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Kelsey Scheitlin

Abstract

This study analyzes the influence of the Atlantic Ocean and Chesapeake Bay on the diurnal temperature range (DTR) reported by nearby weather stations. Coastal locations reported the smallest DTRs and DTR fluctuations, and DTR increased with distance from the ocean. Month of the year and airmass type also proved to be significant predictors of DTR. All locations showed a bimodal annual DTR pattern with peaks during the transitional seasons and experienced the greatest DTR during dry and/or warm air masses. Proximity to the ocean had the largest (smallest) influence on DTR during dry (moist) air masses with extreme (moderate) temperatures. Seasonally, the proximity to the ocean had the strongest impact on DTR during early–middle spring. A multiple regression model using distance from water, month, and airmass type explains over 30% of DTR variability in the area (p < 0.01). Airmass type has the largest influence on DTR, and changes in both air mass and month impacted the DTR of continental locations more than coastal locations. Land use, cloud cover, and wind speed/direction are additional variables that could account for differences not explained by the model.

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Brent M. Lofgren, Andrew D. Gronewold, Anthony Acciaioli, Jessica Cherry, Allison Steiner, and David Watkins

Abstract

Climate change due to anthropogenic greenhouse gases (GHG) is expected to have important impacts on water resources, with a variety of societal impacts. Recent research has shown that applying different methodologies to assess hydrologic impacts can lead to widely diverging projections of water resources. The authors classify methods of projecting hydrologic impacts of climate change into those that estimate potential evapotranspiration (PET) based on air temperature and those that estimate PET based on components of the surface energy budget. In general, air temperature–based methods more frequently show reductions in measures of water resources (e.g., water yield or soil moisture) and greater sensitivity than those using energy budget–based methods. There are significant trade-offs between these two methods in terms of ease of use, input data required, applicability to specific locales, and adherence to fundamental physical constraints: namely, conservation of energy at the surface. Issues of uncertainty in climate projections, stemming from imperfectly known future atmospheric GHG concentrations and disagreement in projections of the resultant climate, are compounded by questions of methodology and input data availability for models that connect climate change to accompanying changes in hydrology. In the joint atmospheric–hydrologic research community investigating climate change, methods need to be developed in which the energy and moisture budgets remain consistent when considering their interaction with both the atmosphere and water resources. This approach should yield better results for both atmospheric and hydrologic processes.

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Tim Bardsley, Andrew Wood, Mike Hobbins, Tracie Kirkham, Laura Briefer, Jeff Niermeyer, and Steven Burian

Abstract

Assessing climate change risk to municipal water supplies is often conducted by hydrologic modeling specific to local watersheds and infrastructure to ensure that outputs are compatible with existing planning frameworks and processes. This study leverages the modeling capacity of an operational National Weather Service River Forecast Center to explore the potential impacts of future climate-driven hydrologic changes on factors important to planning at the Salt Lake City Department of Public Utilities (SLC). Hydrologic modeling results for the study area align with prior research in showing that temperature changes alone will lead to earlier runoff and reduced runoff volume. The sensitivity of average annual flow to temperature varies significantly between watersheds, averaging −3.8% °F−1 and ranging from −1.8% to −6.5% flow reduction per degree Fahrenheit of warming. The largest flow reductions occur during the high water demand months of May–September. Precipitation drives hydrologic response more strongly than temperature, with each 1% precipitation change producing an average 1.9% runoff change of the same sign. This paper explores the consequences of climate change for the reliability of SLC's water supply system using scenarios that include hydrologic changes in average conditions, severe drought scenarios, and future water demand test cases. The most significant water management impacts will be earlier and reduced runoff volume, which threaten the system's ability to maintain adequate streamflow and storage to meet late-summer water demands.

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Mohammad Karamouz, Erfan Goharian, and Sara Nazif

Abstract

Increase in global mean temperature and changes in rainfall amount, pattern, and distribution over the world are all indicative of climate change events. These changes alter the hydroclimatic condition of regions as well as the availability of water resources. In this study, the data generated by 14 general circulation models (GCMs) developed under the Special Report on Emissions Scenarios (SRES) A1B, A2, and B2 are downscaled and utilized to evaluate climate change impact on the hydroclimatic system of the Karaj River basin located in central Iran. The precipitation and temperature of the study region are downscaled using the change factor approach (CFA). The study analyzes future climate data, extreme changes of future climatic conditions of precipitation, and temperature. The Hydrologiska Byråns Vattenbalansavdelning (HBV) model developed by the Swedish Meteorological and Hydrological Institute (SMHI) is used to simulate streamflow under extreme climate change conditions. Two different sources of uncertainty are investigated in this study. First, the model parameters uncertainty is analyzed with the Monte Carlo procedure, and then different datasets of GCMs projection are investigated under the climate of the twentieth-century climate simulation (20C3M). Results show the GCMs projections range can almost capture the historical records during the 1980s through 2000 for the Karaj basin. By applying the HBV model, considerable range of streamflow changes in the future can be projected that will affect the operation scheme of Karaj Reservoir. In this study, the system dynamics (SD) modeling approach is used to simulate the system behavior through time in an integrated fashion and evaluate its overall reliability in supplying water. The results of this study show that the runoff will decrease in the future under the climate change impact. This will result in more than 50% decrease in reliability of the Karaj Reservoir system under the extreme conditions. As a result, this research predicts that the Karaj Reservoir system will face more than 50% decrease in its reliability under the extreme conditions. Consequently, meeting the increasing water demands would be difficult and application of demand management strategies will be unavoidable.

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Alfred J. Kalyanapu, A. K. M. Azad Hossain, Jinwoo Kim, Wondmagegn Yigzaw, Faisal Hossain, and C. K. Shum

Abstract

Recent research in mesoscale hydrology suggests that the size of the reservoirs and the land-use/land-cover (LULC) patterns near them impact the extreme weather [e.g., probable maximum flood (PMF)]. A key question was addressed by W. Yigzaw et al.: How do reservoir size and/or LULC modify extreme flood patterns, specifically PMF via modification of probable maximum precipitation (PMP)? Using the American River watershed (ARW) as a representative example of an impounded watershed with Folsom Dam as the flood control structure, they applied the distributed Variable Infiltration Capacity (VIC) model to simulate the PMF from the atmospheric feedbacks simulated for various LULC scenarios. The current study presents a methodology to extend the impacts of these modified extreme flood patterns on the downstream Sacramento County, California. The research question addressed is, what are the relative effects of downstream flood hazards to population on the American River system under various PMF scenarios for the Folsom Dam? To address this goal, a two-dimensional flood model, the Flood in Two Dimensions–Graphics Processing Unit (Flood2D-GPU), is calibrated using synthetic aperture radar (SAR) and Landsat satellite observations and observed flood stage data. The calibration process emphasized challenges associated with using National Elevation Dataset (NED) digital elevation model (DEM) and topographic light detection and ranging (lidar)–derived DEMs to achieve realistic flood inundation. Following this calibration exercise, the flood model was used to simulate four land-use scenarios (control, predam, reservoir double, and nonirrigation). The flood hazards are quantified as downstream flood hazard zones by estimating flood depths and velocities and its impacts on risk to population using depth–velocity hazard relationships provided by U.S. Bureau of Reclamation (USBR). From the preliminary application of methodology in this study, it is evident from comparing downstream flood hazard that similar trends in PMF comparisons reported by W. Yigzaw et al. were observed. Between the control and nonirrigation, the downstream flood hazard is pronounced by −3.90% for the judgment zone and −2.40% for high hazard zones. Comparing the control and predam scenarios, these differences are amplified, ranging between 0.17% and −1.34%. While there was no change detected in the peak PMF discharges between the control and reservoir-double scenarios, it still yielded an increase in high hazard areas for the latter. Based on this preliminary bottom-up vulnerability assessment study, it is evident that what was observed in PMF comparisons by W. Yigzaw et al. is confirmed in comparisons between control versus predam and control versus nonirrigation. While there was no change detected in the peak PMF discharges between the control and reservoir-double scenarios, it still yielded a noticeable change in the total areal extents: specifically, an increase in high hazard areas for the latter. Continued studies in bottom-up vulnerability assessment of flood hazards will aid in developing suitable mitigation and adaptation options for a much needed resilient urban infrastructure.

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Farhat Abbas

Abstract

Prolonged droughts and uneven monsoons have adversely affected socioeconomic and environmental conditions of Pakistan, especially of the Punjab province. Analysis of historical (1981–2010) daily minimum and maximum temperatures from five cities in semiarid Punjab, Pakistan, was carried out to evaluate spatial and temporal patterns in thermal regimes. A total of 13 climate change indices were calculated using daily minimum and maximum temperatures and analyzed for trend using RClimDex, a program written in the statistical software package R. A nonparametric Mann–Kendall test and Sen's slope estimates were used to determine the statistical significance and magnitude of a trend, respectively. Observed trends in selected indices during 1981–2010 suggest an overall warming in the region. Over the analysis period, the regionally averaged occurrence of extreme cold (10th percentile) nights and days has decreased by −3.94 nights per decade and −0.61 days per decade, respectively. Occurrence of extreme hot (90th percentile) nights and days has increased by 4.19 nights per decade and 0.92 days per decade, respectively. The number of summer days has increased by almost 3 days per decade on average at four out of the five cities. Multan was the only city where the number of summer days has declined by 5 days per decade. Regionally averaged increase in tropical nights was 8.35 nights per decade. Regional warming will dictate increased crop water requirements in this semiarid region agriculture, which is already under water-scarce conditions, especially in the Faisalabad district, where saline groundwater is not suitable for crops.

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Ashley M. Merritt-Takeuchi and Sen Chiao

Abstract

This study investigates phytoplankton blooms following the passage of tropical cyclones in the Atlantic and Pacific Ocean basins. The variables of sea surface temperature (SST), chlorophyll (Chl-a), precipitation, and storm surface winds were monitored for two case studies, Typhoon Xangsane (2006) and Hurricane Earl (2010). Strong near-surface wind from tropical cyclones creates internal friction, which causes deep nutrient enriched waters to displace from the bottom of the ocean floor up toward the surface. In return, the abundance of upwelled nutrients near the surface provides an ideal environment for the growth of biological substances such as chlorophyll and phytoplankton. The inverse correlation coefficients of SST and Chl-a for this study are −0.67 and −0.26 for Xangsane and Earl, respectively. This suggests that, regardless of ocean basin, changing sea surface temperature and chlorophyll concentrations can be correlated to various characteristics of tropical cyclones including precipitation and surface wind, which in combination results in an increase of phytoplankton.

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G. T. Aronica and B. Bonaccorso

Abstract

In recent years, increasing attention has been paid to hydropower generation, since it is a renewable, efficient, and reliable source of energy, as well as an effective tool to reduce the atmospheric concentrations of greenhouse gases resulting from human activities. At the same time, however, hydropower is among the most vulnerable industries to global warming, because water resources are closely linked to climate changes. Indeed, the effects of climate change on water availability are expected to affect hydropower generation with special reference to southern countries, which are supposed to face dryer conditions in the next decades. The aim of this paper is to qualitatively assess the impact of future climate change on the hydrological regime of the Alcantara River basin, eastern Sicily (Italy), based on Monte Carlo simulations. Synthetic series of daily rainfall and temperature are generated, based on observed data, through a first-order Markov chain and an autoregressive moving average (ARMA) model, respectively, for the current scenario and two future scenarios at 2025. In particular, relative changes in the monthly mean and standard deviation values of daily rainfall and temperature at 2025, predicted by the Hadley Centre Coupled Model, version 3 (HadCM3) for A2 and B2 greenhouse gas emissions scenarios, are adopted to generate future values of precipitation and temperature. Synthetic series for the two climatic scenarios are then introduced as input into the Identification of Unit Hydrographs and Component Flows from Rainfall, Evapotranspiration and Streamflow Data (IHACRES) model to simulate the hydrological response of the basin. The effects of climate change are investigated by analyzing potential modification of the resulting flow duration curves and utilization curves, which allow a site's energy potential for the design of run-of-river hydropower plants to be estimated.

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Liming Zhou, Yuhong Tian, Haishan Chen, Yongjiu Dai, and Ronald A. Harris

Abstract

This paper uses the empirical orthogonal function (EOF) analysis to decompose satellite-derived nighttime land surface temperature (LST) for the period of 2003–11 into spatial patterns of different scales and thus to identify whether (i) there is a pattern of LST change associated with the development of wind farms and (ii) the warming effect over wind farms reported previously is an artifact of varied surface topography. Spatial pattern and time series analysis methods are also used to supplement and compare with the EOF results. Two equal-sized regions with similar topography in west-central Texas are chosen to represent the wind farm region (WFR) and nonwind farm region (NWFR), respectively. Results indicate that the nighttime warming effect seen in the first mode (EOF1) in WFR very likely represents the wind farm impacts due to its spatial coupling with the wind turbines, which are generally built on topographic high ground. The time series associated with the EOF1 mode in WFR also shows a persistent upward trend over wind farms from 2003 to 2011, corresponding to the increase of operating wind turbines with time. Also, the wind farm pixels show a warming effect that differs statistically significantly from their upwind high-elevation pixels and their downwind nonwind farm pixels at similar elevations, and this warming effect decreases with elevation. In contrast, NWFR shows a decrease in LST with increasing surface elevation and no warming effects over high-elevation ridges, indicating that the presence of wind farms in WFR has changed the LST–elevation relationship shown in NWFR. The elevation impacts on Moderate Resolution Imaging Spectroradiometer (MODIS) LST, if any, are much smaller and statistically insignificant than the strong and persistent signal of wind farm impacts. These results provide further observational evidence of the warming effect of wind farms reported previously.

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Johna E. Rudzin, Steven L. Morey, Mark A. Bourassa, and Shawn R. Smith

Abstract

Influences of the Gulf of Mexico's Loop Current (LC) position on the sea surface temperature (SST) in the Florida Straits (FS) during the winter season are investigated. Satellite-derived SST data are analyzed on the basis of the LC configuration (mature or immature) as determined by satellite altimetry analyses. Cumulative distributions of FS SSTs for both LC phases during the months of January and February show greater likelihood of cooler SSTs in the FS during a mature LC than during an immature LC. This work suggests that differing transit times of LC water parcels during mature and immature phases result in differences in heat loss of the LC near-surface water. This may contribute to the observed SST differences in FS during mature and immature LC phases via temperature advection.

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