dn = 1
group by mb
having N_R > 500;

## TAMDAR rms RH

**Notes:**
In %RH
Increases dramatically with altitude.  This will also be reflected in the RUC statistics.

## Conclusions (1)

- TAMDAR Temperatures are generally good
- however, ascents have a warm bias, descents have a cool bias
- TAMDAR winds are more troublesome
- substantial errors on descent, possibly due to maneuvers
- errors on ascent are greater than other fleets
- TAMDAR RH bias is small
- but ascent/descent dependent
- TAMDAR rms RH increases substantially with altitude

## Conclusions (2)

- The FSL Aircraft-RUC database is an increasingly rich source of information
- we now know which obs are rejected/accepted by the RUC, and for what reason
- can easily stratify by ascent/descent
- can stratify by airline and airframe type
- we expect to perform increasingly informative studies using this tool