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Overview on Weather forecast and Climate Research in Vietnam

Overview on Weather forecast and Climate Research in Vietnam. Phan Van Tan Hanoi University of Science (HUS) Email: tanpv@vnu.edu.vn. Outline. Brief history of NWP in VN Collaborations and Present status Some recent works and results on Climate Research at our University Some suggestions.

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Overview on Weather forecast and Climate Research in Vietnam

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  1. Overview on Weather forecast and Climate Research in Vietnam Phan Van Tan Hanoi University of Science (HUS) Email: tanpv@vnu.edu.vn

  2. Outline • Brief history of NWP in VN • Collaborations and Present status • Some recent works and results on Climate Research at our University • Some suggestions

  3. Brief history of NWP in VN • Before 2000: • Weather forecast based on mainly synoptic method: Draw weather maps (by hand) using observed data • From 1997: Use forecasts from GSM model (JMA) as additional information • There was no any numerical model run as operational

  4. Brief history of NWP in VN • 2000-2001: • The High resolution Regional Model (HRM) has been obtained from DWD and run at our Meteorological Department (MD), Hanoi University of Science (HUS) • Some sensitivity tests with HRM have been done, such as domain size, physical parameterization schemes (convection, soil moisture, land surface heterogeneity, gridscale precipitation), typhoon forecast, etc

  5. Brief history of NWP in VN • 2002-: • HRM has been used as operational model at Hyrdo-Meteorological Service (HMS) • Our improvement on HRM: • HRM + 3DVAR • HRM + SMA (Soil Moisture Analysis) • HRM-TC: HRM+Tropical Cyclone Bugus Scheme • Now: HRM has been run also at HMS and MD-HUS

  6. Collaborations and Present Status • Hanoi University of Science (HUS) • HydroMeteorological Service (HMS) • Institute of Meteorology, Hydrology and Environment (IMHEN) Ministry of Natural Resources and Environmet VNU, Hanoi HMS HUS IMHEN

  7. Collaborations and Present Status • Models used: • At HUS: • HRM, RAMS, WRF, ETA, MM5: Weather forecast • RegCM, REMO, MM5/BATS: Climate research • At HMS: • HRM (Operational), WRF, BOLAM, ETA: Weather forecast • At IMHEN: • MM5, WRF: Weather forecast • PRECIS: Climate research

  8. Collaborations and Present Status • Climate Change research: • “NATIONAL TARGET PROGRAM TO RESPOND TO CLIMATE CHANGE” (NTP)(The Government Resolution No 60/2007/NQ-CP, Dated 3 Dec. 2007) • General Objectives: “Strategic objectives of the NTP are to assess Climate Change (CC) impacts on sectors and regions in specific periods and to develop feasible action plan to effectively respond to CC in short-term and long-term periods to ensure sustainable development of Viet Nam, to take over opportunities to develop towards a low-carbon economy, and to joint international community’s effort in mitigating CC and protecting the climatic system.” • Established “International Centre for Advanced Research on Global Change (ICARGC)” at VNU

  9. Some recent works and results on Climate Research at our University • We got RegCM from ICTP since 1999 • To implement RegCM for our region, we have done some sensitivity tests on: • Domain size • Resolution: 30, 45, 54 (Km) • Surface heterogeneity • Buffer zone treatment • Spin up time (soil moisture) • Convective parameterization schemes • Continuous vs discontinuous run

  10. Some recent works and results on Climate Research at our University • Impact of aerosols on regional climate • Seasonal forecast using RegCM: • Firstly, run CAM with SST and Sea Ice forcing • Use output from CAM as initial and time dependent boundary conditions for RegCM • Some results: May-Aug 1996 • Long term simulation: • Seasonal and interannual variations:Jan. 1991 – Dec. 2000 (10 years)

  11. Represent the land surface subgrid scale heteogeneities Lowest level of AM • Heterogeneity of: • Surface type • Terrain high Terrain High of AM Grid-box Terrain High of Subgrid-box

  12. Terrain high at different resolutions 30x30 60x60 Increase the resolution results in the more detail representation of terrain 20x20

  13. Landuse at different resolutions 30x30 60x60 Increase the resolution results in the more detail representation of landuse 20x20

  14. 30 km V 20 km Number of land-cover type in the grid-box of 60x60 resolution 30x30 • 3030km: Number of land cover type is almost 23. • 2020km, Most of grid-box over land are heterogeneous, with number of land cover type is 56, even up to 9. 20x20

  15. Sensitivity test with convection schemes • Rainfall in winter time (mm/month): Reg+Kuo, Reg+Man, Reg+GAS, Reg+GFC, CMAP (Left to Right, Upper to Lower).

  16. Sensitivity test with convection schemes • Rainfall in summer time (mm/month) Reg+Kuo, Reg+Man, Reg+GAS, Reg+GFC, CMAP (Left to Right, Upper to Lower).

  17. Seasonal forecast with RegCM3 + CAM

  18. Seasonal forecast with RegCM3 + CAM Wind field and geopotential height at 1008.43mb

  19. Seasonal forecast with RegCM3 + CAM Wind field and geopotential height at 830.23mb

  20. Seasonal forecast with RegCM3 + CAM Monthly T2m: observed (blue) and model interpolated to stations (red)

  21. Seasonal forecast with RegCM3 + CAM Monthly rainfall: Observed (Column) and model interpolated to stations (blue dot)

  22. Seasonal and interannual variations

  23. Regional circulation patterns The 1991-2000 average of PMSL from ERA40 and RegCM3 in Jan, Apr, Jul and Oct

  24. Surface air temperature The 1991-2000 average of T2m (oC) from CRU and RegCM3 in Jan, Apr, Jul and Oct • RegCM3 simulation shows a tendency to underestimate T2m by 1o–2°C with CRU

  25. Precipitation The 19912000 averages of precipitation (mm/month) from CRU and RegCM3 in Jan, Apr, Jul and Oct • Model can capture general rainfall patterns although considerable differencesexist. In some regions, the RegCM3 simulation compares more favorably with observations (over East China in April), while in other regions less favorably

  26. C R U D A T A O B S. D A T A CRU data vs OBS

  27. Validation for Vietnam

  28. The 19912000 averages of Obs (blue) and model (red) T2m at stations in Jan, Apr, July and Oct (Unit in oC)

  29. The 19912000 averages of Obs (blue) and model (red) rainfall at stations in Jan, Apr, Jul and Oct (mm/month)

  30. R2 R1 • Vietnam is divided in to 7 climatological sub-regions: R1-R7 • Climate conditions are different from sub-region to sub-region R3 R4 R6 R5 R7

  31. Seasonal cycle

  32. Interannual variations

  33. Some Remarks • In general, the main features of spatial distribution of T2m simulated by RegCM3 agree well with the CRU data and ERA40, but tend to underestimate by about 1o–2oC, • RegCM3 can capture general rainfall patterns although considerable differences exist, especially at the maximum cores • Over Vietnam, RegCM3 reproduce quite well annual cycles and inter-annual variations of T2m and rainfal for all sub-regions • However, RegCM3 underestimates systematicallyT2mover almost sub-regions (except for R6) in all months, rainfallin rainy season, and overestimatesrainfall in dry season

  34. On going works • Investigate the changes in ECE: Vx, RHm, Tx, Tm, cold fronts, hot/very days, very cold days, heavy rainfall days/spells, drought, Typhoon,… using daily data from meteorological station network • Run RCMs for the period of 1971-2000 (baseline) and detect ECEs from output, and compare to observed (Verification/validation) • Run CCSM or CAM+SOM and use its output as inupt for RCMs (seasonal forecast)

  35. Some suggesttions

  36. This is the second time I’ve been here in CSIRO (First time at the end of 2005) • I am very happy to know that your CCAM have been used not only for weather forecast but also for climate change research, and it demonstrated preeminent advantages compared to other RCMs • I am very pleased if CSIRO can give us licences of CCAM so that we can run in Vietnam, firstly at our University, and maybe also in Philippine (?) • If that, we can establish an international network, including Indonesia, Vietnam, Philippine and CSIRO, to share together results, experiments, data and ideas,…

  37. For example, the researchers from VN, INDO, PHI can use model to do sensitivity studies to understand relevant physical processes, and to improve the representation of those processes in the climate of the region • The results of runing CCAM will be exchanged with scientists at CSIRO. By this way, CMAR will benefit by being provided with critical analyses of model behaviour over the South East Asian region • On the other hand, observed data over the interesting region will be used to compare with the model output • And, more and more

  38. Thank you very much

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