Accurate characterization of vineyard-scale climate is essential for understanding grapevine development, yield formation, and wine quality. However, climate analyses in viticulture are still largely based on interpolated macroclimate datasets, which...
Incomplete climate records pose a major challenge to decision makers that utilize climate data as one of their main inputs. In this study, different climate data infilling methods (arithmetic averaging, inverse distance weighting, UK traditional, nor...
Triggering hydrological simulations with climate change gridded datasets is one of the prevailing approaches in climate change impact assessment at a river basin scale, with bias correction and spatio-temporal interpolation being functions routinely...
The creation of realistic gridded precipitation fields improves our understanding of the observed climate and is necessary for validating climate model output for a wide range of applications. The challenge in trying to represent the highly variable...
Missing values may arise in climate data collection due to sensor malfunction, transmission errors, device calibration and operational issues. This problem can be more catastrophic in the case of multi-dimensional and high-frequency climate data sets...
The distributed measured data in large regions and remote locations, along with a need to estimate climatic data for point sites where no data have been recorded, has encouraged the implementation of spatial interpolation techniques. Recently, the in...
Missing data in precipitable water vapor derived from global navigation satellite systems (GNSS-PWV) is commonly a large hurdle in climatical applications, since continuous PWV is an important prerequisite. Interpolation using principal component ana...
Rainfall data at fine spatial resolutions are often required for various studies in hydrology and water resources. However, such data are not widely available, as their collection is normally expensive and time-consuming. A common practice to obtain...
Uniform grid data are widely used in climate science and related interdisciplinary fields. Such data usually describe the hydrometeorological states averaged over uniform latitude–longitude grids. While these data have larger grid areas in the...
Accurate climate data at fine spatial resolution are essential for scientific research and the development and planning of crucial social systems, such as energy and agriculture. Among them, sea surface temperature plays a critical role as the associ...
For building environments, meteorological factors such as daily mean temperature, extreme temperature and seasonal temperature changes, are essential, as they impact building structures significantly. Due to the importance of detailed and accurate te...
Satellite aerosol products are pivotal in studies of regional air quality and global climate change. Compared with accurate in situ observations, satellite measurements provide valuable large-scale atmospheric information. However, limitations such a...
Pavement deterioration is influenced by various factors with degradation rates varying widely depending on the type of pavement, its use, and the environment in which it is located. In Nepal, where the climate varies from alpine to subtropical monsoo...
The extensive use of high-resolution digital elevation data, along with continuous improvements in computing power and geographic information system (GIS) tools. Has driven the development of spatial data processing, management, and spatial interpola...
The intercomparison between different atmospheric monitoring systems is key for instrument calibration and validation. Common cases involve satellites, radiosonde and atmospheric model outputs. Since instruments and/or measures are not perfectly coll...
This article proposes new values and geospatial models of winter and summer external design temperatures for designing buildings’ heating, ventilation, and air-conditioning (HVAC) systems. The climatic design parameters applicable in Poland for...
Accurate and precise prediction of actual evapotranspiration (AET) on a large scale is a fundamental issue in natural sciences such as forestry (especially in species selection and planning), hydrology, and agriculture. With the estimation of AET, co...
The ability to produce high-resolution climate maps is crucial for assessing climate change impacts and mitigating climate disasters and risks in developing countries. Mainstream geostatistical downscaling techniques use spatial interpolation or mult...
The evaluation of bioclimatic viticulture indices (BVIs) zones, similar to any other crop, necessitates a comprehensive understanding of the spatial variability of climate data. This study focuses on assessing the suitability of BVIs in the Jabal Al...
The global tropospheric zenith delay grid products of VMF1 and VMF3 (Vienna mapping functions) with different resolutions are used to calculate the tropospheric zenith delay of eight IGS (International GNSS Service) stations in China, and the accurac...
The accurate evaluation of shifts in vegetation phenology is essential for understanding of vegetation responses to climate change. Remote-sensing vegetation index (VI) products with multi-day scales have been widely used for phenology trend estimati...
Surface shortwave (SW) irradiation is the primary driving force of energy exchange in the atmosphere and land interface. The global climate is profoundly influenced by irradiation changes due to the special climatic condition in Antarctica. Remote-se...
The comfort level of air temperature in a region is one of the influencing factors that affect tourists’ choice of tourism purpose. As a national red cultural mecca, the study of air temperature in Jiangxi Province can provide an important scie...
The precise interpolation of oceanic temperature and salinity is crucial for comprehending the dynamics of marine systems and the implications of global climate change. Prior neural network-based interpolation methods face constraints related to thei...
In this article, the interpolation of daily data of global solar irradiation, and the maximum, average, and minimum temperatures were measured. These measurements were carried out in the agrometeorological stations belonging to the Agro-climatic Info...
Sunshine duration is an important variable that is widely used in atmospheric energy balance studies, analysis of the thermal loadings on buildings, climate research, and the evaluation of agricultural resources. In most cases, it is calculated using...
The ability to obtain accurate precipitation data from various geographic locations is crucial for many applications. Various global products have been released in recent decades for estimating precipitation spatially and temporally. Nevertheless, it...
Sustainable precision agriculture requires site-specific management procedures. This needs appropriate information combining traditional measured data and mapped conditions, models, and specific interpretation. It is impossible to cover the entire va...
Subglacial topography is a critical boundary condition for ice sheet models projecting past and future ice sheet–climate interactions. Contemporary ice-sheet-wide bed topography datasets are partially derived using mass conservation, but approx...
Meteorological observations are essential for climate modelling, prediction, early warning systems, decision-making processes, and disaster management. These observations are critical to societal development and the safeguarding of human activities a...
Despite the sparse distribution of meteorological stations and issues with missing data, vector-borne disease studies in Ethiopia have been commonly conducted based on the relationships between these diseases and ground-based in situ measurements of...
Mapping wall-to-wall forest aboveground biomass (AGB) at large scales is critical for understanding global climate change and the carbon cycle. In previous studies, a regression-based method was commonly used to map the spatially continuous distribut...
As the largest and most important natural terrestrial ecosystem, forest plays a crucial role in reducing the concentrations of greenhouse gases in the atmosphere, mitigating global warming, maintaining the global ecological balance, and promoting glo...
Phytoplankton phenology studies require a dataset that is continuous in time and space since missing data have been shown to affect the accuracy of seasonality metrics. The interpolated GlobColour product provided by the Copernicus Marine Environment...
The purpose of our work is to leverage the use of artificial intelligence for the emergence of smart greenhouses. Greenhouse agriculture is a sustainable solution for food crises and therefore data-based decision-support mechanisms are needed to opti...
The sea surface temperature (SST) is essential data for the ocean and atmospheric prediction systems and climate change studies. Five global gridded sea surface temperature products were evaluated with independent in situ SST data of the Yellow Sea (...
Thermal simulations of buildings play a critical role in optimizing energy efficiency, thermal comfort, and heating, ventilation and air conditioning (HVAC) systems design. Accurate weather data is essential for reliable simulations, as local weather...
This study evaluates the choice of the meteorological data set in the simulation of the streamflow of a Mexican basin, in the bias correction of climate simulations, and in the climate change impact on hydrological indicators. The selected meteorolog...
Simulating the hydrological process of a river basin helps to understand the evolution of water resources in the region and provides scientific guidance for water resources allocation policies between different river basins and water resources manage...
In Italy, the calculation of the energy needs of buildings has been mainly based on quasi-steady state calculation procedures. Nowadays, the increasing interest in more detailed energy analysis for high-efficiency buildings requires more accurate cal...
The Amazon Rainforest is highlighted by the global community both for its extensive vegetation cover that constantly suffers the effects of anthropic action and for its substantial biodiversity. This dataset presents data of meteorological variables...
Month-to-month air temperature (Tair) surfaces are increasingly demanded to feed quantitative models related to a wide range of fields, such as hydrology, ecology or climate change studies. Geostatistical interpolation techniques provide such continu...
The available wind power resource worldwide at altitudes between 500 and 12,000 m above ground is assessed for the first time. Twenty-eight years of wind data from the reanalyses by the National Centers for Environmental Prediction and the Department...
Amid accelerating global climate change, research quantifying the uncertainty of mountain ecosystems in relation to CMIP6 multi-model ensemble (MME) simulations remains limited. This study addresses this gap by evaluating future temperature and preci...
Surface ocean dynamics play a key role in the Earth system, contributing to regulate its climate and affecting the marine ecosystem functioning. Dynamical processes occur and interact in the upper ocean at multiple scales, down to, or even less than,...
The assessment of the hydrological functions of landscapes and the landscape–hydrological background is an important instrument for minimizing damage from rivers and preventing water conflicts under conditions of data scarcity for hydrological...
Hydrological modeling is essential for runoff simulations in line with climate studies, especially in remote areas with data scarcity. Advancements in climatic precipitation datasets have improved the accuracy of hydrological modeling. This research...
Precipitation records from meteorological stations frequently contain gaps caused by sensor, power, or transmission failures, creating uncertainty in hydrological, agricultural, and water-resources applications. This study compared two simple baselin...
This study examines the spatial associations between climatic conditions and construction land in China during 2000–2020. Using construction land data from CNLUCC and spatially interpolated meteorological data, five climatic indicators were sel...
Monitoring ecosystems at regional or continental scales is paramount for biodiversity conservation, climate change mitigation, and sustainable land management. Effective monitoring requires satellite imagery with both high spatial resolution and high...
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