Authors

Affiliations

1 Meteorological and Hydrological Forecasting Management Department; leha246@gmail.com; haitran84@gmail.com

2 National Center for Hydro-Meteorological Forecasting; nthang0676@gmail.com

3 Ho Chi Minh University of Natural Resource and Environment; nttuyet@hcmunre.edu.vn

*Corresponding author: leha246@gmail.com; Tel.: +84–904290269

Abstracts

Conceptually, forecast verification is simple, you just need to compare the forecast factors and observed factors. The accuracy of a forecast is a measure of how close to the actual weather the forecast was. The reliability of a forecast is the average agreement between the forecast values and the observed values. The skill of a forecast is performed based on some benchmark forecast, usually by comparing the accuracy of the forecast with the accuracy of the benchmark. The benchmark forecast can be a climatic value. Meanwhile, the correct forecast is bias between the forecast value and the observed value within the allowable range.  This study evaluates the correct and forecasting skill of the IFS model (by European Centre for Medium-Range Weather Forecasts) for minimum temperature (Tm), average temperature (Tave), maximum temperature (Tx) forecasting in 24 hours at 09 regions in Viet Nam. The results show that within 24 hours, the IFS model predicts a high bias for the Tm (from 0.2 to 0.9oC) and a low bias for the Tave (from -0.2 to -0.9oC) and Tx (from -1.0 to -2.0oC). The correct in the southern region is higher than in the northern region (average about 10 to 15%). The skill of IFS model is higher than the benchmark (skill for the Tm has exceeded the Benchmark value by 0.4 to 0.6; skill for the Tave has exceeded the Benchmark value by 0.5 to 08), in there, the skill of Tm and Tave is higher than skill of Tx at the most regions, except in the Southern region, the skill of IFS model is lower than the benchmark for Tave and Tx.

Keywords

Cite this paper

Ha, L.T.T.; Hang, N.T.; Hai, T.T.T.; Tuyet, N.T. Evaluate the correct and the skill of the IFS model for minimum temperature, average temperature, maximum temperature forecasting in short term (24 hours) at 09 regions in VietnamJ. Hydro-Meteorol202418, 92-104.

References

1. WMO. Guidelines on performance assessment of public weather services - No. 1023, 2000.

2. Murphy, A.H. What is a good forecast? An essay on the nature of goodness in weather forecasting. Wea. Forecasting 1993, 8, 281–293.

3. Murphy, A.H. Forecast verification. Economic value of weather and climate forecasts. Katz, R.W., Murphy, A.H. (Eds). Cambridge Univ. Press, chapter 7, 1997, pp. 19–74.

4. Thornes, J.E.; Stephenson, D.B. How to judge the quality and value of weather forecast products. Meteorol. Appl. 20018, 307–314.

5. Wilks, D.S. A skill score based on economic value for probability forecasts. Meteorol. Appl. 20018, 209–219.

6. Seaman, R.; Mason, I.; Woodcock, F. Confidence intervals for some performance measures of yes-no forecasts. Aust. Met. Mag. 199645, 49–53.

7. Hamill, T.M. Hypothesis tests for evaluating numerical precipitation forecasts. Wea. Forecasting 1999, 14, 155–167.

8. Kane, T.L.; Brown, B.G. Confidence intervals for some verification measures - a survey of several methods. Proceeding of the 15th Conference on Probability and Statistics in the Atmospheric Sciences, Amer. Met. Soc., 8-11 May 2000, Asheville, North Carolina, 2000.

9. Hamill, T.M.; Juras, J. Measuring forecast skill: is it real skill or is it the varying climatology? Q. J. Royal Met. Soc. 2006, 132, 2905–2923.

10. Stanski, H.R.; Wilson, L.J.; Burrows, W.R. Survey of common verification methods in meteorology. World Weather Watch Tech. Rept. No. 8, WMO/TD No. 358, WMO, Geneva, 1989, pp. 114.

11. Katz, R.W.; Murphy, A.H. (Eds): Economic value of weather and climate forecasts. Cambridge University Press, Cambridge, 1997.

12. Jolliffe, I.T.; Stephenson, D.B. Forecast Verification: A practitioner’s guide in atmospheric science. 2nd Edition. Wiley and Sons Ltd, 2012, pp. 274.

13. Murphy, A.H.; Katz, R.W. Probability, statistics, and decision making in the atmospheric sciences. Westview Press, Boulder, CO, 1985.

14. Murphy, A.H.; Winkler, R.L. A general framework for forecast verification. Mon. Wea. Rev. 1987, 115, 1330–1338.

15. Nurmi, P. Recommendations on the verification of local weather forecasts (at ECWMF member states). ECMWF Operations Department, 2003.

16. Hoa, V.V. Comparative study skills rain forecast the middle part and central highland of several global models. VN J. Hydrometeorol. 2016, 667, 1–8.

17. Ba, T.D.; Hoa, V.V.; Tri, D.Q. A verification of short-term rainfall forecast by using ifs model of ECMWF on the northern central region. VN J. Hydrometeorol. 2019, 697, 33–43.

18. Nga, N.T.; Thanh, C.; Hung, M.K.; Tien, D.D. Verification of quantitative rainfall forecast from IFS and WRF model for the northern region of Viet Nam. VN J. Hydrometeorol. 2021, 730, 79–92.

19. Minh, L.T.; Lam, H.P. Automatically correction for forecasts city temperature from the ifs model output. VN J. Hydrometeorol. 2018, 693, 41–47.

20. MoNRE. Circular No. 41/2017/TT-BTNMT dated October 23rd, 2017 of the Minister of Natural Resources and Environment promulgating technical regulations on assessing the quality of meteorological forecasting, 2017.