This study evaluates the high-resolution climate simulation system CESM/WRF composed of the global climate model, Community Earth System Model (CESM) version 1, and the mesoscale model, Weather Research and Forecasting Model (WRF), for simulating high-resolution climatological temperature and precipitation in the tropics with complex terrain where temperature and precipitation are strongly inhomogeneous. The CESM/WRF climatological annual and seasonal precipitation and temperature simulations for years 1980–1999 at 10 km resolution for Sumatra and nearby regions are evaluated using observations and the global climate reanalysis ERA-Interim (ERA). CESM/WRF simulations at 10 km resolution are also compared with the downscaled reanalysis ERA/WRF at 10 km resolution. Results show that while temperature and precipitation patterns of the original CESM are very different from observations, those for CESM/WRF agree well with observations. Resolution and accuracies of simulations are significantly improved by dynamically downscaling CESM using WRF. CESM/WRF can simulate locations of very cold temperature at mountain peaks well. The high-resolution climate simulation system CESM/WRF can provide useful climate simulations at high resolution for Sumatra and nearby regions. CESM/WRF-simulated climatological temperature and precipitation at 10 km resolution agree well with ERA/WRF. This suggests the use of CESM/WRF for climate projections at high resolution for Sumatra and nearby regions.
Climate change is an important threat to humanity. The global average temperature has been rising and has been projected to increase up to 2–5°C by the end of the twenty-first century [
To obtain climate simulations and projections, global climate models (GCMs), which model physical processes of atmosphere, ocean, land surface, and cryosphere by taking into the account of different scenarios of increasing greenhouse gases, can be employed [
Indonesia’s Sumatra Island is in the tropics with the equator running through it and is one of the rainiest areas on Earth. Weather-related disasters, i.e., floods, landslides, and severe storms often affect Sumatra. Since Sumatra has complex terrain with high mountains and volcanoes and temperature and precipitation are very inhomogeneous, numerical systems for simulating and projecting climate at high resolution are required for appropriately adapting to climate change and reducing climate change impacts. Although there are some previous climate simulation studies for Southeast Asia [
High-resolution climate simulations and projections can be obtained by dynamically downscaling GCM outputs using a mesoscale model [
The Community Earth System Model (CESM) version 1 [
The numerical climate simulation system employed in this study is composed of CESM and WRF and is called CESM/WRF. Although the preliminary study [
Several climate simulation studies [
Observations for temperature and precipitation at 10 km resolution or better for the 20-year period of 1980–1999 and dense ground stations in Sumatra do not exist [
Section
Figure
(a) Coverages of WRF’s 2 co-centered domains employed in this study. (b) Topography (m) above mean sea level of the WRF's inner domain
The climate of Sumatra is tropical with hot and humid weather. There are 2 major seasons, including the rainy season approximately from October to April of each year and the dry season approximately from May to September of each year. Sumatra has significant precipitation amount throughout the year. Precipitation is mostly convective and varies greatly from area to area. Intense convective precipitation could lead to landslides and floods. Sumatra has often been affected by floods, landslides, and severe storms. High-resolution numerical climate simulations and projections are hence important for better understanding of climate change and its potential impacts for Sumatra.
Four observation datasets including the University of Delaware Air Temperature and Precipitation version 3.01 (UD) [
UD monthly global gridded data for air temperature and precipitation are available from 1900 to 2010 and are produced using data both from the Global Historical Climate Network and the archive of Legates and Willmott. CRU monthly global gridded data for air temperature and precipitation are available from 1901 to 2009 and are produced using daily or subdaily data by National Meteorological Services and other external agents. GPCC monthly global gridded precipitation data are available from 1901 to present and are produced using quality-controlled data from 67,200 global stations. CPC daily global gridded precipitation data are available from 1979 to present and are produced using quality-controlled gauge reports from over 30,000 global stations with consideration of orographic effects. UD, CRU, GPCC, and CPC are available only over land and are on regular 0.5° grids.
ERA reanalysis is produced using the four-dimensional variational analysis (4D-Var) system that relies on both observations and model-based forecasts and is available from 1979 to present. ERA is available for both land and sea and is on a regular 0.75° grid with 60 vertical levels from the surface up to 0.1 mb. ERA outputs are available every 6 h, i.e., 00, 06, 12, and 18Z and can be used as initial and boundary conditions for WRF. ERA precipitation is computed using accumulated precipitation available every 12 h. This study treats ERA reanalysis data as observations.
The numerical climate simulation system used in this study is composed of the global climate model Community Earth System Model (CESM) version 1 [
WRF has been widely employed for research and operations. There are several WRF versions. This study employs WRF with the Advanced Research WRF core version 3.7.1. WRF’s initial and boundary conditions are CESM outputs. Figure
Several WRF physics options are available. Surussavadee and Aonchart [
Sumatra’s climate for 20 y covering 1980–1999 is simulated by CESM/WRF. Two separate WRF integrations for each decade are used in order to optimize computational resources and time. The spin up time of 1 y is employed. CESM/WRF outputs from the inner domain at 10 km resolution are employed in this study. Since CESM/WRF outputs are at 10 km resolution, whereas all observation datasets, i.e., CPC, CRU, GPCC, and UD are at 0.5° resolution and the ERA reanalysis is at 0.75° resolution, to generate CESM/WRF simulations at a resolution comparable to those of observations and reanalysis; CESM/WRF simulations at 10 km resolution are convolved with a Gaussian function having full width at half maximum (FWHM) of 50 km before they are evaluated. All observations and reanalysis are bilinearly interpolated on the grid of the CESM/WRF inner domain. The simulation performances of CESM and CESM/WRF are evaluated using the performance metrics, including root-mean-squared errors (RMSEs), mean errors (MEs), which is
The ERA-Interim global atmospheric reanalysis dataset (ERA) [
Figure
Comparisons of 20-y average temperature (°C) simulated by CESM and CESM/WRF with CRU, UD, and ERA and the average of CRU, UD, and ERA. CESM and ERA are at 1° and 0.75° resolutions, respectively. CRU and UD are at 0.5° resolution. CESM/WRF is at 50 km resolution.
Simulated temperature of the original CESM and CESM/WRF is very different for both pattern and intensity. CESM’s temperature over sea is obviously higher than all observations and CESM/WRF. CESM’s temperature over land is also very different from all observations and CESM/WRF. CESM/WRF agrees with observations much better than CESM does, while CESM obviously cannot resolve temperature for high mountains along the west coasts of Sumatra and Java islands; CESM/WRF does it well. CESM/WRF can also simulate cold spots over mountain peaks well. The locations of CESM/WRF’s cold spots agree well with those of UD. CESM/WRF’s temperature over sea is obviously improved over that of CESM. Downscaling CESM using WRF significantly improves the simulated climatological temperature for both land and sea.
Figure
Scatter plots comparing CESM and CESM/WRF simulations with the average of CRU, UD, and ERA for (a) annual average temperature (°C) for 20 y and (b) 20-y average temperature (°C). CESM and ERA are at 1° and 0.75° resolutions, respectively. CRU and UD are at 0.5° resolution. CESM/WRF is at 50 km resolution.
Table
RMSEs, MEs (
Metric | CESM | CESM/WRF | ||||
---|---|---|---|---|---|---|
Land | Sea | All | Land | Sea | All | |
RMSE | 1.49 | 1.74 | 1.69 |
|
|
|
ME |
|
−1.51 | −1.18 | 0.23 |
|
|
CC | 0.31 |
|
0.62 |
|
0.23 |
|
Boldface highlights the model performing best for each performance metric.
RMSEs, MEs (
Metric | CESM | CESM/WRF | ||||
---|---|---|---|---|---|---|
Land | Sea | All | Land | Sea | All | |
RMSE | 1.45 | 1.67 | 1.62 |
|
|
|
ME |
|
−1.51 | −1.18 | 0.23 |
|
|
CC | 0.32 | 0.39 | 0.66 |
|
|
|
Boldface highlights the model performing best for each performance metric.
Climatological temperatures simulated by CESM/WRF and ERA/WRF at 10 km resolution are compared in this section. Figure
Comparisons of CESM/WRF and ERA/WRF 20-y average temperature (°C). Both CESM/WRF and ERA/WRF are at 10 km resolution.
Figure
Scatter plots comparing CESM/WRF and ERA/WRF for (a) annual average temperature (°C) for 20 y and (b) 20-y average temperature (°C). Both CESM/WRF and ERA/WRF are at 10 km resolution.
Table
RMSDs, MDs (
Metric | Annual average temperature for 20 y | 20 y average temperature | ||||
---|---|---|---|---|---|---|
Land | Sea | All | Land | Sea | All | |
RMSD | 0.35 | 0.47 | 0.44 | 0.11 | 0.10 | 0.11 |
MD | 0.06 | 0.01 | 0.02 | 0.06 | 0.01 | 0.02 |
CC | 0.99 | 0.34 | 0.97 | 1.00 | 0.92 | 1.00 |
The accuracies of CESM- and CESM/WRF-simulated climatological precipitation are evaluated using observations and reanalysis. CESM/WRF in this section is the original 10 km resolution CESM/WRF convolved with a Gaussian function having full width at half maximum (FWHM) of 50 km. Figure
Comparisons of 20-y average annual precipitation (mm/y) simulated by CESM and CESM/WRF with CPC, CRU, GPCC, UD, and ERA and the average of CPC, CRU, GPCC, UD, and ERA. CESM and ERA are at 1° and 0.75° resolutions, respectively. CPC, CRU, GPCC, and UD are at 0.5° resolution. CESM/WRF is at 50 km resolution.
Comparison of the observation and reanalysis datasets shows some differences due to the sources and methods employed for different datasets and their spatial resolutions. Comparison of observations over Malaysia shows that CRU has high precipitation at the center of Malaysia and surrounding areas, CPC has high precipitation along the east coast, GPCC and UD have high precipitation along the east and west coasts, and ERA has high precipitation along the west coast. Only ERA has precipitation data over the sea. Three main precipitation patterns consistent with most observation datasets include: (1) high precipitation over land along the west coasts of Sumatra and Java islands and lower precipitation over land along the east coasts, (2) high precipitation over the Indian Ocean to the west of Sumatra, and (3) low precipitation over the Pacific Ocean to the east of Sumatra and Malaysia.
The 20-y average annual precipitation simulated by CESM contradicts the observations and does not have any of the 3 main precipitation patterns shown in observations. CESM has high precipitation over land in northwest Sumatra, all regions of Malaysia, southeast Sumatra, and along the east coast of Java. CESM has low precipitation over the Indian Ocean to the west of Sumatra and high precipitation over the Pacific Ocean to the east of Sumatra and Malaysia.
The pattern, intensity, and spatial resolution of 20-y average annual precipitation simulated by CESM and CESM/WRF are very different. The resolution and accuracies of simulated precipitation are significantly improved by the dynamically downscaling method employed in this study. CESM/WRF can simulate the 3 main precipitation patterns shown in the observations well. Its high precipitation at the center of Malaysia and surrounding areas is also consistent with that of CRU. The main difference between CESM/WRF and observations is the higher precipitation amount of CESM/WRF over high mountains along the west coasts of Sumatra and Java islands. This could be due to (1) the significantly higher resolution of CESM/WRF compared to those of all observations, (2) errors in CESM, and (3) errors in WRF physics.
Figure
Comparisons of 20-y average seasonal precipitation for the rainy season (mm/season) simulated by CESM and CESM/WRF with CPC, CRU, GPCC, UD, and ERA and the average of CPC, CRU, GPCC, UD, and ERA. CESM and ERA are at 1° and 0.75° resolutions, respectively. CPC, CRU, GPCC, and UD are at 0.5° resolution. CESM/WRF is at 50 km resolution.
Comparisons of 20-y average seasonal precipitation for the dry season (mm/season) simulated by CESM and CESM/WRF with CPC, CRU, GPCC, UD, ERA, and the average of CPC, CRU, GPCC, UD, and ERA. CESM and ERA are at 1° and 0.75° resolutions, respectively. CPC, CRU, GPCC, and UD are at 0.5° resolution. CESM/WRF is at 50 km resolution.
The annual precipitation (mm/y) for individual years from 1980 to 1999 simulated by CESM and CESM/WRF is compared with the average of all five observation datasets using scatter plots in Figure
Scatter plots comparing CESM and CESM/WRF simulations with the average of CPC, CRU, GPCC, UD, and ERA for (a) annual precipitation (mm/y) for 20 y and (b) 20-y average annual precipitation (mm/y). CESM/WRF is at 50 km resolution.
The 20-y average annual precipitation (mm/y) simulated by CESM and CESM/WRF is compared with the average of all five observation datasets in Figure
Tables
RMSEs, MEs (
Metric | CESM | CESM/WRF | ||||
---|---|---|---|---|---|---|
Land | Sea | All | Land | Sea | All | |
RMSE |
|
990.53 | 922.32 | 1,061.87 |
|
|
ME |
|
371.76 | 257.78 | −341.19 |
|
|
CC | −0.02 | −0.14 | −0.14 |
|
|
|
Boldface highlights the model performing best for each performance metric.
RMSEs, MEs (
Metric | CESM | CESM/WRF | ||||
---|---|---|---|---|---|---|
Land | Sea | All | Land | Sea | All | |
RMSE |
|
792.57 | 728.92 | 940.19 |
|
|
ME |
|
371.76 | 257.78 | −341.19 |
|
|
CC | −0.29 | −0.36 | −0.38 |
|
|
|
Boldface highlights the model performing best for each performance metric.
CESM/WRF-simulated climatological precipitation at 10 km resolution is compared with ERA/WRF at 10 km resolution. Top to bottom rows of Figure
Top to bottom: comparisons of CESM/WRF and ERA/WRF for 20-y average annual precipitation (mm/y) and 20-y average seasonal precipitation (mm/season) for the rainy and dry seasons, respectively. Both CESM/WRF and ERA/WRF are at 10 km resolution.
The scatter plots in Figure
Scatter plots comparing CESM/WRF and ERA/WRF for (a) annual precipitation (mm/y) for 20 y and (b) 20-y average annual precipitation (mm/y). Both CESM/WRF and ERA/WRF are at 10 km resolution.
The scatter plots in Figure
Scatter plots comparing CESM/WRF and ERA/WRF seasonal precipitation for 20 y (mm/season; left column) and 20-y average seasonal precipitation (mm/season; right column) for (a) rainy and (b) dry seasons. Both CESM/WRF and ERA/WRF are at 10 km resolution.
Table
RMSDs, MDs (
Metric | Precipitation for 20 y | 20 y average precipitation | ||||
---|---|---|---|---|---|---|
Annual | Rain season | Dry season | Annual | Rain season | Dry season | |
RMSD | 846.71 (36.41) | 627.55 (39.54) | 606.12 (58.61) | 419.08 (18.02) | 271.03 (17.08) | 257.93 (24.94) |
MD | −304.58 (−13.10) | −163.79 (−10.32) | −197.10 (−19.06) | −304.58 (−13.10) | −163.79 (−10.32) | −197.10 (−19.06) |
CC | 0.73 | 0.71 | 0.62 | 0.95 | 0.96 | 0.95 |
RMSDs and MDs in the brackets are in percentages of the mean of ERA/WRF.
The performance of a high-resolution climate simulation system CESM/WRF developed to be used for Sumatra and nearby regions is evaluated. CESM/WRF is composed of a mesoscale model WRF and outputs from the global climate model CESM used for initial and boundary conditions. CESM/WRF-simulated temperature and precipitation at 10 km resolution for Sumatra and nearby regions from 1980 to 1999 are evaluated using 4 observation datasets, including CPC, CRU, GPCC, UD, and the ERA reanalysis dataset treated in this study as an observation dataset. Since all observations have resolutions lower than 10 km and dense ground stations in Sumatra do not exist, the CESM/ WRF-simulated climatological temperature and precipitation at 10 km resolution are compared with the downscaled reanalysis ERA/WRF at 10 km resolution.
Although different observation datasets have some differences among themselves for both climatological temperature and precipitation, there are patterns consistent for most observation datasets. While CESM contradicts all observation patterns for both temperature and precipitation, CESM/WRF can simulate all patterns well; CESM/WRF can simulate all patterns well. CESM/WRF can also resolve locations of very cold temperature at mountain peaks consistent with those of UD. Downscaling CESM using WRF significantly improves resolution and accuracies of the simulations. The main discrepancy between CESM/WRF-simulated precipitation and observations is CESM/WRF’s higher precipitation over high mountains along the west coasts of Sumatra and Java islands and could be due to the significantly lower resolutions of observations, errors in CESM outputs, and errors in WRF physics.
Comparisons of CESM/WRF- and ERA/WRF-simulated climatological temperature and precipitation at 10 km resolution show that CESM/WRF simulations agree very well with ERA/WRF and there is no precipitation discrepancy over high mountains along the west coasts of Sumatra and Java islands. The high-resolution climate simulation system CESM/WRF developed in this study can provide useful simulated climatological temperature and precipitation for Sumatra and nearby regions. The good agreement between CESM/WRF and ERA/WRF also gains the confidence of employing CESM/WRF for climate projections for Sumatra and nearby regions.
The WRF model, CESM outputs, observations, and reanalysis employed in this study are publicly available.
The authors declare that they have no conflicts of interest.
This study was supported by the Interdisciplinary Graduate School of Earth System Science and Andaman Natural Disaster Management of the Prince of Songkla University, Phuket Campus, Thailand.