Non-IFS observation processing (OBSPROC): General overview

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IFS documentation Front Page

Table of contents
Chapter 1. Non-IFS observation processing (OBSPROC): General overview

Chapter 2. Observations: Types, variables and error statistics

Chapter 3. CMA creation (MAKEMA)

Chapter 4. The FEEBACK task

Chapter 5. The TOOLS task

Chapter 6. Central-memory array (CMA) structure/format

Chapter 7. BUFR feedback data structure/format

Chapter 8. SIMULATED-observations data structure/format

Chapter 9. NAMELISTS

Chapter 10. Processing of scatterometer data

REFERENCES

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2.2 Observation error statistics

Three types of observation errors are dealt with at this level:

• persistence error,

• prescribed observation error and,

• combination of these two above, so called final observation error.

2.2.1 Persistence error

The persistence error is formulated in such a way to reflect its dependence on:

• a season, and

• the actual geographical position of an observation.

Seasonal dependency is introduced by identifying three regimes:

• winter/summer hemispheres and,

• tropics,

and then positional dependency is introduced to reflect a dependence on the precise latitude within these three regimes.

The persistence error calculation is split in two parts. In the first part the above dependencies are expressed in terms of factors

and

which are defined as:

and

where,

is a day of year and

is latitude.

The persistence error for time difference between analysis and observation

is then expressed as a function of

with a further dependence on latitude and a maximum persistence error (

) for 24 hours:

where,

is expressed as a fraction of a day. The

has the values as shown in the table below:

Table 2.7 Maximum 24-hour persistence errors
Variable (unit)	1000-700 hPa	699-250 hPa	249-0 hPa
(m s^-1)	6.4	12.7	19.1
(m)	48	60	72
(K)	6	7	8

Subroutine SUPERERR is used to define all relevant points in order to carry out this calculation, and is called only once during the general system initialization. The calculation of the actual persistence error is dealt by subroutine OBSPERR.

2.2.2 Prescribed observational errors

Prescribed observational errors have been derived by statistical evaluation of the performance of the observing systems, as components of the assimilation system, over a long period of operational use. The prescribed observational errors are given in the tables below. Currently, observational errors are defined for:

• wind components,

• height,

• temperature, and

• relative humidity

for each observation type which carries these quantities. As it can be seen from the tables below, they are defined at standard pressure levels but the actually used ones are interpolated to the observed pressures. The interpolation is such that the observation error is kept constant below the lowest and above the highest levels, whereas in between it is interpolated linearly in

. Several subroutines are used for working out the prescribed observation error. These subroutines are: SUOBSERR, OBSERR, FIXERR, THIOERR and PWCOERR. In SUOBSERR observation errors are defined for standard pressure levels. In OBSERR and FIXERR the actual values are worked out. THIOERR and PWCOERR are two specialised subroutines to deal with thickness and

errors.

Relative humidity observation error (

) is either prescribed or modelled. More will be said about the modelled

in the next subsection.

is prescribed only for TEMP and SYNOP data.

is preset to 0.17 for TEMP and 0.13 for SYNOP. However, if

it is increased to 0.23 and to 0.28 if

K for both TEMP and SYNOP:

Table 2.8 The RMS observation wind components ( and ) errors ( )
Obs.. Code Types	Levels
Obs.. Code Types	1000 hPA	850 hPa	700 hPa	500 hPa	400 hPa	300 hPa	250 hPa	200 hPa	150 hPa	100 hPa	70 hPa	50 hPa	30 hPa	20 hPa	10 hPa
synop *	2.00	2.00	2.00	3.10	3.30	3.50	2.90	2.90	2.10	1.90	1.70	1.70	1.70	2.20	2.70
airep 141/*	2.46 2.86	2.51 2.91	2.56 2.96	2.71 3.11	2.81 3.21	2.86 3.26	2.91 3.31	2.96 3.36	2.91 3.31	2..76 3.16	2.66 3.06	2.66 3.06	2.86 3.26	3.06 3.46	3.36 3.76
satob *	2.0	2.0	2.0	3.5	4.3	5.0	5.0	5.0	5.0	5.0	5.0	5.0	5.0	5.0	5.7
dribu *	1.80	1.80	1.80	1.80	1.80	1.80	1.80	1.80	1.80	1.80	1.80	1.80	1.80	1.80	1.80
temp *	1.80	1.80	1.90	2.10	2.50	2.60	2.50	2.50	2.40	2.20	2.10	2.00	2.10	2.30	3.00
pilot *	1.80	1.80	1.90	2.10	2.50	2.60	2.50	2.50	2.40	2.20	2.10	2.00	2.10	2.30	3.00
satem *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
paob *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
scat *	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0	2.0
r. raid *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-

Table 2.9 The RMS observation height errors (m)
Obs.. Code Type/	Levels
Obs.. Code Type/	1000 hPA	850 hPa	700 hPa	500 hPa	400 hPa	300 hPa	250 hPa	200 hPa	150 hPa	100 hPa	70 hPa	50 hPa	30 hPa	20 hPa	10 hPa
synop ship/*	5.6 10.0	7.2 10.0	8.6 10,0	12.1 10.0	14.9 10.0	18.8 10.0	25.4 10.0	27.7 10.0	32.4 10.0	39.4 10.0	50.3 10.0	59.3 10.0	69.8 10.0	96.0 10.0	114.2 10.0
airep *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
satob *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
dribu *	7.0	7.0	7.0	7.0	7.0	7.0	7.0	7.0	7.0	7.0	7.0	7.0	7.0	7.0	7.0
temp *	4.3	4.4	5.2	8.4	9.8	10.7	11.8	13.2	15.2	18.1	19.5	22.5	25.0	32.0	40.0
pilot *	4.3	4.4	5.2	8.4	9.8	10.7	11.8	13.2	15.2	18.1	19.5	22.5	25.0	32.0	40.0
satem *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
paob *	24.0	24.0	24.0	24.0	24.0	24.0	24.0	24.0	24.0	24.0	24.0	24.0	24.0	24.0	24.0
scat *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
r rad. *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-

Table 2.10 The RMS observation temperature errors (K)
Obs. Code Types	Levels
Obs. Code Types	1000 hPA	850 hPa	700 hPa	500 hPa	400 hPa	300 hPa	250 hPa	200 hPa	150 hPa	100 hPa	70 hPa	50 hPa	30 hPa	20 hPa	10 hPa
synop ship/*	2.00 1.80	1.50 1.80	1.30 1.80	1.20 1.80	1.30 1.80	1.50 1.80	1.80 1.80	1.80 1.80	1.90 1.80	2.00 1.80	2.20 1.80	2.40 1.80	2.50 1.80	2.50 1.80	2.50 1.80
airep 141/*	1.40 1.65	1.18 1.43	1.00 1.25	0.98 1.23	0.96 1.21	0.95 1.20	0.95 1.20	1.06 1.31	1.18 1.43	1.30 1.55	1.40 1.65	1.50 1.75	1.60 1.85	1.80 2.05	2.10 2.35
satob *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
dribu *	1.80	1.50	1.30	1.20	1.30	1.50	1.80	1.80	1.90	2.00	2.20	2.40	2.50	2.50	2.50
temp *	1.40	1.25	1.10	0.95	0.90	1.00	1.15	1.20	1.25	1.30	1.40	1.40	1.40	1.50	2.10
pilo *t	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
satem *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
paob *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
scat *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
r. rad. *	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-

2.2.3 Derived observation errors

Relative humidity observation error,

, can also be expressed as function of temperature (

This option is currently used for assigning

.

Specific humidity observation error (

) is a function of relative humidity and its observation error (

), pressure and its error (

) and temperature and its error (

), and formally can be expressed as:

or:

where, functions

are given as:

and functions

are:

At the moment only the first term of the above expression for

is taken into account (dependency on relative humidity). Subroutine RH2Q is used to evaluate

.

The surface-pressure observation error (

) is derived by multiplying the height observation error (

) by a constant:

However, the

may be reduced if the pressure-tendency correction is applied. In the case of non-ship data the reduction factor is 4, whereas in the case of ship data the reduction factor is either 2 or 4, depending if the

is adjusted for ship movement or not.

The thickness observation error (

) is derived from the

2.2.4 Final (combined) observation error

In addition to the prescribed observation and persistence errors, the so called final observation error is assigned at this stage too. The final observation error is simply a combination of the observation and the persistence errors:

where, FOE, OE and PE are final, prescribed observation and persistence errors, respectively. The subroutine used for this purpose is FINOERR.

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13.03.2003