Effect Of Modified Scf Parameterizations In 3d Climate Simulations

The effects of the modifications presented in Section 4 are studied in 3-D ECHAM4/T42 experiments described in Chapter 2. For a detailed discussion of the response, the modifications for

(i) flat, non-forested areas (Experiment MOD 1)

(ii) mountainous, non-forested areas and (Experiment MOD2)

(iii) forests (Experiment MOD3)

were separately implemented and tested in three independent model runs.

5.1 Flat areas

The implementation of the tanh-function for computing the snow cover fraction from the SWE in the model experiment MOD 1 (Eq. 6) substantially raises the SCF compared to the 10-year control experiment. This is shown in Fig. 6 for the winter season (DJF) in the Northern Hemisphere. The notable increase in SCF is mainly limited to flat regions with relatively thin snow cover and few forests. These characteristics apply to areas such as the vast lowlands in Ukraine and Kazakhstan with predominantly grass or Steppe vegetation (Fig. 6b). Further significant differences in the simulated SCFs are found south of Lake Baikal in Mongolia. In North America, substantial differences in the SWE are simulated at the Great Lakes and west of Lake Winnipeg with their generally flat landcapes.

The SCF is only marginally affected in highly forested areas (boreal forests) as well as mountainous regions (Rockies, Himalayas or Alps) since the new parameterization is only applied to flat, non-forested areas. Small differences between CTRL and MOD 1 are also found in regions with thick snow cover such as Arctic Russia and northern Canada with a mean (modeled) SCF above 80% during winter (Fig. 6a). The largest differences in the SCF, using Eq. 6, occur for thin snow cover. This difference is larger than the interannual DJF variability given in Fig. 6c.

The maximum difference in the SCF is associated with a snow water equivalent of 1.6 cm and amounts to more than 25%. For thicker snow cover, the difference between the two expressions decreases rapidly and is small for SWE larger than 10 cm.

This modification of the SCF parameterization for flat regions without forests (MOD 1) produces only a few significant changes in the surface climate, as summarized by the sensitivities in Table 2. These sensitivities were averaged from land grid boxes with measurable snow (Sn > 0.1 cm) in February. Annual differences larger than 3% are found for snow cover fraction, surface albedo, reflected shortwave radiation and sensible heat flux. The percentage for the sensible heat flux is large because annual means are close to zero. The larger snow cover fraction increases the reflected shortwave radiation and thus the heating of the ground is reduced, which implies lower surface temperatures. Lower surface temperatures yield a higher fraction of snow in the total precipitation and less snowmelt which again increases the SCF in a positive feedback. However, the cooling of the surface and the increase of snow water equivalent are small, being statistically insignificant. The lower amount of available radiation near the ground may also reduce the magnitude of the hydrological cycle which is supported by a decrease in total precipitation. It should be noted that the above discussion is purely one-dimensional, thus precluding any advective processes. For exam ple, it cannot be excluded that changes in the moisture convergence, rather than lower net radiation, yield the simulated decrease in the annual precipitation.

Figure 6. Simulated SCF for the winter season (DJF). a) mean winter SCF for the control simulation; b) difference between MODI and CTRL; c) standard deviation as calculated from the 10 available winter means simulated in MODI
Table 2. Comparison of 10-year-means between the modified simulation (MODI) and the control climate. Figures refer to averages over all land points with Sn> 0,1 cm in February (according to the USAF snow depth climatology), excluding ice covered grid boxes. Last

Parameter

Unit

MODI

CTRL

Diff.

Diff. {%)

Snow cover

%

35.9

33,6

2.3

6.9

Snow water eq.

cm

3,24

3.23

0.01

0.3

Surface albedo

0.32

0.31

0.01

3.4

Net SW, surface

Wmr2

95.1

95.8

-0.7

-0.7

Global radiation

Wm-2

127.5

127.2

0.3

0.2

SW, up, surface

Wnr2

-32.4

-31.4

-1.0

3.3

Net LW, surface

Wm-2

-51.0

-51.2

0,2

-0.4

2-m temperature

K

272.86

272.95

-0.09

Latent heat flux

Wm-2

-31.3

-31.7

0,4

-1.2

Evapotranspiration

mm/day

1.06

1.07

-0.01

-1.2

Sensible heat flux

Wm-2

-1.4

-1.6

0.2

12,5

Rel. soil moisture

%

73.7

73.4

0,3

0.4

Précipitation

mm/day

1.67

1.69

-0.02

-1,1

¬°0 m windspeed

ms-'

3.59

3.62

-0.01

-0.3

The impact of increasing surface albedo on land evapotranspiration E is negative (Table 2), which is in line with other sensitivity studies with 3-dimensional GCMs (Garratt, 1993). In the current experiment, E decreases by 0.01 mm/day for an increase in surface albedo by 0.1, which compares well with the value determined by Mylne and Rowntree (1991). However, a number of studies quoted in Garratt (1993) suggest a distinctly higher impact of surface albedo on evapotranspiration. The sensitivity of total precipitation to surface albedo is approximately 1.7 times larger than the response of the surface albedo on E, in good agreement with the sensitivity studies reviewed in Garratt (1993). The response of evapotranspiration to changes in surface albedo is consistent with results from off-line experiments using atmospheric forcing from the Cabauw site in the Netherlands (Roesch et al., 1997).

To summarize, the change in directly affected variables such as snow cover fraction and surface albedo is significant, whereas other surface variables do not considerably change in MOD 1 compared to the control simulation.

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