spatio-temporal assessment of precipitation over the mantaro...
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Spatio-temporal assessment of precipitation over the Mantaro
River Basin (Peru)
using different physical parameterizations with the WRF model
G. Rosales, Alan1,2; Silva Vidal, Yamina1; Junquas, Clementine1,3
1Geophysical Institute of Peru (IGP), Peru2 Institute of Astronomy, Geophysics and Atmospheric Sciences (IAG), Brazil
3Institute of Environmental Geosciences, Grenoble, FranceContact: [email protected]
Abstract
Introduction Experimental Settings
Validation of simulations
Future work References
Behavior of different parameterizations
The Mantaro valley is highly productive and supplies the main food
products to the capital of Peru, Lima. On the other hand, the precipitation of
the basin supplies the Mantaro hydroelectric power plant (IGP, 2005).
However, high climate variability and extreme weather events affect these
activities. With the objective of finding the physical mechanisms
responsible for the variability of rainfall in the Mantaro river basin, the
WRF model is used, applying different parametrizations.
In this study we present the preliminary results of four runs conducted with
WRF for the month of February 2002, a control run and three experimental
runs using different parameterization of cumulus and microphysics schemes
, for three domains with horizontal resolutions of 27, 9 and 3km.
In this study, the purpose was to apply different configurations to improve the degree of response of the Weather Research and Forecasting (WRF) model over the Mantaro river basin, to
identify an adequate configuration for the simulation of precipitation in this region. The month of February 2002 was simulated because it represents a wet year. High-resolution
simulations reached up to 3 km of horizontal resolution, where the cumulus schemes were deactivated allowing the convection-permitting. As a result, we found a significant
improvement by combining the Kain-Fritch (cumulus) and the Lin (Purdue) (microphysics), schemes, which reduced the overestimation up to 58% over the basin when compared to the
control simulation. This results indicates that it is important to perform tests of sensibility to different combinations of parameterization schemes when using the WRF model in a complex
topographic region. In addition, the analysis of the physical processes associated with each simulation is needed to understand why a parameterization scheme is more appropriate than an
other in terms of simulated precipitation at the local scale.
Figure 1. Study zone and domains of simulations.
*Simulations forced by reanalysis NCEP FNL
*WRF-ARW version 3.4.1
*Control configurations:
Thompson (Microphysics)
Grell-Devenyi (Cumulus Parameterizations)
Unified Noah land-surface model
Yonsei University (YSU) with Topo wind (Boundary Layer)
The experiments of simulations are described in table 1.
Table 1. Configuration of experiments.
Parameterization Scheme Reference Abbreviationsof the
experimentMicrophysics(mp_physics)
Lin (Purdue) Lin, Farley and Orville (1983, JCAM)
MP_LP
Cumulusparameterizations
(cu_physics)
Kain-Fritsh Kain (2004, JAM) CU_KF
Betts-Miller-Janjic Janjic (1994, MWR; 2000, JAS)
CU_BMJ
Surface layer(sf_surface_physics)
Noah-MP land-surface model
Niu et al. (2011); Yang et al. (2011)
LS_NMP
Boundary layer(bl_pbl_physics)
Mellor-Yamada-Janjic Janjic (1994, MWR) PBL_MYJ
Figure 2. Comparison between TRMM products and WRF
simulations in (a and b) 27km and (c and d) 9km of
horizontal resolution.
Figure 3. Diurnal cycle of precipitation in Huayao Station.
• WRF shows an adequately
representation of the
precipitation over the
amazon, convective points
in the Andes and dry
conditions over the coast.
• The simulated precipitation
is low in the valleys and
high on the slopes of the
Andes.
• WRF overestimates three
times the precipitation
when compared to TRMM
2A25.
• WRF accurately represents
the diurnal cycle showing
only one lag of one hour at
the peak of the observed
(18hr).
Figure 4. Difference between each experiment with the control
simulation in 9km of horizontal resolution.
Figure 5. Difference between each experiment with the control
simulation in 3km of horizontal resolution.
During the master research we will focus on a different region, with strong
local valley processes, situated in the Cordillera Blanca.
The importance of this research:
-Understanding dynamic processes in Valley Mountain area.
-Evaluate the impact of these processes on the formation of rainfall/snowfall.
-The research colaborates in the studies of Glaciers in the Cordillera Blanca.
-The study offers a process-oriented alternative for retrieving precipitation
fields of high spatiotemporal resolution in complex terrain regions like the
Cordillera Blanca. Figure 8. Santa Watershed 8-10°S 79-77°W. Source: L. Mourre et al., 2015.
.
Instituto Geofísico del Perú (IGP), 2005.a: Atlas climático de precipitación y
temperatura del aire en la cuenca del río Mantaro. Vol I, Fondo Editorial
CONAM. Lima, Perú
Mourre, L; Condom, T; Junquas, C; Lebel, T; Sicart, JE; Figueroa, R;
Cochachin, A. 2015. Hydrology Earth System Sciences 12: 6635–6681.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M.,
Duda, M. G., et al. (2008). Mesoescale and Microscale Meteorology
Division, National Center for Atmospheric Research: Boulder,CO.
Experiments 27km 9km 3km
CONTROL 284 154 125
CU_BMJ 381 190 133
CU_KF 268 134 30
MP_LP 198 83 52
PBL_MYJ 262 129 111
LS_NMP 294 168 141
Table 2. Bias (%) with reference to the
observed data of weather stations (blue points
in figure 1).
• The MP_LP experiment demonstrates a 58% reduction
of the precipitation BIAS with respect to the control.Figure 6. Cross section over the Mantaro basin. In
latitude -12°S and longitudes from -76°W to -75°W.
Reductionof Bias (%)