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Short-term (0-24 hours) precipitation forecasting is highly valuable to socioeconomic activities and public safety. However, the highly complex evolution patterns of precipitation events, the extreme imbalance between precipitation and…
Author suggests and researches a new revolutionary idea for regional and global weather control. He offers to cover cities, bad regions of country, full country or a continent by a thin closed film with control clarity located at a top…
The strength of mid-latitude storm tracks shapes weather and climate phenomena in the extra-tropics, as these storm tracks control the daily to multi-decadal variability of precipitation, temperature and winds. By the end of this century,…
Climate change has intensified the frequency and severity of extreme weather events, presenting unprecedented challenges to the agricultural industry worldwide. In this investigation, we focus on kiwifruit farming in New Zealand. We propose…
Our study aims at quantifying the impact of climate change on corn farming in Ontario under several warming scenarios at the 2068 horizon. It is articulated around a discrete-time dynamic model of corn farm income with an annual time-step,…
In this paper we assess the snow cover and its dynamics for the western river basins of the Indus River system and their subbasins located in Afghanistan, China, India and Pakistan for the period 2001-2012. First, we validate the Moderate…
We reduce measurements made by the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) to give the total Birkeland (field-aligned) current flowing in both hemispheres in monthly and hourly bins. We analyze these…
Small seasonal wetlands are a distinctive feature of the semi-arid environments. Although these systems are small and ephemeral in nature, they provide habitats to aquatic flora and fauna, and play a critical role in sustaining livelihoods…
Streamflow observation data is vital for flood monitoring, agricultural, and settlement planning. However, such streamflow data are commonly plagued with missing observations due to various causes such as harsh environmental conditions and…
Assessing the availability of rainfall water plays a crucial role in rainfed agriculture. Given the substantial proportion of agricultural practices in India being rainfed and considering the potential trends in rainfall amounts across…
Accurate monsoon rainfall prediction is vital for India's agriculture, water management, and climate risk planning, yet remains challenging due to sparse ground observations and complex regional variability. We present a multimodal deep…
Floods are one of the most common natural disasters, with a disproportionate impact in developing countries that often lack dense streamflow gauge networks. Accurate and timely warnings are critical for mitigating flood risks, but…
The Amazon rainforest (ARF) is threatened by deforestation and climate change, which could trigger a regime shift to a savanna-like state. Previous work suggesting declining resilience in recent decades was based only on local resilience…
Lightning flashes are rare albeit hazardous events. Despite this scarcity, generalized additive models (GAMs) succeed in producing a climatology of lightning occurrence for the eastern Alps and surrounding lowlands at an unprecedented…
Numerical weather prediction (NWP) models often underperform compared to simpler climatology-based precipitation forecasts in northern tropical Africa, even after statistical postprocessing. AI-based forecasting models show promise but have…
The accurate estimation of terrestrial water and vegetation is a grand challenge in hydrometeorology. Many previous studies developed land data assimilation systems (LDASs) and provided global-scale land surface datasets by integrating…
This paper presents an integrated modelling assessment that estimated the sensitivities of five endogenous factors in commercial rangelands, i.e. number of active farmers, profits, stocking rate, standing herbage biomass, and soil erosion,…
Climate change projections for boreal winter precipitation in Tropical America has beenaddressed by statistical downscaling (SD) using the principal component regression with sea-level pressure (SLP) as the predictor variable. The SD model…
In data-sparse regions, satellite and reanalysis rainfall estimates (SREs) are vital but limited by inherent biases. This study evaluates bias correction (BC) methods, including traditional statistical (LOCI, QM) and machine learning (SVR,…
Extreme precipitation in the Arctic region plays a crucial role in global weather and climate patterns. Bear Island (Bj{\o}rn{\o}ya) is located in the Norwegian Svalbard archipelago, which is, therefore, selected for our study on extreme…