36 research outputs found

    How can we use MODIS land surface temperature to validate long-term urban model simulations?

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    This is the authors accepted manuscript. The published version is available here: http://dx.doi.org/10.1002/2013JD021101.High spatial resolution urban climate modeling is essential for understanding urban climatology and predicting the human health impacts under climate change. Satellite thermal remote-sensing data are potential observational sources for urban climate model validation with comparable spatial scales, temporal consistency, broad coverage, and long-term archives. However, sensor view angle, cloud distribution, and cloud-contaminated pixels can confound comparisons between satellite land surface temperature (LST) and modeled surface radiometric temperature. The impacts of sensor view angles on urban LST values are investigated and addressed. Three methods to minimize the confounding factors of clouds are proposed and evaluated using 10years of Moderate Resolution Imaging Spectroradiometer (MODIS) data and simulations from the High-Resolution Land Data Assimilation System (HRLDAS) over Greater Houston, Texas, U.S. For the satellite cloud mask (SCM) method, prior to comparison, the cloud mask for each MODIS scene is applied to its concurrent HRLDAS simulation. For the max/min temperature (MMT) method, the 50 warmest days and coolest nights for each data set are selected and compared to avoid cloud impacts. For the high clear-sky fraction (HCF) method, only those MODIS scenes that have a high percentage of clear-sky pixels are compared. The SCM method is recommended for validation of long-term simulations because it provides the largest sample size as well as temporal consistency with the simulations. The MMT method is best for comparison at the extremes. And the HCF method gives the best absolute temperature comparison due to the spatial and temporal consistency between simulations and observations.Funded by National Aeronautics and Space Administration. Grant Number: (NNX10AK79G

    Compounding Hazards and Intersecting Vulnerabilities: Experiences and Responses to Extreme Heat During COVID-19

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    Extreme heat is a major threat to human health worldwide. The COVID-19 pandemic, with its complexity and global reach, created unprecedented challenges for public health and highlighted societal vulnerability to hazardous hot weather. In this study, we used data from a three-wave nationally representative survey of 3036 American adults to examine how the COVID-19 pandemic affected extreme heat vulnerability during the summer of 2020. We used mixed effects models to examine the roles of socio-demographic characteristics and pandemic-related factors in the distribution of negative heat effects and experiences across the United States. The survey findings show that over a quarter of the US population experienced heat-related symptoms during the summer of 2020. Mixed effects models demonstrate that among all socio-economic groups, those who were most vulnerable were women, those in low-income households, unemployed or on furlough, and people who identify as Hispanic or Latino or as other non-white census categories (including Asian, American Indian or Alaska Native, Native Hawaiian or other Pacific Islander, and multi-racial US residents). The study findings indicate that millions of people in the US had difficulty coping with or responding to extreme heat because of the direct and indirect effects of the COVID-19 pandemic. Limited access to cooling as well as COVID-19 related social isolation played a major role in adverse heat health effects. Geographically, the South and the West of the US stood out in terms of self-reported negative heat effects. Overall, the study suggests that the intersection of two health hazards—extreme heat and coronavirus SARS-CoV2—amplified existing systemic vulnerabilities and expanded the demographic range of people vulnerable to heat stress

    The food water energy nexus in an urban context: Connecting theory and practice for nexus governance

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    The growing body of literature on the Food-Water-Energy (FWE) nexus during the last decade covers a variety of disciplinary perspectives and spatial scales. However, to date the urban FWE nexus has received less attention. In this paper, we review the FWE nexus literature with the focus on urban scale and identify gaps in the scholarly knowledge base with regard to practical applications for the FWE nexus governance in cities. Our findings suggest that there is still a mismatch between theoretical nexus governance and community perceptions. Successful governance is an iterative process, necessitating stakeholder input, reflection and response. While research developing the body of urban FWE governance knowledge has increased rapidly, reflection on those results to unpack the nexus complexity and support different governance actors is still limited. We discuss an approach for making the FWE nexus connections more visible and practical by focusing on the urban governance actors and illustrating the intersecting interests and concerns of different actors within the food, water, and energy systems. Mapping the urban governance actors to the sub-elements of the FWE systems highlights common connections and overlapping interests, paving the road toward more integrated governance and participatory solutions. Identifying the tangible and intangible connections among governance actors also helps to reduce the ambiguity of the FWE nexus, and facilitates multi-stakeholder knowledge, data or resources sharing. The resultant approach aims to disaggregate the complexity of the FWE nexus and make its governance more attainable in cities

    Assessing Vulnerability to Agricultural Drought: A Nebraska Case Study

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    Recent drought events in the United States and the magnitude of drought losses indicate the continuing vulnerability of the country to drought. Until recently, drought management in many states, including Nebraska, has been largely response oriented with little or no attention to mitigation and preparedness. In 1998, Nebraska began to revise its drought plan in order to place more emphasis on mitigation. One of the main aspects of drought mitigation and planning is the assessment of who and what is vulnerable and why. This paper presents a method for spatial, Geographic Information Systems-based assessment of agricultural drought vulnerability in Nebraska. It was hypothesized that the key biophysical and social factors that define agricultural drought vulnerability were climate, soils, land use, and access to irrigation. The framework for derivation of an agricultural drought vulnerability map was created through development of a numerical weighting scheme to evaluate the drought potential of the classes within each factor. The results indicate that the most vulnerable areas to agricultural drought were non-irrigated cropland and rangeland on sandy soils, located in areas with a very high probability of seasonal crop moisture deficiency. The identification of drought vulnerability is an essential step in addressing the issue of drought vulnerability in the state and can lead to mitigation-oriented drought management

    Spatial Representation of Agroclimatology in a Study of Agricultural Drought

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    Agricultural drought is the leading cause for crop failure throughout the world. In the USA, significant impacts of recent droughts on agricultural production indicate the continuing vulnerability of the country to drought. This paper presents a methodology for spatial representation of the agroclimatic component of agricultural drought vulnerability. This methodology was developed as a part of an integrated assessment of drought vulnerability. For the spatial analysis, the state of Nebraska was selected as a study area because of the considerable variation in climatology, soil characteristics, land use, and cropping patterns. The underlying approach assumes that the best spatial characterization of the state’s agroclimatology from the agricultural drought vulnerability perspective is the probability of seasonal crop moisture deficiency. Seasonal crop water-use thresholds for well-watered crops (e.g. corn, soybean, and sorghum) were estimated using the evapotranspiration (ET) mathematical model. For wheat and grass, ET values were estimated based on the relationship between ET, water-use efficiency, and crop yield. Historical grain yield data were analyzed to define an economically viable threshold for wheat. Seasonal ET thresholds determined for the crops were used to calculate area-weighted mean ET for the combination of crops in every county. The threshold values and long-term precipitation data were used for calculating statistical probabilities of seasonal crop moisture deficiency. Probability values were analyzed at 112 weather stations across Nebraska, spatially interpolated and classified using geographic information systems. The spatial pattern of probabilities of seasonal crop moisture deficiency reflected both seasonal precipitation across Nebraska and the distribution of crops and grasses

    The growing threat of heat disasters

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    Heat is the number one weather-related killer in the United States and indoor exposure is responsible for a significant portion of the resulting fatalities. Evolving construction practices combined with urban development in harsh climates has led building occupants in many cities to rely on air conditioning (AC) to a degree that their health and well-being are compromised in its absence. The risks are substantial if loss of AC coincides with a hot weather episode (henceforth, a heat disaster). Using simulations, we found that residential buildings in many US cities are highly vulnerable to heat disasters—with more than 50 million citizens living in cities at significant risk. This situation will be exacerbated by intensification of urban heat islands, climate change, and evolving construction practices. It is therefore crucial that future building codes consider thermal resiliency in addition to energy efficiency

    A comprehensive framework for tourism and recreation drought vulnerability reduction

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    The effects of drought are vast, but loss statistics often do not reflect the impacts on the tourism and recreation sector, which for many places is one of the most critical economic drivers. This is concerning because drought events are common across the globe, with varying frequency, duration, and intensity, and are therefore unavoidable. Over the years, drought conditions have been at record levels in many regions, causing deep societal and economic impacts. However, little research has been conducted on connections between tourism/recreation and drought, revealing a distinct disconnect between the tourism/recreation sector and drought management. To bridge this gap in the current understanding of, and approaches to, managing drought in the tourism/recreation sector, we present an interdisciplinary conceptual framework that integrates tourism/recreation into the drought management process to ensure sustainable economic development and community vitality. The model presented here promotes understanding of critical interactions through a bottom-up stakeholder engagement process balanced with formal top-down management approaches

    An Analysis of an Incomplete Marked Point Pattern of Heat-Related 911 Calls

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    <div><p>We analyze an incomplete marked point pattern of heat-related 911 calls between the years 2006–2010 in Houston, TX, to primarily investigate conditions that are associated with increased vulnerability to heat-related morbidity and, secondarily, build a statistical model that can be used as a public health tool to predict the volume of 911 calls given a time frame and heat exposure. We model the calls as arising from a nonhomogenous Cox process with unknown intensity measure. By using the kernel convolution construction of a Gaussian process, the intensity surface is modeled using a low-dimensional representation and properly adheres to circular domain constraints. We account for the incomplete observations by marginalizing the joint intensity measure over the domain of the missing marks and also demonstrate model based imputation. We find that spatial regions of high risk for heat-related 911 calls are temporally dynamic with the highest risk occurring in urban areas during the day. We also find that elderly populations have an increased probability of calling 911 with heat-related issues than younger populations. Finally, the age of individuals and hour of the day with the highest intensity of heat-related 911 calls varies by race/ethnicity. Supplementary materials are included with this article.</p></div
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