Intercomparison of horizontal wind speed
components from NCEP/NCAR-Reanalysis
and NCEP-DOE Reanalysis II.
Jörg Winterfeldt1,21

Institute for Coastal Research, GKSS Research Center, Geesthacht, Germany
2

IMPRS-ESM, Max Planck Institute for Meteorology, Hamburg, Germany

Hindcasts with reanalysis driven Regional Climate Models (RCMs) are a common
tool to assess weather statistics (i.e. climate) and recent changes and trends. The
capability of the two state-of-the-art RCMs REMO in two configurations (withand without spectral nudging applied) and CLM (with spectral nudging applied)
to add value for surface marine wind fields in comparison to the reanalysis windspeed forcing is assessed by the comparison with wind speed observations in theeastern North Atlantic. For the locations of the in-situ observations and for
details on the added value assessment please refer to the extended abstract on”Assessment of value added for surface marine wind fields obtained from tworeanalysis driven Regional Climate Models (RCM).”The added value is assessed with in-situ marine wind speed data at 10 m height in
1998. The observed 10 m wind speed is compared with the diagnostic 10 m windspeed of the RCMs and the forecast 10 m wind speed of the reanalysis, which isused as best guess for the 10 m wind speed of the reanalysis forcing because boththe NCEP/NCAR (hereafter:NRA R1) and NCEP/DOE II (NRA R2) reanalyses do not deliver reanalysed 10 m wind speed. The SN-REMO, STD-REMO andCLM hindcasts were forced by the NRA R2 in 1998. Consequently the forecast
10 m wind speed of the NRA R2 should be used in the added value assessment.
Unfortunately the NRA R2 10 m wind speed forecast represents a rather unplausible data set with limited agreement with in-situ wind speed, as will bedemonstrated in the following.
For the comparison of the in-situ wind speed with both NRA R1 and NRA R2
10 m wind speed forecasts, the latter are bilinearly interpolated onto the loca-

tions of the in-situ measurements. In addition, both the NRA R1 and NRA R2
forecasts were time interpolated linearly to the one hour resolution given by theobservations. The results of the comparison are displayed in Figure 1.
12Standard Deviation of wind speed [m/s]11
mean wind speed [m/s]5.5

NRA_R2Obs
NRA_R11098765

K1

RARH

K5

FRIGG NSBII
GRW
K13
DeBu
F3
ChanSand
Ems
Observation

NRA_R2Obs
NRA_R1

54.5
4
3.5
32.5

K1

RARH FRIGG NSBII
GRW
K13
DeBu
Sand
K5
F3
ChanEms
Observation

(a)

(b)
514
NRA_R2
NRA_R1
8000

0.4

6000
4000

0.20

RARH
K1

FRIGG NSBII

K5

GRW

F3
Chan
Observation

K13

Sand

DeBu
Ems

2000
0

RMSE [m/s]0.6

number of observations

correlation r0.8

NRA_R2NRA_R1

3210K1

RARH

K5

FRIGG

(c)

NSBII

GRWF3ChanObservation

K13SandDeBuEms(d)Figure 1: Comparison of in-situ wind speed with 10 m wind speed forecasts of NRA R1
and NRA R2 in 1998: a) mean wind speed, b) its standard deviation, c) number ofobservations and correlation r, d) root-mean-square error.

In general a large positive bias between the NRA R2 and the NRA R1 in theorder of 2 m s−1 can be inferred (see also Figure 2(a)). Far offshore at K1,RARH, K5, FRIGG and F3 the NRA R1 agrees better with observed mean windspeed while the NRA R2 overestimates 10 m wind speed by up to 2 m s−1 (3m s−1 at K5 due to both NRA R2 large bias and too low wind speed measure-ments at K5). Closer to the coast and, especially within the English Channel,
the NRA R2 shows a much better agreement with the observations.
The latter represents a highly unplausible result, because both forecasts calculate
wind speed over approximately 200x200 km wide grid boxes and can thereforehardly resolve the topography within the English Channel. At each grid box
within the English Channel some kind of smoothed topography, averaged over
the water and adjacent land surfaces, is used in both forecasts. As a result thesurface roughness will be higher and consequently the forecast wind speed within
the English Channel should be lower than that measured by the English Channel
lightships Chan, GRW and Sand. While this is the case for the NRA R1, theNRA R2 gives mean wind speeds comparable to the in-situ data.
70NSimilarly,

10m wind speed forecast: NRA_R2 - NRA_R1

68N

10m wind speed forecast: NRA_R2 - NRA_R1

66N
64N

60N

62N
60N

30N

58N
56N

EQ

54N
30S

52N
50N

60S

48N
46N
20W

15W

10W

–2 –1.5 –1

5W

0–0.5 –0.3 –0.1 0.1

(a)

5E
0.3

10E
0.5

1

15E
1.5

220E(m/s)

180120W–2–1.560W–1–0.5

0–0.3

–0.1

120E

60E
0.1

0.3

0.5

11.5

1802(m/s)(b)

Figure 2: Bias between the 10 m forecast wind speed of the NRA R2 and NRA R1 inthe eastern North Atlantic and the North Sea (left) and globally (right) in 1998 .

where topographic features, averaged over a forecast grid cell, are relatively homogeneous (such as for open waters) near-surface wind speed is expected to showless variance and in-turn a better agreement between in-situ and forecast windspeed might be expected. While again this is the case for the NRA R1, it is not
for the NRA R2. While representing an average over 200x200 km with an integration time step of 20 min, the NRA R2 forecast gives wind speed variabilities
higher than observed for 9 of 12 cases, which is highly unplausible. The RMSE

70N

NRA_R1 wind speed: 1000 hPa – 10m fc

70N

68N

68N

66N

66N

64N

64N

62N

62N

60N

60N

58N

58N

56N

56N

54N

54N

52N

52N

50N

50N

48N

48N
46N

46N
20W

15W

10W
–2–1.5

5W
–1

0–0.5

5E
0.5

110E
1.5

15E

20E(m/s)2(a)70N

NRA_R2 wind speed: 1000 hPa – 10m fc

20W

15W

10W
–2

–1.5

5W
–1

0–0.5

5E
0.5

110E
1.5

15E
220E

(m/s)

(b)

NRA_R2 1000 hPa – NRA_R1 10m fc

68N
66N
64N
62N
60N
58N
56N
54N
52N
50N
48N
46N
20W

15W

10W
–2

–1.5

5W
–10–0.5(c)

5E
0.5

110E
1.5

15E
220E(m/s)(d)Figure 3: Comparison of the reanalysed 1000 hPa and forecast (fc) 10 m wind speed ofboth reanalyses in 1998: a) NRA R1: 1000 hPa - 10 m fc, b) NRA R2: 1000 hPa - 10m fc, c) NRA R2 1000 hPa - NRA R1 10 m fc, d) 1000 hPa: NRA R2 - NRA R1.

of the NRA R2 10 m forecast again shows its counterintuitive behaviour, since itgives lower RMSE values near coastlines it cannot resolve and higher RMSE forareas far offshore.
As depicted in Figure 2(b), the strong bias between the NRA R2 and NRA R1
10 m wind speed forecasts is not constrained to the Northeast Atlantic. With
the exception of the subtropical latitudes around 30◦ and some patches in theAntarctic, the NRA R2 shows too high 10 m wind speed as compared to theNRA R1. This positive bias peaks to 1.5 m s−1 and above in and around theAntarctic and on the Eurasian and North American land masses.
In 1998, the mean sea level pressure in the investigated area is similar to the1013 hPa given for the U.S. Standard Atmosphere after NASA(1976)(not shown).
Thus, in agreement with the standard atmosphere, the 1000 hPa level is expected
to be in average at a height of around 100 m. Consequently, according to thevertical wind speed profile in the surface layer, the wind speed at 1000 hPa is in
average higher than that at 10 m height. For 1998, the differences of the annual
averages of the reanalysed 1000 hPa and forecast 10 m wind speed are depicted
in Figure 3. While the NRA R1 shows higher wind speeds on the 1000 hPa level(Figure 3(a)), the NRA R2 forecast wind speed in 10 m height even exceeds thereanalysed wind speed at the 1000 hPa level (Figure 3(b)), indicating a major
inconsistency in the NRA R2 reanalysis/forecast system, as far as near-surface
wind speed is concerned.
Both reanalyses show similar wind speed patterns at 1000 hPa, which is not
surprising given that both reanalyses assimilate similar marine near-surface windspeed observations. In detail, the differences are much smaller than the differences between the 10 m wind speed forecasts and have the opposite sign (Figure3(d)). These findings indicate on the one hand, that the NRA R2 10 m windspeed forecast is not representative for the near-surface wind field of the NRA R2
reanalysis. On the other hand, a problem within the Hong-Pan planetary boundary layer non-local vertical diffusion scheme (Hong and Pang, 1996) implemented
in the NRA R2 forecast model is indicated. Additionally, the strong bias may
be attributed at least in part to the different convective parameterizations leading to more intense storms in the NRA R2 (W. Ebisuzaki (Climate Prediction
Center, NCEP), pers. comment). The effects are also visible in the wind speed
frequency distributions (Fig 4). While the bias between both forecasts is similar
at all stations, the bias between the NRA R2 forecasts and in-situ wind speed isstrongest for open ocean areas (4(a)). The latter bias is lowered in coastal areasby the increasing influence of the surrounding land mass on the forecast windspeed, leading to apparently well matched wind speed frequency distributions inthe German Bight at the light ships Ems and Debu and especially in the English

Channel at Chan (Figures 4(b)-4(d)).

wind speed [m/s]2025

NRA_R2
NRA_R120
wind speed [m/s]25151050

NRA_R2
NRA_R115105051015
RARH: wind speed [m/s]2002505(a)wind speed [m/s]2025

NRA_R2
NRA_R1

2015
105020252025(b)wind speed [m/s]251015
Chan: wind speed [m/s]

NRA_R2
NRA_R115105051015Ems: wind speed [m/s](c)20250051015DeBu: wind speed [m/s](d)Figure 4: Comparison of percentile-percentile distributions of 10 m wind speed fromNRA R1 and NRA R2 forecasts and in-situ data at a) RARH, b) Chan, c) Ems andd) DeBu.

Because of the plausibility arguments discussed, the NRA R2 10 m forecast is
not considered as an appropriate product to assess the added value of RCM
hindcasts. However, the difference between the NRA R2 1000 hPa wind speed
and the 10 m wind speed forecast of the NRA R1 shows a similar spatial pattern as the difference between the NRA R1 1000 hPa and its forecast wind speed(Figures 3(c) and 3(a)). It is therefore suggested to use the NRA R1 10 m windspeed forecast as best guess for the 10 m wind speed within the NRA R2 reanal-ysis. Still, this approach is suboptimal and the added value assessment should
be redone, when in-situ data is available for periods prior to 1997, when the SNREMO and STD-REMO hindcasts are forced with the NRA R1.
Literature:
NASA (1976). U.S. Standard Atmosphere. NOAA, NASA and USAF.
Hong, S.-Y. and Pang, H.-L. (1996). Nonlocal boundary layer vertical diffusion
in a medium-range forecast model. Monthly Weather Review, 124, 2322-2339.