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found to be shifted eastwards in all the three experiments as
compared to the NNRP. In general it can be said that
compared to KF and GD, BMJ is in good agreement with
the observation in both the level.
b. Distribution of mean monsoonal precipitation
and underlying variability
In comparing three convective parameterization schemes
from IMD, KF is found to have high moist bias over central
Indian region along with the west coast (Fig. 2b) in the
seasonal mean. GD (Fig. 2c) on the other hand shows the
opposite, where as BMJ (Fig. 2a) is found to produce most
reasonable seasonal distribution of rainfall out of the three
convective schemes.
Figure 2. Spatial distribution of model simulated
JJAS averaged precipitation difference of (a) BMJ, (b)
KF, and (c) GD from IMD observation.
To investigate the spatio-temporal variability of
precipitation superimposed in the seasonal mean, daily mean
rainfall PDFs are computed for different range of rain-rates.
The PDF plot indicates that BMJ and KF underestimates the
observation for lighter rain-rates ( 40 mm/day) category. The time evolutions of PDF
for the above three rain rate categories are computed. In the
lighter category GD shows a systematic overestimation
throughout the season whereas BMJ and KF have problem
(overestimation) during the first 30 days of integrations. In
the moderate rain-rate category GD has systematically
underestimated the observed PDF throughout the season.
BMJ and KF have underestimated the observed PDF for the
first 30 days and are in good agreement in the rest of the
season for the same category. In the heavy category KF has
significantly overestimated the observed PDF throughout the
season. Further by analyzing the percentage contributions of
each rain-rate to the total seasonal rain for each of the three
schemes, it is found that GD has substantially large
contribution to the total rain by the light rain-rate bins and
significantly lesser contribution from moderate rain-rates.
BMJ appears to produce the closest possible contribution
amongst the three for all the rain-rate categories. The higher
percentage contribution by KF from the rain-rate bins of 25
mm/day or more along with significant overestimation of
observed PDF in the high rain-rate category can be
attributed to the positive biases in seasonal mean
precipitation by KF. To gain further insight about the role of
each scheme in adding dry or moist bias in the evolution of
seasonal rain and its spatial patterns, the time evolution and
also the spatial pattern of percentage of rainy grid cells are
computed. This brings out that the underestimation of
precipitation in GD mainly came from the moderate rainrate
and overestimation of KF is because of heavy rain-rate.
After identifying details of biases for each convection
schemes arising from different rain-rate category and its
manifestation on spatio-temporal variability of
precipitation, a critical evolution of apparent heat source
(Q 1 ) and moisture sink (Q 2 ) is carried out over mother
domain to determine the physical reason behind the
deficiency in reproducing seasonal mean precipitation.
The seasonal evolution of Q 1 and Q 2 clearly tells about the
competition between the evaporation and condensation
throughout the season. It is found that KF could not
reproduce the domination of evaporation over
condensation at the time of withdrawal which means KF
continues to produce rain even at the end of the season.
Whereas GD shows a very weak seasonal cycle with the
natural cycle of evaporation and condensation is totally
missing. On the other hand BMJ could realistically depict
the domination of evaporation compared to condensation
till the mid June prominently. The enhancement of
condensation over evaporation after the monsoon onset
and followed by a maxima in the July-August and
reduction of condensation at the time of withdrawal is
only reasonably captured by BMJ.
4. Conclusion
The erroneous spatio-temporal evolution of apparent heat
source and moisture sink is the main reason behind the
seasonal bias of precipitation by different convective
closures. KF appears to produce stronger instability and
intense updraft and end up with a large moist bias. GD on
the other hand produces weaker instability and weaker
updraft to produce relatively dry bias. BMJ is found to be
better than KF and GD but it also shows certain biases
compared to observation. The improvement in formulation
that can give a more accurate profile of Q 1 and Q 2 and
remove the deficiency of producing the right PDF at
correct proportion could result in the improvement of the
precipitation bias significantly in weather and climate
mode of application of regional model.
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