Source: ARIZONA STATE UNIVERSITY submitted to
EASM-3: COLLABORATIVE RESEARCH: PHYSICS-BASED PREDICTIVE MODELING FOR INTEGRATED AGRICULTURAL AND URBAN APPLICATIONS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
NEW
Funding Source
AFRI COMPETITIVE GRANT
Reporting Frequency
Annual
Accession No.
1005123
Grant No.
2015-67003-23508
Project No.
ARZW-2014-09752
Proposal No.
2014-09752
Multistate No.
(N/A)
Program Code
A3151
Project Start Date
May 1, 2015
Project End Date
Apr 30, 2020
Grant Year
2015
Project Director
Mahalov, A. -.
Recipient Organization
ARIZONA STATE UNIVERSITY
660 S MILL AVE STE 312
TEMPE,AZ 85281-3670
Performing Department
Mathematics and Statistical Sc
Non Technical Summary
Challenges associated with a rapidly rising global population that is increasingly food-insecure and lacks fundamental awareness of how to build tomorrow's sustainable cities necessitate urgent study in light of a rapidly urbanizing planet. Unrelenting urban population growth -- an increase of more than 2.5 billion new urban inhabitants is projected by 2050, relative to 2011 -- requires considerable conversion of natural to agricultural (to meet increased food demand) and to urban (to meet increased commercial, housing, and transportation demand) landscapes. Strategic adaptation plans require development to increase production of agricultural commodities, maximize land-use efficiency, enhance community engagement, decrease reliance on outsourced food, reduce transportation costs while enhancing profitability, and mitigate adverse impacts such as the urban heat island effect. Localizing food strategies within urban areas can therefore concurrently address concerns associated with food insecurity, environmental degradation, citizen health, and socioeconomic well-being. Development and refinement of physics-based predictive modeling and assessment tools used at fine spatial resolution is necessary to effectively quantify co-benefits and reveal tradeoffs prior to any strategy deployment. A collaborative and interdisciplinary team from Arizona State University and the National Center for Atmospheric Research jointly develops integrated agricultural and urban models necessary to examine hydroclimatic impacts and economic and social benefits/tradeoffs associated with agricultural and urban land use/cover changes accompanying localization of food production within cities. Students and postdocs are trained in the course of this project. The project is funded jointly by the National Science Foundation and by the US Department of Agriculture.The overarching goal of this project is to develop high-resolution physics-based, coupled, dynamic, and predictive capabilities that not only characterize current multi-scale environmental and socio-economic impacts associated with agricultural productivity within cities but also enable the prediction of future impacts. Feedback loops and nonlinear interactions interconnect physical and human processes. Understanding of emergent regional climate modifiers (e.g., agriculture, urbanization, etc.) on decadal scales cannot be realized simply by studying these components in isolation. Novel computational methods to accelerate and improve accuracy of multi-scale nested models are developed by the team and integrated within an interactively coupled urban-climate-agricultural model utilizing high-resolution land use/land cover data to examine scale dependency of simulated outcomes. The team develops a conceptual framework to evaluate economic and social impacts of community gardens, quantifies socioeconomic benefits, and recommends geographically dependent strategies for sustainable integrated agri-urban development. The advanced modeling tools are utilized to conduct ensemble-based regional hydroclimate simulations, focusing on a set of rapidly urbanizing and diverse megapolitan areas across multiple US climate zones. Because the geographic focus spans emerging and expanding megapolitan areas across the US, techniques, strategies, and prioritization for sustainable integrated agri-urban development can be applied globally for comparable climate zones. These studies advance scientific knowledge and develop next-generation predictive modeling capabilities for linked agricultural and urban climate dynamics on regional and decadal scales.
Animal Health Component
0%
Research Effort Categories
Basic
40%
Applied
40%
Developmental
20%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
13204302070100%
Knowledge Area
132 - Weather and Climate;

Subject Of Investigation
0430 - Climate;

Field Of Science
2070 - Meteorology and climatology;
Goals / Objectives
This is a collaborative project between Arizona State University (ASU) and the National Center for Atmospheric Research (NCAR). The overarching goal of our project is to develop a high-resolution integrated regional climate prediction system linked with socioeconomic assessment tools to advance our understanding of consequences owing to future agricultural productivity within and adjacent to selected cities in the U.S. To achieve this overarching goal, we will address the following specific goals and objectives: Goal 1: Developing a physics-based predictive agricultural-urban modeling and high resolution data framework.Objectives: 1) Develop novel computational methods to accelerate and improve accuracy of multi-scale nested models. Fast and accurate algorithms and solvers for use in high-resolution decadal regional climate simulations will be developed.2) Develop an integrated agricultural and urban modeling system which will include crop modeling capabilities in an existing land surface/hydrology/urban model with sub-grid tiling for accommodating a mixture of urban/crop landscapes.3) Develop land-cover architecture and high-resolution land cover/use data. Using remote sensing imagery available resources will be utilized to determine which scales and data provide robust modeling outcomes to augment existing Integrated Climate and Land Use Scenarios (ICLUS) data.Goal 2: Investigate socio-economic impacts associated with agricultural-urban development.Objectives:1) Assessment of economic impacts. Economic analysis based on USDA and IMPLAN datasets will be performed and utility of USDA dataset for regional-scale applications will be assessed.2) Assessment of social impacts. Social network analysis will illustrate, compare and contrast the social networks of likely and unlikely participants of community gardens/urban farms.3) Conceptual framework will be established. Conceptual framework and methodology for evaluating the economic and social impacts of a community garden/urban farm import substitution strategy.Goal 3: Characterize decadal and regional impacts associated with agriculture-urban expansion.Objective:1. Assessment of agri-urban development pathways. With new advanced modeling capabilities, ensemble-based regional climate simulations focusing on rapidly urbanizing regions whose built environment is expanding at the expense of agriculture, and where native landscapes such as forest and marshlands are currently being replaced with urban land use, will be conducted.
Project Methods
Developing the integrated WRF-Crop modeling system will involve two steps: 1) Implementing a novel, fast and accurate semi-implicit and split-explicit numerical in WRF so we can conduct high-resolution regional climate simulations within the constrain of current computational resources; 2) developing crop-specific growth model in WRF to simulate phenological development, growth and yield from emergence until maturity using crop genetic properties, weather, and soil conditions following methods developed and adapted from agriculture communities. Crop models parameterize four main processes that regulate plant development: (1) Phenological development. This process simulates the passing of the crop through successive development stages (e.g., emergence, flowering, and maturity). (2) Gross CO2 assimilation. This process describes the actual gross CO2 assimilation by the plant. Assimilation is mainly driven by the amount of light intercepted by photosynthetic (green) organs (constrained by the development stage), the effect of temperature (optimum temperatures being crop-specific), and also the effect of water stress. (3) Crop growth. Gross CO2 assimilation is the basis for crop growth, which will be further constrained by assimilation-reducing factors and assimilation requirements for maintenance respiration and conversion of primary assimilates into plant tissue. The primary assimilates in excess of the maintenance costs are converted into structural plant material, with some weight lost due to growth respiration. Dry matter is first partitioned between shoots and roots. Growth rate of leaves, stems and grains is the product of the shoots dry matter growth rate and the fraction of carbon assimilation allocated to these organs. (4) Root growth. The root growth process acts as the interface between the aerial part of the plant and the soil water balance. Particularly the rooting depth is a critical parameter that will allow estimating which part of the water stored in the soil is available for the plant to be used in the transpiration process. The unique aspect of this WRF-Crop modeling system is a new capability to capture the feedback mechanisms among crop growth, soil conditions, urbanization hydrology, weather, and climate.EvaluationEvaluation and testing of decadal and regional climate impact predictions will be major components of the proposed work. It will involve validation and verification of computational results using observational data and conducting sensitivity studies due to land cover/use change (as informed by ICLUS and the high resolution data output from RT1). The urbanized WRF-Crop model developed in in this project will be validated as follows. High-resolution nested regional climate model simulations will be conducted for the past decades using the current WRF version and the enhanced WRF-Crop. The results from these models will be compared with observations. We will particularly focus on the ability of both models to resolve the observed change in the diurnal cycle of temperature and moisture, as well as the physical processes upon which these climate metrics depend, and will assess the improvements made by the proposed model compared with the current WRF. After validating the model, we will conduct future regional climate simulations using projected land use data. We will conduct scenario-based experiments centered on upcoming decades (e.g., simulation utilizing 2020-ICLUS data will be run for 2015 through 2025 for A2 and B1 projections) to examine the evolving nature of gradual landscape change, rather than the traditional focus on two endpoints in time (i.e., current landscape and 2050). This will help shed light on the importance of slowly evolving local regional forcing due to changes in land use/cover. WRF-Crop will therefore be used to predictively model the decadal and regional climate/environmental trends, and characterize low frequency variability of regional climate driven by changes in agricultural and urban landscapes at high-resolution. The urbanized WRF-Crop model output and results will be used to estimate economic and social benefits and tradeoffs for geographical regions described above using socio-economic analysis and survey tools developed in in this project

Progress 05/01/17 to 04/30/18

Outputs
Target Audience:The findings of this project are aimed at reaching broad audiences. Data are placed online in a digital library for public use. The WRF-Crop-UrbanModeling System is developed and officially released by NCAR for use by the scientific, agricultural, and urban planning communities. Project results and findings are shared and broadly disseminated to the local community through the Global Institute of Sustainability seminar series (the hub of ASU's sustainability initiatives and open to public); via peer-reviewed and popular publications; presentations at scientific meetings; and online. Relevant data is made accessible to a wide audience, for both researchers interested in utilizing simulation results to further their research and more general audiences (e.g., stakeholders, Farmers, City Mayors, Decision makers) interested in fundamental knowledge and applications of the results. Special efforts are made to recruit women and underrepresented minority students interested in the project activities. The team members engage with diverse, non- academic audiences through programs that take research into schools and public forums, including the CAP LTER and the Sustainable Schools GK12 Program in GIOS. Outreach activities with broader impacts include collaboration with the Desert Botanical Garden in Phoenix to facilitate Spaces of Opportunity, a community-driven community garden/urban agriculture "food hub" project developed through a collaboration between the Garden, Cultivate South Phoenix (CUSP) and the Roosevelt School District. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?The project provides opportunities for training and professional development of students and postdocs. Francisco Salamanca visited NCAR for 1 month to conduct research and implement the urban canopy models (UCMs) in the new Noah-MP land surface model (Noah-MP LSM). Postdoc Stephen Shaffer presented papers at the NCAR annual WRF conference in June 2017 and at the annual meeting of the American Geophysical Union in December 2017. Graduate student Iryna Printezis, advised by Co-PI Grebitus, won the ASU Institute for Social Science Research'sFall 2017 Graduate StudentPosterContest. There were 53 contestants. Iryna took the first place among graduate research participants, and won a $1,200 prize.The title of her poster was "Willingness to Pay for Local Foodfrom Different Marketing Channels". Co-PI Grebitus also advised Barrett's Honors Students Yann Raymond and Mary Curtiss on topics related to the project. The students have accomplished the following: Founded the student Venture Garden of Eden (an urban agriculture venture), won $500 from the Ford/Flashfood challenge during Demo Day Fall 2017 for their venture, won $1,000 from the eSeed Challenge during Demo Day Fall 2017, and won $2,500 from the Changemaker Challenge round Fall 2017 for their venture. Graduate studentJordan Smith with his advisor and EaSM Co-PI Prof Billie Turner developed a novel method to identify vacant parcels in the Phoenix Metropolitan area using the remote sensing and geographic information science techniques. The systematic approach identification of the vacant parcels provides the availability to the study of potential urban agriculture and heat amelioration. Jordan presented a paper at the annual USDA NIFA meeting in Tampa, FL, Oct 2017 (Lots for greening: Identification of metropolitan vacant land and its potential use for cooling and agriculture in Phoenix, published in Applied Geography, Vol. 85, pp. 139-151). Initial land NAIP land classification for Fresno has been taken over by graduate student Ryan Reynolds, with the aim of completing the effort by end of the Spring 2018 semester. Training is underway on the K nearest neighbor classifier in eCognation and batch classification of the rural and mountain areas adjacent to Fresno. During the reporting period, EaSM Co-PI Prof Grebitus supervised graduated student Iryna Printezis and collaborated with Co-PI Billie Turner and graduate student Jordan Smith. Ms. Printezis and Dr. Grebitus presented work on consumers' preferences for urban farming.Printezis, I., and Grebitus, C.: Does where you shop matter? Consumers' willingness to pay for processed versus non-processed local food at different outlets. Presented at the 2017 Applied and Agricultural Economics Association Conference, Chicago, IL 7/30-8/1/2017. Based on the publication in Ecological Economics Dr. Grebitus and graduate student Iryna Printezis conducted two consumer surveys (one in March 2017 and one in July 2017) addressing specifically community gardens and the likelihood of consumers to grow food there implemented in two different major cities in the US, namely Detroit and Phoenix to account for differences in regional and socio-demographic characteristics. How have the results been disseminated to communities of interest?Enhanced crop and urban modeling capabilities have been released in the public version 3.9 of the community Weather Research and Forecasting (WRF) model. What do you plan to do during the next reporting period to accomplish the goals?We will continue to integrate datasets from USDA and other sources in the WRF-Urban-Crop modeling system to enhance the regional climate modeling capabilities of WRF. We will explore the scaling up of field-scale irrigation model to continental scales and examine the effects of irrigation in the U.S. Corn Belt on regional hydrometeorology. We plan to conduct high-resolution WRF-Urban-Crop simulations to investigate the urban and cropland expansion on regional climate.

Impacts
What was accomplished under these goals? For the Goal-1: (1) The WRF-Crop modeling system was enhanced with incorporation of numerous USDA agriculture management data, which are based on 20 years of historical crop progress estimates and the knowledge of industry specialists. The integration of those data, including state-maps of growing degree days, planting dates, and harvest dates, provides observation constrain to better represent regional differences in agriculture management in the earth system models. Those new date sets for the continental U.S. domain were released in the public version of the WRF V3.9 in April 2018. (2) We investigated the effects of chronic ozone exposure on hydrometeorology and crop productivity using ourfully coupled crop, meteorology and chemistry model. (3) Studies of extreme events for integrated agricultural and urban systems included simulations of the meteorology and PM10concentrations in Arizona dust storms. For the Goal-2: (a) completed work on open land classification for the Phoenix metro-area, publishing a paper on the subject and providing a presentation on it at the USDA NIFA annual meeting in Oct 2017 (graduate student Jordan Smith et al 2017) (b) created and delivered a targeted survey of expert communities to determine those open spaces that would serve as most suitable for urban farms and community gardens. The results will be used in a Multiple Criteria Evaluation as part of an effort to optimize possible urban farms and garden sites. (c) geo-located the respondents to EaSM survey as part of the optimization research. (d) The NAIP 1 m land classification for Phoenix data were converted to the NLCD classification and delivered to the project WRF modelers. (e) An initial exploration of WRF-land cover modification scenarios was made using USDA crop types. (f) The Baltimore 1 m classification using NAIP data was completed. Co-PI Grebitus also conducted a consumer survey to identify the effects of social networks on consumer behavior as it relates to urban farming.The aim is to connect peer effects to answer questions regarding consumer behavior and success of urban farming. For the Goal-3: The integrated WRF-Urban-Crop model was applied to investigate: Impacts of projected urban expansion and global warming on cooling energy demand over a semiarid region including Phoenix and Tucson metropolitan areas; District-level cooling electric loads during a heatwave event and impacts of air-conditioning waste heat on 2-m air temperature using the latest WRF-Urban coupled to Noah-MP. The simulated spatial distribution of AC electric loads in suburban and rural districts is significantly improved by introducing the urban-class dependent building cooled fraction.Sensitivity results demonstrate that spatially-varying maps of AC working schedules and the ratio of sensible to latent waste heat release are critical for correctly simulating the cooling electric loads and capturing the thermal stratification of urban boundary layer. Interactions of soil moisture and summer heatwaves. Soil moisture deficits can amplify summer heatwaves (HWs) through soil moisture-temperature feedback which has critical impacts on society, economy and human health. In this study, we evaluated decade-long fine-resolution WRF model simulations over contiguous U.S. on simulating heatwaves and its relationship with antecedent soil moisture with dense observational networks. The WRF model is capable of capturing most of the HW characteristics, such as heatwave temperature threshold, HWF, and HWM, while showing warm bias in Midwest and cold bias in western mountainous regions. Significant anti-correlations between antecedent soil moisture and both HW aspects have been found in most parts of the domain except the South Pacific Coast. This study focused on Midwest and South Great Plain that experienced extreme heatwaves in the last decade. In both regions, HWF responses to dry soil moisture much stronger on the upper end of the frequency distribution than lower end (high frequency gets more frequent). Conversely, the dry soil has stronger impacts on lower percentile than higher percentile of HWM (mild HW get hotter). WRF well represents the heterogeneous responses to dry soil on HWF distribution in both regions, but underestimates these responses on HWM in Midwest while overestimates them in South Great Plain. These results show confidence in WRF's ability to simulate HW characteristics and the amplification through soil moisture-temperature feedback mechanism, and have potential to improve HW forecasting using antecedent soil moisture as important proxy. Memory of irrigation effects on local hydroclimate. Irrigation modifies land-surface water and energy budgets, and also influences weather and climate. However, current earth-system models, used for weather prediction and climate projection, are still in their infancy stage to consider irrigation effects. This study used long-term data collected from two contrasting (irrigated and rainfed) nearby maize-soybean rotation fields, to study the effects of irrigation memory on local hydroclimate. For a 12-year average, irrigation decreases summer surface-air temperature by less than 1 °C and increases surface humidity by 0.52 g kg-1. The irrigation cooling effect is more pronounced and longer lasting for maize than for soybean. Irrigation reduces maximum, minimum, and averaged temperature over maize by more than 0.5 °C for the first 6 days after irrigation, but its temperature effect over soybean is mixed and negligible two or three days after irrigation. Irrigation increases near-surface humidity over maize by about 1 g kg-1 up to ten days and increases surface humidity over soybean (~ 0.8 g kg-1) with a similar memory. Those differing effects of irrigation memory on temperature and humidity are associated with respective changes in the surface sensible and latent heat fluxes for maize and soybean. Sensitivity of urban boundary layer simulation to urban canopy models and PBL schemes over urban areas. This study combines data from new high-resolution Doppler lidar observations, automatic weather stations (AWS), and a flux tower located in an urban site to assess the performance of the WRF using three urban canopy models and four planetary boundary layer (PBL), especially focusing on the representation of the urban boundary layer (UBL) processes. Results show that the simulated 2-m temperature and 10-m wind speed are more sensitive to urban canopy models than to PBL schemes. Using the BouLac PBL scheme and the multi-layer BEP urban canopy model generates the best agreement with AWS observations. Simulations with the multi-layer BEM model produces the highest mixing-layer heights. The convective boundary layer (CBL) from UCM experiment develops at the slowest pace when compared with other two multi-layer urban canopy models. When the single-layer UCM is used, simulations with the non-local mixing YSU, SH and ACM2 schemes perform better than the TKE-based scheme (BouLac) for representing the CBL structure. Additionally, the scale-aware SH scheme considering the effect of grid resolution on the vertical dimension, simulates the potential temperature profiles that are closest to observations.

Publications

  • Type: Journal Articles Status: Published Year Published: 2018 Citation: F. Salamanca, Y. Zhang, M. Barlage, F. Chen, A. Mahalov, and S. Miao (2018), Evaluation of the WRF-urban modeling system coupled to Noah and Noah-MP land surface models over a semiarid urban environment, Journal of Geophysical Research Atmospheres, published, doi: 10.1002/2018JD028377
  • Type: Journal Articles Status: Accepted Year Published: 2018 Citation: Xu, X., F. Chen, S. Shen, S. Miao, M. Barlage, W. Guo, and A. Mahalov, 2018: Using WRF-Urban to assess summertime air conditioning electric loads and their impacts on urban weather in Beijing. J. Geophys. Res., in press.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Hunt, J. C. R., Aktas, Y. D., Mahalov, A., Moustaoui, M., Salamanca, F. and Georgescu, M. (2017). Climate change and growing megacities: hazards and vulnerability. Proceedings of the Institution of Civil Engineers - Engineering Sustainability, 113.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Tewari, M., F. Salamanca, A. Martilli, L. Treinish, and A. Mahalov (2017), Impacts of projected urban expansion and global warming on cooling energy demand over a semiarid region, Atmospheric Science Letters, doi: 10.1002/asl.784.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: P. Hyde, A. Mahalov, and J. Li, 2017: Simulating the meteorology and PM10 concentrations in Arizona dust storms with WRF-Chem, Journal of the Air & Waste Management Association, published, (http://www.tandfonline.com/doi/abs/10.1080/10962247.2017.1357662?journalCode=uawm20).
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Grebitus, C., I. Printezis and A. Printezis (2017): Relationship between consumer behavior and success of urban agriculture. Ecological Economics, 136, 189-200; IF 3.227; 5-yr IF 4.227.
  • Type: Journal Articles Status: Submitted Year Published: 2018 Citation: Printezis, I., C. Grebitus and S. Hirsch (2018): A meta regression analysis on local food  Informing on willingness to pay opportunities for produce from urban farms, Food Policy, submitted.
  • Type: Journal Articles Status: Published Year Published: 2018 Citation: N. Clinton, M. Stuhimacher, A. Miles, N. Aragon, M. Wagner, M. Georgescu, C. Herwig, P. Gong (2018), A global geospatial ecosystem services estimate of urban agriculture, Earths Future, vol. 6, Issue 1.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Jordan P. Smith, X. Li, B L. Turner II. 2017. Lots for greening: Identification of metropolitan vacant land and its potential use for cooling and agriculture in Phoenix, AZ, USA. Applied Geography, Vol. 85, pp. 139-151. https://doi.org/10.1016/j.apgeog.2017.06.005.
  • Type: Journal Articles Status: Submitted Year Published: 2018 Citation: S.R. Shaffer (2018). Urban fraction and urban area parameter bias - demonstration of parameter bias and model sensitivity using a 1 meter resolution land cover data product, J. Appl. Meteorol. Climatol., Manuscript ID: JAMC-D-18-0026, Submitted.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Salamanca F., Y. Zhang, M. Barlage, F. Chen, and A. Mahalov (2017), Evaluation of the Noah-MP land surface model coupled to WRF in a semiarid urban environment, 18th Annual WRF Users Workshop, NCAR, Boulder, Colorado, June 12-June 16, 2017.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: S.R. Shaffer, A High Resolution Land cover Data Product to Remove Urban Density Over Estimation Bias for Coupled Urban-Vegetation-Atmosphere Interaction Studies Fall Meeting of American Geophysical Union, New Orleans, LA, 1 1-15 December, 2017. Talk A42D-02 ID:260967 Session A42D: Land-Atmosphere Interactions, Biosphere-Boundary Layer Feedbacks, and Moist Convection II.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: S.R. Shaffer, Sensitivity analysi s of urban canopy and land surface models to input land cover data products, 18th Annual WRF Users Workshop, 12-16 June 2017, Boulder, CO.


Progress 05/01/16 to 04/30/17

Outputs
Target Audience:The findings of this project are aimed at reaching broad audiences. Data are placed online in a digital library for public use. The urbanized WRF-Crop Regional Modeling System is developed and will be officially released by NCAR for use by the scientific, agricultural application, and urban planning communities. Project results and findings are shared and broadly disseminated to the local community through the Global Institute of Sustainability seminar series (the hub of ASU's sustainability initiatives and open to public); seminars hosted at ASU's Decision Center; via peer-reviewed and popular publications; presentations at scientific meetings; and online.Relevant data is made accessible to a wide audience, for both researchers interested in utilizing simulation results to further their research and more general audiences (e.g., stakeholders, Farmers, City Mayors, Decision makers) interested in fundamental knowledge and applications of the results. Special efforts are made to recruit women and underrepresented minority students interested in the project activities. The team members also engage with diverse, non- academic audiences through programs that take research into schools and public forums, including the CAP LTER and the Sustainable Schools GK12 Program in GIOS. Outreach activities with broader impacts include collaboration with the Desert Botanical Garden in Phoenix to facilitate Spaces of Opportunity, a community-driven community garden/urban agriculture "food hub" project developed through a collaboration between the Garden, Cultivate South Phoenix (CUSP) and the Roosevelt School District. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?The project providedopportunities for training and professional development of students and postdocs. For example, postdoc Salamanca visited NCAR to conduct research and implement the urban canopy models (UCMs) in the new Noah-MP land surface model (Noah-MP LSM). Graduate student Meng Wang received funding from NCAR to participate and present a paper in the environmental statistics summer program. How have the results been disseminated to communities of interest?Enhanced urban and crop modeling capabilities have been released in the public version 3.9 of the community Weather Research and Forecasting (WRF) model.Alex Mahalov and Fei Chen were invited to give invited lectures on urban environments at the Croucher Foundation Advanced Study Institute 2015-2016: "Changing Urban Climate & the Impact on Urban Thermal Environment and Urban Living". What do you plan to do during the next reporting period to accomplish the goals?We will continue to integrate datasets from USDA and other sources in WRF-Urban-Crop modeling system to enhance the modeling capabilities of WRF. We plan to conduct high-resolution WRF-Urban-Crop simulations to investigate the impacts of urban and cropland expansion on regional climate. We will further investigatethe concepts of personality and social networks to answer questions regarding consumer behavior and success of urban farming. These studieswill focus on both, individuals who are and who are not, engaged in urban gardening, and subsequently map their social networks. Additional questions will consider their personality traits.

Impacts
What was accomplished under these goals? For the Goal-1: One major accomplishment was the incorporation of corn and soybean modeling modules in the Noah-MP land-surface model, which was evaluated against data obtained from crop sites in the AmeriFlux network. The resultant new Noah-MP-Crop model is released in the public version of the WRF V3.9 in April 2017. The other effort was to couple the more advanced Noah-MP land model with urban canopy models in WRF and to evaluate its performance for different urban regions, and the new WRF-Urban with Noah-MP will be released in the public version of the WRF V3.9 in April 2017. During the reporting period, we also developeda novel, machine learning method to identify vacant parcels for potential agriculture for large metropolitan areas with the assistance of NAIP imagery and cadastral data.Land classification at 1m resolution from NAIP imagery was completed for the Phoenix and Baltimore metropolitan areas, and1m NAIP data wascollected and the image processing started on the land classification of the Frenso, CA, area. For the Goal-2: The 30-meter USDA/GMU Cropscape crop type dataset was integrated in the WRF-Crop modeling system to enhance the regional crop modeling capability in WRF. We also developedan optimization model to address the placement pattern of green spaces in the central Phoenix area to mitigate the nighttime and daytime UHI effect. The model indicates up to 2°C local and 0.5°C regional cooling can be achieved and 96% of the daytime and nighttime cooling effect can be reached through the optimal pattern. During the reproting period, Co-PI Grebitus designeda study addressing specifically community gardens and the likelihood of consumers to grow food there to be implemented in two different major cities in the US, namely Detroit and Phoenix, to account for differences in regional and socio-demographic characteristics. Consumer survey identifiedthe effects of social networks on consumer behavior as it relates to urban farming. She also organizeda track session for the 2016 Applied and Agricultural Economics Association Conference, Boston, MA 7/29-8/3/2016. The track session "Transformations in Food Systems: Opportunities and Challenges for Alternative Food Systems.wassponsored by the Community and Regional Economics Network. For the Goal-3: The integrated WRF-Urban-Crop model was applied to investigate: 1) the use of green roof, cool roofs, and rooftop solar photovoltaic deployment to mitigate urban heat island effects, 2) impacts of physics parameterizations on high-resolution weather prediction in metropolitan areas, 3) impact of Enhanced Hydrological Processes on Urban Hydrometeorology with Application to cities in contrasting climates, 4) and effects of new city land-cover data and building-height data on WRF-Urban simulations. During the reproting period, the impacts of Mexican and southwestern U.S. agricultural and urban irrigation on North American monsoon (NAM) rainfall and other hydrometeorological fields wereinvestigated by implementing an irrigation scheme into the WRF-land surface model.The Noah-Multiparameterization land surface model in the WRF/Chemwasmodified to include the effects of chronic ozone exposure (COE) on plant conductance and photosynthesis (PCP) found from field experiments. The impacts of chronic ozone exposure on plant's conductance and photosynthesis were investigated.Employing this modified WRF/Chem model in high ozoneregions improved ourunderstanding of the interactions of vegetation, meteorology, chemistry/emissions, and crop productivity.

Publications

  • Type: Journal Articles Status: Accepted Year Published: 2016 Citation: Salamanca F., M. Georgescu, A. Mahalov, M. Moustaoui, and A. Martilli (2016), Citywide impacts of cool roof and rooftop solar photovoltaic deployment on near-surface air temperature and cooling energy demand, Boundary-Layer Meteorol., 161 (1), 203-221.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Hunt, J. C. R., Y. D. Aktas, A. Mahalov, M. Moustaoui, F. Salamanca, and M. Georgescu (2017), Climate change and growing megacities: hazards and vulnerability, Engineering Sustainability, DOI: 10.1680/jensu.16.00068, Published March 13, 2017.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: S.R. Shaffer, M. Moustaoui, A. Mahalov, and B. L. Ruddell, 2016: A method of aggregating heterogeneous subgrid land cover input data for multi-scale urban parameterization. J. Appl. Meteor. Climatol., doi: 10.1175/JAMC-D-16-0027.1.
  • Type: Journal Articles Status: Accepted Year Published: 2017 Citation: Li, X., Kamarianakis, Y., Ouyang, Y., Turner, B. L., II, & Braze, A.l (2017). On the Association between Land System Architecture and Land Surface Temperatures: Evidence from a Desert MetropolisPhoenix, Arizona, U.S.A. Landscape and Urban Planning. DOI:10.1016/j.landurbplan.2017.02.009
  • Type: Journal Articles Status: Accepted Year Published: 2017 Citation: Zhang, Y., Murray, A. & Turner, B. L., II. (2017) Optimizing green space locations to reduce daytime and nighttime urban heat island effects in Phoenix, Arizona. Landscape and Urban Planning.
  • Type: Journal Articles Status: Published Year Published: 2017 Citation: Grebitus, C., Printezis, I., and A. Printezis (2017): Relationship between consumer behavior and success of urban agriculture. Ecological Economics, 136, 189-200.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2016 Citation: Grebitus, C., Printezis, I., and A. Printezis: Consumer Perception of Urban Agriculture. Presented at the 2016 Applied and Agricultural Economics Association Conference, Boston, MA 7/29-8/3/2016.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2017 Citation: Grebitus, C., Kolodinsky, J., and D. Thilmany McFadden (2017): Theme Overview: Transformations in the Food System, Nutritional and Economic Impacts. Choices. Quarter 1.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Li, J., A. Mahalov and P. Hyde, Impact of agricultural irrigation on ozone concentrations in the Central Valley of California and in the contiguous United States, J. Agricultural and Forest Meteorology, 2016, pp. 34-49.DOI: 10.1016/j.agrformet.2016.02.004.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Mahalov, A., Li and P. Hyde, Regional impacts of irrigation in Mexico and southwestern U.S. on hydrometeorological fields in the North American Monsoon region, Journal of Hydrometeorology, American Meteorological Society, 2016, published DOI: http://dx.doi.org/10.1175/JHM-D-15-0223.1
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Li, J., A. Mahalov and P. Hyde, Simulating the impacts of chronic ozone exposure on plants conductance and photosynthesis, and on hydroclimate in the continental U.S., Environ. Res. Lett,, 2016, published, Environ. Res. Lett. 11 (2016) 114017, doi:10.1088/1748-9326/11/11/114017
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Barlage, M., S. Miao, and F. Chen, 2016: Impact of physics parameterizations on high-resolution weather prediction over complex urban areas. J. Geophys. Res., 121, 44874498, doi:10.1002/2015JD024450.
  • Type: Journal Articles Status: Submitted Year Published: 2017 Citation: F. Salamanca, Y. Zhang, M. Barlage, F. Chen, A. Mahalov, and S. Miao (2017), Evaluation of Noah-MP land surface model coupled to WRF in a semiarid urban environment (submitted).


Progress 05/01/15 to 04/30/16

Outputs
Target Audience:This study advances scientificunderstanding and modeling capabilities of linked LULC agriculturaland urban processes on decadal and regional scalesfor integrated agricultural and urban applications.It produces fundamental knowledge regarding techniques for generating economic andsocial impact projections of urban agriculture/community gardens, which are increasingly criticalto the social fabric, food security and wellness of local communities. Project techniques serve as a new paradigm for integrated studies of regional agriculturaland urban climate systems on decadal timescales, which arecritically important for policymakers. Itassesses the impact of projected land cover/use change viaend-to-end high resolution nested simulations, thereby providing vital information for agriculturaland urban planning and mitigation of climate impacts. Training of graduate students and youngscientists to undertake interdisciplinary research and conduct policy discussions based onresearch results arealsoattributes of the project. The integrated agricultural and urban modeling system will be released for communityuse. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?The project providesopportunities for training and professional development of students and postdocs. For example, during the reporting period, postdoc Salamanca visited NCAR for 3.5 months to implementthe urban canopy models (UCMs) in the new Noah-MP land surface model (Noah-MP LSM). Graduate student Meng Wang received funding from NCAR to participate and present a paper in the environmental statistics summer program. How have the results been disseminated to communities of interest?The results have been disseminated to communities of interest inpublications, conference presentations and public forums. During the reporting period, Dr. Mahalov presenteda plenary lecturein the opening ceremony of the Croucher Advanced Study Institute ``Changing Urban Climate and the Impact on Thermal Urban Environment and Urban Living'', Hong Kong, 7-11 December, 2015.The primary objectives of the institute includedthe dissemination of climatic knowledge and technologies, climatic planning and design strategies. ``CroucherAdvanced Study Institutes are presented by faculty of international standing, following a competitive process,Bringing together groups of practitioners at the forefront of their respective fields,CroucherAdvanced Study Institutes provide an opportunity to assess recent findings and to explore potential new avenues of research.''More information inhttp://www.arch.cuhk.edu.hk/asi2015/en/People/guests.htm Dr. Georgescu served as invited panelist at the 16th National Conference and Global Forum on Science, Policy and the Environment, held in Washington DC, during January 2016. The emphasis of this year's conference was on the Food-Energy-Water-Nexus, providing a unique opportunity to address ongoing research to broader communities. Dr. Grebitus (ASU Morrison School of Agribusiness) submitted a track session proposal for the 2016 Applied and Agricultural Economics Association Conference to be held in Boston, MA in July. The track session was accepted and is sponsored among others by the Community and Regional Economics Network. The title of the track session is "Transformations in Food Systems: Opportunities and Challenges for Alternative Food Systems." The rationale for the session is that in order to feed the increasing urban population alternative food production systems need to be identified and implemented. Among those are Community Supported Agriculture (CSA) and other urban farming systems. This session aims to highlight opportunities and challenges of these food production systems along the supply chain. In particular, the presentations will focus on consumers' perception of urban farming, and their acceptance of and willingness to pay for produce grown in a vertical farm production system. The impacts of CSA program participation on consumer attitudes and behaviors related to food consumption and preparation are discussed. Teaching Gardens that provide school children with opportunities to learn about food and nutrition while planting, maintaining, harvesting, and preparing produce from their school garden are analyzed. Presenters examine whether subsidizing the cost of CSAs, integrated with tailored education increases produce consumption and improves overall diet quality. Finally, this session provides a forumon the emerging marketing and business strategies in the CSA sector, with a focus on multi-farm operations. Specifically, the impact of these innovations on firm and producer-level profitability are evaluated and prospects for the future evolution of the sector are assessed. Dr. Grebitus will present her paperon Consumer Perception of Urban Agriculture. Additional presentations in the session are on Consumer Acceptance of Alternative Production Systems: The Case of Vertical Farming, CSA Programs and Dietary Behavioral Change, Impacts of the American Heart Association Teaching Gardens Program on Fruit and Vegetable Consumption: A National Study,Economic Contribution and Potential Impact of Farm to School Programs in Vermont, Cost-offset CSA's: Working Toward Better Nutrition for Resource Challenged Families and Better Livelihoods for Farmers as well as The Changing CSA Strategic Business Model and The Promise of Urban Agriculture: National Study of Commercial Farming in Urban Areas (the latter two presentations will be given by Debra Tropp and Samantha Schaffstall from USDA Agricultural Marketing Service). What do you plan to do during the next reporting period to accomplish the goals?The NAIP and Landsat TM land-cover/use data for Baltimore metropolitan area is being classified. The aim is create data sets consistent with those for the Phoenix metropolitan area for assessments with WRF modeling efforts. In addition, we will continue to improve our Phoenix open land product and, if feasible, apply it to Baltimore as well. These improvement include the addition of commercial and public vacant lands and as well as large portions of non-vacant but open lands. If possible through ancillary data, current urban agriculture too small to systematically detect through remote sensing will be added. Coupling the land surface model to the Weather Research and Forecasting (WRF) atmospheric model. The new modeling capability will be available for the scientific community next year inWRF (V3.9). Development of mosaic land surface models to incorporate percent cover of classifications derived from 1 m National Agricultural Imagery Program (NAIP; aerial imagery) and 30 m Landsat TM (satellite imagery). The aggregation method together with a mosaic approach are also being employed to investigate hydroclimate impacts from conversion of urban "open land" identified as suitable for cultivation, via urban farms or community gardens.A study of WRF model sensitivity to land surface representation when derived from these data products and for different aggregation methods will beconducted. Other areas currently under investigation will include:improved non-urban representation within urban areas - heterogeneous vegetation land cover;scenarios of land cover conversion from barren or degraded to potential cropland, sensitivity and scenarios;irrigation scenarios and implementation techniques within non-urban tiles of grid cells containing urban tiles, along with agricultural tiles toinclude modified timings and mode of irrigation application, along with method, e.g. sprinkler, drip, flood, lower soil-layer/root-zone moisture modification.

Impacts
What was accomplished under these goals? Data Development High resolution land-cover/use classification data and mapping were developed and provided to the project. The 1 m National Agricultural Imagery Program (NAIP; aerial imagery) and 30 m Landsat TM (satellite imagery) classifications and data for the Phoenix metropolitan area in formats have been produced. The 1m and 30m resolution remotely sensed classified images have been aggregated to several coarser levels of resolutions (e.g.,, 250m and 1000m) and are being used as input in the WRF model to examine the effect of accuracy and sensitivity of land-cover/use maps to the model results.We employed the data to address "sub-WRF" scale UHI effects of land architecture (land composition and land configuration) by land surface temperature and near ground air temperature. Another effort for the project was undertaken to determine the amount of open space in the Phoenix metropolitan area suitable for urban agriculture. This effort combines cadastral, elevational, and remote sensing data to identify privately owned but open (vacant, unused) land with low slope levels that could be used for agriculture or for green spaces.Work continues to add different types of vacant land as well asto address extent urban agriculture. The NAIP and Landsat TM land-cover/use data for Baltimore metropolitan area is being classified. The aim is create data sets consistent with those for the Phoenix metropolitan area for assessments with WRF modeling efforts. In addition, we will continue to improve our Phoenix open land product and, if feasible, apply it to Baltimore as well. These improvement include the addition of commercial and public vacant lands and as well as large portions of non-vacant but open lands.If possible through ancillary data, current urban agriculture too small to systematically detect through remote sensing will be added. Physics Based Predictive Modeling and NOAH MP Land Surface Model Development in WRF Design and implementation of sustainable strategies that reduce the direct impacts of urban expansion and simultaneously reduce emissions of long-lived greenhouse gases. Within this context, the first activity has been focused on the assessment of mitigation strategies that combat simultaneously global warming, urban heat islands, and urban energy demands. Adetailed physics-based parameterization of solar photovoltaic (PV) panels was developed and implemented in a multilayer building energy model that is fully coupled to the WRFatmospheric model. Specifically, the multilayer urban canopy model is dynamically integrated in the Noah land surface model (Noah LSM) that is coupled to WRF. For the non-urban part, land-use categories were implemented using the MODIS land-cover classification. The Noah land surface model was applied to the fraction of grid cells with natural cover and the multilayer building energy model to the fraction with built cover. Development of physics-based predictive modeling tools that are able to effectively quantify co-benefits and reveal tradeoffs associated with the conversion of natural to agricultural and to urban landscapes. Within this context, the second activity [in direct collaboration between ASUand NCAR] was focused on the implementation of the urban canopy models (UCMs) in the new Noah-MP land surface model (Noah-MP LSM). Computational tests revealed that the new Noah-MP LSM developed by ASU and NCAR performs better than the former Noah LSM, and that the new WRF/Noah-MP modeling system is a promising predictive modeling tool forcharacterizationcurrent and future multi-scale environmental impacts associated with agricultural productivity within cities.The new modeling capability will be available for the scientific community next year inWRF (V3.9). Development of Heterogeneous subgrid land cover input data for multi-scale parameterizations Computational & Information Systems Laboratory (CISL) computing support for ourEaSM project was approvedby the CISL HPC Advisory Panel (CHAP). We receivedan allocation of 402,000 core-hours on Yellowstone.CISL Project:UASU0006,CISL Project End: 8/31/19,Project Leads:Stephen Shaffer and Alex Mahalov, ASU,Project Title:Hydroclimatic impacts accompanying localization of food production within cities, part 1: improving urban parameterization and performing high resolution simulations. As part of model development and evaluation for application within an interactively coupled urban-climate-agricultural model for urban settings, there have been several activities.Firstly, methods of downscaling computationalmodel within the urban environment have been evaluated. Secondly, improved techniques for incorporating subgrid land cover data have been developed and are being applied for both urban and non-urban land cover classes.Observations from a new 22.1-m flux tower situated within a residential neighborhood in Phoenix, Arizona, were utilized to evaluate the ability of the urbanized WRF to resolve finescale surface energy balance (SEB) when using the urban classes derived from the 30-m-resolution National Land Cover Database. A method for representing grid-scale heterogeneous development density for urban climate models from probability density functions of sub-grid resolution observed data is proposed in Shaffer et al. 2016(accepted for publication). Derived values are evaluated in relation to normalized Shannon Entropy to provide guidance in assessing model input data. The method enables obtaining urban fraction dependent upon resolution and class partition scheme, based upon improved parameterization of observed data, which provides one means of influencing simulation prediction at various aggregated grid scales. These methods are being applied within mosaic land surface models to incorporate percent cover of classifications derived from 1 m National Agricultural Imagery Program (NAIP; aerial imagery) and 30 m Landsat TM (satellite imagery). The aggregation method together with a mosaic approach are also being employed to investigate hydroclimate impacts from conversion of urban "open land" identified as suitable for cultivation, via urban farms or community gardens. Impacts of agricultural irrigation on ozone concentrations in the Central Valley of California and in the contiguous United States based on WRF-Chem simulations Our paper was published inAgricultural and Forest Meteorology, vol. 221, p. 34-49, 2016. Examination of socio-economic impacts associated with agri-urban development Co-PI Grebitus (Morrison School of Agribusiness at ASU)developed a consumer survey instrument. The purpose of this study was to determine (1) whether consumers perceive that there are personal health impacts, environmental health benefits of local/organic produce vs. conventional produce and (2) what attitudes consumers hold towards urban gardening as a source of local produce after being informed about what urban gardens are. More broadly, the study focused onevaluating the extent to which consumers may be motivated by benefits to themselves/their own family vs. benefits to the environment and/or community with regards to going to urban gardens. Developing the WRF-Crop modeling system and enhancing hydrologic modeling In this collaborative study between ASU and NCAR, physically-based parametrizations of hydrological processes were implemented into the single layer canopy model in the WRF model.As the first phase of study conducted in FY15-16, dynamic corn and soybean growth models and field management (e.g., planting date) were introduced into Noah-MPand the enhanced model (Noah-MP-Crop) was evaluated at field scales using crop biomass datasets, surface heat fluxes, and soil moisture observations.We are in the final stage of testing the release of the Noah-MP-Crop model in the public WRF version, and plan also to enhance the modeling system with the incorporation of global crop-type maps and modeling dynamic crop rooting depth and density.

Publications

  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Li. X., Li, W., Middel, A., Harlan, S.L., Brazel, A., and Turner II, B.L., 2016. Remote sensing of the surface urban heat island and land architecture in Phoenix, Arizona: combined effects of land composition and configuration and cadastral-demographic-economic factors, Remote Sensing of Environment, 174, 233-243.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Li, A. Mahalov and P. Hyde, 2016: Impacts of agricultural irrigation on ozone concentrations in the Central Valley of California and in the contiguous United States based on WRF-Chem simulations, Agricultural and Forest Meteorology, vol. 221, p. 34-49.
  • Type: Journal Articles Status: Accepted Year Published: 2016 Citation: Salamanca F., M. Georgescu, A. Mahalov, M. Moustaoui, and A. Martilli (2016), Citywide impacts of cool roof and rooftop solar photovoltaic deployment on near-surface air temperature and cooling energy demand, Boundary-Layer Meteorology (accepted for publication).
  • Type: Journal Articles Status: Accepted Year Published: 2016 Citation: S.R. Shaffer, M. Moustaoui, A. Mahalov, and B. L. Ruddell, (Accepted): A method of aggregating heterogeneous subgrid land cover input data for multi-scale urban parameterization. J. Appl. Meteor. Climatol..
  • Type: Journal Articles Status: Under Review Year Published: 2016 Citation: Liu, X., F. Chen, M. Barlage, G. Zhou, D. Niyogi, 2015: Noah-MP-Crop: Introducing Dynamic Crop Growth in the Noah-MP Land-Surface Model. J. Geophys. Res., in revision.
  • Type: Journal Articles Status: Published Year Published: 2016 Citation: Yang, J., Z.-H Wang, M. Georgescu, F. Chen, and M. Tewar, 2016: Assessing the impact of hydrological processes on urban meteorology using an integrated WRF-Urban modelling system. J. Hydrometeor., 17, 1031-1046.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2016 Citation: Georgescu M. (2016), Embedding sustainability within a social and physical framework, Wednesday, January 20, 2016 (Invited Talk at 16th National Conference and Global Forum on Science, Policy and the Environment, Washington DC, USA).
  • Type: Conference Papers and Presentations Status: Other Year Published: 2015 Citation: Plenary address by Alex Mahalov in the Croucher Advanced Study Institute ``Changing Urban Climate and the Impact on Thermal Urban Environment and Urban Living, Hong Kong, 7-11 December, 2015