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Determining climate effects on US total agricultural productivity

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2017年第12期114卷 E2285-E2292页

作者： Liang, Xin-Zhong Wu, You Chambers, Robert G. Schmoldt, Daniel L. Gao, Wei Liu, Chaoshun Liu, Yan-An Sun, Chao Kennedy, Jennifer A. Univ Maryland Dept Atmospher & Ocean Sci College Pk MD 20740 USA Univ Maryland Earth Syst Sci Interdisciplinary Ctr College Pk MD 20740 USA Nanjing Univ Informat Sci & Technol Climate Environm & Sustainabil Ctr Nanjing 210044 Jiangsu Peoples R China Univ Maryland Agr & Resource Econ College Pk MD 20742 USA USDA Natl Inst Food & Agr Washington DC 20250 USA Colorado State Univ USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO 80521 USA Colorado State Univ Dept Ecosyst Sci & Sustainabil Ft Collins CO 80523 USA East China Normal Univ Minist Educ Key Lab Geog Informat Sci Shanghai 200241 Peoples R China East China Normal Univ Sch Geog Sci Shanghai 200241 Peoples R China

The sensitivity of agricultural productivity to climate has not been sufficiently quantified. The total factor productivity (TFP) of the US agricultural economy has grown continuously for over half a century, with most of the growth typically attributed to technical change. Many studies have examined the effects of local climate on partial productivity measures.such as crop yields and economic returns, but these measures.cannot account for national-level impacts. Quantifying the relationships between TFP and climate is critical to understanding whether current US agricultural productivity growth will continue into the future. We analyze correlations between regional climate variations and national TFP changes, identify key climate indices, and build a multivariate regres.ion model predicting the growth of agricultural TFP based on a physical understanding of its historical relationship with climate. We show that temperature and precipitation in distinct agricultural regions and seasons explain similar to 70% of variations in TFP growth during 1981-2010. To date, the aggregate effects of these regional climate trends on TFP have been outweighed by improvements in technology. Should these relationships continue, however, 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. As a res.lt, TFP could fall to pre-1980 levels by 2050 even when accounting for pres.nt rates of innovation. Our analysis provides an empirical foundation for integrated assessment by linking regional climate effects to national economic outcomes, offering a more objective res.urce for policy making.

关键词： total factor productivity agricultural economy economic growth climate impacts crop yield EARTH

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Effects of bias in solar radiation inputs on ecosystem model performance 12

Effects of bias in solar radiation inputs on ecosystem model...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability XII

作者： Asao, Shinichi Sun, Zhibin Gao, Wei Colorado State Univ USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO 80523 USA Colorado State Univ Dept Ecosyst Sci & Sustainabil Ft Collins CO 80523 USA

ISBN: (纸本)9781628417760

Solar radiation inputs drive many processes in terres.rial ecosystem models. The processes (e.g. photosynthesis) account for most of the fluxes of carbon and water cycling in the models. It is thus clear that errors in solar radiation inputs cause key model outputs to deviate from observations, parameters to become suboptimal, and model predictions to loose confidence. However, errors in solar radiation inputs are unavoidable for most model predictions since models are often run with observations with spatial or / and temporal gaps. As modeled processes are non-linear and interacting with each other, it is unclear how much confidence most model predictions merits without examining the effects of those errors on the model performance. In this study, we examined the effects using a terres.rial ecosystem model, DayCent. DayCent was parameterized for annual grassland in California with six years of daily eddy covariance data totaling 15,337 data points. Using observed solar radiation values, we introduced bias at four different levels. We then simultaneously calibrated 48 DayCent parameters through inverse modeling using the PEST parameter estimation software. The bias in solar radiation inputs affected the calibration only slightly and pres.rved model performance. bias slightly worsened simulations of water flux, but did not affect simulations of CO2 fluxes. This arose from distinct parameter set for each bias level, and the parameter sets were surprisingly unconstrained by the extensive observations. We conclude that ecosystem models perform relatively well even with substantial bias in solar radiation inputs. However, model parameters and predictions warrant skepticism because model parameters can accommodate biases in input data despite extensive observations.

关键词： Ecosystem ecology Century inverse modeling data assimilation shortwave solar radiation carbon fluxes and pools grassland

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Combined uv Irradiance from TOMS-OMI satellite and uvMRP ground measurements across the continental US 12

Combined UV Irradiance from TOMS-OMI satellite and UVMRP gro...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability XII

作者： Sun, Zhibin Davis, John Gao, Wei Colorado State Univ Nat Resource Ecol Lab USDA UV B Monitoring & Res Program Ft Collins CO 80523 USA Colorado State Univ Dept Ecosyst Sci & Sustainabil Ft Collins CO 80523 USA

ISBN: (纸本)9781628417760

Surface ultraviolet (uv) observations can be obtained from satellite or ground observations. This study uses data fusion to combine the advantages from both sources of observations, aiming at achieving a better estimate of surface uv. In this study, ensemble methods were used to estimate the covariances, which are the most important components in data fusion. The combined uv observations not only have the same coverage as satellite data, but also improve their regional accuracy around the ground observatories.

关键词： data fusion data assimilation uv irradiance TOMS-OMI uvMRP covariance

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Two-stage reference channel calibration for collocated uv and VIS Multi-Filter Rotating Shadowband Radiometers 12

Two-stage reference channel calibration for collocated UV an...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability XII

作者： Chen, Maosi Davis, John Sun, Zhibin Gao, Wei Colorado State Univ USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO 80521 USA Colorado State Univ Dept Ecosyst Sci & Sustainabil Ft Collins CO 80521 USA

ISBN: (纸本)9781628417760

Multi-Filter Rotating Shadowband Radiometer (MFRSR) and its uv version (uv-MFRSR) are ground-based instruments for measuring solar uv and VIS radiation, deployed together in field at most usda uv-b monitoring and res.arch program (uvMRP) sites. The performance of the traditional calibration method, Langley Analysis (LA), varies with MFRSR channels and sites, res.lting in less confidence in some irradiance products. A two-stage calibration method is developed. We attributed the variation in Langley Analysis performance to the monotonically changing total optical depth (TOD) in the cloud screened points. Constant TOD is an assumption in LA. Since (1) aerosol is the main source of TOD variation at the 368nm channel and (2) uv-MFRSR measures.direct normal and diffuse horizontal simultaneously, we used the radiative transfer model (i.e. MODTRAN) to create the look-up table of the ratio of direct normal and diffuse (DDR) with res.ect to aerosol optical depth (AOD) and solar zenith angle to evaluate the quality of the Langley Offset (V-LO) by giving lower weights to V-LO generated from points with monotonic AOD variation. With one or two calibrated channels as Reference Channels (RC), the most stable points in RC were selected and LA was applied on those time points to generate V-LO at the adjacent un-calibrated channel. The test of this method on the uv-b program site at Homestead, Florida showed that (1) The long-term trend of the original LA V-LO is impacted by the monotonic changing in AOD at 368nm channel;and (2) more clustered and abundant V-LO at all channels are generated compared with the original Langley method.

关键词： MFRSR calibration Langley Analysis (LA) direct diffuse ratio (DDR) radiative transfer model reference channels

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Dynamic Analysis on Coastline and Sea reclamation in the Efficient Ecological Economic Zone of the Yellow River Delta based on 30-years Satellite Data 12

Dynamic Analysis on Coastline and Sea reclamation in the Eff...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability XII

作者： Zheng, Xiangyu Gao, Zhiqiang Ning, Jicai Lu, Qingshui Chinese Acad Sci Yantai Inst Coastal Zone Res Yantai 264003 Peoples R China Colorado State Univ USDA UV B Monitoring & Res Program Ft Collins CO 80523 USA Colorado State Univ Nat Resource Ecol Lab Ctr Remote Sensing & Modeling Agr Sustainabil Ft Collins CO 80523 USA

ISBN: (纸本)9781628417760

In this paper, with four remote sensing images from the 1980 to 2010 periods and the coastal survey data as data sources, then integrated use remote sensing and GIS technology, the Efficient Ecological Economic Zone of the Yellow River Delta's coastline and sea reclamation changes were extracted by the means of visual interpretation and the artificial vector method. The conclusions are as follows: The coastline of this study area showed a rising trend during 1980 to 2010, the silty coastline showed a reduction trend while the artificial coastline showed an increasing trend, natural and social factors together determined the evolution of coastline. The reclamation area was the largest during 1980 to 1990 and the area was the smallest during 1990 to 2000, demographic factors and economic factors are the most prominent driving reasons of the reclamation. This paper can provide data support and services for the study area to implement management and sustainable development more efficiently.

关键词： The Efficient Ecological Economic Zone of the Yellow River Delta Remote Sensing Coastline Sea Reclamation Dynamic Change

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Study on Coastline Change in Shandong Province based on Geo-information TuPu 12

Study on Coastline Change in Shandong Province Based on Geo-...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability XII

作者： Liu, Xiangyang Gao, Zhiqiang Ning, Jicai Gao, Wei Chinese Acad Sci Yantai Inst Coastal Zone Res Yantai 264003 Peoples R China Colorado State Univ USDA UV B Monitoring & Res Program Ft Collins CO 80523 USA Colorado State Univ Nat Resource Ecol Lab Ctr Remote Sensing & Modeling Agr Sustainabil Ft Collins CO 80523 USA

ISBN: (纸本)9781628417760

With 4 periods of remote sensing images as data sources, based on Geo-information TuPu analysis method, coastline change information mapping of Shandong province during the past 30 years is established using ArcGIS software, and then this kind of information was studied deeply. The conclusions are as follows: 1) During the past 30 years, coastline of Shandong province shows an increasing trend;the centre of increasing shifts eastward gradually;different areas have different increasing situations. 2) During the past 30 years, coastline change degree of Shandong province is basically stable, change fiercely areas concentrate on the Yellow River estuary while Zhaoyuan, Penglai and Longkou have a rather slow degree. 3) From 1980 to 1990, coastline of Shandong province retreats to land quickly, draws back slowly from 1990 to 2000 while advances to sea rapidly entering into 21st century;Dongying has a backward trace for 30 years, Zhaoyuan and Laiyang have been basically unchanged, Yantai, Rizhao and Jiaonan have a obvious trend of advancing to sea.

关键词： Geo-information TuPu coastline change GIS temporal and spatial change

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An Ensemble Algorithm based Component for Geomagnetic Data Assimilation

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TERres.RIAL ATMOSPHERIC AND OCEANIC SCIENCES 2015年第1期26卷 53-61页

作者： Sun, Zhibin Kuang, Weijia Colorado State Univ USDA UV B Monitoring & Res Program Ft Collins CO 80523 USA NASA Goddard Space Flight Ctr Planetary Geodynam Lab Greenbelt MD 20771 USA

Geomagnetic data assimilation is one of the most recent developments in geomagnetic studies. It combines geodynamo model outputs and surface geomagnetic observations to provide more accurate estimates of the core dynamic state and provide accurate geomagnetic secular variation forecasting. To facilitate geomagnetic data assimilation studies, we develop a stand-alone data assimilation component for the geomagnetic community This component is used to calculate the forecast error covariance matrices and the gain matrix from a given geodynamo solution, which can then be used for sequential geomagnetic data assimilation. This component is very flexible and can be executed independently. It can also be easily integrated with arbitrary dynamo models.

关键词： Geomagnetic data assimilation Ensemble algorithm Geodynamo

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Climate Change Impacts on the US Agricultural Economy 12

Climate Change Impacts on the US Agricultural Economy

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability XII

作者： Wu, You Liang, Xin-Zhong Gao, Wei Univ Maryland Earth Syst Sci Interdisciplinary Ctr College Pk MD 20740 USA Nanjing Univ Informat Sci & Technol China Inst Mfg Dev Nanjing 210044 Jiangsu Peoples R China Univ Maryland Dept Atmospher & Ocean Sci College Pk MD 20740 USA Colorado State Univ Nat Resource Ecol Lab USDA UV B Monitoring & Res Program Ft Collins CO 80523 USA Colorado State Univ Dept Ecosyst Sci & Sustainabil Ft Collins CO 80523 USA

ISBN: (纸本)9781628417760

The most important aggregate measure of the long run health of the productive component of the agricultural economy is agricultural total factor productivity (TFP). between 1948 and 2011, average annual input growth in US agriculture averaged approximately 0.07% while annual average output growth averaged roughly 1.5%. That translates into an annual average agricultural TFP growth rate of approximately 1.43%. That growth has led to a remarkable expansion of the productive ability of the US agricultural sector. However, climate change poses unprecedented challenges to U.S. agricultural production because of the sensitivity of agricultural productivity and costs to changing climate conditions. Some studies have examined the effect of climate change on U.S. agriculture. but none has investigated how climate affects the overall U.S. agricultural productivity. This study intends to find out climate change impacts on U.S. agricultural TFP change (TFPC). by correlation analysis with data in 1979-2005, we found that precipitation and temperature had significant positive or negative correlations with U.S. agricultural TFPC. Those correlation coefficients ranged from -0.8 to 0.8. And significant correlations, whether positive or negative, existed in different regions and different seasons. This is important information for policy-makers in decisions to support U.S. agriculture sustainability.

关键词： Climate change total factor productivity agricultural economy

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Nuclear Power Plants in China's Coastal Zone: Risk and Safety 11

Nuclear Power Plants in China's Coastal Zone: Risk and Safet...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability XI

作者： Lu Qingshui Gao Zhiqiang Ning Jicai bi Xiaoli Gao Wei Chinese Acad Sci Yantai Inst Coastal Zone Yantai 264003 Shandong Peoples R China Colorado State Univ USDA UV B Monitoring & Res Program Ctr Remote Sensing & Modeling Agr Sustainabil Nat Resource Ecol Lab Ft Collins CO USA

ISBN: (纸本)9781628412482

Nuclear power plants are used as an option to meet the demands for electricity due to the low emission of CO2 and other contaminants. The accident at the Fukushima nuclear power plant in 2011 has forced the Chinese government to adjust its original plans for nuclear power. The construction of inland nuclear power plants was stopped, and construction is currently only permitted in coastal zones. However, one obstacle of those plants is that the elevation of those plants is notably low, ranging from 2 to 9 meters and a number of the nuclear power plants are located in or near geological fault zones. In addition, the population density is very high in the coastal zones of China. To reduce those risks of nuclear power plants, central government should close the nuclear power plants within the fault zones, evaluate the combined effects of storm surges, inland floods and tidal waves on nuclear power plants and build closed dams around nuclear power plants to prevent damage from storm surges and tidal waves. The areas without fault zones and with low elevation should be considered to be possible sites for future nuclear power plants if the elevation can be increased using soil or civil materials.

关键词： Nuclear power plant coastal zone risk safety

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The Grain Production Potential Assessment With Multiple Cropping Index (MCI) in China 11

The Grain Production Potential Assessment With Multiple Crop...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability XI

作者： Gao, Zhiqiang Ning, Jicai Gao, Wei Chinese Acad Sci Yantai Inst Coastal Zone Res Yantai 264003 Peoples R China Colorado State Univ Ctr Remote Sensing & Modeling Agr Sustainabil Nat Resource Ecol Lab Ft Collins CO USA Colorado State Univ USDA UV B Monitoring & Res Program Ft Collins CO USA

ISBN: (纸本)9781628412482

This paper retrieved the information of cropland and MCI (Multiple Cropping Index) of China in 2000 and 2009 with SPOT NDVI time series data and utilized meteorological data and statistical data released by the state to calculate potential MCI and statistical MCI. Then, the MCI potential of China and grain production potential based on MCI were calculated in order to analyze the potential spatial distribution characteristics of MCI and the potential spatial pattern characteristics. The national mean MCI potentials in 2000 and 2009 are 0.485 and 0.506 res.ectively calculated with the remote sensing method and statistical method. And the grain productivity potentials of China based on MCI are 51% and 53% res.ectively. The improvement of MCI potential not only increases hydrothermal utilization rate and the utilization rate of cropland but also enormously enhances the food security degree of China and provides more available cropland area for the economic development.

关键词： China Time Series Data MCI Change of Cropland Grain Production Potential

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