Climate model systematic biases in the Maritime Continent

Email: y.y.toh@pgr.reading.ac.uk

The Maritime Continent commonly refers to the groups of islands of Indonesia, Borneo, New Guinea and the surrounding seas in the literature. My study area covers the Maritime Continent domain from 20°S to 20°N and 80°E to 160°E as shown in Figure 1. This includes Indonesia, Malaysia, Brunei, Singapore, Philippines, Papua New Guinea, Solomon islands, northern Australia and parts of mainland Southeast Asia including Thailand, Laos, Cambodia, Vietnam and Myanmar.

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Figure 1: JJA precipitation (mm/day) and 850 hPa wind (m s−1) for (a) GPCP and ERA-interim, (b) MMM biases and (c)–(j) AMIP biases for 1979–2008 over the Maritime Continent region (20°S–20ºN, 80°E–160ºE). Third panel shows the Maritime Continent domain and land-sea mask

The ability of climate model to simulate the mean climate and climate variability over the Maritime Continent remains a modelling challenge (Jourdain et al. 2013). Our study examines the fidelity of Coupled Model Intercomparison Project phase 5 (CMIP5) models at simulating mean climate over the Maritime Continent. We find that there is a considerable spread in the performance of the Atmospheric Model Intercomparison Project (AMIP) models in reproducing the seasonal mean climate and annual cycle over the Maritime Continent region. The multi-model mean (MMM) (Figure 1b) JJA precipitation and 850hPa wind biases with respect to observations (Figure 1a) are small compared to individual model biases (Figure 1c-j) over the Maritime Continent. Figure 1 shows only a subset of Fig. 2 from Toh et al. (2017), for the full figure and paper please click here.

We also investigate the model characteristics that may be potential sources of bias. We find that AMIP model performance is largely unrelated to model horizontal resolution. Instead, a model’s local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon.

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Figure 2: Latitude-time plot of precipitation zonally averaged between 80°E and 160°E for (a) GPCP, (b) Cluster I and (c) Cluster II. White dashed line shows the position of the maximum precipitation each month. Precipitation biases with respect to GPCP for (d) Cluster I and (e) Cluster II.

To characterize model systematic biases in the AMIP runs and determine if these biases are related to common factors elsewhere in the tropics, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I (Figure 2b,d) is able to reproduce the observed seasonal migration of Maritime Continent precipitation, but it overestimates the precipitation, especially during the JJA and SON seasons. Cluster II (Figure 2c,e) simulate weaker seasonal migration of Intertropical Convergence Zone (ITCZ) than observed, and the maximum rainfall position stays closer to the equator throughout the year. Tropics-wide properties of clusters also demonstrate a connection between errors at regional scale of the Maritime Continent and errors at large scale circulation and global monsoon.

On the other hand, comparison with coupled models showed that air-sea coupling yielded complex impacts on Maritime Continent precipitation biases. One of the outstanding problems in the coupled CMIP5 models is the sea surface temperature (SST) biases in tropical ocean basins. Our study highlighted central Pacific and western Indian Oceans as the key regions which exhibit the most surface temperature correlation with Maritime Continent mean state precipitation in the coupled CMIP5 models. Future work will investigate the impact of SST perturbations in these two regions on Maritime Continent precipitation using Atmospheric General Circulation Model (AGCM) sensitivity experiments.

 

 

References:

Jourdain N.C., Gupta A.S., Taschetto A.S., Ummenhofer C.C., Moise A.F., Ashok K. (2013) The Indo-Australian monsoon and its relationship to ENSO and IOD in reanalysis data and the CMIP3/CMIP5 simulations. Climate Dynamics. 41(11–12):3073–3102

Toh, Y.Y., Turner, A.G., Johnson, S.J., & Holloway, C.E. (2017). Maritime Continent seasonal climate biases in AMIP experiments of the CMIP5 multimodel ensemble. Climate Dynamics. doi: 10.1007/s00382-017-3641-x

The effect of local topography on severe tropical convective rainfall development.

Email: m.f.f.b.mohdnor@pgr.reading.ac.uk

The occurrence of severe convective rainfall is common over the tropical rainforest region. While the basic mechanism of the development of severe convective rainfall over the tropics is well understood in previous studies, the effect of local topography may yield a unique development process.

One part of my PhD project is to look at how local topography modifies severe rainfall events over the western Peninsular Malaysia. This was examined via a case study of severe rainfall that took place on 2nd May 2012. On that day, heavy rainfall caused flash floods and landslides over Klang Valley (red box in Fig. 1). Although the total rainfall on the 2nd May was above the Apr-May average, it was not extremely high.

fig1_geography_malaysia

Fig. 1. The study area, specifically over the western Peninsular Malaysia. The red box is Klang valley area.

Looking at observational data was not enough to understand the processes involved in the development of severe rainfall event on 2nd May 2012 and therefore a simulation study was conducted using the UK Met Office Unified Model (1.5km horizontal resolution).

One theory which could explain  the rainfall event on 2nd May 2012 is the influence of a series of rainfall events that developed earlier. There were rainfall events over the Peninsular Malaysia and Sumatra Island in the early evening of 1st May 2012 along the Titiwangsa mountains (Peninsular Malaysia) and Barisan Mountains (Sumatra Island). These rainfall events influenced the development of rainfall over the Malacca Strait overnight. The rainfall event over the strait strengthened by the morning of 2nd May. In the afternoon of 2nd May, the western peninsula had the right atmospheric conditions to develop convective rainfall, and the rainfall over the strait influenced the intensification of rainfall over the western peninsula. Thus, we believe that the local topography has a large impact on the development of the 2nd May rainfall event.

So, how do we test the hypothesis? One way is to perform sensitivity experiments. Four sensitivity experiments were conducted, modifying the orography of both the peninsula and Sumatra, and removing Sumatra altogether (Fig. 2).

fig2_experiments_all

Fig. 2. Sensitivity experiments on the local orography and Sumatra Island. Control run on the first panel, flatPM (flat peninsula to sea level), flatSI (flat Sumatra), flatALL(both peninsula and Sumatra are flat), and noSI (Sumatra is removed)

The results show that orography influenced and modified the development of late evening rainfall over both landmasses on both days. On 2nd May, total rainfall in the experiments are as follows:
1. flatPM : Klang valley received less rainfall than control,
2. flatSI : Klang valley received less rainfall than control but more than flatPM,
3. flatALL : Klang valley received more rainfall than control, flatPM and flatSI experiments,
4. noSI : Klang valley received triple the amount of rainfall of the control and other experiments.
These results hint the complex relationship between local topography and rainfall. Moreover, both the peninsula and Sumatra are important for the development of the morning rainfall over the Malacca Strait, regardless of the orographic variability.

Whilst looking at one case study is not enough to draw a general conclusion, this will definitely be a step forward on broadening the information that we already have. A more robust conclusion would require further studies to be taken.

(This PhD project is supervised by Pete Inness and Christopher Holloway, and funded by MARA Malaysia).