Climate Dynamics

, Volume 47, Issue 3–4, pp 1143–1159 | Cite as

Precipitation over urban areas in the western Maritime Continent using a convection-permitting model

  • Daniel Argüeso
  • Alejandro Di Luca
  • Jason P. Evans


This study investigates the effects of urban areas on precipitation in the western Maritime Continent using a convection-permitting regional atmospheric model. The Weather Research and Forecasting model was used to simulate the atmosphere at a range of spatial resolutions using a multiple nesting approach. Two experiments (with and without urban areas) were completed over a 5-year period (2008–2012) each to estimate the contribution of cities to changes in local circulation. At first, the model is evaluated against two satellite-derived precipitation products and the benefit of using a very high-resolution model (2-km grid spacing) over a region where rainfall is dominated by convective processes is demonstrated, particularly in terms of its diurnal cycle phase and amplitude. The influence of cities on precipitation characteristics is quantified for two major urban nuclei in the region (Jakarta and Kuala Lumpur) and results indicate that their presence locally enhances precipitation by over 30 %. This increase is mainly due to an intensification of the diurnal cycle. We analyse the impact on temperature, humidity and wind to put forward physical mechanisms that explain such changes. Cities increase near surface temperature, generating instability. They also make land-sea temperature contrasts stronger, which enhances sea breeze circulations. Together, they increase near-surface moisture flux convergence and favour convective processes leading to an overall increase of precipitation over urban areas. The diurnal cycle of these effects is reflected in the atmospheric footprint of cities on variables such as humidity and cloud mixing ratio and accompanies changes in precipitation.


Regional climate modelling Precipitation Maritime Continent Urban climate Convection Convection-permitting models 



This work was made possible by funding from the Australian Research Council (ARC) as part of the Centre of Excellence for Climate System Science (CE110001028), as well as the NSW Office of Environment and Heritage. Jason Evans was supported by the Australian Research Council Future Fellowship FT110100576. This work was supported by an award under the Merit Allocation Scheme on the NCI National Facility at the ANU. We are thankful to the European Centre for Medium-Range Weather Forecasts for providing ERA-Interim data. We also thank Dr. Thomas Chubb from Monash University (Australia) for making the Skew-T code publicly available.

Supplementary material

382_2015_2893_MOESM1_ESM.png (605 kb)
Supplementary material 1 (PNG 604 kb)
382_2015_2893_MOESM2_ESM.png (539 kb)
Supplementary material 2 (PNG 539 kb)
382_2015_2893_MOESM3_ESM.png (238 kb)
Supplementary material 3 (PNG 238 kb)
382_2015_2893_MOESM4_ESM.png (695 kb)
Supplementary material 4 (PNG 695 kb)
382_2015_2893_MOESM5_ESM.png (806 kb)
Supplementary material 5 (PNG 806 kb)


  1. Ackerman B, Changnon SA Jr, Dzurisin G et al (1978) Summary of METROMEX, volume 2: causes of precipitation anomalies. Bulletin 63. Illinois State Water Survey, UrbanaGoogle Scholar
  2. Argüeso D, Evans JP, Fita L, Bormann KJ (2014) Temperature response to future urbanization and climate change. Clim Dyn 42:2183–2199. doi: 10.1007/s00382-013-1789-6 CrossRefGoogle Scholar
  3. Argüeso D, Evans JP, Pitman AJ, Di Luca A (2015) Effects of city expansion on heat stress under climate change conditions. PLoS ONE 10:e0117066. doi: 10.1371/journal.pone.0117066 CrossRefGoogle Scholar
  4. Atkinson BW (1971) The effect of an urban area on the precipitation from a moving thunderstorm. J Appl Meteorol 10:47–55CrossRefGoogle Scholar
  5. Banacos PC, Schultz DM (2005) The use of moisture flux convergence in forecasting convective initiation: historical and operational perspectives. Weather Forecast 20:351–366. doi: 10.1175/WAF858.1 CrossRefGoogle Scholar
  6. Bluestein HB (1992) Synoptic-dynamic meteorology in midlatitudes. Oxford University Press, OxfordGoogle Scholar
  7. Changnon SA Jr (1968) The La Porte weather anomaly—fact or fiction? Bull Am Meteorol Soc 49:4–11Google Scholar
  8. Chen F, Kusaka H, Bornstein R et al (2011) The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems. Int J Climatol 31:273–288. doi: 10.1002/joc.2158 CrossRefGoogle Scholar
  9. Childs PP, Raman S (2005) Observations and numerical simulations of urban heat island and sea breeze circulations over New York City. Pure appl Geophys 162:1955–1980. doi: 10.1007/s00024-005-2700-0 CrossRefGoogle Scholar
  10. Cleugh H, Grimmond CSB (2011) Chapter 3—urban climates and global climate change, 2nd edition. The future of the world’s climate, pp 47–76. doi: 10.1016/B978-0-12-386917-3.00003-8
  11. Comarazamy DE, González JE, Luvall JC et al (2010) A land-atmospheric interaction study in the coastal tropical city of San Juan, Puerto Rico. Earth Interact 14:1–24. doi: 10.1175/2010EI309.1 CrossRefGoogle Scholar
  12. Dee DP, Uppala SM, Simmons AJ et al (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. QJR Meteorol Soc 137:553–597. doi: 10.1002/qj.828 CrossRefGoogle Scholar
  13. Di Luca A, de Elía R, Laprise R (2015) Challenges in the quest for added value of regional climate dynamical downscaling. Curr Clim Change Rep 1(1):10–21. doi: 10.1007/s40641-015-0003-9 CrossRefGoogle Scholar
  14. Ebert EE, Janowiak JE, Kidd C (2007) Comparison of near-real-time precipitation estimates from satellite observations and numerical models. Bull Am Meteorol Soc 88:47–64. doi: 10.1175/BAMS-88-1-47 CrossRefGoogle Scholar
  15. Evans JP, Bormann K, Katzfey J, Dean S, Arritt RW (2015) Regional climate model projections of the South Pacific Convergence Zone. Clim Dyn. doi: 10.1007/s00382-015-2873-x
  16. Ganeshan M, Murtugudde R, Imhoff ML (2013) A multi-city analysis of the UHI-influence on warm season rainfall. Urban Clim. doi: 10.1016/j.uclim.2013.09.004 Google Scholar
  17. Gianotti RL, Zhang D, Eltahir EAB (2012) Assessment of the regional climate model version 3 over the Maritime Continent using different cumulus parameterization and land surface schemes. J Clim 25:638–656. doi: 10.1175/JCLI-D-11-00025.1 CrossRefGoogle Scholar
  18. Han J-Y, Baik J-J, Lee H (2014) Urban impacts on precipitation. Asia Pacific J Atmos Sci 50:17–30. doi: 10.1007/s13143-014-0016-7 CrossRefGoogle Scholar
  19. Haylock M, McBride J (2001) Spatial coherence and predictability of Indonesian wet season rainfall. J Clim 14:3882–3887CrossRefGoogle Scholar
  20. Hirpa FA, Gebremichael M, Hopson T (2010) Evaluation of high-resolution satellite precipitation products over very complex terrain in Ethiopia. J Appl Meteorol Climatol 49:1044–1051. doi: 10.1175/2009JAMC2298.1 CrossRefGoogle Scholar
  21. Holloway CE, Woolnough SJ, Lister GMS (2012) Precipitation distributions for explicit versus parametrized convection in a large-domain high-resolution tropical case study. QJR Meteorol Soc 138:1692–1708. doi: 10.1002/qj.1903 CrossRefGoogle Scholar
  22. Hong S-Y, Noh Y, Dudhia J (2006) A new vertical diffusion package with explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341. doi: 10.1175/MWR3199.1 CrossRefGoogle Scholar
  23. Huffman GJ, Bolvin DT, Nelkin EJ et al (2007) The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8:38–55. doi: 10.1175/JHM560.1 CrossRefGoogle Scholar
  24. Janowiak JE, Kousky VE, Joyce RJ (2005) Diurnal cycle of precipitation determined from the CMORPH high spatial and temporal resolution global precipitation analyses. J Geophys Res 110:D23105–D23118. doi: 10.1029/2005JD006156 CrossRefGoogle Scholar
  25. Jauregui E, Romales E (1996) Urban effects on convective precipitation in Mexico city. Atmos Environ 30:3383–3389. doi: 10.1016/1352-2310(96)00041-6 CrossRefGoogle Scholar
  26. Jourdain NC, Marchesiello P, Menkes CE et al (2011) Mesoscale simulation of tropical cyclones in the South Pacific: climatology and interannual variability. J Clim 24:3–25. doi: 10.1175/2010JCLI3559.1 CrossRefGoogle Scholar
  27. Joyce RJ, Janowiak JE, Arkin PA (2004) CMORPH: a method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J Hydrometeorol 5:487–503. doi: 10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2 CrossRefGoogle Scholar
  28. Jullien S (2013) Ocean response and feedback to tropical cyclones in the South Pacific: processes and climatology, pp 1–229Google Scholar
  29. Kidd C, Ferraro R, Levizzani V (2010) The fourth international precipitation working group workshop. Bull Am Meteorol Soc 91:1095–1099. doi: 10.1175/2009BAMS2871.1 CrossRefGoogle Scholar
  30. Kusaka H, Kimura F (2004) Coupling a single-layer urban canopy model with a simple atmospheric model: impact on urban heat island simulation for an idealized case. J Meteorol Soc Jpn 82:67–80CrossRefGoogle Scholar
  31. Kusaka H, Kondo H, Kikegawa Y, Kimura F (2001) A simple single-layer urban canopy model for atmospheric models: comparison with multi-layer and slab models. Bound-Layer Meteorol 101:329–358CrossRefGoogle Scholar
  32. Kusaka H, Nawata K, Suzuki-Parker A et al (2014) Mechanism of precipitation increase with urbanization in Tokyo as revealed by ensemble climate simulations. J Appl Meteorol Climatol 53:824–839. doi: 10.1175/JAMC-D-13-065.1 CrossRefGoogle Scholar
  33. Kwan MS, Tangang FT, Juneng L (2013) Present-day regional climate simulation over Malaysia and western Maritime Continent region using PRECIS forced with ERA40 reanalysis. Theor Appl Climatol 115:1–14. doi: 10.1007/s00704-013-0873-5 CrossRefGoogle Scholar
  34. Love BS, Matthews AJ, Lister GMS (2011) The diurnal cycle of precipitation over the Maritime Continent in a high-resolution atmospheric model. QJR Meteorol Soc 137:934–947. doi: 10.1002/qj.809 CrossRefGoogle Scholar
  35. Mesinger F (2008) An essay on the eta cumulus convection (BMJ) scheme, pp 1–7Google Scholar
  36. Mishra V, Ganguly AR, Nijssen B, Lettenmaier DP (2015) Changes in observed climate extremes in global urban areas. Environ Res Lett 10:1–10. doi: 10.1088/1748-9326/10/2/024005 Google Scholar
  37. Neale R, Slingo J (2003) The Maritime Continent and its role in the global climate: a GCM study. J Clim 16:834–848. doi: 10.1175/1520-0442(2003)016<0834:TMCAIR>2.0.CO;2 CrossRefGoogle Scholar
  38. Oke TR (1988) The urban energy balance. Progress Phys Geogr 12:471–508. doi: 10.1177/030913338801200401
  39. Prein AF, Langhans W, Fosser G et al (2015) A review on regional convection-permitting climate modeling: demonstrations, prospects, and challenges. Rev Geophys. doi: 10.1002/(ISSN)1944-9208 Google Scholar
  40. Qian J-H, Robertson AW, Moron V (2010) Interactions among ENSO, the monsoon, and diurnal cycle in rainfall variability over Java, Indonesia. J Atmos Sci 67:3509–3524. doi: 10.1175/2010JAS3348.1 CrossRefGoogle Scholar
  41. Schmid PE, Niyogi D (2013) Impact of city size on precipitation-modifying potential. Geophys Res Lett 40:5263–5267. doi: 10.1002/grl.50656 CrossRefGoogle Scholar
  42. Shepherd JM (2005) A review of current investigations of urban-induced rainfall and recommendations for the future. Earth Interact 9:1–27CrossRefGoogle Scholar
  43. Shepherd JM, Burian SJ (2003) Detection of urban-induced rainfall anomalies in a Major Coastal City. Earth Interact 7:1–17CrossRefGoogle Scholar
  44. Skamarock WC, Klemp JB, Dudhia J et al (2009) A description of the advanced research WRF version 3. NCAR/TN-475 + STR NCAR technical note 125Google Scholar
  45. Tan M, Ibrahim A, Duan Z et al (2015) Evaluation of six high-resolution satellite and ground-based precipitation products over Malaysia. Remote Sens 7:1504–1528. doi: 10.3390/rs70201504 CrossRefGoogle Scholar
  46. Teo C-K, Koh T-Y, Chun-Fung Lo J, Chandra Bhatt B (2011) Principal component analysis of observed and modeled diurnal rainfall in the Maritime Continent. J Clim 24:4662–4675. doi: 10.1175/2011JCLI4047.1 CrossRefGoogle Scholar
  47. Turk FJ, Xian P (2013) An assessment of satellite-based high resolution precipitation datasets for atmospheric composition studies in the Maritime Continent. Atmos Res 122:579–598. doi: 10.1016/j.atmosres.2012.02.017 CrossRefGoogle Scholar
  48. Ulate M, Dudhia J, Zhang C (2014) Sensitivity of the water cycle over the Indian Ocean and Maritime Continent to parameterized physics in a regional model. J Adv Model Earth Syst 6:1095–1120. doi: 10.1002/2014MS000313 CrossRefGoogle Scholar
  49. Vernimmen RRE, Hooijer A, Mamenun et al (2012) Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia. Hydrol Earth Syst Sci 16:133–146. doi: 10.5194/hess-16-133-2012 CrossRefGoogle Scholar
  50. Wang Y, Zhou L, Hamilton K (2007) Effect of convective entrainment/detrainment on the simulation of the tropical precipitation diurnal cycle*. Mon Weather Rev 135:567–585. doi: 10.1175/MWR3308.1 CrossRefGoogle Scholar
  51. Wang Y, Long CN, Leung LR et al (2009) Evaluating regional cloud-permitting simulations of the WRF model for the tropical warm pool international cloud experiment (TWP-ICE), Darwin, 2006. J Geophys Res 114:D21203–D21221. doi: 10.1029/2009JD012729 CrossRefGoogle Scholar
  52. Wang X, Liao J, Zhang J et al (2014) A numeric study of regional climate change induced by urban expansion in the Pearl River Delta, China. J Appl Meteorol Climatol 53:346–362. doi: 10.1175/JAMC-D-13-054.1 CrossRefGoogle Scholar
  53. Yang GY, Slingo J (2001) The diurnal cycle in the tropics. Mon Weather Rev 129:784–801. doi: 10.1175/1520-0493(2001)129<0784:TDCITT>2.0.CO;2 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.ARC Centre of Excellence for Climate System ScienceUniversity of New South WalesSydneyAustralia
  2. 2.Climate Change Research Centre, Level 4, Matthews BuildingUniversity of New South WalesSydneyAustralia

Personalised recommendations