Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Zin Mie Mie Sein"'
Autor:
Zin Mie Mie Sein, Xiefei Zhi, Faustin Katchele Ogou, Isaac Kwesi Nooni, Khant Hmu Paing, Emmanuel Yeboah
Publikováno v:
Environmental Research Letters, Vol 19, Iss 4, p 044056 (2024)
The Myanmar’ Southeast Asian country is currently experiencing environmental changes, with temperature change being one the major contributing factors. Although many studies have shown the contribution of anthropogenic activities, the factors susta
Externí odkaz:
https://doaj.org/article/bf5ce9a11fae4d4f98b4f1c526cac731
Publikováno v:
Frontiers in Environmental Science, Vol 10 (2022)
The study investigated the precipitation variability over Myanmar at the annual and seasonal scales by comparing 12 model outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) with gridded observational data provided by the Global Pr
Externí odkaz:
https://doaj.org/article/e87ed195a21f48e2a9b7db8788c6e60d
Publikováno v:
Atmosphere, Vol 13, Iss 2, p 354 (2022)
As an important component of the East Asian monsoon system, the northeast cold vortex (NECV) exerts a significant impact on weather and climate, especially in Northeast China. This study investigated the interdecadal spatiotemporal variability of hea
Externí odkaz:
https://doaj.org/article/0c628caa706b4e998c367e32b5122083
Autor:
Zin Mie Mie Sein, Xiefei Zhi, Faustin Katchele Ogou, Isaac Kwesi Nooni, Kenny T. C. Lim Kam Sian, Gnim Tchalim Gnitou
Publikováno v:
Agronomy, Vol 11, Iss 9, p 1691 (2021)
Drought research is an important aspect of drought disaster mitigation and adaptation. For this purpose, we used the Standardized Precipitation Evapotranspiration Index (SPEI) to investigate the spatial-temporal pattern of drought and its impact on c
Externí odkaz:
https://doaj.org/article/aa418f3fcb3543f9a443baecca87ab1f
Interdecadal Variability in Myanmar Rainfall in the Monsoon Season (May–October) Using Eigen Methods
Publikováno v:
Water, Vol 13, Iss 5, p 729 (2021)
In this study, we investigated the interdecadal variability in monsoon rainfall in the Myanmar region. The gauge-based gridded rainfall dataset of the Global Precipitation Climatology Centre (GPCC) and Climatic Research Unit version TS4.0 (CRU TS4.0)
Externí odkaz:
https://doaj.org/article/833c70bed9f74e139031f4c82e84d1a3
Publikováno v:
Climate, Vol 9, Iss 2, p 35 (2021)
Myanmar is located in a tropical region where temperature rises very fast and hence is highly vulnerable to climate change. The high variability of the air temperature poses potential risks to the local community. Thus, the current study uses 42 syno
Externí odkaz:
https://doaj.org/article/6948fb62334e457aa0a6f0761dc045cb
Rainfall and temperature are essential roles in weather forecasting in a tropical country like Myanmar. In this study, we explored data-driven feed-forward neural networks (FNN) and recurrent neural networks in terms of long short-term memory (RNN-LS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f66f7cafbf07f6eb504d1a13580aab6
Autor:
Farhan Saleem, Kamran Azam, Xiefei Zhi, Hamida Ngoma, Yun Xing, Athanase Nkunzimana, Zin Mie Mie Sein, Sidra Syed, Vedaste Iyakaremye, Irfan Ullah, Saadia Hina
Publikováno v:
International Journal of Climatology. 42:3341-3359
Autor:
Vedaste Iyakaremye, Zin Mie Mie Sein, Kamran Azam, Sidra Syed, Xieyao Ma, Irfan Ullah, Xiefei Zhi
Publikováno v:
Meteorology and Atmospheric Physics. 134
Understanding the prevailing changes in temperature and relative humidity (RH) is of crucial importance for climate risk reduction and management. Despite their importance, trends and temperature variability associated with other climate variables ov
Publikováno v:
Climate, Vol 9, Iss 35, p 35 (2021)
Climate
Volume 9
Issue 2
Climate
Volume 9
Issue 2
Myanmar is located in a tropical region where temperature rises very fast and hence is highly vulnerable to climate change. The high variability of the air temperature poses potential risks to the local community. Thus, the current study uses 42 syno