skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: A probabilistic drought forecasting framework: A combined dynamical and statistical approach

Abstract

In order to improve drought forecasting skill, this study develops a probabilistic drought forecasting framework comprised of dynamical and statistical modeling components. The novelty of this study is to seek the use of data assimilation to quantify initial condition uncertainty with the Monte Carlo ensemble members, rather than relying entirely on the hydrologic model or land surface model to generate a single deterministic initial condition, as currently implemented in the operational drought forecasting systems. Next, the initial condition uncertainty is quantified through data assimilation and coupled with a newly developed probabilistic drought forecasting model using a copula function. The initial condition at each forecast start date are sampled from the data assimilation ensembles for forecast initialization. Finally, seasonal drought forecasting products are generated with the updated initial conditions. This study introduces the theory behind the proposed drought forecasting system, with an application in Columbia River Basin, Pacific Northwest, United States. Results from both synthetic and real case studies suggest that the proposed drought forecasting system significantly improves the seasonal drought forecasting skills and can facilitate the state drought preparation and declaration, at least three months before the official state drought declaration.

Authors:
ORCiD logo; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1347861
Report Number(s):
PNNL-SA-123469
Journal ID: ISSN 0022-1694
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Hydrology; Journal Volume: 548
Country of Publication:
United States
Language:
English
Subject:
data assimilation; particle markov chain monte carlo; initial condition uncertainity; probablistic drought forecasting

Citation Formats

Yan, Hongxiang, Moradkhani, Hamid, and Zarekarizi, Mahkameh. A probabilistic drought forecasting framework: A combined dynamical and statistical approach. United States: N. p., 2017. Web. doi:10.1016/j.jhydrol.2017.03.004.
Yan, Hongxiang, Moradkhani, Hamid, & Zarekarizi, Mahkameh. A probabilistic drought forecasting framework: A combined dynamical and statistical approach. United States. doi:10.1016/j.jhydrol.2017.03.004.
Yan, Hongxiang, Moradkhani, Hamid, and Zarekarizi, Mahkameh. Mon . "A probabilistic drought forecasting framework: A combined dynamical and statistical approach". United States. doi:10.1016/j.jhydrol.2017.03.004.
@article{osti_1347861,
title = {A probabilistic drought forecasting framework: A combined dynamical and statistical approach},
author = {Yan, Hongxiang and Moradkhani, Hamid and Zarekarizi, Mahkameh},
abstractNote = {In order to improve drought forecasting skill, this study develops a probabilistic drought forecasting framework comprised of dynamical and statistical modeling components. The novelty of this study is to seek the use of data assimilation to quantify initial condition uncertainty with the Monte Carlo ensemble members, rather than relying entirely on the hydrologic model or land surface model to generate a single deterministic initial condition, as currently implemented in the operational drought forecasting systems. Next, the initial condition uncertainty is quantified through data assimilation and coupled with a newly developed probabilistic drought forecasting model using a copula function. The initial condition at each forecast start date are sampled from the data assimilation ensembles for forecast initialization. Finally, seasonal drought forecasting products are generated with the updated initial conditions. This study introduces the theory behind the proposed drought forecasting system, with an application in Columbia River Basin, Pacific Northwest, United States. Results from both synthetic and real case studies suggest that the proposed drought forecasting system significantly improves the seasonal drought forecasting skills and can facilitate the state drought preparation and declaration, at least three months before the official state drought declaration.},
doi = {10.1016/j.jhydrol.2017.03.004},
journal = {Journal of Hydrology},
number = ,
volume = 548,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2017},
month = {Mon May 01 00:00:00 EDT 2017}
}
  • The authors extract a universal deformation-dependent reduced-friction coefficient of the fission mode by analyzing experimental data with a combined dynamical (Langevin) and statistical model. They successfully describe excitation functions of neutron (and charged particle) multiplicities and fission (respectively survival) probabilities. They stress, in particular, the sensitivity of the friction coefficient on evaporation-residue cross sections and prescission {gamma}-multiplicities. A comparison of their results with related work is also performed. 35 refs., 5 figs.
  • A negative feedback of vegetation cover on subsequent annual precipitation is simulated for the mid-Holocene over North Africa using a fully coupled general circulation model with dynamic vegetation, FOAM-LPJ (Fast Ocean Atmosphere Model-Lund Potsdam Jena Model). By computing a vegetation feedback parameter based on lagged autocovariances, the simulated impact of North African vegetation on precipitation is statistically quantified. The feedback is also dynamically assessed through initial value ensemble experiments, in which North African grass cover is initially reduced and the climatic response analyzed. The statistical and dynamical assessments of the negative vegetation feedback agree in sign and relative magnitude formore » FOAM-LPJ. The negative feedback on annual precipitation largely results from a competition between bare soil evaporation and plant transpiration, with increases in the former outweighing reductions in the latter given reduced grass cover. This negative feedback weakens and eventually reverses sign over time during a transient simulation from the mid-Holocene to present. A similar, but weaker, negative feedback is identified in Community Climate System Model Version 2 (CCSM2) over North Africa for the mid-Holocene.« less
  • Real-time monitoring and predicting drought development with several months in advance is of critical importance for drought risk adaptation and mitigation. In this paper, we present a drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity (VIC) hydrologic model over Southwest China (SW). The satellite precipitation data are used to force VIC model for near real-time estimate of land surface hydrologic conditions. As initialized with satellite-aided monitoring, the climate model-based forecast (CFSv2_VIC) and ensemble streamflow prediction (ESP)-based forecast (ESP_VIC) are both performed and evaluated through their ability in reproducing the evolution of the 2009/2010 severe drought overmore » SW. The results show that the satellite-aided monitoring is able to provide reasonable estimate of forecast initial conditions (ICs) in a real-time manner. Both of CFSv2_VIC and ESP_VIC exhibit comparable performance against the observation-based estimates for the first month, whereas the predictive skill largely drops beyond 1-month. Compared to ESP_VIC, CFSv2_VIC shows better performance as indicated by the smaller ensemble range. This study highlights the value of this operational framework in generating near real-time ICs and giving a reliable prediction with 1-month ahead, which has great implications for drought risk assessment, preparation and relief.« less
  • Five-year-old ponderosa (Pinus ponderosa Laws.) seedlings from 18 half-sib and one full-sib families obtained from the California Tree Improvement Program were harvested after 1, 2, and 3 growing seasons of exposure to three levels of ozone (O{sub 3}) and two levels of available soil water (ASW) in open-top chambers in the California Sierras. Seedlings were evaluated for O{sub 3} injury symptoms, biomass, and radial growth in response to these stresses. Ozone injury responses were highly variable across families, but family rankings for O{sub 3} injury were consistent across years. Family rankings for O{sub 3} injury were highly correlated with thosemore » for reductions in biomass and radial growth for trees in the high ASW treatment, but drought-stressed trees showed no consistent relation between foliar 03 injury and reductions in growth. After three seasons of exposure to 88 ppb O{sub 3}, foliar biomass of the three most susceptible families averaged 60% less than trees in the low-O{sub 3} control, while O{sub 3} had no effect on growth of the three most resistant families. Variability across families of growth responses to drought was significantly less than the variability in seedling responses to O{sub 3}.« less