A5011603408- Climate variability and models
- Plant Water Relations and Carbon Dynamics
- Hydrology and Watershed Management Studies
- Soil Moisture and Remote Sensing
- Meteorological Phenomena and Simulations
- Hydrological Forecasting Using AI
- Land Use and Ecosystem Services
- Hydrology and Drought Analysis
- Flood Risk Assessment and Management
- Forest Management and Policy
- Oceanographic and Atmospheric Processes
- Ecology and Vegetation Dynamics Studies
- Climate change and permafrost
- Natural Language Processing Techniques
- Agricultural risk and resilience
- Nuclear and radioactivity studies
- Soil and Unsaturated Flow
- Marine and Coastal Research
- Speech and dialogue systems
- Fuzzy Logic and Control Systems
- Geological formations and processes
- Rangeland Management and Livestock Ecology
- Soil Geostatistics and Mapping
- Water-Energy-Food Nexus Studies
- Regional resilience and development
NSF National Center for Atmospheric Research
2023-2024
Auburn University
2018-2024
University of Colorado System
2024
Chinese Academy of Meteorological Sciences
2024
George Mason University
2023
Sichuan University
2021-2023
North China Electric Power University
2020
Abstract Subseasonal prediction fills the gap between weather forecasts and seasonal outlooks. There is evidence that predictability on subseasonal timescales comes from a combination of atmosphere, land, ocean initial conditions. Predictability land often attributed to slowly varying changes in soil moisture snowpack, while sources such as El Niño Southern Oscillation. Here we use set reforecast experiments with CESM2 quantify respective roles conditions skill over land. These reveal...
Forest parks constitute one of the crucial types urban green spaces. Studying cultural ecosystem services (CESs) in forest is critical for ecological conservation and human well-being. Taking Xijiao Park (XFP) Dalian, Liaoning Province, as study area, Latent Dirichlet Allocation (LDA) model was applied to extract latent topic classifications from web text data. An evaluation system established by integrating public participation geographic information (PPGIS) social values (SolVES) model,...
Introduction Glucose-6-phosphate dehydrogenase (G6PD) deficiency has a distinct regional and ethnic heterogeneity in distribution, information on the molecular characteristics of G6PD deficiencies Heze area, Shandong Province, China, is limited. We aimed to explore incidence genetic mutations characteristic enzyme newborns area investigate pathogenicity new mutations. Methods measured activity 114,285 neonates born identified 80 patients with deficiencies. The these were analyzed using...
Earthquakes are one of the most serious natural disasters, threatening ecological balance and security. Ecosystem services (ESs) reflect multiple functions an ecosystem. However, based on catastrophic contributions various factors to ESs recovery have not been previously quantified. We follow after 2008 Wenchuan earthquake gain insight into these processes. To quantify ESs, biophysical models were applied, including scenario simulation Geodetector methods that used explore driving forces....
Abstract Climate change adaptation planning requires a robust understanding of the projected in hydroclimate variability and predictability. We use two large ensemble data sets to quantify land its potential Additionally, we “reddened El Niño‐Southern Oscillation (ENSO)” framework that partitions annually averaged root‐zone soil moisture into ENSO, surface memory, internal understand drivers changes Even when global warming is increase ENSO teleconnected precipitation over North America,...
Abstract In mid-June to July 2023, North China witnessed extreme heatwaves, marked by intense near-surface warming with an advanced seasonal cycle of local air temperature. An unconventional upper-tropospheric cold vortex in early June, deviating from conventional “heat dome” patterns, preceded the heatwave extremes. The zonal SSTA gradient Indo-Pacific warm pool initially suppressed Indian summer monsoon convection, which stimulated around via a tropical-extratropical teleconnection. This...
Subseasonal prediction fills the gap between weather forecasts and seasonal outlooks. There is evidence that predictability on subseasonal timescales comes from a combination of atmosphere, land, ocean initial conditions. Predictability land often attributed to slowly varying changes in soil moisture snowpack, while sources such as El Niño Southern Oscillation. Here we use unique set reforecast experiments with CESM2 quantify respective roles conditions skill over land. These reveal...
The Grain for Green Program (GFGP) is an important policy implemented by the Chinese government to restore degraded forests. However, there a limited understanding of eco-economic benefits GFGP in Sichuan province. In this study, ecosystem service value (ESV) from 2001 2019 was evaluated dynamically based on improved equivalent method. Then, impact climate and human activities ESV explored. Finally, benefit model afforestation constructed calculate its efficiency 183 counties return rate...
Abstract The signal-to-noise ratio paradox is interpreted as the climate model’s ability to predict observations better than model itself. This view counterintuitive, given that models are simplified numerical representations of complex earth system dynamics. A revised interpretation provided here: represents excessive noise in predictions and projections. Noise potentially reducible, providing a scientific basis for improving signal regional was assessed long-term projections using...
Abstract This study investigates the potential predictability of streamflow and soil moisture in Alabama–Coosa–Tallapoosa (ACT) river basin southeastern United States. The employs state-of-the-art National Water Model (NWM) compares effects initial condition with those seasonal climate anomalies on forecast skills. We have designed implemented ensemble experiments following methodology suggested by Dirmeyer et al. also variability NWM situ measurements remote sensing data from Soil Moisture...
Abstract This study conducts a robust assessment of the Coupled Model Intercomparison Project Phase 6 to capture observed temperature trends and variability at global regional scales. The warming rate in second half twentieth century (0.19°C/decade) is twice as large full analysis period (1901–2014; 0.10°C/decade). Multidecadal climate results considerable uncertainties trend, but multidecadal does not represent statistically significant trend. Globally, spatial pattern most similar among...
Abstract The National Oceanic and Atmospheric Administration has developed a very high-resolution streamflow forecast using Water Model (NWM) for 2.7 million stream locations in the United States. However, considerable challenges exist quantifying uncertainty at ungauged reliability. A data science approach is presented to address challenge. long-range daily forecasts are analyzed from December 2018 August 2021 Alabama Georgia. evaluated 389 observed USGS gauging standard deterministic...
<title>Abstract</title> We assess the relative contributions of land, atmosphere, and oceanic initializations to forecast skill root zone soil moisture (SM) utilizing Community Earth System Model version 2 Sub-seasonal climate experiments (CESM2-SubX). Using eight sensitivity experiments, we disentangle individual impacts these three components their interactions on skill, quantified using anomaly correlation coefficient. The SubX experiment, in which land states are realistically...
Soil moisture is crucial for agriculture and hydrology, but its accurate prediction challenging due to inadequate representation of various complex land surface processes meteorological influences. In this research, we employ the Long Short-Term Memory (LSTM) framework, a specific architecture deep learning networks that effective in processing time series data, predicting soil moisture. We have developed Next Generation Interactive Moisture Forecasting System advance skillful predictions at...
Abstract Subseasonal prediction fills the gap between weather forecasts and seasonal outlooks. There is evidence that predictability on subseasonal timescales comes from a combination of atmosphere, land, ocean initial conditions. Predictability land often attributed to slowly varying changes in soil moisture snow pack, while sources such as El Niño Southern Oscillation. Here we use unique set reforecast experiments quantify respective roles conditions skill over land. The majority for...
Abstract We establish a Multiple Linear Regression Model to study the relationship between climate change and national vulnerability. Meanwhile, put forward state driven interventions estimate total cost reduce