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Aging water infrastructure in the United States (U.S.) is a growing concern. In the U.S., over 90,000 dams were registered in the 2018 National Inventory of Dams (NID) database, and their average age was 57 years old. Here, we aim to assess spatiotemporal patterns of the growth of artificial water storage of the existing dams and their hazard potential and potential economic benefit. In this study, we use more than 70,000 NID-registered dams to assess the cumulative hazard potential of dam failure in terms of the total number and the cumulative maximum storage of dams over the 12 National Weather Service River Forecast Center (RFC) regions. In addition, we also estimate potential economic benefits of the existing dams based on their cumulative storage capacity. Results show that the ratios of the cumulative storage capacity to the long-term averaged precipitation range from 8% (Mid-Atlantic) to 50% (Colorado), indicating the significant anthropogenic contribution to the land surface water budget. We also find that the cumulative storage capacity of the dams with high (probable loss of human life is if the dam fails) and significant (potential economic loss and environmental damage with no probable casualty) hazard potential ranges from 50% (North Central) to 98% (Missouri and Colorado) of the total storage capacity within the corresponding region. Surprisingly, 43% of the dams with either high or significant potential hazards have no Emergency Action Plan. Potential economic benefits from the existing dams range from $0.7 billion (Mid Atlantic) to $15.4 billion (West Gulf). Spatiotemporal patterns of hazard potential and economic benefits from the NID-registered dams indicate a need for the development of region-specific preparation, emergency, and recovery plans for dam failure. This study provides an insight about how big data, such as the NID database, can provide actionable information for community resilience toward a safer and more sustainable environment.
Junho Song; Madden Sciubba; JongHun Kam. Risk and Impact Assessment of Dams in the Contiguous United States Using the 2018 National Inventory of Dams Database. Water 2021, 13, 1066 .
AMA StyleJunho Song, Madden Sciubba, JongHun Kam. Risk and Impact Assessment of Dams in the Contiguous United States Using the 2018 National Inventory of Dams Database. Water. 2021; 13 (8):1066.
Chicago/Turabian StyleJunho Song; Madden Sciubba; JongHun Kam. 2021. "Risk and Impact Assessment of Dams in the Contiguous United States Using the 2018 National Inventory of Dams Database." Water 13, no. 8: 1066.
This study used the North American Multi-Model Ensemble (NMME) system to understand the role of near surface temperature in the prediction skill for US climate extremes. In this study, the forecasting skill was measured by anomaly correlation coefficient (ACC) between the observed and forecasted precipitation (PREC) or 2-meter air temperature (T2m) over the contiguous United States (CONUS) during 1982–2012. The strength of the PREC-T2m coupling was measured by ACC between observed PREC and T2m or forecasted PREC and T2m over the CONUS. This study also assessed the NMME forecasting skill for the summers of 2004 (spatial anomaly correlation between PREC and T2m: 0.05), 2011 (-0.65), and 2012 (-0.60) when the PREC-T2m coupling is weaker or stronger than the 1982–2012 climatology (ACC:-0.34). This study found that most of the NMME models show stronger (negative) PREC-T2m coupling than the observed coupling, indicating that they fail to reproduce interannual variability of the observed PREC-T2m coupling. Some NMME models with skillful prediction for T2m show the skillful prediction of the precipitation anomalies and US droughts in 2011 and 2012 via strong PREC-T2m coupling despite the fact that the forecasting skill is year-dependent and model-dependent. Lastly, we explored how the forecasting skill for SSTs over north Pacific and Atlantic Oceans affects the forecasting skill for T2m and PREC over the US. The findings of this study suggest a need for the selective use of the current NMME seasonal forecasts for US droughts and pluvials.
JongHun Kam; Sungyoon Kim; Joshua Roundy. NMME-based Assessment of Prediction Skills of US Summertime Droughts and Pluvials: Role of Near-surface Temperature Prediction Skill. 2021, 1 .
AMA StyleJongHun Kam, Sungyoon Kim, Joshua Roundy. NMME-based Assessment of Prediction Skills of US Summertime Droughts and Pluvials: Role of Near-surface Temperature Prediction Skill. . 2021; ():1.
Chicago/Turabian StyleJongHun Kam; Sungyoon Kim; Joshua Roundy. 2021. "NMME-based Assessment of Prediction Skills of US Summertime Droughts and Pluvials: Role of Near-surface Temperature Prediction Skill." , no. : 1.
Seasonal reconstructions of streamflow are valuable because they provide water planners, policy makers, and stakeholders with information on the range and variability of water resources before the observational period. In this study, we used streamflow data from five gages near the Alabama-Florida border and centuries-long tree-ring chronologies to create and analyze seasonal flow reconstructions. Prescreening methods included correlation and temporal stability analysis of predictors to ensure practical and reliable reconstructions. Seasonal correlation analysis revealed that several regional tree-ring chronologies were significantly correlated (p ≤ 0.05) with March–October streamflow, and stepwise linear regression was used to create the reconstructions. Reconstructions spanned 1203–1985, 1652–1983, 1725–1993, 1867–2011, and 1238–1985 for the Choctawhatchee, Conecuh, Escambia, Perdido, and Pascagoula Rivers, respectively, all of which were statistically skillful (R2 ≥ 0.50). The reconstructions were statistically validated using the following parameters: R2 predicted validation, the sign test, the variance inflation factor (VIF), and the Durbin–Watson (D–W) statistic. The long-term streamflow variability was analyzed for the Choctawhatchee, Conecuh, Escambia, and Perdido Rivers, and the recent (2000s) drought was identified as being the most severe in the instrumental record. The 2000s drought was also identified as being one of the most severe droughts throughout the entire reconstructed paleo-record developed for all five rivers. This information is vital for the consideration of present and future conditions within the system.
Melanie Vines; Glenn Tootle; Leigh Terry; Emily Elliott; Joni Corbin; Grant Harley; JongHun Kam; Sahar Sadeghi; Matthew Therrell. A Paleo Perspective of Alabama and Florida (USA) Interstate Streamflow. Water 2021, 13, 657 .
AMA StyleMelanie Vines, Glenn Tootle, Leigh Terry, Emily Elliott, Joni Corbin, Grant Harley, JongHun Kam, Sahar Sadeghi, Matthew Therrell. A Paleo Perspective of Alabama and Florida (USA) Interstate Streamflow. Water. 2021; 13 (5):657.
Chicago/Turabian StyleMelanie Vines; Glenn Tootle; Leigh Terry; Emily Elliott; Joni Corbin; Grant Harley; JongHun Kam; Sahar Sadeghi; Matthew Therrell. 2021. "A Paleo Perspective of Alabama and Florida (USA) Interstate Streamflow." Water 13, no. 5: 657.
This study aims to understand the role of near surface temperature in the prediction skill for US climate extremes using the North American Multi-Model Ensemble (NMME) system. In this study, the forecasting skill was measured by anomaly correlation coefficient (ACC) between the observed and forecasted precipitation (PREC)/2-meter air temperature (T2m) anomalies over the contiguous United States (CONUS) during 1982–2012. The strength of the PREC-T2m coupling was measured by ACC between observed PREC and T2m or forecasted PREC and T2m over the CONUS. This study also assessed the NMME forecasting skill for the summers of 2004 (spatial anomaly correlation between PREC and T2m: 0.05), 2011 (-0.65), and 2012 (-0.60) when the PREC-T2m coupling was weaker or stronger than the 1982–2012 climatology (ACC:-0.34). This study found that most of the NMME models show stronger PREC-T2m coupling than the observed coupling over 1982–2012, indicating that they failed to reproduce interannual variability of the observed PREC-T2m coupling. Some NMME models show strong PREC-T2m coupling and a skillful prediction for T2m in 2011 and 2012, leading to a skillful prediction of the precipitation deficits despite the fact that the forecasting skill is year-dependent and model-dependent. Most of the NMME models show the limited seasonal forecasting skill of the PREC surplus in 2004 and thus fail to reproduce weak PREC-T2m coupling. Lastly, this study explored how the role of sea surface temperatures in predicting T2m, PREC, and T2m-PREC coupling. The findings of this study suggest a need for the selective use of the current NMME seasonal forecasts for US droughts and pluvials.
JongHun Kam; Sungyoon Kim; Joshua K. Roundy. Did a skillful prediction of near-surface temperatures help or hinder forecasting of the 2012 US drought? Environmental Research Letters 2021, 16, 034044 .
AMA StyleJongHun Kam, Sungyoon Kim, Joshua K. Roundy. Did a skillful prediction of near-surface temperatures help or hinder forecasting of the 2012 US drought? Environmental Research Letters. 2021; 16 (3):034044.
Chicago/Turabian StyleJongHun Kam; Sungyoon Kim; Joshua K. Roundy. 2021. "Did a skillful prediction of near-surface temperatures help or hinder forecasting of the 2012 US drought?" Environmental Research Letters 16, no. 3: 034044.
Earthquake insurance can be a useful tool to build more sustainable societies and disaster-resilient communities. However, the coverage is not common in many countries. This article aims to contribute to the literature through an empirical analysis of the online interest in earthquake insurance through Google Trends. The proposed methodology implies to move from a top-down conceptual approach to a bottom-up/data-enabled one. It allows us to explore potential triggers and dynamic patterns of online interest in earthquake insurance at daily time-scale through the lens of Big Data. In order to validate the methodology, the article considers Italy as a test area. For this country, where the coverage rate is low, we fuse multiple databases to create 16-year daily time series of public search activities about the insurance in Italy and analyse it with other data sources. As a result, the peak analysis shows a connection with the occurrences of large domestic earthquakes, overseas earthquakes, and policy decisions, which create time windows of opportunities for insurers and policymakers to boost the public’s motivation towards the coverages. The research outcomes suggest that the data-enabled approach can additionally be applied in other countries where the coverage rate is low and stakeholders are facing the challenge to strive against earthquake under-insurance.
Fabrizio Terenzio Gizzi; JongHun Kam; Donatella Porrini. Time windows of opportunities to fight earthquake under-insurance: evidence from Google Trends. Humanities and Social Sciences Communications 2020, 7, 1 -11.
AMA StyleFabrizio Terenzio Gizzi, JongHun Kam, Donatella Porrini. Time windows of opportunities to fight earthquake under-insurance: evidence from Google Trends. Humanities and Social Sciences Communications. 2020; 7 (1):1-11.
Chicago/Turabian StyleFabrizio Terenzio Gizzi; JongHun Kam; Donatella Porrini. 2020. "Time windows of opportunities to fight earthquake under-insurance: evidence from Google Trends." Humanities and Social Sciences Communications 7, no. 1: 1-11.
Climate extremes will be intensified and become more frequent. One of the regions where this is the case is the U.S. Gulf coast region. This region is susceptible to the impacts of climate extremes. This region has recently experienced large amounts of economic damages caused by high-impact hurricanes and floods. Meanwhile, drought can also pose serious risks once it occurs. By using a 2019 U.S. Gulf Coast survey combined with Standard Precipitation Index, we closely examined retrospective and prospective evaluations of drought and flood among coastal residents. Drawing upon literature on human-environment system, we were interested in how the objective conditions of past drought and flood influenced individual's perceptions of these hazards and how their retrospective evaluations were correlated with their prospective evaluations of future trends of these hazards. Coastal residents' retrospective evaluations of past drought and flood were found to be influenced by historic objective conditions. Higher drought frequencies were found to increase the probability of perceiving increasing trend of drought number in the past. Higher flood frequencies were found to decrease the probability of perceiving increasing trend of flood number in the past. Higher intensities of drought and flood were found to increase the probabilities of perceiving increasing trends of drought duration and flood amount in the past. Coastal residents' prospective evaluations of future drought and flood were found to be influenced by retrospective evaluations of these hazards, suggesting the temporal continuity in human judgment. Moreover, those who relied on a longer time span in reference to the future were found to be more likely to perceive increasing trends of drought and flood. We ended this paper by proposing a theoretical framework to guide future studies and discussing policy implications.
Wanyun Shao; JongHun Kam. Retrospective and prospective evaluations of drought and flood. Science of The Total Environment 2020, 748, 141155 .
AMA StyleWanyun Shao, JongHun Kam. Retrospective and prospective evaluations of drought and flood. Science of The Total Environment. 2020; 748 ():141155.
Chicago/Turabian StyleWanyun Shao; JongHun Kam. 2020. "Retrospective and prospective evaluations of drought and flood." Science of The Total Environment 748, no. : 141155.
Big data have meaningful, but hidden, information about our society's behavior and response to influential events. Particularly, water-related disasters, such as drought and flood, cause rapid increase in public awareness/interest when they already happen. Despite the improved prediction skill, lack of timely social response to these disasters exacerbates economic losses and fatalities.
In this presentation, I will introduce the utility of Google Trends data in monitoring and understanding the dynamic patterns of social response to drought at the state and national level. The first part of this presentation will show a case study of the dynamics of Californian awareness during the 2011–17 California Drought. The second part of this seminar will show a spatiotemporal analysis of US national drought awareness among the 49 US states. In closing, I will discuss the role of big data in transforming our society to a water-related disaster-ready environment.
JongHun Kam. A Multi-Scale Study of US Drought Awareness. 2020, 1 .
AMA StyleJongHun Kam. A Multi-Scale Study of US Drought Awareness. . 2020; ():1.
Chicago/Turabian StyleJongHun Kam. 2020. "A Multi-Scale Study of US Drought Awareness." , no. : 1.
Drought is a creeping climatological phenomenon with persistent precipitation deficits. Unlike rapid onset natural hazards such as floods and wildfires, the intangible and gradual characteristics of drought cause a lack of social response during the onset. The level of awareness of a local drought increases rapidly through mass media reports and online information searching activities when the drought reaches its peak severity. This high level of local drought awareness drives concerns for water shortage and support for water policy. However, spatiotemporal patterns of national-scale drought awareness have never been studied due to constraints imposed by time-consuming and costly survey data collection and surveys’ limited sample sizes. Here, we present the national-scale study to reveal the spatiotemporal patterns of drought awareness over the contiguous United States (CONUS) using Google Trends data and Principal Component Analysis (PCA). Results show that the first two PC modes can explain 48% (38% for PC1 and 10% for PC2) of the total variance of state-level drought awareness. We find that the PC1 mode relates to a national pattern of drought awareness across the CONUS. The spatiotemporal patterns further imply that residents in the Northeastern US region are the most aware of the emergence of drought, regardless of the geographic location of the occurrence. The results illustrate how big data, such as search query and social media data, can help develop an effective and efficient plan for drought mitigation in the future.
Sungyoon Kim; Wanyun Shao; JongHun Kam. Spatiotemporal patterns of US drought awareness. Palgrave Communications 2019, 5, 1 -9.
AMA StyleSungyoon Kim, Wanyun Shao, JongHun Kam. Spatiotemporal patterns of US drought awareness. Palgrave Communications. 2019; 5 (1):1-9.
Chicago/Turabian StyleSungyoon Kim; Wanyun Shao; JongHun Kam. 2019. "Spatiotemporal patterns of US drought awareness." Palgrave Communications 5, no. 1: 1-9.
Unprecedented population growth combined with environmental and energy demands have led to water conflict in the Southeastern United States (SEUS). The states of Alabama, Florida, and Georgia have been engaged in litigation since 1990 on minimum in-stream flows to maintain ecosystems, fisheries and energy demands while satisfying a growing thirst in metropolitan Atlanta. A study of twenty-six unimpaired SEUS (Alabama, Florida, Georgia, Louisiana, Mississippi, North Carolina, and Tennessee) streamflow stations identified a decreased pattern of flow over the past ∼25 years with more frequent dry periods being observed in the last several decades. When evaluating calendar year streamflow, a period of high streamflow in the 1970’s was followed by a consistent decrease in streamflow from the late 1980’s to present. The identification of Atlantic Ocean (AO) Sea Surface Temperature (SST) teleconnections with SEUS streamflow may prove valuable in explaining decadal patterns of streamflow variability. Previous studies have identified the Atlantic Multidecadal Oscillation (AMO) as being teleconnected with SEUS precipitation and streamflow. The current research applied the Singular Value Decomposition (SVD) statistical method to AO Sea Surface Temperatures (SSTs) and SEUS streamflow. Annual streamflow volumes from the twenty-six unimpaired SEUS streamflow stations (1952-2016) were selected as the hydrologic response while average AO SSTs were calculated for three different six month averages (January to June or JFMAMJ, April to September or AMJJAS, and July to December or JASOND) for the year (1951-2015) preceding streamflow. The results confirmed an SST region in the North Atlantic as being teleconnected with SEUS streamflow and that an observed multi-decadal increase in temperatures in this SST region may be associated with the observed recent multi-decadal decline in SEUS streamflow.
Sahar Sadeghi; Glenn Tootle; Emily Elliott; Venkat Lakshmi; Matthew Therrell; JongHun Kam; Bennett Bearden. Atlantic Ocean Sea Surface Temperatures and Southeast United States streamflow variability: Associations with the recent multi-decadal decline. Journal of Hydrology 2019, 576, 422 -429.
AMA StyleSahar Sadeghi, Glenn Tootle, Emily Elliott, Venkat Lakshmi, Matthew Therrell, JongHun Kam, Bennett Bearden. Atlantic Ocean Sea Surface Temperatures and Southeast United States streamflow variability: Associations with the recent multi-decadal decline. Journal of Hydrology. 2019; 576 ():422-429.
Chicago/Turabian StyleSahar Sadeghi; Glenn Tootle; Emily Elliott; Venkat Lakshmi; Matthew Therrell; JongHun Kam; Bennett Bearden. 2019. "Atlantic Ocean Sea Surface Temperatures and Southeast United States streamflow variability: Associations with the recent multi-decadal decline." Journal of Hydrology 576, no. : 422-429.
This study introduces “Google Trends” as a social data source in monitoring and modeling the dynamics of drought awareness during the 2011–17 California drought. In this study, drought awareness is defined and operationalized as the relative search interest activities within California, using the search term “drought” from Google Trends. First, the 2011–17 California drought is characterized in the duration–intensity curve with other historical California droughts for comparative purposes, using the 12-month standard precipitation index data (1895–2017). Second, the potential triggers of the peaks of drought awareness during the 2011–17 California drought are investigated through Google Trends and Google Search. The Google Trends data show that the first peak of drought awareness occurred when the drought condition reached its peak and the governor declared the drought emergency (January 2014). The other peaks in August 2014, April 2015, and January 2017 are related to public interest in drought recovery driven by the forecast of the strong El Niño winter of 2014/15, the governor’s issue of water use rules, and California floods in early 2017, respectively. Last, a power-law decay model of drought awareness is fitted to the Google Trends data. According to the fitted power-law model, Californians remained interested in drought after the social trigger–related peaks longer than they did after the natural trigger–related peaks. The findings of this study suggest that it is necessary to develop a more realistic social dynamic modeling for communities that can respond to natural and human triggers and capture interactions with awareness of related disasters.
JongHun Kam; Kimberly Stowers; Sungyoon Kim. Monitoring of Drought Awareness from Google Trends: A Case Study of the 2011–17 California Drought. Weather, Climate, and Society 2019, 11, 419 -429.
AMA StyleJongHun Kam, Kimberly Stowers, Sungyoon Kim. Monitoring of Drought Awareness from Google Trends: A Case Study of the 2011–17 California Drought. Weather, Climate, and Society. 2019; 11 (2):419-429.
Chicago/Turabian StyleJongHun Kam; Kimberly Stowers; Sungyoon Kim. 2019. "Monitoring of Drought Awareness from Google Trends: A Case Study of the 2011–17 California Drought." Weather, Climate, and Society 11, no. 2: 419-429.
Over regions where snowmelt runoff substantially contributes to winter–spring streamflows, warming can accelerate snowmelt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by the brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, the detection/attribution of changes in midlatitude North American winter–spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. Robustness across models, start/end dates for trends, and assumptions about internal variability are evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central United States, where winter–spring streamflows have been starting earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western United States/southwestern Canada and in the extreme northeastern United States/Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.
JongHun Kam; Thomas R. Knutson; P. C. D. Milly. Climate Model Assessment of Changes in Winter–Spring Streamflow Timing over North America. Journal of Climate 2018, 31, 5581 -5593.
AMA StyleJongHun Kam, Thomas R. Knutson, P. C. D. Milly. Climate Model Assessment of Changes in Winter–Spring Streamflow Timing over North America. Journal of Climate. 2018; 31 (14):5581-5593.
Chicago/Turabian StyleJongHun Kam; Thomas R. Knutson; P. C. D. Milly. 2018. "Climate Model Assessment of Changes in Winter–Spring Streamflow Timing over North America." Journal of Climate 31, no. 14: 5581-5593.
Although interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (E) to those of precipitation (P) and temperature. The theory is based on extensions of the Budyko water‐balance hypothesis, the Priestley‐Taylor theory for potential evapotranspiration (Ep), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius‐Clapeyron‐like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced “strong” extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (E/P) and the index of dryness (Ep/P) at an annual time scale is identical to that linking inter‐basin variations of the corresponding long‐term means, and (2) a “weak” extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently. Human communities, economies, and natural ecosystems require a reliable supply of water, and this often is provided by rivers. It has at times been noted that rivers deliver less water in warm years than in cool years, even after adjustment for variations in precipitation. This dependence on temperature raises concerns about the effect of heat waves or climatic warming on water supply. Just why and how much the flow of rivers depends on temperature has not been well understood, but the answers to these questions are relevant for ensuring future water security. Here we present and evaluate a process‐based theory that attempts to answer both questions. In those river basins where long‐term observations of river flow, temperature, and precipitation data are available, the theory is consistent overall with observed sensitivities of river flows to temperature. This success implies potential applicability of the theory also where such observations are not available.
P. C. D. Milly; JongHun Kam; Krista A. Dunne. On the Sensitivity of Annual Streamflow to Air Temperature. Water Resources Research 2018, 54, 2624 -2641.
AMA StyleP. C. D. Milly, JongHun Kam, Krista A. Dunne. On the Sensitivity of Annual Streamflow to Air Temperature. Water Resources Research. 2018; 54 (4):2624-2641.
Chicago/Turabian StyleP. C. D. Milly; JongHun Kam; Krista A. Dunne. 2018. "On the Sensitivity of Annual Streamflow to Air Temperature." Water Resources Research 54, no. 4: 2624-2641.
JongHun Kam; Thomas R. Knutson; Fanrong Zeng; Andrew T. Wittenberg. CMIP5 Model-based Assessment of Anthropogenic Influence on Highly Anomalous Arctic Warmth During November–December 2016. Bulletin of the American Meteorological Society 2018, 99, S34 -S38.
AMA StyleJongHun Kam, Thomas R. Knutson, Fanrong Zeng, Andrew T. Wittenberg. CMIP5 Model-based Assessment of Anthropogenic Influence on Highly Anomalous Arctic Warmth During November–December 2016. Bulletin of the American Meteorological Society. 2018; 99 (1):S34-S38.
Chicago/Turabian StyleJongHun Kam; Thomas R. Knutson; Fanrong Zeng; Andrew T. Wittenberg. 2018. "CMIP5 Model-based Assessment of Anthropogenic Influence on Highly Anomalous Arctic Warmth During November–December 2016." Bulletin of the American Meteorological Society 99, no. 1: S34-S38.
Thomas R. Knutson; JongHun Kam; Fanrong Zeng; Andrew T. Wittenberg. CMIP5 Model-based Assessment of Anthropogenic Influence on Record Global Warmth During 2016. Bulletin of the American Meteorological Society 2018, 99, S11 -S15.
AMA StyleThomas R. Knutson, JongHun Kam, Fanrong Zeng, Andrew T. Wittenberg. CMIP5 Model-based Assessment of Anthropogenic Influence on Record Global Warmth During 2016. Bulletin of the American Meteorological Society. 2018; 99 (1):S11-S15.
Chicago/Turabian StyleThomas R. Knutson; JongHun Kam; Fanrong Zeng; Andrew T. Wittenberg. 2018. "CMIP5 Model-based Assessment of Anthropogenic Influence on Record Global Warmth During 2016." Bulletin of the American Meteorological Society 99, no. 1: S11-S15.
JongHun Kam; Thomas R. Knutson; Fanrong Zeng; Andrew T. Wittenberg. Multimodel Assessment of Anthropogenic Influence on Record Global and Regional Warmth During 2015. Bulletin of the American Meteorological Society 2016, 97, S4 -S8.
AMA StyleJongHun Kam, Thomas R. Knutson, Fanrong Zeng, Andrew T. Wittenberg. Multimodel Assessment of Anthropogenic Influence on Record Global and Regional Warmth During 2015. Bulletin of the American Meteorological Society. 2016; 97 (12):S4-S8.
Chicago/Turabian StyleJongHun Kam; Thomas R. Knutson; Fanrong Zeng; Andrew T. Wittenberg. 2016. "Multimodel Assessment of Anthropogenic Influence on Record Global and Regional Warmth During 2015." Bulletin of the American Meteorological Society 97, no. 12: S4-S8.
This study evaluates wintertime drought and pluvial risk over California through a Bayesian analysis of the upper and lower quartile of PRISM-based precipitation from 1901 to 2015. Risk is evaluated for different time windows to estimate the impact of interannual and decadal-to-multidecadal Pacific and Atlantic variability [positive and negative phases of ENSO, Pacific decadal oscillation (PDO), and Atlantic multidecadal oscillation (AMO)]. The impact of increasing trends in global sea surface temperature (SST) on drought and pluvial risk is also examined with idealized experimental runs from three climate models [GFDL Atmospheric Model version 2.1 (AM2.1), CCM3, and GFS]. The results show that the influence of oceanic conditions on drought risk in California is significant but has changed with higher risk in the last half century, especially in Southern California. The influence of oceanic conditions on pluvial risk has also been significant, especially during the warm phase of the Pacific Ocean, but increases over the last century are small compared to drought. Results from the idealized climate model experiments show that natural variability likely played a major role in the observed changes in risk, with the global SST increasing trend possibly tempering the increases regionally but not significantly over California. Despite evolving preferential oceanic conditions for a pluvial event during the 2015/16 winter (positive phase of ENSO and PDO), California received an 11% winter precipitation surplus, which was not sufficient for drought recovery. The seasonal and longer-term outlook for negative phases of ENSO and PDO implies that drought risk will be elevated in Southern California for the next decade.
JongHun Kam; Justin Sheffield. Increased Drought and Pluvial Risk over California due to Changing Oceanic Conditions. Journal of Climate 2016, 29, 8269 -8279.
AMA StyleJongHun Kam, Justin Sheffield. Increased Drought and Pluvial Risk over California due to Changing Oceanic Conditions. Journal of Climate. 2016; 29 (22):8269-8279.
Chicago/Turabian StyleJongHun Kam; Justin Sheffield. 2016. "Increased Drought and Pluvial Risk over California due to Changing Oceanic Conditions." Journal of Climate 29, no. 22: 8269-8279.
The analysis of the spatial and temporal patterns of low flows as well as their generation mechanisms over large geographic regions can provide valuable insights and understanding for climate change impacts, regional frequency analysis, risk assessment of extreme events, and decision-making regarding allowable withdrawals. The goal of this paper is to examine nonstationarity in low flow generation across the eastern US and explore the potential anthropogenic influences or climate drivers. We use nonparametric tests to identify abrupt and gradual changes in time series of low flows and their timing for 508 USGS streamflow gauging sites in the eastern US with more than 50 years of daily data, to systematically distinguish the effects of human intervention from those of climate variability. A time series decomposition algorithm was applied to 1-day, 7-day, 30-day, and 90-day annual low flow time series that combines the Box–Ljung test for detection of autocorrelation, the Pettitt test for abrupt step changes and the Mann–Kendall test for monotonic trends. Examination of the USGS notes for each site showed that many of the sites with step changes and around half of the sites with an increasing trend have been documented as having some kind of regulation. Sites with decreasing or no trend are less likely to have documented influences on flows. Overall, a general pattern of increasing low flows in the northeast and decreasing low flows in the southeast is evident over a common time period (1951–2005), even when discarding sites with significant autocorrelation, documented regulation or other human impacts. The north–south pattern of trends is consistent with changes in antecedent precipitation. The main exception is along the mid-Atlantic coastal aquifer system from eastern Virginia northwards, where low flows have decreased despite increasing precipitation, and suggests that declining groundwater levels due to pumping may have contributed to decreased low flows. For most sites, the majority of low flows occur in one season in the late summer to fall, as driven by the lower precipitation and higher evaporative demand in this season, but this is complicated in many regions because of the presence of a secondary low flow season in the winter for sites in the extreme northeast and in the spring for sites in Florida. Trends in low flow timing are generally undetectable, although abrupt step changes appear to be associated with regulation.
S. Sadri; J. Kam; J. Sheffield. Nonstationarity of low flows and their timing in the eastern United States. Hydrology and Earth System Sciences 2016, 20, 633 -649.
AMA StyleS. Sadri, J. Kam, J. Sheffield. Nonstationarity of low flows and their timing in the eastern United States. Hydrology and Earth System Sciences. 2016; 20 (2):633-649.
Chicago/Turabian StyleS. Sadri; J. Kam; J. Sheffield. 2016. "Nonstationarity of low flows and their timing in the eastern United States." Hydrology and Earth System Sciences 20, no. 2: 633-649.
We examine trends and variability in low flows over the eastern U.S. (S. Carolina to Maine) and their attribution in a changing climate. We select 149 out of 4878 USGS stations over the eastern U.S., taking into account data availability and minimal direct management. Annual 7-day low flows (Q7) are computed from the series of daily streamflow records for 1962–2011 and compared to an antecedent precipitation (AP) index calculated over the corresponding basin for each station. In general, a north–south (increasing-decreasing) dipole pattern in low flow trends is associated with trends in AP. The exception is in the southern part of the study area including Virginia and the Carolinas, where moderate increasing trends in AP may have been offset by water withdrawals and increasing potential evapotranspiration (PET) as driven by increasing temperature and vapor pressure deficit. A principal component analysis (PCA) of Q7 and AP indicates that the North Atlantic Oscillation (NAO) and Pacific North America (PNA) pattern show statistically significant correlations for Q7 at 1 and 2 month lead time, respectively, via large-scale pressure patterns. Our findings suggest that the inter-annual variability of low flows has increased due to significant anti-correlation between the NAO and PNA during recent decades, and the future risk of low flow extremes may be further enhanced with temperature driven increases in PET and persistence of the multi-decadal relationship between NAO and PNA.
JongHun Kam; Justin Sheffield. Changes in the low flow regime over the eastern United States (1962–2011): variability, trends, and attributions. Climatic Change 2015, 135, 639 -653.
AMA StyleJongHun Kam, Justin Sheffield. Changes in the low flow regime over the eastern United States (1962–2011): variability, trends, and attributions. Climatic Change. 2015; 135 (3-4):639-653.
Chicago/Turabian StyleJongHun Kam; Justin Sheffield. 2015. "Changes in the low flow regime over the eastern United States (1962–2011): variability, trends, and attributions." Climatic Change 135, no. 3-4: 639-653.
JongHun Kam; Thomas R. Knutson; Fanrong Zeng; Andrew T. Wittenberg. Record Annual Mean Warmth Over Europe, the Northeast Pacific, and the Northwest Atlantic During 2014: Assessment of Anthropogenic Influence. Bulletin of the American Meteorological Society 2015, 96, S61 -S65.
AMA StyleJongHun Kam, Thomas R. Knutson, Fanrong Zeng, Andrew T. Wittenberg. Record Annual Mean Warmth Over Europe, the Northeast Pacific, and the Northwest Atlantic During 2014: Assessment of Anthropogenic Influence. Bulletin of the American Meteorological Society. 2015; 96 (12):S61-S65.
Chicago/Turabian StyleJongHun Kam; Thomas R. Knutson; Fanrong Zeng; Andrew T. Wittenberg. 2015. "Record Annual Mean Warmth Over Europe, the Northeast Pacific, and the Northwest Atlantic During 2014: Assessment of Anthropogenic Influence." Bulletin of the American Meteorological Society 96, no. 12: S61-S65.
The analysis of the spatial and temporal patterns of low flows as well as their generation mechanisms over large geographic regions can provide valuable insights and understanding for climate change impacts, regional frequency analysis, risk assessment of extreme events, and decision-making regarding allowable withdrawals. We use nonparametric tests to identify abrupt and gradual changes in time series of low flows and their timing for 508 USGS streamflow gauging sites in the eastern US with more than 50 years of daily data, to systematically distinguish the effects of human intervention from those of climate variability. A time series decomposition algorithm was applied to 1 day, 7 day, 30 day, and 90 day annual low flow time series that combines the Box–Ljung test for detection of autocorrelation, the Pettitt test for abrupt step changes and the Mann–Kendall test for monotonic trends. Examination of the USGS notes for each site confirmed that many of the step changes and around half of the sites with an increasing trend were associated with regulation. Around a third of the sites with a decreasing trend were associated with a change of gauge datum. Overall, a general pattern of increasing low flows in the northeast and decreasing low flows in the southeast is evident over a common time period (1951–2005), even when discarding sites with significant autocorrelation, documented regulation or other human impacts. The north–south pattern of trends is consistent with changes in antecedent precipitation. The main exception is along the mid-Atlantic coastal aquifer system from eastern Virginia northwards, where low flows have decreased despite increasing precipitation, and suggests that declining groundwater levels due to pumping may have contributed to decreased low flows. For most sites, the majority of low flows occur in one season in the late summer to autumn, as driven by the lower precipitation and higher evaporative demand in this season, but this is complicated in many regions because of the presence of a secondary low flow season in the winter for sites in the extreme northeast and in the spring for sites in Florida. Trends in low flow timing are generally undetectable, although abrupt step changes appear to be associated with regulation.
Sara Sadri; JongHun Kam; Justin Sheffield. Nonstationarity of low flows and their timing in the eastern United States. Hydrology and Earth System Sciences Discussions 2015, 1 .
AMA StyleSara Sadri, JongHun Kam, Justin Sheffield. Nonstationarity of low flows and their timing in the eastern United States. Hydrology and Earth System Sciences Discussions. 2015; ():1.
Chicago/Turabian StyleSara Sadri; JongHun Kam; Justin Sheffield. 2015. "Nonstationarity of low flows and their timing in the eastern United States." Hydrology and Earth System Sciences Discussions , no. : 1.