آمار
| تعداد نشریات | 13 |
| تعداد شمارهها | 654 |
| تعداد مقالات | 6,815 |
| تعداد مشاهده مقاله | 9,746,285 |
| تعداد دریافت فایل اصل مقاله | 9,140,901 |
Determination of dew point temperature based on simultaneous multivariate models and vector time series considering heterogeneity in meteorological stations in eastern Iran | ||
| Environmental Resources Research | ||
| دوره 12، شماره 2، آذر 2024، صفحه 229-256 اصل مقاله (4.97 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22069/ijerr.2024.22535.1441 | ||
| نویسندگان | ||
| Abolfazl Akbarpour* 1؛ Vahid KhorramNezhad2؛ Mohammad Nazeri Tahrodi3 | ||
| 1Professor, Department of Civil Engineering, Birjand University, Birjand, Iran | ||
| 2M.Sc. student in Water Resources Managment, Department of Civil Engineering, Birjand University, Birjand, Iran | ||
| 3Professor Assistant, Department of Water Engineering, Lorestan University, Khorramabad, Iran | ||
| چکیده | ||
| In this research, meteorological parameters of eleven stations were monitored to build a suitable model for predicting dew point values. Considering the importance of dew point temperature in forecasting frosts or rainfall and its other applications, the prediction of this parameter is of particular importance. The stations investigated in this research are: Bam, Birjand, Chabahar, Iranshahr, Kerman, Mashhad, Sabzevar, Tabas, Torbat Heydarieh, Zabul, and Zahedan, all of which are classified in dry climate. First, the correlation of different weather parameters with dew point was checked and then three parameters of average, maximum and minimum temperature were entered into the model as input with the highest correlation with dew point. CARMA and VAR models were used. Then, the stability of the remaining series was calculated for both models and these series were developed using the GARCH model. The result of the development of the models was the modeling of the dew point in eleven meteorological stations with the developed CARMA-GARCH and VAR-GARCH models. Our findings show that the VAR-GARCH model has superior performance in both training and testing stages and is selected as the best model of this research. One of the important reasons for the superiority of this model is its higher memory in processing time series. The definitive result is the improvement of both primary models if the remaining series of the model are developed using the GARCH model, which increases the accuracy of both models in the test phase by 6 to 30 percent. | ||
| کلیدواژهها | ||
| Modeling؛ Climate؛ Dew temperature؛ Time series؛ VAR model | ||
| مراجع | ||
|
Aguirre-Gutiérrez, C. A., Holwerda, F., Goldsmith, G. R., Delgado, J., Yepez, E., Carbajal, N., and Arredondo, J. T. 2019. The importance of dew in the water balance of a continental semiarid grassland. Journal of Arid Environments. 168, 26-35.
Baguskas, S. A., King, J. Y., Fischer, D. T., D’Antonio, C. M., and Still, C. J. 2016. Impact of fog drip versus fog immersion on the physiology of Bishop pine saplings. Functional Plant Biology. 44(3), 339-350.
Campbell, J. Y., Lo, A. W., MacKinlay, A. C., and Whitelaw, R. F. 1998. The econometrics of financial markets. Macroeconomic Dynamics. 2(4), 559-562.
Cuthbertson, K., and Nitzsche, D. 2005. Quantitative financial economics: Stocks, bonds and foreign exchange. John Wiley and Sons.
Engle, R. 1982. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica. 50, 391-407.
Hamilton, J. D. 2020. Time series analysis. Princeton University Press.
Lin, J., Shahzad, M. W., Li, J., Long, J., Li, C., and Chua, K. J. 2021. A robust physics-based model framework of the dew point evaporative cooler: From fundamentals to applications. Energy Conversion and Management. 233, 113925.
Lütkepohl, H. 1991. Introduction to multiple time series. Berlin: Springer-Verlag.
Lütkepohl, H. 2001. Vector autoregressions. In Companion to Theoretical Econometrics (pp. 678-699). Blackwell, Oxford.
Maestre-Valero, J., Martin-Gorriz, B., and Martínez-Alvarez, V. 2015. Dew condensation on different natural and artificial passive surfaces in a semiarid climate. Journal of Arid Environments. 116, 63-70.
Mills, T. C., and Markellos, R. N. 2008. The econometric modelling of financial time series. Cambridge University Press.
Ramezani, Y., Nazeri Tahroudi, M., De Michele, C., and Mirabbasi, R. 2023. Application of copula-based and ARCH-based models in storm prediction. Theoretical and Applied Climatology. 151(3), 1239-1255.
Shahidi, A., Ramezani, Y., Nazeri-Tahroudi, M., and Mohammadi, S. 2020. Application of vector autoregressive models to estimate pan evaporation values at the Salt Lake Basin, Iran. IDŐJÁRÁS/Quarterly Journal of the Hungarian Meteorological Service. 124(4), 463-482.
Sims, C. A. 1980. Macroeconomics and reality. Econometrica: Journal of the Econometric Society. 1-48.
Tomaszkiewicz, M., Abou Najm, M., Zurayk, R., and El-Fadel, M. 2017. Dew as an adaptation measure to meet water demand in agriculture and reforestation. Agricultural and Forest Meteorology. 232, 411-421.
Tsay, R. S. 2005. Analysis of financial time series. John Wiley & Sons.
Waggoner, D. F., and Zha, T. 1999. Conditional forecasts in dynamic multivariate models. Review of Economics and Statistics. 81(4), 639-651.
Watson, M. W. 1994. Vector autoregressions and cointegration. In Handbook of Econometrics (pp. 2843-2915).
Yokoyama, G., Yasutake, D., Minami, K., Kimura, K., Marui, A., Yueru, W., and Kitano, M. 2021. Evaluation of the physiological significance of leaf wetting by dew as a supplemental water resource in semi-arid crop production. Agricultural Water Management. 255, 106964.
Zhang, Q., Wang, S., Yang, F.-L., Yue, P., Yao, T., and Wang, W.-Y. 2015. Characteristics of dew formation and distribution, and its contribution to the surface water budget in a semi-arid region in China. Boundary-Layer Meteorology. 154, 317-331.
Zhang, Q., Wang, S., Yue, P., and Wang, S. 2019. Variation characteristics of non-rainfall water and its contribution to crop water requirements in China’s summer monsoon transition zone. Journal of Hydrology. 578, 124039.
| ||
|
آمار تعداد مشاهده مقاله: 358 تعداد دریافت فایل اصل مقاله: 358 |
||
سامانه مدیریت نشریات علمی. طراحی و پیاده سازی از سیناوب