Article
Green & Sustainable Science & Technology
Ismallianto Isia, Tony Hadibarata, Muhammad Noor Hazwan Jusoh, Rajib Kumar Bhattacharjya, Noor Fifinatasha Shahedan, Aissa Bouaissi, Norma Latif Fitriyani, Muhammad Syafrudin
Summary: Drought analysis using SPI and SPEI is crucial for water resource management in Sarawak, Malaysia. Both rainfall and temperature are important indicators for drought, and the SPI and SPEI can effectively detect temporal variations of drought with different time scales. The SPEI, considering both precipitation and evapotranspiration data, can identify more severe and longer-lasting droughts compared to the SPI. Temperature plays a decisive role in drought classification, and the SPI is recommended only when temperature data is unavailable.
Article
Multidisciplinary Sciences
Changhong Liu, Cuiping Yang, Qi Yang, Jiao Wang
Summary: Drought in Sichuan Province shows differences in characteristics between different physiognomy types, with increasing intensity in the western region mainly concentrated in the Sichuan basin. Altitude is not the main factor causing spatial unevenness of precipitation in Sichuan Province, as altitude, temperature, longitude, and latitude jointly determine precipitation distribution.
SCIENTIFIC REPORTS
(2021)
Article
Geochemistry & Geophysics
David MacLeod, Richard Graham, Chris O'Reilly, George Otieno, Martin Todd
Summary: The traditional El Nino events have a strong influence on the wet short rains in the Greater Horn of Africa due to its strong relationship with the Indian Ocean Dipole (IOD), while the Modoki El Nino events have a significantly weaker connection to the region as they are uncorrelated with the IOD. Idealized atmospheric simulations show that neither the longitudinal position nor the weaker magnitude of Modoki Pacific heating anomalies can explain the difference in teleconnections between the two types of El Nino events.
ATMOSPHERIC SCIENCE LETTERS
(2021)
Article
Meteorology & Atmospheric Sciences
Yue Zhang, Wen Zhou, Xin Wang, Xuan Wang, Ruhua Zhang, Yana Li, Jianping Gan
Summary: This study investigates the influence of Indian Ocean Dipole (IOD) and El Nino-Southern Oscillation (ENSO) on seasonal precipitation variation over eastern China. The results show that IOD primarily affects precipitation in South China during autumn and in the region between the Yangtze River and Yellow River during summer, while ENSO primarily boosts precipitation over eastern China during winter and spring. The distinct effects of IOD on ensuing summer precipitation contrast with the weaker signals associated with ENSO. These precipitation responses are associated with anomalous anticyclonic circulation patterns and the direct and indirect heating effects of IOD.
ATMOSPHERIC RESEARCH
(2022)
Article
Environmental Sciences
Wenhao Jia, Yawen Wu, Sen Wang, Mufeng Chen, Xia Liu
Summary: This study investigated the combined impacts of El Nino-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on streamflow in the Jinsha River Basin. Statistical methods such as coherent wavelet analysis were used to analyze the impact of ENSO and IOD events on the mean and extreme values of runoff. The results showed that both ENSO and IOD events have significant effects on the annual and seasonal streamflow in the basin.
Article
Environmental Sciences
Ahmed Elbeltagi, Chaitanya B. B. Pande, Manish Kumar, Abebe Debele Tolche, Sudhir Kumar Singh, Akshay Kumar, Dinesh Kumar Vishwakarma
Summary: This study aims to predict meteorological drought events in the central India of Maharashtra state using machine learning algorithms. Random forest, random tree, and Gaussian process regression models were tested, and the results showed that the random forest model performed the best in forecasting drought events.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Environmental Sciences
Dong-Dong Zuo, Wei Hou, Qiang Zhang, Peng-Cheng Yan
Summary: This study analyzed the influence of different reference climate states on the accuracy of SPI calculation, using monthly precipitation data from 1184 stations in China. The results showed that calculating SPI based on continuous 30-year precipitation data is reliable in most regions, but the reliability is relatively low in areas with frequent drought.
ADVANCES IN CLIMATE CHANGE RESEARCH
(2022)
Article
Engineering, Civil
L. Vergni, A. Vinci, F. Todisco
Summary: This study tested and compared several standardized meteorological indices in identifying agricultural drought impacts in central Italy, with SDDI and SPEI showing slightly better performance and potential in assessing drought impacts.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Civil
K. L. Chong, Y. F. Huang, C. H. Koo, Ali Najah Ahmed, Ahmed El-Shafie
Summary: Statistical drought characterization is crucial for drought studies, and efficient drought management can enhance preparedness and risk management. This study analyzed meteorological drought trends and periodicities in Sabah and Sarawak, Malaysia using Standardized Precipitation Indices, identifying declining tendencies and dominant periodicities. Wavelet coherence analysis revealed intermittent coherence between SPI and climatic indices.
JOURNAL OF HYDROLOGY
(2022)
Article
Geosciences, Multidisciplinary
Giovanni Liguori, Shayne McGregor, Martin Singh, Julie Arblaster, Emanuele Di Lorenzo
Summary: Tropical modes of variability, such as El Nino-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), have a strong influence on the interannual variability of Australian precipitation. However, the commonly used indices of ENSO and IOD display significant co-variability, making it difficult to quantify the independent contribution of each mode to precipitation anomalies. In this study, through modeling experiments, it is found that the ENSO-only-driven precipitation patterns significantly underestimate the impact of ENSO on Australian precipitation when the influence of IOD is statistically removed. A conceptual model is proposed to effectively separate the contribution of each mode to Australian precipitation variability.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Environmental Sciences
Patrick Pieper, Andre Dusterhus, Johanna Baehr
Summary: By utilizing the relationship between El Nino-Southern Oscillation and precipitation, useful predictive skill for meteorological drought can be extended to lead times of 2 to 4 months in equatorial South America and southern North America during dry ENSO phases.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Article
Meteorology & Atmospheric Sciences
Mohammad Jafar Nazemosadat, Kokab Shahgholian, Habib Ghaedamini
Summary: We enhanced our understanding of wet and dry spells within phase 8 of the Madden-Julian Oscillation (MJO) by separating dates with pervasive precipitation (SWPP) from dates with widespread dryness (SWWD). While Iranian southwest precipitation data was utilized, the study demonstrated that SWPP or SWWD is associated with large-scale climate variability. Non-MJO indexes were introduced to explain differences between SWPP and SWWD after proving that MJO indices were insufficient. Two quasi-oscillations of sea surface temperature and air pressure systems were found to be more significant, operating between the Arabian Sea, Mediterranean Sea, and the west and east of it.
ATMOSPHERIC RESEARCH
(2023)
Article
Engineering, Civil
Rongjun Wu, Yibo Liu, Xiaoyong Xing
Summary: The study demonstrates the effectiveness of ETDI in indicating regional agricultural drought in the major winter wheat production area of Northern China, showing high consistency with SPI and PDSI. The results highlight the importance of ETDI in guiding drought mitigation activities.
JOURNAL OF HYDROLOGY
(2021)
Editorial Material
Water Resources
Khouloud Gader, Ahlem Gara, Marnik Vanclooster, Slaheddine Khlifi, Mohamed Slimani
Summary: This study focuses on the changes in rainfall and drought patterns in the Medjerda catchment in Tunisia and analyzes the underlying causes. Suggestions for improving the drought assessment methodology are proposed, and the discussion mainly revolves around the use of the Standardized Precipitation Index (SPI) and drought classification based on SPI values.
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
(2022)
Article
Oceanography
Qian Heng, Xu Shibin, Wu Xin
Summary: By analyzing precipitation data from the Yangtze River Basin in the past 36 years, it was found that the dominant interannual variation of the first mode is mainly due to the West Pacific subtropical high and anticyclones over the Philippine islands, while the second mode may be related to the Indian Ocean-East Asian teleconnection and early withdrawal of the summer monsoon.
JOURNAL OF OCEAN UNIVERSITY OF CHINA
(2021)
Article
Geochemistry & Geophysics
E. Forootan, S. Farzaneh, M. Kosary, M. Schmidt, M. Schumacher
Summary: Improving thermospheric neutral density estimates is crucial for computing drag forces on LEO satellites and debris. By using accelerometer measurements to improve the NRLMSISE-00 model and implementing a novel C/DA technique, the accuracy of TND predictions has been significantly enhanced, leading to a reduction in misfit between model and observations.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2021)
Article
Remote Sensing
Ashty Saleem, J. L. Awange, R. Corner
Summary: This study examines the potential of utilizing panchromatic images for remote sensing applications through proposing new methods and employing texture analysis to enhance the images. By evaluating the classification results in Iran, Syria, and Kurdistan, it demonstrates the capability of the approach in handling complex panchromatic datasets.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Environmental Sciences
Nooshin Mehrnegar, Owen Jones, Michael Bliss Singer, Maike Schumacher, Thomas Jagdhuber, Bridget R. Scanlon, Ashraf Rateb, Ehsan Forootan
Summary: The novel Bayesian MCMC-DA approach integrates GRACE TWSC data into the water balance model, improving water storage estimates across the CONUS, particularly for groundwater and soil water storage. This hybrid approach shows promise for understanding the links between climate and the water balance over broad regions, with improved representation of ENSO-related variability.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Chemistry, Analytical
Hoa Thi Pham, Joseph Awange, Michael Kuhn, Binh Van Nguyen, Luyen K. Bui
Summary: Accurate crop yield forecasting is crucial in the food industry. This study proposes a framework that combines machine learning algorithms, higher-order spatial independent component analysis, and principal component analysis to enhance rice yield prediction accuracy.
Article
Environmental Sciences
Amir Allahvirdi-Zadeh, Joseph Awange, Ahmed El-Mowafy, Tong Ding, Kan Wang
Summary: Global Navigation Satellite Systems' radio occultation (GNSS-RO) plays a crucial role in providing atmospheric profiles for weather forecasting and climate change studies. This study compares the clock stabilities of CubeSats and larger low Earth orbit (LEO) satellites, and proposes methods to improve CubeSats' clock stabilities. The results show that CubeSats can achieve high-quality atmospheric profiles comparable to those of LEO satellites, even with unstable onboard clocks. Advancements in chip-scale atomic clocks and onboard processing units present a promising future for real-time applications.
Article
Geochemistry & Geophysics
M. Kosary, E. Forootan, S. Farzaneh, M. Schumacher
Summary: This study presents a sequential calibration approach based on the Ensemble Kalman Filter to improve Total Electron Content (TEC) estimations in the ionosphere. The calibrated model, called 'C-EnKF-IRI', shows improved accuracy compared to existing models and can be used for real-time TEC estimations. The results demonstrate the importance of accurate ionospheric models in reducing the effects on Global Navigation Satellite Systems.
JOURNAL OF GEODESY
(2022)
Article
Chemistry, Analytical
Luyen K. Bui, Joseph Awange, Dinh Toan Vu
Summary: This study investigates the spatio-temporal variability in precipitation and soil moisture in Vietnam using independent component analysis. The results show that the wetter period in the southern and South Central Coast areas is later than in the northern and North Central Coast areas. The spatial patterns of annual mean precipitation and soil moisture disagree, likely due to factors other than precipitation. The CHIRPS Standardized Precipitation Index and GLDAS Standardized Soil Moisture Index are useful in capturing climate extremes and identifying their influences on rice production in Vietnam.
Article
Environmental Sciences
Leandro Fernandes Coladello, Maria de Lourdes Bueno Trindade Galo, Milton Hirokazu Shimabukuro, Ivana Ivanova, Joseph Awange
Summary: The overgrowth of macrophytes in urbanized and industrialized reservoirs is a common problem triggered by human activities. While remote sensing is used to monitor the occurrence of aquatic plants, studies seldom consider the influence of climate variables on macrophyte dynamics at medium to long-term scales. This study examines the spatiotemporal dynamics of macrophytes in a eutrophic reservoir, using the Normalized Difference Vegetation Index (NDVI) as a proxy for macrophytes and matching it with climate variables from NOAA. The results show that climate fluctuations contribute to the spatial dispersion of macrophytes.
Article
Environmental Sciences
Gebiaw T. Ayele, Ayalkibet M. Seka, Habitamu Taddese, Mengistu A. Jemberrie, Christopher E. Ndehedehe, Solomon S. Demissie, Joseph L. Awange, Jaehak Jeong, David P. Hamilton, Assefa M. Melesse
Summary: Understanding the spatiotemporal trend of land cover change and its impact on hydrology, ecosystems, and the environment is crucial. This study analyzed the land cover change in a specific area using remotely-sensed data and assessed its relationship with watershed characteristics. The findings revealed an increase in agricultural land and a decrease in bushland, grazing land, and forest, influenced by soil type, fertility, and slope.
Article
Environmental Sciences
Shaoxing Mo, Yulong Zhong, Ehsan Forootan, Xiaoqing Shi, Wei Feng, Xin Yin, Jichun Wu
Summary: This study reconstructs and analyzes droughts during the gap period between two GRACE missions using a Bayesian convolutional neural network. It identifies severe droughts in mid-latitude regions lasting over 1 year, which are mainly attributed to continuous below-normal precipitation. The reconstructed signals maintain data continuity and are recommended for hydro-climatological studies.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Wei Chen, C. K. Shum, Ehsan Forootan, Wei Feng, Min Zhong, Yuanyuan Jia, Wenhao Li, Junyi Guo, Changqing Wang, Quanguo Li, Lei Liang
Summary: Accurately monitoring spatio-temporal changes in lake water levels is important for studying the impacts of climate change on freshwater resources, and for predicting natural hazards. In this study, multi-mission radar satellite altimetry data was used to reconstruct lake-wide spatio-temporal changes in water level. The results indicate a significant correlation between lake level changes and ENSO episodes.
Article
Environmental Sciences
Omweno Ondari, Joseph Awange, Yongze Song, Allan Kasedde
Summary: The formation of floating islands in the Nalubaale, Kiira, and Bujagali dams in Uganda is caused by precipitation, fluctuating water levels, and wind variations, which negatively impact hydropower production.
Article
Environmental Sciences
Nooshin Mehrnegar, Maike Schumacher, Thomas Jagdhuber, Ehsan Forootan
Summary: In this study, a newly developed Constrained Bayesian (ConBay) optimization approach is used to merge the TWSC of GRACE/GRACE-FO with SMAP soil moisture data and assess the groundwater storage of the High Plain aquifer in the United States. The results show that assimilating GRACE/GRACE-FO data can improve groundwater estimates, and incorporating SMAP data controls the updates of surface storage.
WATER RESOURCES RESEARCH
(2023)
Article
Chemistry, Analytical
Hoa Thi Pham, Joseph Awange, Michael Kuhn
Summary: Machine learning has played a crucial role in crop yield forecasting, but identifying critical features from datasets remains challenging. This study proposes a framework that compares feature selection, feature extraction, and their combination to enhance model performance, finding that the combined approach performs the best. The results emphasize the significant role of feature selection, feature extraction, and their combination with various machine learning algorithms in improving the accuracy of crop yield predictions.
Article
Geosciences, Multidisciplinary
Ehsan Forootan, Nooshin Mehrnegar
Summary: This study presents a hierarchical constrained Bayesian approach to estimate the contributions of terrestrial water storage changes (TWSC) and post-glacial rebound (PGR) in GRACE(-FO) signals. The proposed method combines GRACE(-FO) fields and uplift rate measurements from GNSS stations, and incorporates uncertainties of prior information and observations. Validations against independent measurements show that the ConBay approach significantly improves PGR estimates and accurately updates long-term trends as well as seasonal and inter-annual components.
