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| Title | Year Sort ascending | Author | Topic | Dataset |
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| Hydrometeor Identification Using GMI Passive Microwave Brightness Temperatures | Cecil, Daniel J., Solomon, Michael B., Mecikalski, Retha, Leppert, Kenneth D. | Atmospheric Water Vapor, Precipitation, Brightness Temperature, Radar Reflectivity, Precipitation Rate | ||
| Hydrometeorological Trends in a Low-Gradient Forested Watershed on the Southeastern Atlantic Coastal Plain in the USA | Amatya, Devendra M., Callahan, Timothy J., Mukherjee, Sourav, Harrison, Charles A., Trettin, Carl C., Waega, Andrzej, Mynski, Dariusz, Emmett, Kristen D. | Forests, Fire Disturbance, Deforestation, Wildfires | ||
| Hydrometric data discretization into environmental flow components: a new, practical approach to explore concentration-discharge relationships | Ariano, Sarah S., Ali, Genevieve | Maximum/Minimum Temperature, 24 Hour Precipitation Amount, Snow Water Equivalent, Shortwave Radiation, Vapor Pressure, Carbon, Soil Ph, Cation Exchange Capacity, Soil Bulk Density, Soil Depth | ||
| Identifying and correcting interferences to PTR-ToF-MS measurements of isoprene and other urban volatile organic compounds | Coggon, Matthew M., Stockwell, Chelsea E., Claflin, Megan S., Pfannerstill, Eva Y., Xu, Lu, Gilman, Jessica B., Marcantonio, Julia, Cao, Cong, Bates, Kelvin, Gkatzelis, Georgios I., Lamplugh, Aaron, Katz, Erin F., Arata, Caleb, Apel, Eric C., Hornbrook, Rebecca S., Piel, Felix, Majluf, Francesca, Blake, Donald R., Wisthaler, Armin, Canagaratna, Manjula, Lerner, Brian M., Goldstein, Allen H., Mak, John E., Warneke, Carsten | Air Quality, Atmospheric Carbon Monoxide, Atmospheric Ozone, Sulfur Compounds, Sulfur Dioxide, Trace Gases/Trace Species, Carbon Monoxide, Sulfur Oxides, Nitrogen Dioxide, Nitrogen Oxides, Volatile Organic Compounds, Particulates, Nitrogen Oxides, Atmospheric Chemistry, Nitrogen Compounds, Tropospheric Ozone, Carbon And Hydrocarbon Compounds, Black Carbon, Wind Direction, Wind Speed, Atmospheric Temperature, Atmospheric Pressure, PARTICULATE MATTER (PM 2.5), Particulate Matter (PM 2.5), RELATIVE HUMIDITY | ||
| Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1 | Mahesh, Ankur, O'Brien, Travis A., Loring, Burlen, Elbashandy, Abdelrahman, Boos, William, Collins, William D. | Atmospheric Ozone, Sea Level Pressure, Surface Pressure, U/V Wind Components, U/V Wind Components, Potential Vorticity, Vertical Wind Velocity/Speed, Vertical Profiles, Upper Air Temperature, Air Temperature, Relative Humidity, Specific Humidity, Atmospheric Water Vapor, Cloud Liquid Water/Ice, Altitude, Geopotential Height, Ozone Profiles | ||
| Identifying decadal trends in deweathered concentrations of criteria air pollutants in Canadian urban atmospheres with machine learning approaches | Yao, Xiaohong, Zhang, Leiming | Carbonaceous Aerosols, Nitrogen Oxides, Particulates, Hydrogen Cyanide, Emissions, Non-methane Hydrocarbons/Volatile Organic Compounds, Particulate Matter, Fire Occurrence, Nitrogen Oxides, Sulfur Dioxide, Carbon And Hydrocarbon Compounds | ||
| Identifying Determinants of Spatiotemporal Disparities in Ecological Quality of Mongolian Plateau | Wang, Zhengtong, Song, Yongze, Zhang, Zehua, Lin, Gang, Luo, Peng, Zhang, Xueyuan, Chai, Zhengyuan | Land Use/Land Cover Classification, Photosynthesis, Primary Production, Vegetation Productivity, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) |
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| Identifying indicators of polar bear population status | Rode, Karyn D., Wilson, Ryan R., Crawford, Justin A., Quakenbush, Lori T. | Sea Ice Concentration | ||
| Humid, warm and treed ecosystems show longer timelag of vegetation response to climate | Gao, Xinran, Zhuo, Wen, Gonsamo, Alemu | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | ||
| Hunter-gatherer impact on European interglacial vegetation: A modelling approach | Nikulina, Anastasia, MacDonald, Katharine, Zapolska, Anhelina, Serge, Maria Antonia, Roche, Didier M., Mazier, Florence, Davoli, Marco, Svenning, Jens-Christian, van Wees, Dave, Pearce, Elena A., Fyfe, Ralph, Roebroeks, Wil, Scherjon, Fulco | Land Use/Land Cover Classification | ||
| Hurricane Otis: the costliest and strongest hurricane at landfall on record in Mexico | GarciaFranco, Jorge L., GomezRamos, Octavio, Dominguez, Christian | Atmospheric Water Vapor, Precipitation | ||
| Hy-TeC: a hybrid vision transformer model for high-resolution and large-scale mapping of canopy height | Fayad, Ibrahim, Ciais, Philippe, Schwartz, Martin, Wigneron, Jean-Pierre, Baghdadi, Nicolas, de Truchis, Aurelien, d'Aspremont, Alexandre, Frappart, Frederic, Saatchi, Sassan, Sean, Ewan, Pellissier-Tanon, Agnes, Bazzi, Hassan | Plant Phenology, Canopy Characteristics, Vegetation Cover, Lidar, Topography, Vegetation Height, Digital Elevation/Terrain Model (DEM), LIDAR WAVEFORM, VIEWING GEOMETRY, Terrain Elevation | ||
| Hybrid hydrological modeling for large alpine basins: a semi-distributed approach | Li, Bu, Sun, Ting, Tian, Fuqiang, Tudaji, Mahmut, Qin, Li, Ni, Guangheng | Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Characteristics, Photosynthetically Active Radiation |
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| Hybrid Machine Learning Approach to Zero-Inflated Data Improves Accuracy | Francisco, Micanaldo Ernesto, Carvajal, Thaddeus M., Watanabe, Kozo | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature, Emissivity, Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain |
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| Hybrid Machine Learning Forest Height Estimation from TanDEM-X InSAR | Mansour, Islam, Papathanassiou, Konstantinos, Hansch, Ronny, Hajnsek, Irena | Forests, Plant Characteristics, Canopy Characteristics, Biomass, Terrain Elevation | ||
| Hybrid modeling for grassland productivity prediction: A parametric and machine learning technique for grazing management with applicability to digital twin decision ... | Paruelo, Jose M., Texeira, Marcos, Tomasel, Fernando | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain |
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| Hydro-pedotransfer functions: a roadmap for future development | Weber, Tobias Karl David, Weihermuller, Lutz, Nemes, Attila, Bechtold, Michel, Degre, Aurore, Diamantopoulos, Efstathios, Fatichi, Simone, Filipovic, Vilim, Gupta, Surya, Hohenbrink, Tobias L., Hirmas, Daniel R., Jackisch, Conrad, de Jong van Lier, Quirijn, Koestel, John, Lehmann, Peter, Marthews, Toby R., Minasny, Budiman, Pagel, Holger, van der Ploeg, Martine, Shojaeezadeh, Shahab Aldin, Svane, Simon Fiil, Szabo, Brigitta, Vereecken, Harry, Verhoef, Anne, Young, Michael, Zeng, Yijian, Zhang, Yonggen, Bonetti, Sara | Stratigraphic Sequence, Digital Elevation/Terrain Model (DEM), Soil Depth, Sediments | ||
| Identifying Risk Factors for <i>Stephanofilaria</i>-Caused Ulcerative | Kingori, Edward, Waiguchu, Grace, Ruoro, Mukami, Muriithi, Kenneth, Mumbi, Cecilia, Omondi, Martin, Aminga, Duncan, Angwenyi, Shaleen, Mijele, Domnic, Chiyo, Patrick I. | Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | ||
| Identifying Spatial Determinants of Rice Yields in Main Producing Areas of China Using Geospatial Machine Learning | Wang, Qingyan, Sun, Longzhi, Yang, Xuan | Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | ||
| Identifying the Mechanism of Interaction Between Soil Moisture State and Summertime MCS Initiations in Weakly Forced Synoptic Environments Using Convective-Permitting Simulations | Gaal, Rachel, Kinter, James L., Dirmeyer, Paul A., Singh, Bohar | Precipitation, Brightness Temperature | ||
| Identifying the optimal type and locations of natural water retention measures using spatial modeling and cost-benefit analysis | Tal-maon, Merav, Portman, Michelle E., Broitman, Dani, Housh, Mashor | Runoff, Soil Texture | ||
| Identifying thresholds of time-lag and accumulative effects of extreme precipitation on major vegetation types at global scale | Liu, Min, Wang, Hao, Zhai, Huiliang, Zhang, Xiaochong, Shakir, Muhammad, Ma, Jianying, Sun, Wei | Total Surface Precipitation Rate, Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Precipitation, Precipitation Amount, Precipitation Rate, Snow, Rain |
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| Impact of boundary conditions on the modeled thermal regime of the Antarctic ice sheet | Park, In-Woo, Jin, Emilia Kyung, Morlighem, Mathieu, Lee, Kang-Kun | Surface Temperature, Skin Temperature, Upper Air Temperature, Air Temperature, Atmospheric Winds, Surface Winds, U/V Wind Components, Atmospheric Pressure, Sea Level Pressure, Surface Pressure, Specific Humidity, Total Precipitable Water, Cloud Liquid Water/Ice, Atmospheric Water Vapor, Atmospheric Ozone, Oxygen Compounds, Altitude, Boundary Layer Winds, Ice Velocity | ||
| Impact of boundary layer parameterizations on simulated seasonal | Barman, Neeldip, Gokhale, Sharad, Tiwari, Dewashish | Land Use/Land Cover Classification | ||
| Impact of Canadian wildfires on aerosol and ice clouds in the early-autumn Arctic | Sato, Kazutoshi, Takahashi, Kazu, Inoue, Jun | Carbonaceous Aerosols, Dust/Ash/Smoke, Sulfate Particles, Pressure Thickness, Atmospheric Ozone, Sea Level Pressure, Surface Pressure, U/V Wind Components, U/V Wind Components, Potential Vorticity, Vertical Wind Velocity/Speed, Vertical Profiles, Upper Air Temperature, Air Temperature, Relative Humidity, Specific Humidity, Atmospheric Water Vapor, Cloud Liquid Water/Ice, Altitude, Geopotential Height, Ozone Profiles, Aerosols, Aerosol Extinction, Aerosol Optical Depth/Thickness, Angstrom Exponent, Aerosol Particle Properties, Organic Particles, Sulfur Oxides, Sulfur Compounds, Sulfate, Sulfur Dioxide, Sulfur Oxides, Particulate Matter, Dimethyl Sulfide, Black Carbon, Sea Salt, PARTICULATE MATTER (PM 2.5), PARTICULATE MATTER (PM 10), PARTICULATE MATTER (PM 1.0), Cloud Fraction |
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