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- Author or Editor: Xiang-Yu Huang x
- Years of the Maritime Continent x
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Abstract
Biases in simulating the diurnal cycle of convection near the western coast of the island of Sumatra have been investigated using the data from the pilot field campaign of the Years of the Maritime Continent (pre-YMC). The campaign was carried out at a sea [Research Vessel (R/V) Mirai] and a land (Bengkulu, Sumatra) site. Simulations are performed using a tropical configuration of the Met Office model at a grid resolution of 1.5 km in a limited-area mode. The focus of this study is to understand how biases in the input conditions from ECMWF high-resolution deterministic forecast affect the diurnal cycle. Modeled precipitation is found to be delayed and weak, with cold SST bias in the model as the key contributing factor affecting convection at both sites. Colder SST causes a delay in the trigger of convection at Bengkulu by delaying the onset of the local land breeze, which in turn delays the local convergence. The cold outflow from precipitation over the adjacent mountain is also found to be delayed in the model, contributing to the total delay. This delay in the evening convection at Bengkulu is shown to directly affect the timing of nighttime convection at Mirai. Weaker convection at Bengkulu is argued to be due to lower-tropospheric dry humidity bias in the model initial condition. Convection at Mirai is shown to be caused by the convergence of the cold outflow from Bengkulu with the prevailing landward wind over the sea. Both thermodynamic and dynamic conditions near the cold outflow front are found to be less favorable for intense convection in the simulation, the reason for which is argued to be a combination of the cold SST bias and a weaker cold outflow.
Abstract
Biases in simulating the diurnal cycle of convection near the western coast of the island of Sumatra have been investigated using the data from the pilot field campaign of the Years of the Maritime Continent (pre-YMC). The campaign was carried out at a sea [Research Vessel (R/V) Mirai] and a land (Bengkulu, Sumatra) site. Simulations are performed using a tropical configuration of the Met Office model at a grid resolution of 1.5 km in a limited-area mode. The focus of this study is to understand how biases in the input conditions from ECMWF high-resolution deterministic forecast affect the diurnal cycle. Modeled precipitation is found to be delayed and weak, with cold SST bias in the model as the key contributing factor affecting convection at both sites. Colder SST causes a delay in the trigger of convection at Bengkulu by delaying the onset of the local land breeze, which in turn delays the local convergence. The cold outflow from precipitation over the adjacent mountain is also found to be delayed in the model, contributing to the total delay. This delay in the evening convection at Bengkulu is shown to directly affect the timing of nighttime convection at Mirai. Weaker convection at Bengkulu is argued to be due to lower-tropospheric dry humidity bias in the model initial condition. Convection at Mirai is shown to be caused by the convergence of the cold outflow from Bengkulu with the prevailing landward wind over the sea. Both thermodynamic and dynamic conditions near the cold outflow front are found to be less favorable for intense convection in the simulation, the reason for which is argued to be a combination of the cold SST bias and a weaker cold outflow.
Abstract
The diurnal cycle is the most prominent mode of rainfall variability in the tropics, governed mainly by the strong solar heating and land–sea interactions that trigger convection. Over the western Maritime Continent, complex orographic and coastal effects can also play an important role. Weather and climate models often struggle to represent these physical processes, resulting in substantial model biases in simulations over the region. For numerical weather prediction, these biases manifest themselves in the initial conditions, leading to phase and amplitude errors in the diurnal cycle of precipitation. Using a tropical convective-scale data assimilation system, we assimilate 3-hourly radiosonde data from the pilot field campaign of the Years of Maritime Continent, in addition to existing available observations, to diagnose the model biases and assess the relative impacts of the additional wind, temperature, and moisture information on the simulated diurnal cycle of precipitation over the western coast of Sumatra. We show how assimilating such high-frequency in situ observations can improve the simulated diurnal cycle, verified against satellite-derived precipitation, radar-derived precipitation, and rain gauge data. The improvements are due to a better representation of the sea breeze and increased available moisture in the lowest 4 km prior to peak convection. Assimilating wind information alone was sufficient to improve the simulations. We also highlight how during the assimilation, certain multivariate background error constraints and moisture addition in an ad hoc manner can negatively impact the simulations. Other approaches should be explored to better exploit information from such high-frequency observations over this region.
Abstract
The diurnal cycle is the most prominent mode of rainfall variability in the tropics, governed mainly by the strong solar heating and land–sea interactions that trigger convection. Over the western Maritime Continent, complex orographic and coastal effects can also play an important role. Weather and climate models often struggle to represent these physical processes, resulting in substantial model biases in simulations over the region. For numerical weather prediction, these biases manifest themselves in the initial conditions, leading to phase and amplitude errors in the diurnal cycle of precipitation. Using a tropical convective-scale data assimilation system, we assimilate 3-hourly radiosonde data from the pilot field campaign of the Years of Maritime Continent, in addition to existing available observations, to diagnose the model biases and assess the relative impacts of the additional wind, temperature, and moisture information on the simulated diurnal cycle of precipitation over the western coast of Sumatra. We show how assimilating such high-frequency in situ observations can improve the simulated diurnal cycle, verified against satellite-derived precipitation, radar-derived precipitation, and rain gauge data. The improvements are due to a better representation of the sea breeze and increased available moisture in the lowest 4 km prior to peak convection. Assimilating wind information alone was sufficient to improve the simulations. We also highlight how during the assimilation, certain multivariate background error constraints and moisture addition in an ad hoc manner can negatively impact the simulations. Other approaches should be explored to better exploit information from such high-frequency observations over this region.
