Progress 09/01/18 to 08/31/19
Outputs
Target Audience:The UVMRP mission is to provide high quality data, data products, and services in support of agricultural research, and to facilitate the use of these measurements with climate and crop models. Research topics span the geographic distribution of UV-B solar irradiance and the effects of increased or diminished UV-B on crops, native and invasive plants, and animals. The program participates in international instrument inter-comparisons to ensure quality control and a common reference standard for comparing U.S. data with the rest of the world. Over the past years there have been between 6,000 and 10,000 visits per month to the web site by users to obtain data and/or related information. Over the years, 45% of web data downloads have come from .EDU domains, 45% from .GOV domains and the balance from other domains. Both national and international educators and students have retrieved data or related information via the program website. Most academic data use is for agricultural research. The UVMRP measurements and tools have been the source for numerous research studies conducted by universities and agricultural research facilities across the nation. Fourteen land grant universities have prior and/or current research studies in collaboration with the UVMRP, and all of them have a UVMRP instrument array at their location. In addition, the UVMRP has prior and/or current research collaborations with government agencies such as NASA, NOAA, DOE, EPA, and NSF. UVMRP stakeholders include: a) USDA personnel at all levels who fund, participate, or have an interest in the program, b) agricultural researchers from governmental, academic, and other institutions, and c) educators and students at all levels who make use of network data and tutorials. Collaboration and support of research in the effects of UV-B on plants and materials has resulted in papers that were presented at scientific conferences. As ground based measurements of UV-B and study of UV-B effects on agriculture continue to be important, and predictive crop yield tools come of age, an increasing number of researchers could make use of UVMRP products. Perhaps the best measure of the effectiveness of the UVMRP in serving stakeholders is the large number of publications that have come directly from the program or from collaboration with affiliated researchers. There have been over 300 publications to date in the 25-year history of the UVMRP. Agricultural effects studies account for two-thirds of publications, with UV-B climatology making up most of the remainder. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Undergraduate and graduate students as well as post-doctoral researchers have been included in all project areas. During their involvement with the program, young investigators may lead measurement and analysis efforts, serve as lead- and co-authors on papers in scientific journals, proceedings, and transactions, and/or deliver presentations of research work at professional society events. Currently, two graduate students and a Postdoctoral fellow are focusing on addressing technical challenges primarily related to CWRF/DSSAT model version inconsistencies and computing system configuration changes. UVMRP is also providing training for a postdoctoral fellow on modeling of relationships between the environment, agricultural and economic factors, focusing on attributions of U.S. crop production to various natural and human factors. UVMRP researchers also trained four undergraduate students in the navigation of remote sensing data sets and utilization of machine learning techniques. We are also collaborating with Southern University, Baton Rouge, Louisiana on their project "Urban Tree Interception of UV (A/B) Radiation and Its Genetic Consequences", which utilizes a mobile version of a typical UVMRP agroclimatological site. As part of this collaboration, we assist Southern University with data issues and interpretation and engage in discussions of research activities pertaining to modeling impacts of UV radiation on agricultural and forest ecosystems. How have the results been disseminated to communities of interest?Data from all agroclimatologic and research network sites are available on the project's web site (http://uvb.nrel.colostate.edu). Our scientifically peer-reviewed papers and associated conference presentations are also available on the website for scientific and/or wider communities of interest. Additionally, UVMRP staff routinely respond directly to data inquiries and requests for UV-related expertise via telephone and email. Currently we have users from more than 300 different organizations, with 48% from national educational institutions; 33% from national governmental agencies; 2% from commercial enterprises; and 17% from international institutions. What do you plan to do during the next reporting period to accomplish the goals?We will deliver continuous maintenance of the network instruments, preserve high rates of data collection, develop up-to-date calibration protocols, and provide reliable primary and derived data products. We will continue to work with Mississippi State University and utilize their SPAR facility to evaluate the isolated and combined effects of UV-B and other environmental stressors on crops (cotton, corn, soybean, sweetpotato, and rice). Further progress towards the completion of the Integrated Agricultural Impact Assessment System framework is expected through ongoing collaborations with the University of Maryland. This includes advancing efforts to couple the Agroecosystem modules (CROP) with the CWRF model as well as developing and integrating an economic module into the impact assessment system to provide insight for farm management practices and policy decisions. For climatology data collection, we will continue to follow our established QC protocols and schedule annual site visits to perform necessary instrument maintenance. Ongoing evaluation of the shadowband and pyranometer QC flags and methodology is expected to simplify and improve the efficiency of the automated component of the QC procedure. We will continue to work with site operators to ensure rapid response to instrument issues. Evaluation of the in-house calibration facility software and hardware will be conducted to improve the efficiency and accuracy of the (UV-) MFRSR spectral response measurements. We will continue to investigate state-of-the-art methodologies for data processing. Specifically, the Gaussian Process regression based smooth and prediction method will be applied for historic in-situ calibration factors at all UVMRP sites. Critical parameters for the Gaussian Process regression will be adjusted according to the noise and gap patterns at different channels and sites. Planned analysis of existing UVMRP data will aim to address emerging transdisciplinary questions. This includes an investigation of the impact of smoke from the historic 2018 California fires on surface radiation at the UVMRP sites. Of particular interest is the relationship between wavelength, diffuse fraction of radiation, and aerosol optical depth and the impact this relationship has on crop radiation use efficiency. For effects research, we will continue to evaluate the isolated and combined effects of UV-B and other environmental stressors on the growth and development of major crops including rice, soybean, corn, sweetpotato, and cotton and to identify the cultivars/lines tolerance for future environmental conditions. This includes conducting SPAR chamber experiments to investigate the temperature effects on cotton seedling emergence, growth, and development. Additionally, we will use the SPAR chamber to characterize the morphology and physiology of over 50 rice genotypes under adverse temperature and drought conditions in early season or at seedling stage. In a separate study, the best traits associated with enhanced yield and early maturity among 100 elite rice genotypes will be identified. We will also investigate the impacts of soil moisture and temperature stress on soybean growth, yield, and/or seed quality. These experiments will facilitate the development of quantitative algorithms that will be incorporated into climate-crop simulation models for the Climate-Agroecosystem-UV Interactions and Economic system. For integrated assessment, we will continue to develop the coupled CWRF-CROP system to simulate the growth and yields of corn and soybean. Specifically, we will convert the CWRF data into DSSAT input data, and DSSAT output data into CWRF-ready formats needed to predict one season of soybean growth at one geographic location. We will continue to combine statistical analysis and dynamic modeling to determine quantitative relationships between crop yields and environmental, technological, and adaptation factors. To achieve this, we will compile a consistent dataset of available records, including USDA crop yields and acreages, NOAA daily temperature and precipitation, EPA surface ozone, and USDA state-level agricultural total factor productivity. We will conduct coupled and uncoupled dynamic environment-crop model simulations to investigate the physical processes and underlying mechanisms that may explain the statistical relationships. We will continue to develop the coupled CWRF and BioCro model to simulate the effects of growing biofuel crops in the US marginal lands on soil moisture, leaf area index, evapotranspiration, and biomass, to determine the teleconnections between regional climate and hydrologic processes, and to better understand the impacts of growing biofuel crops on regional food-energy-water nexus system resilience. The CWRF model will also be improved via evaluation of the impacts of five cumulus parameterization schemes on microphysics, radiation, boundary layer, and land surface processes. Specific mechanisms (e.g., water and energy supply, surface and cloud forcing) associated with the cumulus parameterizations that impact spatiotemporal characteristics of daily 95th percentile precipitation (P95) over the US Gulf States and Central-Midwest States will be identified. We will continue to develop the DayCent-UV and CWRF coupling. As part of this effort, we will determine the dominant cropland type in each NARR grid cell; evaluate DayCent output for the NARR grid for vegetation and agricultural regions; and optimize the reading of crop, management, and disturbance parameters. Additional UV decomposition mechanisms will be incorporated into the biogeochemical model DayCent-UV to simulate the soil carbon and nitrogen dynamics in ranchlands and dry lands in the western U.S. Specifically, we will modify the soil organic matter decomposition module "SOMDEC" to incorporate the solar UV radiation effect on soil slow pool (SOM2) decomposition.
Impacts
What was accomplished under these goals?
UVMRP objectives are to: collect high-quality and geographically-distributed solar ultraviolet and visible radiation measurements; make historic and current data publicly available in near-real time to the agricultural community and in support of UV-related research; conduct experiments exploring the isolated and combined effects of UV and other abiotic factors on economically-important crops; collaborate on the development of an assessment system, which integrates meteorology, soil, plant processes, agricultural practices, and economic impacts, to assist with predicting effects of environmental stressors on agriculture for policymakers. For climatology data collection, we continue to provide high-quality measurements via our webpage for users investigating the impacts of solar UV radiation on agriculture. UVMRP manages the only surface UV-B monitoring network in the US. The project supports 37 agroclimatological sites, plus 4 long-duration research sites, that together encompass 20 ecoregion provinces and a variety of land types. UVMRP staff perform daily checks of the polling success and initiate timely contact with site operators to correct any problems. Conversion from analog telephone modems to Ethernet/cellular connections has been accomplished for 66% of sites and is ongoing. UVMRP uses algorithms to set appropriate QC flags for each station based on range checks and daily visual data inspection. The network status report is updated routinely and disseminated to UVMRP staff. We continue to improve the accuracy of our irradiance measurements. The in-house calibration facility is currently capable of (UV-) MFRSR spectral response measurements. All shadowband and pyranometer instruments receive periodic re-calibration at NOAA's Mauna Loa Observatory (MLO). Comparisons between the instruments, a Brewer Spectrometer and modeled irradiances indicate that the MLO Langley calibration uncertainties lie within the World Meteorological Organization's recommended 10%. PAR sensors are calibrated by the manufacturer. Monthly in-situ calibrations are performed using the Langley Analyzer and a supplemental cloud screening algorithm. A data fusion technique was used to merge TOMS-OMI satellite data and UVMRP ground measurements to achieve better estimates of surface UV. Numerical results using data from 2005-2015 showed that TOMS-OMI data were improved when combined with UVMRP data over the continental US. We built a Deep Neural Network (DNN) to distinguish cloudy and clear-sky conditions using daily 3-minute time-series' of direct normal measurements. Hyper parameter tuning results suggest that the best DNN is the 3-layer 250-hidden-unit Bi-LSTM with 80-epochs training. The model learned to approximate total optical depth and finds an appropriate threshold on logits for cloud screening. We continue to investigate impacts of UV-B radiation and other environmental factors on the growth and development of economically important crops through collaboration with Mississippi State University. Experiments were conducted in MSU's Soil-Plant-Atmosphere-Research (SPAR) chambers, which monitor and control plant- growing conditions, including temperature, water inputs, and UV-B radiation, with current emphasis on cotton, soybean, and sweetpotato. For instance, temperature (T) impacts on cotton seed germination and early plant development was examined. Shoot system morphology parameters (leaf area, number of leaves, plant height) for 4 cultivars displayed a positive relationship with T. Similarly, emergence rate and root morphology parameters increased with T for all cultivars with slightly different rates. We also investigated the response of 9 cotton lines to drought and temperature stress. Both drought and low-T had adverse effects on all examined root (number of root tips, forks, and crossings) and shoot morphology parameters across genotypes, with more pronounced impacts associated with low-T; some variation in the sensitivity of the cotton lines to these abiotic stressors was observed. To quantify shoot and root vigor responses during sweetpotato early transplant establishment, an experiment was conducted at three day/night T conditions for 10 sweetpotato cultivars. Sweetpotato cultivars varied significantly for many traits, particularly root components. To evaluate cotton cultivars for heat and drought stresses, pollen-based traits and physiological parameters at optimum and high T were measured during the boll-filling period. Principle Component Analysis and drought stress response index were used to categorize cultivars into three heat and drought tolerant clusters. Another study compared 2 soybean cultivars each with different growth habits for yield components and pod distribution patterns. Results indicate that the 2 cultivars have marked variations in plant growth parameters under soil moisture deficit. In ongoing collaboration with University of Maryland, we are developing a comprehensive predictive system available to the agricultural community and policy makers for risk analysis, economic impacts evaluation, and strategic planning to achieve sustainable agricultural development under changing environmental conditions as part of our integrated assessment efforts. We continue to develop the coupled CWRF-CROP system to simulate and predict the growth and yields of corn and soybean in the US. Specifically, we are separating key components for the soybean module (CROPGRPO) from other crop modules in DSSAT, identifying DSSAT inputs (outputs) from (to) CWRF such as daily temperature and precipitation, and transforming DSSAT outputs to CWRF such as daily leaf area index and root fraction during growing seasons. Specifically, the soil organic matter decomposition FORTRAN module "SOMDEC" was modified to incorporate the solar UV radiation effect on the microbial turnover rate in the surface microbial pool. We continue to combine statistical analysis and dynamic modeling to attribute variations in US crop production to environment, technology, and adaptation factors. Consolidation of US crop history data from Survey and Census using regression or more advanced fitting functions is ongoing and addresses unreliable and/or missing data records to generate a complete dataset for all crop types at the county level. So far, the harvested fractions of corn, soybean, cotton, and hay between 1978 and 2012 have been processed. We continue to couple CWRF with a biomass growth model (BioCro) to simulate biofuel crop growth on US marginal land and to study land use change impacts on environment. We have also worked on using the Newton-method to solve stomatal conductance equilibrium; re-parameterizing the miscanthus root distribution; simplifying the estimation of some phenology parameters; and replacing the radiation and hydrology modules with CWRF counterparts. To inform the integrated assessment framework, we have also completed a literature review of environmental impacts on agricultural production, adaptation strategies, and technology influences to compare indicators, methodologies, experiments and impacts among the studies. We continue to develop the DayCent-UV model and couple it with CWRF. We adapted the photosynthetic sub-module from the SIPNET/PnET model and incorporated it into DayCent so that the maximum net photosynthetic rate varied with seasons. With optimization, the modified DayCent showed improved accuracy in simulating the seasonal patterns of net ecosystem exchange (NEE), gross primary production (GPP), actual evapotranspiration (AET), and ecosystem respiration (at two AmeriFlux sites). We used DayCent to evaluate the role of photodegradation in nutrient cycling at a California grassland site. Validation indicated the model robustly captures ecosystem dynamics on annual and seasonal scales. Sensitivity analysis suggested photodegradation accelerated C and N cycling, suppressed microbial N immobilization and did not impact plant productivity.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Reddy, K. R., D. Brand, C. Wijewardana, and W. Gao. 2017. Temperature Effects on Cotton Seedling Emergence, Growth, and Development. Agronomy Journal, 109(4), 1379-1387, doi:10.2134/agronj2016.07.0439
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Chen M., W. J. Parton, S. Del Grosso, M. D. Hartman, K. Day, C. J. Tucker, J. Derner, A. Knapp, W. C. Smith, D. Ojima, and W. Gao. 2017. The Signature of Sea Surface Temperature Anomalies on the Dynamics of Semi-arid Grassland Productivity. Ecosphere. 8, e02069. doi: 10.1002/ecs2.2069
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Sun, Z., J. Davis, and W. Gao. 2017. Estimating Error Covariance and Correlation Region in UV Irradiance Data Fusion by Combining TOMS-OMI and UVMRP Ground Observations. IEEE Transactions on Geoscience and Remote Sensing, vol. 56, no. 1, doi: 10.1109/TGRS.2017.2748031
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2017
Citation:
Chen M., J. M. Davis, C. Liu, Z. Sun, M. Zempila, W. Gao. 2017. Using Deep Recurrent Neural Network for direct beam solar irradiance cloud screening. Proceedings of SPIE, Remote Sensing and Modeling of Ecosystems for Sustainability XIV, 10405, 1040503. doi: 10.1117/12.2273364
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2017
Citation:
Zempila, M.M., J. Davis, G. Janson, B. Olson, M. Chen, B. Durham, S. Simpson, J. Straube, Z. Sun, and W. Gao. 2017. Quality assurance of the UV irradiances of the UV-B Monitoring and Research Program: the Mauna Loa test case. Proceedings of SPIE, Remote Sensing and Modeling of Ecosystems for Sustainability XIV, 10405, 104050A, doi: 10.1117/12.2274525
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Wijewardana, C., K. R. Reddy, F. A. Alsajri, J. T. Irby, B. Golden, and J. Krutz. 2018. Quantifying soil moisture deficit effects on soybean yield and yield component distribution patterns. Irrigation Science, 1432-1319. doi: 10.1007/s00271-018-0580-1
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Wijewardana, C., K. R. Reddy, M. W. Shankle, S. Meyers, and W. Gao. 2018. Low and high-temperature effects on sweetpotato storage root initiation and early transplant establishment. Scientia Horticulturae, 240, 38-48. doi: 10.1016/j.scienta.2018.05.052
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Straube, J. R., M. Chen, W. J. Parton, S. Asao, Y. Liu, D. S. Ojima, W. Gao. 2018. Development of the DayCent-Photo model and integration of variable photosynthetic capacity. 2018. Frontiers of Earth Science, 12, 4, 765778. https://doi.org/10.1007/s11707-018-0736-6
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Chen, M., Z. Sun, J. M. Davis, C. Liu, and W. Gao. 2018. Spatial interpolation of surface ozone observations using deep learning. Proceedings of SPIE, Remote Sensing and Modeling of Ecosystems for Sustainability XV. 10767. 107670C-1 - 107670C-15. doi: 10.1117/12.2320755
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Singh, B., E. Norvell, C. Wijewardana, T. Wallace, D. Chastain, and K. R. Reddy. 2018. Assessing morpho-physiological characteristics of elite cotton lines from different breeding programs for low temperature and drought tolerance. Journal of Agronomy and Crop Science, 00, 1-10. doi: 10.1111/jac.12276
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Singh, K., C. Wijewardana, B. Gajanayake, S. Lokhande, T. Wallace, D. Jones, and K. R. Reddy. 2018. Genotypic variability among cotton cultivars for heat and drought tolerance using reproductive and physiological traits. Euphytica, 214(3), 56-77. doi: 10.1007/s10681-018-2135-1
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Asao, S., W. J. Parton, M. Chen, and W. Gao. 2018. Photodegradation accelerates ecosystem N cycling in a simulated California grassland. Ecosphere, 9(8), e02370-1 - e02370-18. doi: 10.1002/ecs2.2370
|
Progress 09/01/16 to 08/31/19
Outputs
Target Audience:The UVMRP mission is to provide high quality data, data products, and services in support of agricultural research, and to facilitate the use of these measurements with climate and crop models. Research topics span the geographic distribution of UV-B solar irradiance and the effects of increased or diminished UV-B on crops, native and invasive plants, and animals. The program participates in international instrument inter-comparisons to ensure quality control and a common reference standard for comparing U.S. data with the rest of the world. Over the past years there have been between 6,000 and 10,000 visits per month to the web site by users to obtain data and/or related information. Over the years, 45% of web data downloads have come from .EDU domains, 45% from .GOV domains and the balance from other domains. Both national and international educators and students have retrieved data or related information via the program website. Most academic data use is for agricultural research. The UVMRP measurements and tools have been the source for numerous research studies conducted by universities and agricultural research facilities across the nation. Fourteen land grant universities have prior and/or current research studies in collaboration with the UVMRP, and all of them have a UVMRP instrument array at their location. In addition, the UVMRP has prior and/or current research collaborations with government agencies such as NASA, NOAA, DOE, EPA, and NSF. UVMRP stakeholders include: a) USDA personnel at all levels who fund, participate, or have an interest in the program, b) agricultural researchers from governmental, academic, and other institutions, and c) educators and students at all levels who make use of network data and tutorials. Collaboration and support of research in the effects of UV-B on plants and materials has resulted in papers that were presented at scientific conferences. As ground-based measurements of UV-B and study of UV-B effects on agriculture continue to be important, and predictive crop yield tools come of age, an increasing number of researchers could make use of UVMRP products. Perhaps the best measure of the effectiveness of the UVMRP in serving stakeholders is the large number of publications that have come directly from the program or from collaboration with affiliated researchers. There have been over 300 publications to date in the 28-year history of the UVMRP. Agricultural effects studies account for two-thirds of publications, with UV-B climatology making up most of the remainder. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Undergraduate, graduate, and post-doctoral participation and mentoring are taking place in all phases of the project, through co-authorship of papers in scientific journals, proceedings, and transactions, as well as presentations of research work at professional society events. A master student worked with Dr. K. Raja Reddy's group at Mississippi State University to explore the isolated and interactive effects of UV-B radiation and nitrogen supply on multiple sweetpotato species conducting two experiments between August and November, 2016 using their SPAR chambers. The student completed his degree in March 2017. UVMRP provided training for a postdoctoral fellow on modeling of relationships between the environment, agricultural and economic factors, focusing on attributions of U.S. crop production to various natural and human factors. We are collaborating with Southern University, Baton Rouge, Louisiana on their project "Urban Tree Interception of UV (A/B) Radiation and Its Genetic Consequences", which utilizes a mobile version of a typical UVMRP agroclimatological site. As part of this collaboration, we assist Southern University with data issues and interpretation and engage in discussions of research activities pertaining to modeling impacts of UV radiation on agricultural and forest ecosystems. Two graduate students and a Postdoctoral fellow are focusing on addressing technical challenges primarily related to CWRF/DSSAT model version inconsistencies and computing system configuration changes. How have the results been disseminated to communities of interest?Data from all agroclimatologic and research network sites are available on the project's web site (http://uvb.nrel.colostate.edu). Our scientifically peer-reviewed papers and associated conference presentations are also available on the website for scientific and/or wider communities of interest. Additionally, UVMRP staff routinely respond directly to data inquiries and requests for UV-related expertise via telephone and email. Currently we have users from more than 300 different organizations, with 48% from national educational institutions; 33% from national governmental agencies; 2% from commercial enterprises; and 17% from international institutions. Our paper in determining climate effects on US total agricultural productivity that was published in the Proceedings for the National Academy of Sciences of the United States of America (PNAS), attracted significant media attention, and which was covered by Nature Research Highlights in 2017. The 5-year impact factor of the PNAS is 10.4, while the current altmetric score of the article is 117 revealing the significance of its findings. Furthermore, it has been cited 17 times, downloaded over 12,000 times, picked up by 8 news outlets, tweeted by 55 users with potential 166,904 followers, and have 134 readers on Mendeley. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
UVMRP objectives are (1) to collect high-quality and geographically-distributed solar ultraviolet and visible radiation measurements and to make these data publicly available for the agricultural and science communities; (2) to conduct experiments on the isolated and combined effects of UV and other abiotic factors on economically important crops; (3) to collaborate on the development of the assessment system to project effects of environmental stressors on the agricultural system. For climatology data collection, we continue to provide high-quality UV and Visible surface radiation measurements via our web page. UVMRP manages the only surface UVB monitoring network in the US. The project supports 37 agroclimatological sites and 4 long-duration research sites that together encompass 20 ecoregions and a variety of land types. UVMRP staff checks the polling success daily and work with site operators to correct any problems. Conversion from analog telephone modem connections to Ethernet/cellular modem connections has been performed for 66% of the sites and is ongoing. UVMRP uses QC/QA algorithms to set appropriate flags for each station based on range checks which are augmented with daily visual data inspection and log files. We continue to improve the accuracy of our measurements. The in-house calibration facility is currently capable of (UV-) MFRSR spectral response measurements. All radiometers receive periodic recalibration at NOAA's Mauna Loa Observatory (MLO), Hawaii. Monthly in-situ calibrations are performed using the Langley Analyzer and a supplemental cloud screening algorithm. UVMRP investigated an in-situ calibration method for 940nm irradiance data using column water vapor retrieved from GPS constellations. UVB-1 and UVA radiometers are calibrated at MLO against standards established at the International UV Filter Radiometer comparison (Davos, Switzerland, 2017). PAR sensors are calibrated by the manufacturer. We continue to develop new algorithms to improve our in-situ calibration, retrieve atmospheric parameters, and perform analysis using our measurements. One algorithm utilized Gaussian Process Regression to estimate the mean and uncertainty of in-situ calibration factors for UV-MFRSR. Additionally, we built a Deep Neural Network to distinguish cloudy and clear-sky conditions using direct normal measurements. The model approximated total optical depth and found a suitable threshold for cloud screening. We also employed a data fusion technique to merge TOMS-OMI and UVMRP data that improved surface UV measurements over the continental US (2005-2015). For effects research, several experiments were conducted in Mississippi State University's Soil-Plant-Atmosphere-Research (SPAR) environmental chambers to investigate impacts of UVB radiation and other environmental factors on the growth and development of economically important crops. In general, physiological and morphological parameters of cotton cultivars were adversely affected by low temperature (T) and drought across tested cotton cultivars. However, some variation in the sensitivity of the cotton cultivars to these abiotic stressors was observed. A study also found that UVB exposure had detrimental effects on root and shoot vigor in cotton and these effects were amplified by T stress. CO2 fertilization did offset, but not fully compensate, for the UVB and/or T damages. The effects of UVB radiation on soybean growth, seed quality, and root structure were also examined. Exposure to higher UVB radiation adversely impacted seed quality and root morphology parameters. These results have improved crop modeling efforts including simulated soybean growth parameters in the CROPGRO Fortran module. Another study indicates that two soybean cultivars have marked variations in plant growth parameters under soil moisture deficit. To quantify shoot and root vigor responses during sweetpotato early transplant establishment, an experiment was conducted under different day/night T conditions for 10 sweetpotato cultivars. Traits significantly varied among sweetpotato cultivars, particularly root components. The findings of these studies could allow for selection of cultivars with the best coping ability for future climate change environments. For integrated assessment, we are working with the University of Maryland to develop a comprehensive predictive system for risk analysis, economic impacts evaluation, and strategic planning to achieve sustainable agricultural development in a changing environment. We continue to develop the coupled CWRF-CROP system to simulate and predict the growth and yields of corn and soybean in the US. Replacement of soil dynamic modules and advancements in a bi-directional communication between CWRF and DSSAT models are ongoing. For instance, DSSAT nitrogen (N) uptake modules are being coupled with CWRF N-related modules so that the potential availability of soil NO3 and NH4 can be estimated correctly. Using the DSSAT corn sub-module coupled with CWRF, we simulated production in corn-belt states based on historical environmental conditions. The modeled mean annual corn yields (1979-2005) generally capture the geographic distribution of the county-level data and show strong correlations with T and precipitation over most areas. This analysis validated the coupled DSSAT-CWRF model for simulating corn yields in the US. We are also separating distinctive components for the DSSAT soybean module and identifying soybean relevant inputs (outputs) from (to) CWRF. We continue to couple CWRF with a biomass growth model (BioCro) to simulate biofuel crop growth on US marginal land and to study land use change impacts on climate. Consolidation of U.S. crop history data from Survey and Census is ongoing and addresses unreliable or missing data records to generate a complete county-level crop dataset. Our study featured in the Proceedings for the National Academy of Sciences focused on the correlation between total factor productivity (TFP) and environmental variables. Results suggest that T and precipitation in distinct agricultural regions explained ~70% of variations in TFP growth (1981-2010) and that projected environmental extremes could cause TFP to drop to pre-1980 levels by 2050. Additionally, linear regression between TFP change and environment factors indicate that the projected climate changes could cause TFP to drop up to ~4%/yr under medium to high emissions scenarios. The Tropospheric Ultraviolet and Visible Radiation Model (TUV) has been incorporated into CWRF-CROP for clear-sky conditions. We continue to work on coupling these models for all-sky conditions using cloud parameters retrieved from space-borne and ground-based sensors (NCEP historical re-analysis products). We continue to develop the DayCent-UV model to quantify UV impacts on ecosystems and couple it with CWRF. We adapted the photosynthetic sub-module from the SIPNET model so that the maximum net photosynthetic rate varied with season in DayCent. Ecosystem variables (NEE,GPP,AET) modeled by the optimized DayCent compared well with observations at two AmeriFlux sites. Direct photolysis, facilitation of microbial decomposition, and microbial inhibition effects were incorporated into DayCent. Results showed the 3 mechanisms can simulate linear carbon loss and persistent net N release observed in long-term litter decomposition experiments. DayCent-UV was used to evaluate the role of photodecay in nutrient cycling at a California grassland site. Validation showed the model robustly captures ecosystem dynamics on annual and seasonal scales. Sensitivity analysis showed photodecay accelerated C and N cycling, suppressed microbial N immobilization and did not impact plant productivity. We continue to develop the DayCent crop management files and parameters for dominant crop rotations (e.g. wheat/fallow) to couple DayCent with CWRF. The equilibrium simulation (pre-1979) for the NARR grid was also improved.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Chen, M., Z. Sun, J.M. Davis, Y.-A. Liu, C.A. Corr, and W. Gao. 2019. Improving the mean and uncertainty of ultraviolet multi-filter rotating shadowband radiometer in situ calibration factors: utilizing Gaussian process regression with a new method to estimate dynamic input uncertainty. Atmospheric Measurement Techniques, 12, 935-953. doi: 10.5194/amt-12-935-2019.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Singh, B., D.R. Chastainb, S. Jumaa, C. Wijewardana, E.D. Redona, W. Gao, K.R. Reddy. 2019. Projected day/night temperatures specifically limits rubisco activity and electron transport in diverse rice cultivars. Environmental and Experimental Botany, 159, 191-199
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Jumaa, S.H., E.D. Redona, T. Walker, W. Gao, And K.R. Reddy. 2018. Developing screening tools for early-season high- and low-temperature stress. Sabrao Journal of Breeding and Genetics, 51:12-36
|
Progress 09/01/17 to 08/31/18
Outputs
Target Audience:The UVMRP mission is to provide high quality data, data products, and services in support of agricultural research, and to facilitate the use of these measurements with climate and crop models. Research topics span the geographic distribution of UV-B solar irradiance and the effects of increased or diminished UV-B on crops, native and invasive plants, and animals. The program participates in international instrument inter-comparisons to ensure quality control and a common reference standard for comparing U.S. data with the rest of the world. Over the past years there have been between 6,000 and 10,000 visits per month to the web site by users to obtain data and/or related information. Over the years, 45% of web data downloads have come from .EDU domains, 45% from .GOV domains and the balance from other domains. Both national and international educators and students have retrieved data or related information via the program website. Most academic data use is for agricultural research. The UVMRP measurements and tools have been the source for numerous research studies conducted by universities and agricultural research facilities across the nation. Fourteen land grant universities have prior and/or current research studies in collaboration with the UVMRP, and all of them have a UVMRP instrument array at their location. In addition, the UVMRP has prior and/or current research collaborations with government agencies such as NASA, NOAA, DOE, EPA, and NSF. UVMRP stakeholders include: a) USDA personnel at all levels who fund, participate, or have an interest in the program, b) agricultural researchers from governmental, academic, and other institutions, and c) educators and students at all levels who make use of network data and tutorials. Collaboration and support of research in the effects of UV-B on plants and materials has resulted in papers that were presented at scientific conferences. As ground based measurements of UV-B and study of UV-B effects on agriculture continue to be important, and predictive crop yield tools come of age, an increasing number of researchers could make use of UVMRP products. Perhaps the best measure of the effectiveness of the UVMRP in serving stakeholders is the large number of publications that have come directly from the program or from collaboration with affiliated researchers. There have been over 320 publications to date in the 25-year history of the UVMRP. Agricultural effects studies account for 66% of publications, with UV-B climatology making up most of the remainder. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Undergraduate, graduate, and post-doctoral participation and mentoring are taking place in all phases of the project, through co-authorship of papers in scientific journals, proceedings, and transactions, as well as presentations of research work at professional society events. We are collaborating with Southern University, Baton Rouge, Louisiana on their project "Urban Tree Interception of UV (A/B) Radiation and Its Genetic Consequences", for which they use a mobile cart which contains all the instruments of a typical UVMRP agroclimatological site. We helped them diagnose and solve the abnormal data issues and clarified the physical meanings of our data for them. We also discussed with their scientists about research activities pertaining to modeling impacts of UV radiation on agricultural and forest ecosystems. Two graduate students and a Postdoctoral fellow are focusing on addressing technical challenges primarily related to model version inconsistencies and computing system configuration changes. UVMRP scientists provided training for a postdoctoral fellow on modeling of relationships between the environment, agricultural and economic factors, focusing on attributions of U.S. crop production to various natural and human factors. How have the results been disseminated to communities of interest?The agroclimatologic and research network sites data are available on the project's web site (http://uvb.nrel.colostate.edu) after thorough examination of the quality. Our publication list is available via the Program's web site as well. These scientifically peer-reviewed papers and associated conference presentations provide most of our outreach to scientific and/or wider communities of interest, and replying to data users specific requests complements this outreach. Currently we have users from more than 300 different organizations, with 48% from national educational institutions; 33% from national governmental agencies; 2% from commercial enterprises; and 17% from international institutions. What do you plan to do during the next reporting period to accomplish the goals?We will deliver continuous maintenance of the network instruments, preserve high rates of data collection, develop up-to-date calibration protocols, and provide reliable secondary products. We will continue our collaboration with Mississippi State University, to utilize their SPAR facility to evaluate the isolated and combined effects of UV-B and other environmental stressors on crops (cotton, corn, soybean, sweetpotato, and rice). We will also continue our collaboration with the University of Maryland to develop the Integrated Agricultural Impact Assessment System framework. We will continue our efforts in coupling the Agroecosystem modules (CROP) with the CWRF model. We will continue to develop and integrate an economic module into the impact assessment system, which will provide insight for farm management practices and policy decisions. For climatology data collection, we will continue to follow our well established Quality Assurance and Quality Control (QA/QC) protocols and schedule annual site visits to perform necessary instrument maintenance. We annually renew the collaborations with site operators, which are necessary to preserve a high data collection rate. As part of improving our calibration procedures, we will continue to develop the in-house calibration facility in order to provide stability tests of our suite of instruments. We will continue to investigate state-of-the-art methodologies. Specifically, the Gaussian Process regression based smooth and prediction method will be applied for historic in-situ calibration factors at all UVMRP sites. Critical parameters for the Gaussian Process regression will be adjusted according to the noise and gap patterns at different channels and sites. We will develop and validate cloud screening methods based on deep neural network algorithms. At our MLO calibration site, we will keep using the pair of Kipp & Zonen YES UV-B broadband radiometers (UVS-ET-UV) calibrated at the Davos, Switzerland intercomparison in summer 2017 as the reference standards to calibrate the network's fleet of YES UVB-1 pyranometers. In effects research, we will continue to evaluate the isolated and combined effects of UV-B and other environmental stressors on cotton, corn, soybean, sweetpotato, and rice, which are some of the most economically important crops. Specifically, we will use the SPAR chamber to investigate the temperature effects on cotton seedling emergence, growth, and development. We will also examine the effects of UV-B and other environmental stressors such as temperature on growth and development (including root architectures) for rice. These experiments will facilitate the development of quantitative algorithms that will be incorporated into climate-crop simulation models for the Climate-Agroecosystem-UV Interactions and Economic system. In integrated assessment, we will continue to develop the coupled CWRF-CROP system for simulating the growth and yields of corn and soybean. Specifically, we will separate the components and variables for soybean module (CROPGRPO module) from other crop modules in DSSAT, and identify its possible inputs from CWRF and outputs to CWRF. We will continue to develop the DayCent-UV and CWRF coupling. Specifically, we will determine the dominant cropland type in each NARR grid cell; continue to evaluate DayCent output for the NARR grid for vegetation and agricultural regions; and optimize the reading of crop, management, and disturbance parameters. We will continue to incorporate the UV decomposition mechanisms into the biogeochemical model DayCent-UV, to simulate the soil carbon and nitrogen dynamics in ranchlands and dry lands in the western U.S. Specifically, we will modify the Soil Organic Matter Decomposition module "SOMDEC" to incorporate the solar UV radiation effect on the microbial turnover rate in the surface SOM1 pool (surface microbial pool). The relationship between environments, agricultural production, and its economic values will enable us to analyze best practices and evaluate the economic consequences of land use and crop production responses. In order to facilitate study of crop production, technology advances, and climate adaptation, we will continue to synthesize the historical county-level crop data (including total acres harvested and crop yield per acre) in the U.S. using the every-5-year Census reports and the annual Surveys. We will continue to analyze the long-term correlation between the U.S. agricultural TFP and the key environmental variables to evaluate US agricultural sustainability.
Impacts
What was accomplished under these goals?
UVMRP objectives are: to collect high-quality and geographically distributed solar ultraviolet and visible radiation measurements; to make both the historic and current data publicly available in near-real time to the agricultural community and in support of science research that studies UV effects; to conduct experiments exploring both isolated and combined effects of UV and other abiotic factors on economically important crops; to collaborate on the development of the assessment system, which integrates meteorology, soil, plant processes, agricultural practices, and economic impacts, to assist with predicting effects of environmental stressors on agriculture for the benefit of policymakers. In climatology data collection, we continue to provide high-quality measurements daily via our web page for users to investigate the impacts of solar UV radiation on agriculture. UVMRP manages the only remaining network of nationwide surface monitoring of UV-B irradiance. The project supports 36 agroclimatological sites, plus 5 long-duration research sites, that together encompass 20 ecoregion provinces covering a variety of land types. UVMRP staff perform daily checks of the polling success, and initiate timely contact with site operators to correct problems. Conversion from analog telephone modem connections to Ethernet/cellular modem connections has been performed for 40% of the sites and is ongoing. UVMRP staff have developed semi-automated QC/QA algorithms which set appropriate flags for each station based on range checks, and which are augmented with daily visual data inspection and log files. The network status report is updated routinely and is disseminated to UVMRP staff. We continue to improve the accuracy of our irradiance measurements. The in-house calibration facility is under development, which measures the spectral responses of (UV-) MFRSRs, with potential to include UVB-1 and PAR radiometers in the future. All shadowband and pyranometer instruments receive periodic re-calibration at NOAA's Mauna Loa Observatory. The PAR sensors receive periodic re-calibration at the manufacturer's laboratory. For in-situ calibration, UVMRP has applied the new cloud screening algorithm as a supplement to the Langley Analyzer at network sites. UVMRP is also investigating an automatic procedure to smooth in-situ calibration factor time series. We continue to develop new algorithms to improve the retrieval of total column ozone (TOC) from our irradiance measurements. One algorithm retrieves TOC from direct normal irradiances of UV-MFRSR using Beer's Law. The algorithm was validated at HI02 against Dobson TOC values for the period 2010-2015. The results showed that the new algorithm had an up to 4% underestimation compared to the Dobson values (R2~0.91). In effects research, we continue the collaboration with Mississippi State University to study both isolated and interactive impacts of UV-B radiation and other environmental factors on growth and development of economically important crops. Experiments were conducted in MSU's Soil-Plant-Atmosphere-Research (SPAR) chambers, which monitor and control plant-growing conditions, including temperature, water inputs, and UV-B radiation, with current emphasis on cotton. Brand et al. 2016 investigated the difference of three cotton cultivars in their responses to multiple environmental factors of +CO2, temperature (-T), and +UV-B. This work found that plants grown under -T alone or in combination with +UV-B treatment caused more detrimental effects on root and shoot vigor. The +CO2 treatment weakened but did not fully compensate the damaging effects of +UV-B treatment. Among the three environmental stresses, -T caused the most damaging to cotton early seedling vigor while +CO2 caused the least. Based on PCA, the four cultivars were classified as tolerant (DP1522B2XF), intermediate (PHY496W3R and ST4747GLB2), and sensitive (TM-1) to multiple environmental stresses. The findings of this study could allow for selection of cultivars with the best coping ability and higher lint yield for future climate change environments. In integrated assessment, we collaborate with the University of Maryland to develop a comprehensive predictive system that specifically meets the needs of the agricultural community and policy makers, to perform risk analysis, economic impacts evaluation, and strategic planning for effective solutions to achieve sustainable agricultural development under changing environmental conditions. We continue to develop the coupled CWRF-CROP system to simulate and predict the growth and yields of corn and soybean in the US. Specifically, we are modifying nitrogen uptake modules (NUPTAK) in DSSAT model, to interact with CWRF nitrogen-related input/output and the crop model, so that the potential availability of NO3 and NH4 for soil layers can be estimated correctly. We continue to develop DayCent-UV model and couple it with the CWRF model. We continue to develop the DayCent crop management files and parameters for ten dominant crop rotations (e.g. wheat/fallow, continuous wheat, continuous cotton, and corn/soybean). The equilibrium simulation (pre-1979) for the NARR grid was also improved. For the DayCent-UV development, Chen et al. 2016 reviewed the recent research regarding the solar UV radiation effects on plant litter decomposition. We are working on incorporating the following three mechanisms into the DayCent-UV model: direct photolysis; facilitation of microbial decomposition via production of labile materials, and microbial inhibition effects. The preliminary results showed that photodecay rate should be parameterized as a function of litter's initial lignin fraction, and the three mechanisms have the potential to simulate linear carbon loss and persistent net nitrogen release patterns observed in the long-term litter decomposition experiments in the western US. Specifically, the subroutine "DAILYMOIST" was modified to provide litter-level solar radiation estimated from the canopy-level one by an exponential function. The estimated daily litter-level radiation will be past to litter decomposition related subroutine(s). We continue to analyze performance of the distributed DSSAT (corn) model in simulating historical (1979 to 2005) corn growth and yield variation in the US with an emphasis on temperature and precipitation effects. The simulated mean annual corn yields generally capture the geographic distribution of the county-level data, showing high correlation coefficients (>0.6) and low relative biases (<5%), and strong correlations with temperature and precipitation over most areas of the Corn Belt. This analysis validated the coupled DSSAT-CWRF model for simulating corn yields in the US. We continue to synthesize the historical (i.e. from 1910 to 2017) county-level crop data (including total acres harvested and crop yield per acre) in the US using the every-5-year Census reports and the annual Surveys. In addition, we continue to analyze the spatial pattern and the interannual variation of county-level corn harvests and yields between 1978 and 2012 over the entire US, with an emphasis on the Corn Belt. We continue to develop the economic assessment model. Linear regression models between the total factor productivity change (TFPC) and environment factors were built by analyzing TFPC, temperature and precipitation observational data across the US. The model results indicate that the projected climate changes could cause TFP to drop by an average 2.84 to 4.34% per year under medium to high emissions scenarios. In addition, Hallar et al. 2017 correlated the summertime aerosol loading with aridity and fire area burned at several western US sites. The work concluded that wildfires are the main contributor to the surface-level organic aerosol loading.The conclusion of this work will help better constrain environmental projections in organic aerosol loading with increased fire activity.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
Chen, M., W. J. Parton, E. C. Adair, S. Asao, M. D. Hartman, and W. Gao. 2016. Simulation of the effects of photodecay on long-term litter decay using DayCent. Ecosphere, 7, e01631. doi: 10.1002/ecs2.1631
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
Brand, D., C. Wijewardana, W. Gao, and K.R. Reddy. 2016. Interactive effects of carbon dioxide, low temperature, and ultraviolet-B radiation on cotton seedling root and shoot morphology and growth. Frontiers of Earth Science 10:607-620
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Hallar, A. G., N. P. Molotch, J. L. Hand, B. Livney, I. B. McCubbin, R. Petersen, J. Michalsky, D. Lowenthal, and K. E. Kunkel. 2017. Impacts of increasing aridity and wildfires on aerosol loading in the intermountain Western US. Environmental Research Letters, Volume 12, Number 1
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2017
Citation:
Zempila, M.M., K. Fragkos, J. Davis, Z. Sun, M. Chen, and W. Gao. 2017. Total ozone column retrieval from UV-MFRSR irradiance measurements: evaluation at Mauna Loa station. Proceedings of SPIE, Remote Sensing and Modeling of Ecosystems for Sustainability XIV, 10405, 1040507, doi: 10.1117/12.2274565
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Progress 09/01/16 to 08/31/17
Outputs
Target Audience:The UVMRP mission is to provide high quality data, data products, and services in support of agricultural research, and to facilitate the use of these measurements with climate and crop models. Research topics span the geographic distribution of UV-B solar irradiance and the effects of increased or diminished UV-B on crops, native and invasive plants, and animals. The program participates in international instrument inter-comparisons to ensure quality control and a common reference standard for comparing US data with the rest of the world. Over the past years there have been between 6,000 and 10,000 visits per month to the web site by users obtaining data and/or informational material. Over the years, 45% of web data downloads have come from .EDU domains, 45% from .GOV domains and the balance from other domains. Both national and international educators and students have retrieved data or informational material via the program website. Most academic data use is for agricultural research. The UVMRP measurements and tools have been the source for numerous research studies conducted by universities and agricultural research facilities across the nation. Fourteen land grant universities have prior and/or current research studies in collaboration with the UVMRP, and all of them have a UVMRP instrument array at their location. In addition, the UVMRP has prior and/or current research collaborations with government agencies such as NASA, NOAA, DOE, EPA, and NSF. UVMRP stakeholders include: a) USDA personnel at all levels who fund, participate, or have an interest in the program, b) agricultural researchers from governmental, academic, and other institutions, and c) educators and students at all levels who make use of network data and tutorials. Collaboration and support of research in the effects of UV-B on plants and materials has resulted in papers that were presented at scientific conferences. As ground based measurement of UV-B and study of its effects on agriculture continue to be important, and predictive crop yield tools come of age, an increasing number of researchers could make use of UVMRP products. Perhaps the best measure of the effectiveness of the UVMRP in serving stakeholders is the large number of publications that have come directly from the program or from collaboration with affiliated researchers. There have been over 320 publications to date in the 24 year history of the UVMRP. Agricultural effects studies account for 66% of publications, with UV-B climatology making up most of the remainder. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?Undergraduate, graduate, and post-doctoral participation and mentoring are taking place in all phases of the project, through co-authorship of papers in scientific journals, proceedings, and transactions, as well as presentations of research work at professional society events. We are collaborating with Southern University, Baton Rouge, Louisiana on their project "Urban Tree Interception of UV (A/B) Radiation and Its Genetic Consequences", for which they use a mobile cart which contains all the instruments of a typical UVMRP agroclimatological site. A UVMRP field technician visited their location to provide technical support and training to the graduate and doctoral students of the research team about the use of their mobile cart. Later, this project's co-PI and a Professor of Urban Forestry at Southern University spent a week visiting the UVMRP office. While here, she discussed our current research collaborations, learned how to process and calibrate the data obtained from her mobile UV-B monitoring station and interacted with students and other scientists on research activities pertaining to modeling impacts of UV radiation on agricultural and forest ecosystems. One of our master's students worked with Dr. K. Raja Reddy's group at Mississippi State University using their SPAR chambers to explore the isolated and interactive effects of UV-B radiation and nitrogen supply on multiple sweetpotato species conducting two experiments between August and November, 2016. We provided training for a postdoctoral fellow on modeling of relationships between the environment, agricultural and economic factors, focusing on attributions of U.S. crop production to various natural and human factors. How have the results been disseminated to communities of interest?The agroclimatologic and research network sites data are available daily, in near real time, on the project's web site (http://uvb.nrel.colostate.edu). Our publication list is available via the Program's web site as well. These scientifically peer-reviewed papers and associated conference presentations provide most of our outreach to scientific and/or wider communities of interest, and replying to data users specific requests complements this outreach. Currently we have users from more than 300 different organizations, with 48% from national educational institutions; 33% from national governmental agencies; 2% from commercial enterprises; and 17% from international institutions. Our paper in determining climate effects on US total agricultural productivity that was published in the Proceedings for the National Academy of Sciences of the United States of America (PNAS), attracted significant media attention, and which was covered by Nature Research Highlights in 2017. The 5-year impact factor of the PNAS is 10.3, while the current altmetric score of the article is 91 revealing the significance of its findings. Furthermore, it has been downloaded 12,246 times, picked up by 7 news outlets, tweeted by 51 users with potential 85,144 followers, and have 55 readers on Mendeley. What do you plan to do during the next reporting period to accomplish the goals?We plan to continue the progress resulting from 20 years of diligent project management to deliver continuous maintenance of the Network instruments, preserve high rates of data collection, the most-up-to-date calibration protocols, and reliable secondary products. We continue our collaboration with Mississippi State University, in order to use their SPAR facility to evaluate the isolated and combined effects of UV-B and other environmental stressors on crops. We will continue to work with the University of Maryland to develop the CAIE framework. We continue coupling the Agroecosystem modules (CROP) with the CWRF model. We will also continue to develop and integrate an economic module into the impact assessment system, which will provide insight for farm management practices and policy decisions. For the agroclimatological network, we intend to follow our well-established Quality Assurance and Quality Control (QA/QC) protocols and to continue with annual visits to the instrument sites to perform necessary maintenance. We annually renew the collaborations with site operators and data users, both of which are necessary to preserve a high data collection rate. As part of improving our calibration procedures, we will continue to investigate state-of-the-art methodologies, and continue developing the in-house calibration facility in order to measure both spectral and angular responses of our entire suite of instruments. The newly introduced cloud screening algorithms, along with the reference-channel calibration method, will be implemented in more stations as part of our efforts for improving our in-situ calibration processes. A multi-pass analysis to compensate for the ozone contribution and the use of extraterrestrial spectra measured by the suite of space born sensors of the Solar Radiation and Climate Experiment (SORCE) program are also under consideration. UVMRP will likewise investigate modifying the calibration procedure of the 940 nm channel by using collocated a priori precipitable water vapor information where available. In effects research, we continue evaluating the isolated and combined effects of UV-B and other environmental stressors on soybean, and possibly sweetpotato, which are some of the most economically important crops. These experiments will focus on analyzing the effects of several stress factors, such as temperature, precipitation, nitrogen fertilizer, and UV-B radiation on the crops' growth and development responses. To study the root architecture and the physiology of these crops, we will continue to conduct its planned experiments in the SPAR chambers by measuring the cumulative length, total length, chlorophyll and UV-B screening compounds as phenolics along with other significant variables under several combinations of computer-controlled levels of stress factors. These experiments will facilitate the development of quantitative algorithms that can be incorporated into climate-crop simulation models for the Climate-Agroecosystem-UV Interactions and Economic (CAIE) system. For integrated assessment, we continue to develop the coupled CWRF-CROP system for simulating the growth and yields of corn and soybean (from the DSSAT model). Coupling the proposed models including UV-B effects will improve the accuracy of the projected growth and productivity for these particular crops, providing a tool to evaluate farm management practices and policy decisions. We will continue researching correlations between TFP and key environmental indices, develop a multivariate model to predict the national aggregate agricultural TFP, and apply this combined system to estimate the potential trend of the future US agricultural TFP. Obtaining credible and quantitative assessment of key inputs will allow UVMRP scientists to incorporate an economics module into the CWRF-CROP conceptual framework. Inclusion of the economics module will enable the user to analyze best practices and evaluate the economic consequences of land use and crop production responses. We will continue to incorporate the UV decomposition mechanisms, including direct photolysis, microbial facilitation, and inhibition effects, into the biogeochemical model DayCent-UV, to simulate the soil carbon and nitrogen dynamics in ranchlands and dry lands in western US. We continue to investigate the coupling of DayCent-UV with the CWRF model (i.e. CWRF-DayCent) to examine the effects of UV-B on ecosystems and how they subsequently impact climate at the regional scale.
Impacts
What was accomplished under these goals?
Since 1992 UVMRP has managed the only network of nationwide surface monitoring of UV-B irradiance, with 36 agroclimatological sites, plus 4 long-duration research sites, that encompass 20 ecoregion provinces covering various land types. UVMRP staff perform daily checks of the polling success and initiate timely contact with site operators to correct problems. Conversion from telephone connection to Ethernet/Cellular connection is underway (45% complete) which generally improves the data collection percentage. Semi-automated QC algorithms set appropriate flags based on range checks, and are augmented with daily visual inspection of the data and associated log files. A network status report is updated weekly and disseminated to UVMRP staff. All shadowband and radiometer instruments receive periodic recalibration at NOAA's Mauna Loa Observatory (MLO), Hawaii. In early 2017, a set of upgrades increased the number of instruments deployed, including adding 3 UVA-501 biometers to calibrate these ancillary measurements. PAR sensors receive periodic recalibration at the manufacturer's facility. Instruments which have undergone repair of optical components and/or gain circuitry are first sent to NOAA's Central UV Calibration Facility (CUCF) in Boulder, CO for full NIST-traceable characterization. Last year 4 UV-MFRSR and 4 VIS-MFRSR instruments received this recalibration. UVMRP is developing an in-house calibration facility, which currently measures spectral response of UV- and VIS-MFRSRs, with potential to include UVB-1 and PAR radiometers. This in-house capability will be used to monitor stability of our instrument fleet in between CUCF and MLO calibrations. UVMRP participated in the International UV Filter Radiometer comparison at Davos, Switzerland, June 19 to August 18, 2017. This comparison and calibration campaign links global UV radiation observations to the World Meteorological Organization (WMO) Global Atmospheric Watch Reference Scale. UVMRP sent 2 UVB-1 radiometers and 2 UVA-501A biometers. These calibrations will be the benchmark for MLO inter-calibration of our UVB-1 and UVA radiometers. UVMRP developed, analyzed, and validated a new process for MLO calibration of UV-MFRSR instruments that incorporates the corresponding uncertainty into the retrieved absolute calibration factors. The revised calibration scheme includes new cloud-screening algorithms based on direct and global horizontal irradiance measurements from the UV-MFRSR, and introduces a second level of point limitations for the Langley processing. Irradiances from UVB-1 pyranometers were validated at MLO using collocated Brewer measurements and model retrievals (libradtran and TUV). Chen et al. (2016) investigated a new in-situ calibration procedure for obtaining 940nm irradiance data. The original Modified Langley Method (MLM) requires a uniform presence of water vapor over the calibration period, which is difficult to assure. This proposed method uses a priori precipitable water vapor retrieved from (dual-band) GPS constellations near our Oklahoma site. Preliminary results suggest this method improves calibration as compared to the MLM. UVMRP is investigating how to apply this methodology throughout the Network, as part of on-going efforts to improve our calibration protocols. In effects research, UVMRP continues the collaboration with Mississippi State University to study both isolated and interactive impacts of UV-B radiation and other environmental stress factors on growth and development of economically important crops, currently for soybean. Experiments are conducted in MSU's Soil-Plant-Atmosphere-Research (SPAR) chambers, which monitor and control plant growing conditions including temperature, water inputs, and UV-B radiation. One experiment imposed 4 levels of UV-B radiation on soybean cultivar Pioneer 93Y92 to quantify UV-B radiation impacts on its growth and seed quality keeping optimal conditions for the remaining environmental parameters. UV-B doses ranged from current levels to the upper limit expected in the 21st century and were delivered to plants for eight hours each day. Seed quality parameters that are important for seed industry and human and animal nutrition were all affected by UV-B, along with other growth and seed quality parameters. To further these findings, another experiment examined effects of UV-B and other abiotic stressors on soybean root architecture, to develop quantified response functions. 64 soybean cultivars were exposed to 2 daily biologically effective UV-B radiation intensities. Preliminary results revealed that soybean cultivars grown under UV-B stress showed chlorosis, had shorter stems, lower dry mass, and shorter root lengths compared to those under controlled conditions. We are currently modifying the CROPGRO Fortran key module to simulate the growth parameters of soybean. In integrated assessment, we continue to re-engineer the corn sub-module in the DSSAT (Decision Support System for Agrotechnology Transfer) model to be fully coupled with the CWRF (Climate-Weather Research and Forecasting) model, so that production in corn-belt states can be predicted based on projected environmental conditions over the coming decades. This coupling requires replacement of soil dynamic modules, and interconnection of output information of CWRF (air temperature, precipitation, and surface solar radiation) into the crop model, and in a vice versa mode, to feed CWRF with crop traits (crop height, leaf area). We continue to expand the Tropospheric Ultraviolet and Visible Radiation Model (TUV) into CWRF-CROP from clear-sky to all-sky conditions. All-sky conditions require more sophisticated information on clouds (cloud top pressure, cloud optical depth, cloud coverage) that are currently retrieved and incorporated into CWRF-CROP from both space-borne and ground-based sensors (NCEP historical re-analysis products). We used maximum covariance analysis to explore relationships between the moistening pattern of Southern Hemisphere precipitation and forcing factors of Antarctic ozone, water vapor, sea surface temperature, and CO2. It was found that Antarctic ozone patterns are the primary forcing driver, while sea surface temperature and CO2 have mild effects. Incorporating these interactions for CWRF-CROP model will improve its capability of predicting precipitation patterns (Bai et al., 2016). We continue to develop the biogeochemical model DayCent, to quantify impacts of solar UV radiation in conjunction with other environmental stress factors on rangelands and dry lands in western US. We are currently investigating direct photolysis, microbial facilitation, and inhibition effects to be incorporated in the new UV-B sub-module of the DayCent-UV model. We recently top listed the study on "Determining climate effects on US Total Agricultural Activity" in the Proceedings for the National Academy of Sciences of the United States of America (PNAS) by Liang et al. (2017). The journal paper was also reported in Nature Research Highlights. The study focused on the correlation between crop growth and production and the environment on a regional scale. Total factor productivity (TFP) was chosen as the indicator for US agricultural economics, and temperature and precipitation were chosen as the key environmental indices. Preliminary results suggest that temperature and precipitation in distinct agricultural regions and seasons explained ~70% of variations in TFP growth during 1981-2010. This model also suggests that projected environmental extremes could cause TFP to drop to pre-1980 levels by 2050 even when accounting for present rates of innovation. These findings represent the continuing work of UVMRP in developing an integrated agroclimatological assessment by linking regional environmental conditions to national economic outcomes, to provide a more objective resource for policy-making.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Liang, X., Y. Wu, R. G. Chambers, D. L. Schmoldt, W. Gao, C. Liu, Y. Liu, C. Sun, and J. A. Kennedy. 2017. Determining climate effects on US total agricultural productivity. Proceedings for the National Academy of Sciences of the United States of America (PNAS), vol. 114 no. 12, E2285E2292, doi: 10.1073/pnas.1615922114
- Type:
Journal Articles
Status:
Published
Year Published:
2016
Citation:
Bai, K., N. Chang, and W. Gao. 2016. Quantification of relative contribution of Antarctic ozone depletion to increased austral extratropical precipitation during 1979-2013. Journal of Geophysical Research: Atmospheres, 121, 1459-1474. doi: 10.1002/2015JD024247
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2016
Citation:
Chen, M., M. Zempila, J. M. Davis, R. W. King, and W. Gao. 2016. In-situ calibration of the water vapor channel for multi-filter rotating shadowband radiometer using collocated GPS, AERONET and meteorology data. Proceedings of SPIE, Remote Sensing and Modeling of Ecosystems for Sustainability XIII, 9975, 99750E. doi:10.1117/12.2236572
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