Modern computational approaches for rice yield prediction: A systematic review of statistical and machine learning-based methods

Computers and Electronics in Agriculture, Journal Year: 2025, Volume and Issue: 231, P. 109852 - 109852

Published: Feb. 5, 2025

Language: Английский

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Diverse responses of gross primary production and leaf area index to drought on the Mongolian Plateau

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 902, P. 166507 - 166507

Published: Aug. 22, 2023

Language: Английский

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Evaluating the performance of key ERA‐Interim, ERA5 and ERA5‐Land climate variables across Siberia

International Journal of Climatology, Journal Year: 2024, Volume and Issue: 44(7), P. 2318 - 2342

Published: April 11, 2024

Abstract Reanalysis datasets provide a continuous picture of the past climate for every point on Earth. They are especially useful in areas with few direct observations, such as Siberia. However, to ensure these sufficiently accurate they need be validated against readings from meteorological stations. Here, we analyse how values six variables—the minimum, mean and maximum 2‐metre air temperature, snow depth (SD), total precipitation wind speed (WSP)—from three reanalysis datasets—ERA‐Interim, ERA5 ERA5‐Land—compare observations 29 stations across Siberia Russian Far East daily timescale 1979 2019. All reanalyses produce temperature that close those observed, average absolute bias not exceeding 1.54°C. care should taken minimum during summer months—there nine where correlation <0.60 due inadequate night‐time cooling. The SD generally observed after 1992, ERA5, when data some began assimilated, but used caution (if at all) before 1992 lack assimilation leads large overestimations. For low good approximations, however struggle attain extreme high values. Similarly, 10‐metre WSP; perform well speeds up 2.5 ms −1 above 5.0 . variables, recommend using over ERA‐Interim ERA5‐Land future research. shows minor improvements ERA‐Interim, and, despite an increased spatial resolution, there is no advantage ERA5‐Land.

Language: Английский

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Multi-decadal trends of low-clouds at the Tropical Montane Cloud Forests

Ecological Indicators, Journal Year: 2024, Volume and Issue: 158, P. 111599 - 111599

Published: Jan. 1, 2024

Clouds are critical to the biodiversity and function of Tropical Montane Cloud Forests (TMCF) as they control water regimes sunlight that can be perceived by plants. These ecosystems provide a key role in ecosystem services humanity considered hotspots endemism, given number species is restricted their microclimates. The cloudiness these projected decline owing global warming, but recent temporal trends remain unclear. Here, we evaluated low-cloud fractions (CF) (e.g., proportion an area covered low-cloud) other Essential Climatic Variables (ECV) surface temperature, pressure, soil moisture, precipitation) for 521 sites worldwide with TMFCs from 1997 2020. We hypothesize traces warming over last few decades have led decreases CF on TMCFs. previous was also assessed globally among biogeographic realms identify regional trends. calculated aggregating hourly observations ERA5 reanalysis CHIRPS into annual averages then using linear regressions calculate slopes (i.e., rate change) (Δ, year−1). Our results suggest at TMCFs range between −64.7×10−4 51.4×10−4 year−1, revealing 70 % experienced reductions CF. Declines low-clouds 253 more severe than tropical landmasses when peak values density distribution compared (TMCFs: −7.8×10−4 year−1; −2.3×10−4 Despite this, differ realms, those Neotropics Indomalayan most pronounced declines. Decreases were associated increases temperature pressure TMCF's climate changing warmer environments. climatic shifts may represent imprints change TMCFs, highlighting current threat essential provide.

Language: Английский

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Enhancing streamflow simulation in large and human-regulated basins: Long short-term memory with multiscale attributes

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 630, P. 130771 - 130771

Published: Jan. 26, 2024

Language: Английский

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The Impact of Climate Change on Construction Activity Performance

Buildings, Journal Year: 2024, Volume and Issue: 14(2), P. 372 - 372

Published: Jan. 31, 2024

There are specific construction operations that require weather forecast data to make short-term decisions regarding construction; however, most resource-related decision making and all project management plans must be carried out anticipate conditions beyond the capabilities of currently available forecasting technologies. In this study, a series single- multi-risk analyses were performed with ~9 km grid resolution over Türkiye using combinations climate variables their threshold values which have an impact on execution performance activities. These will improve predictability potential delays, enable scheduled future-proof basis by considering calculated normal periodic predictions scale, serve as dispute tool for related claims. A comprehensive case study showcasing methodology illustrating its application shows duration is expected extended because both historical future periods. While original was 207 days, when effects considered, optimum mean median increased 255 238 respectively, period. The change 239 days end century, according SSP5-8.5 scenario, if schedules consider change. in mainly due rising temperatures, winter workability reduced summer workability. However, practices schedules, increase 258 244 may cause unavoidable direct, indirect, or overhead costs.

Language: Английский

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A 40-year remote sensing analysis of spatiotemporal temperature and rainfall patterns in Senegal

Frontiers in Climate, Journal Year: 2025, Volume and Issue: 7

Published: Feb. 6, 2025

Climate change impacts manifest differently worldwide, with many African countries, including Senegal, being particularly vulnerable. The decline in ground observations and limited access to these continue impede research efforts understand, plan, mitigate the current future of climate change. This occurs at a time rapid growth Earth (EO) data, methodologies, computational capabilities, which could potentially augment studies data-scarce regions. In this study, we utilized satellite remote sensing data leveraging historical EO using Google Engine investigate spatio-temporal rainfall temperature patterns Senegal from 1981 2020. We combined CHIRPS precipitation ERA5-Land reanalysis datasets for analysis used Mann–Kendall Sen's Slope statistical tests trend detection. Our results indicate that annual temperatures increased by 0.73°C 18 mm All six Senegal's agroecological zones showed statistically significant upward trends. However, Casamance, Ferlo, Eastern Groundnut Basin, River Valley regions exhibited trends temperature. south, approach would be centered on effects rainfall, such as flooding soil erosion. Conversely, drier northern areas Podo Saint Louis, focus addressing water scarcity drought conditions. High key crop-producing regions, Saraya, Goudiry, Tambacounda area also threaten crop yields, especially maize, sorghum, millet, peanuts. By acknowledging unique various zones, policymakers stakeholders can develop implement customized adaptation strategies are more successful fostering resilience ensuring sustainable agricultural production face changing climate.

Language: Английский

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Impacts of Climate Change on Extreme Climate Indices in Türkiye Driven by High-Resolution Downscaled CMIP6 Climate Models

Sustainability, Journal Year: 2023, Volume and Issue: 15(9), P. 7202 - 7202

Published: April 26, 2023

In this study, the latest release of all available Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models with two future scenarios Shared Socio-Economic Pathways, SSP2-4.5 and SSP5-8.5, over period 2015–2100 are utilized in diagnosing extremes Türkiye. Coarse-resolution were downscaled to a 0.1° × (~9 km) spatial resolution using European Centre for Medium-Range Weather Forecasts Reanalysis 5-Land (ERA5-Land) dataset based on three types quantile mapping: mapping, detrended delta mapping. The temporal variations 12 extreme precipitation indices (EPIs) temperature (ETIs) from 2015 2100 consistently suggest drier conditions, addition more frequent severe warming Türkiye, under scenarios. SSP5-8.5 scenario indicates water stress than scenario; total decreases up 20% Aegean Mediterranean regions Precipitation indicate decrease frequency heavy rains but an increase very also increasing amount rain days. Temperature such as coldest, warmest, mean daily maximum expected across indicating conditions by 7.5 °C end century. Additionally, coldest maximums exhibit higher variability change subregions Aegean, Southeastern Anatolia, Marmara, Türkiye while showed greater sensitivity Black Sea, Central Eastern Anatolia regions.

Language: Английский

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Comparison of Machine Learning Models in Simulating Glacier Mass Balance: Insights from Maritime and Continental Glaciers in High Mountain Asia

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(6), P. 956 - 956

Published: March 8, 2024

Accurately simulating glacier mass balance (GMB) data is crucial for assessing the impacts of climate change on dynamics. Since physical models often face challenges in comprehensively accounting factors influencing glacial melt and uncertainties inputs, machine learning (ML) offers a viable alternative due to its robust flexibility nonlinear fitting capability. However, effectiveness ML modeling GMB across diverse types within High Mountain Asia has not yet been thoroughly explored. This study addresses this research gap by evaluating used simulation annual glacier-wide data, with specific focus comparing maritime glaciers Niyang River basin continental Manas basin. For purpose, meteorological predictive derived from monthly ERA5-Land datasets, topographical obtained Randolph Glacier Inventory, along target rooted geodetic observations, were employed drive four selective models: random forest model, gradient boosting decision tree (GBDT) deep neural network ordinary least-square linear regression model. The results highlighted that generally exhibit superior performance compared ones. Moreover, among models, GBDT model was found consistently coefficient determination (R2) values 0.72 0.67 root mean squared error (RMSE) 0.21 m w.e. 0.30 river basins, respectively. Furthermore, reveals climatic differentially influence simulations glaciers, providing key insights into dynamics response change. In summary, ML, particularly demonstrates significant potential simulation. application can enhance accuracy modeling, promising approach assess

Language: Английский

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Inter‐comparison and validation of high‐resolution surface air temperature reanalysis fields over Italy

International Journal of Climatology, Journal Year: 2024, Volume and Issue: 44(8), P. 2681 - 2700

Published: May 10, 2024

Abstract Surface air temperature (t2m) data are essential for understanding climate dynamics and assessing the impacts of change. Reanalysis products, which combine observations with retrospective short‐range weather forecasts, can provide consistent comprehensive datasets. ERA5 represents state‐of‐the‐art in global reanalyses supplies initial boundary conditions higher‐resolution regional designed to capture finer‐scale atmospheric processes. However, these products require validation, especially complex terrains like Italy. This study analyses capability different reanalysis reproduce t2m fields over Italy during 1991–2020 period. The encompass ERA5, ERA5‐Land, MEteorological Italian DAtaset (MERIDA), Copernicus European Regional ReAnalysis (CERRA), Very High‐Resolution dynamical downscaling REAnalysis ITaly (VHR‐REA_IT). validation we conduct pertains both spatial distribution 30‐year seasonal annual normal values daily anomaly records. Each is compared projected onto its respective grid positions elevations, overcoming any model bias resulting from an inaccurate representation real topography. Key findings reveal that closely match observational values, deviations typically below 1°C. Alps, winter cold biases sometimes exceed 3°C show a relation elevation. Similar occur Apennines, Sicily, Sardinia. Conversely, VHR‐REA_IT shows warm Po Valley up summer. Daily anomalies generally exhibit lower errors, MERIDA showing highest accuracy correlation fields. Moreover, when aggregating time scales, errors records rapidly decrease <0.5°C. results this empower users across multiple sectors gain more profound insight into capabilities constraints products. knowledge characterization against indeed be crucial incorporating their research practical applications.

Language: Английский

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