A5017206929- Climate variability and models
- Meteorological Phenomena and Simulations
- Hydrology and Watershed Management Studies
- Hydrology and Drought Analysis
- Soil Moisture and Remote Sensing
- Precipitation Measurement and Analysis
- Cryospheric studies and observations
- Geophysics and Gravity Measurements
- Hydrological Forecasting Using AI
- Energy Load and Power Forecasting
- Climate change and permafrost
- Soil Geostatistics and Mapping
- Plant Water Relations and Carbon Dynamics
- Geology and Paleoclimatology Research
- Atmospheric and Environmental Gas Dynamics
- Climate change impacts on agriculture
- demographic modeling and climate adaptation
- Neural Networks and Applications
- Innovations in Educational Methods
- Pleistocene-Era Hominins and Archaeology
- Environmental Changes in China
- Forecasting Techniques and Applications
- Water resources management and optimization
- 3D Modeling in Geospatial Applications
- Tropical and Extratropical Cyclones Research
University of Kansas
2015-2025
University of Chinese Academy of Sciences
2019
Nanjing University of Information Science and Technology
2019
Czech Academy of Sciences, Institute of Atmospheric Physics
2019
Chinese Academy of Sciences
2019
China Meteorological Administration
2019
Northeast Climate Science Center
2016
University of Massachusetts Amherst
2016
Princeton University
2011-2015
Goddard Space Flight Center
2014-2015
Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing resources sustainability; and flood, drought, climate change prediction. These needs have motivated the development of pilot monitoring prediction systems for hydrologic vegetative states, but date only at rather coarse spatial resolutions (∼10–100 km) over continental domains. Adequately addressing critical cycle science questions requires that...
Abstract Land–atmosphere (L-A) interactions are a main driver of Earth’s surface water and energy budgets; as such, they modulate near-surface climate, including clouds precipitation, can influence the persistence extremes such drought. Despite their importance, representation L-A in weather climate models remains poorly constrained, involve complex set processes that difficult to observe nature. In addition, complete understanding requires interdisciplinary expertise approaches transcend...
Abstract There is a long history of debate on the usefulness climate model–based seasonal hydroclimatic forecasts as compared to ensemble streamflow prediction (ESP). In this study, authors use NCEP's operational forecast system, Climate Forecast System version 2 (CFSv2), and its previous version, CFSv1, investigate value models by conducting set 27-yr hindcasts over conterminous United States (CONUS). Through Bayesian downscaling, have higher squared correlation R2 smaller error than ESP...
The spatial heterogeneity of soil moisture remains a persistent challenge in the design situ measurement networks, downscaling coarse estimates (e.g., satellite retrievals), and hydrologic modeling.To address this challenge, we analyze high-resolution (9 m) simulated fields over Little River Experimental Watershed (LREW) Georgia, USA, to assess role interaction controls moisture.We calibrate validate TOPLATS distributed model with high moderate resolution land meteorological data sets...
Abstract Seasonal hydrologic extremes in the form of droughts and wet spells have devastating impacts on human natural systems. Improving understanding predictive capability extremes, facilitating adaptations through establishing climate service systems at regional to global scales are among grand challenges proposed by World Climate Research Programme (WCRP) core themes Regional Hydroclimate Projects (RHP) under Global Energy Water Cycle Experiment (GEWEX). An experimental seasonal...
Abstract Droughts represent a significant source of social and economic damage in the southeast United States. Having sufficient warning these extreme events enables managers to prepare for potentially mitigate severity their impacts. A seasonal hydrologic forecast system can provide such warning, but current skill is low during convective season when precipitation affected by regionally varying land surface heat flux contributions. Previous studies have classified regions into coupling...
Northeast and Midwest, United States. Assessing the climate change impacts on basin scale is important for water natural resource managers. Here, presence of monotonic trends changes in climate-driven simulated 3-day peak flows, 7-day low mean base flows are evaluated Midwest U.S. during 20th 21st centuries using projections from sixteen models. Proven statistical methods used to spatially temporally disaggregate precipitation temperature fields a finer resolution before being as drivers...
Abstract The potential effects of climate change on the snowpack northeastern and upper Midwest United States are assessed using statistically downscaled projections from an ensemble 10 models a macroscale hydrological model. Climate simulations for region indicate warmer-than-normal temperatures wetter conditions snow season (November–April) during twenty-first century. However, despite projected increases in seasonal precipitation, significant negative trends water equivalent (SWE) found...
Abstract The coupling of the land with planetary boundary layer (PBL) on diurnal time scales is critical to regulating strength connection between soil moisture and precipitation. To improve understanding land–atmosphere (L–A) interactions, recent studies have focused development diagnostics quantify accuracy land–PBL at process level. In this paper, authors apply a suite local (LoCo) metrics modern reanalysis (RA) products observations during 17-yr period over U.S. southern Great Plains....
Northeast China (NEC) suffered a severe drought that persisted from March to July of 2017 with profound impacts on agriculture and society, raising an urgent need understand the mechanism for persistent droughts over midlatitudes. Previous studies focused either large-scale teleconnections or local land–atmosphere coupling, while less attention was paid their synergistic effects persistence. Here we show NEC triggered by strong positive phase Arctic Oscillation in March, maintained...
Feedbacks between the land and atmosphere can play an important role in water cycle a number of studies have quantified Land-Atmosphere (L-A) interactions feedbacks through observations prediction models. Due to complex nature L-A interactions, observed variables are not always available at needed temporal spatial scales. This work derives Coupling Drought Index (CDI) solely from satellite data evaluates input resultant CDI against in-situ reanalysis products. NASA's AQUA retrievals soil...
The impact of extreme climate events, especially prolonged drought, on ecosystem response, can influence the land-atmosphere interactions and modify local regional weather climate. To investigate vegetation dynamics simulation energy, water, carbon exchange at land surface streamflow, during drought conditions, we compared performance multiple versions Noah- multiparameterization (MP) model (both Noah-MP LSM, version 3.6 4.0.1) with default configurations as well various physics options,...
Abstract The multimodel Global Land–Atmosphere Coupling Experiment (GLACE) identified the semiarid Southern Great Plains (SGP) as a hotspot for land–atmosphere (LA) coupling and, consequently, land-derived temperature and precipitation predictability. area including surrounding U.S. Department of Energy Atmospheric Radiation Measurement (ARM) SGP Climate Research Facility has in particular been well studied context LA coupling. Observation-based studies suggest signal that is much weaker...
Abstract HEART is a university‐led alliance of institutions, agencies, and industries committed to voicing the needs states in central land area US advancing research develop innovative environmental solutions that strengthen communities support policymakers improve lives livelihoods people across Heartland. The Heartland “Breadbasket” Nation home nation's largest aquifer river basin. However, highly vulnerable impacts our changing environment. aims leverage amplify existing strengths...
ABSTRACT In recent years, numerous flood events have caused loss of life, widespread disruption, and damage across the globe. These devastating impacts highlight importance a better understanding generating processes, their impacts, variability under climate landscape changes. Here, we argue that ability to model flooding is underpinned by grand challenge generation mechanisms potential impacts. To address this challenge, World Meteorological Organization‐Global Energy Water Exchanges...
WATER RESOURCES RESEARCH, VOL. 48, W01802, doi:10.1029/2011WR011202, 2012 Reply to comment by Keith J. Beven and Hannah L. Cloke on ‘‘Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth’s terrestrial water’’ Eric F. Wood, 1 Joshua K. Roundy, Tara Troy, Rens van Beek, 2 Marc Bierkens, Eleanor Blyth, 3 Ad de Roo, 4 Petra Doll, 5 Mike Ek, 6 James Famiglietti, 7 David Gochis, 8 Nick Giesen, 9 Paul Houser, 10 Peter Jaffe, Stefan Kollet, 11 Bernhard Lehner,...
Abstract Drought has significant social and economic impacts that could be reduced by preparations made possible through seasonal prediction. During the convective season, when potential of extreme drought is highest, soil moisture can provide a means improved predictability land–atmosphere interactions. In past decade, there been amount work aimed at better understanding One such approach classifies interactions between land atmosphere into coupling states. The states have shown to...
Abstract Hydrologic extremes in the form of flood and drought have large impacts on society that can be reduced through preparations made possible by seasonal prediction. However, skill predictions from global climate models is uncertain, which severely limits their practical use. In past, assessment has been limited to a single temporal or spatial resolution for short hindcast period, prone sampling errors, noise leads uncertainty. this work framework uses “canonical” forecast events,...
Abstract This study aims to understand the role of near-surface temperatures in predicting US climatic extremes using North American Multi-Model Ensemble (NMME) system. Here, forecasting skill was measured by anomaly correlation coefficient (ACC) between observed and forecasted precipitation (PREC)/2-meter air temperature (T2m) anomalies over contiguous United States (CONUS) during 1982–2012. The strength T2m–PREC coupling ACC PREC T2m or CONUS. We also assessed NMME for summers 2004...