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: jesusgarciabio@gmail.com

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 (%)