The rainfall modeling at regional scale remains a great challenge in the tropics because of the complexity of the processes that induce rainfall variability. Then the good parameterization of some atmospheric processes will be of great contribution towards the improvement of regional models. In this paper we applied wavelet transform on 2.5°×2.5° daily Outgoing Long-wave Radiation (OLR) datasets for the period 1981-2015 (35 years) to extract Intraseasonal Intensity (ISOI) and intraseasonal Period (ISOP), with application to Central Africa (CA). In fact for each grid point in the study area, the wavelet transform was applied to the 25-70-day filtered daily OLR time series and the wavelet spectrum is obtained. In the resulting spectrum, the maximum variance for each day is taken as ISOI and the period exhibiting that maximum variance is the ISOP. The plots of seasonal mean ISOI and ISOP obtained showed that the ISO characteristics (amplitude, frequency) strongly vary from season to another. The ISO amplitude is extremely high during December-February (DJF) and March-May (MAM) and lower during JJA and SON seasons. As for the period of oscillations, the ISOP peaks during MAM and JJA seasons. But for the four seasons, the period is predominantly contained between 40-50 days, suggesting the dominance of Madden-Julian Oscillation (MJO) signal.
Published in | International Journal of Environmental Monitoring and Analysis (Volume 8, Issue 4) |
DOI | 10.11648/j.ijema.20200804.14 |
Page(s) | 111-116 |
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Intraseasonal Oscillations, Central Africa, Wavelets Analysis, Intensity, Frequency
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APA Style
Alain Tchakoutio Sandjon, Armand Nzeukou Takougang. (2020). A Wavelet-based Algorithm for the Computation of Intraseasonal Oscillations Intensity and Frequency Indices and Application to Central Africa. International Journal of Environmental Monitoring and Analysis, 8(4), 111-116. https://doi.org/10.11648/j.ijema.20200804.14
ACS Style
Alain Tchakoutio Sandjon; Armand Nzeukou Takougang. A Wavelet-based Algorithm for the Computation of Intraseasonal Oscillations Intensity and Frequency Indices and Application to Central Africa. Int. J. Environ. Monit. Anal. 2020, 8(4), 111-116. doi: 10.11648/j.ijema.20200804.14
AMA Style
Alain Tchakoutio Sandjon, Armand Nzeukou Takougang. A Wavelet-based Algorithm for the Computation of Intraseasonal Oscillations Intensity and Frequency Indices and Application to Central Africa. Int J Environ Monit Anal. 2020;8(4):111-116. doi: 10.11648/j.ijema.20200804.14
@article{10.11648/j.ijema.20200804.14, author = {Alain Tchakoutio Sandjon and Armand Nzeukou Takougang}, title = {A Wavelet-based Algorithm for the Computation of Intraseasonal Oscillations Intensity and Frequency Indices and Application to Central Africa}, journal = {International Journal of Environmental Monitoring and Analysis}, volume = {8}, number = {4}, pages = {111-116}, doi = {10.11648/j.ijema.20200804.14}, url = {https://doi.org/10.11648/j.ijema.20200804.14}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20200804.14}, abstract = {The rainfall modeling at regional scale remains a great challenge in the tropics because of the complexity of the processes that induce rainfall variability. Then the good parameterization of some atmospheric processes will be of great contribution towards the improvement of regional models. In this paper we applied wavelet transform on 2.5°×2.5° daily Outgoing Long-wave Radiation (OLR) datasets for the period 1981-2015 (35 years) to extract Intraseasonal Intensity (ISOI) and intraseasonal Period (ISOP), with application to Central Africa (CA). In fact for each grid point in the study area, the wavelet transform was applied to the 25-70-day filtered daily OLR time series and the wavelet spectrum is obtained. In the resulting spectrum, the maximum variance for each day is taken as ISOI and the period exhibiting that maximum variance is the ISOP. The plots of seasonal mean ISOI and ISOP obtained showed that the ISO characteristics (amplitude, frequency) strongly vary from season to another. The ISO amplitude is extremely high during December-February (DJF) and March-May (MAM) and lower during JJA and SON seasons. As for the period of oscillations, the ISOP peaks during MAM and JJA seasons. But for the four seasons, the period is predominantly contained between 40-50 days, suggesting the dominance of Madden-Julian Oscillation (MJO) signal.}, year = {2020} }
TY - JOUR T1 - A Wavelet-based Algorithm for the Computation of Intraseasonal Oscillations Intensity and Frequency Indices and Application to Central Africa AU - Alain Tchakoutio Sandjon AU - Armand Nzeukou Takougang Y1 - 2020/08/31 PY - 2020 N1 - https://doi.org/10.11648/j.ijema.20200804.14 DO - 10.11648/j.ijema.20200804.14 T2 - International Journal of Environmental Monitoring and Analysis JF - International Journal of Environmental Monitoring and Analysis JO - International Journal of Environmental Monitoring and Analysis SP - 111 EP - 116 PB - Science Publishing Group SN - 2328-7667 UR - https://doi.org/10.11648/j.ijema.20200804.14 AB - The rainfall modeling at regional scale remains a great challenge in the tropics because of the complexity of the processes that induce rainfall variability. Then the good parameterization of some atmospheric processes will be of great contribution towards the improvement of regional models. In this paper we applied wavelet transform on 2.5°×2.5° daily Outgoing Long-wave Radiation (OLR) datasets for the period 1981-2015 (35 years) to extract Intraseasonal Intensity (ISOI) and intraseasonal Period (ISOP), with application to Central Africa (CA). In fact for each grid point in the study area, the wavelet transform was applied to the 25-70-day filtered daily OLR time series and the wavelet spectrum is obtained. In the resulting spectrum, the maximum variance for each day is taken as ISOI and the period exhibiting that maximum variance is the ISOP. The plots of seasonal mean ISOI and ISOP obtained showed that the ISO characteristics (amplitude, frequency) strongly vary from season to another. The ISO amplitude is extremely high during December-February (DJF) and March-May (MAM) and lower during JJA and SON seasons. As for the period of oscillations, the ISOP peaks during MAM and JJA seasons. But for the four seasons, the period is predominantly contained between 40-50 days, suggesting the dominance of Madden-Julian Oscillation (MJO) signal. VL - 8 IS - 4 ER -